Sample records for fmri simulation database
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Volumetric BOLD fMRI simulation: from neurovascular coupling to multivoxel imaging
International Nuclear Information System (INIS)
Chen, Zikuan; Calhoun, Vince
2012-01-01
The blood oxygenation-level dependent (BOLD) functional magnetic resonance imaging (fMRI) modality has been numerically simulated by calculating single voxel signals. However, the observation on single voxel signals cannot provide information regarding the spatial distribution of the signals. Specifically, a single BOLD voxel signal simulation cannot answer the fundamental question: is the magnetic resonance (MR) image a replica of its underling magnetic susceptibility source? In this paper, we address this problem by proposing a multivoxel volumetric BOLD fMRI simulation model and a susceptibility expression formula for linear neurovascular coupling process, that allow us to examine the BOLD fMRI procedure from neurovascular coupling to MR image formation. Since MRI technology only senses the magnetism property, we represent a linear neurovascular-coupled BOLD state by a magnetic susceptibility expression formula, which accounts for the parameters of cortical vasculature, intravascular blood oxygenation level, and local neuroactivity. Upon the susceptibility expression of a BOLD state, we carry out volumetric BOLD fMRI simulation by calculating the fieldmap (established by susceptibility magnetization) and the complex multivoxel MR image (by intravoxel dephasing). Given the predefined susceptibility source and the calculated complex MR image, we compare the MR magnitude (phase, respectively) image with the predefined susceptibility source (the calculated fieldmap) by spatial correlation. The spatial correlation between the MR magnitude image and the magnetic susceptibility source is about 0.90 for the settings of T E = 30 ms, B 0 = 3 T, voxel size = 100 micron, vessel radius = 3 micron, and blood volume fraction = 2%. Using these parameters value, the spatial correlation between the MR phase image and the susceptibility-induced fieldmap is close to 1.00. Our simulation results show that the MR magnitude image is not an exact replica of the magnetic susceptibility
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A task-related and resting state realistic fMRI simulator for fMRI data validation
Hill, Jason E.; Liu, Xiangyu; Nutter, Brian; Mitra, Sunanda
2017-02-01
After more than 25 years of published functional magnetic resonance imaging (fMRI) studies, careful scrutiny reveals that most of the reported results lack fully decisive validation. The complex nature of fMRI data generation and acquisition results in unavoidable uncertainties in the true estimation and interpretation of both task-related activation maps and resting state functional connectivity networks, despite the use of various statistical data analysis methodologies. The goal of developing the proposed STANCE (Spontaneous and Task-related Activation of Neuronally Correlated Events) simulator is to generate realistic task-related and/or resting-state 4D blood oxygenation level dependent (BOLD) signals, given the experimental paradigm and scan protocol, by using digital phantoms of twenty normal brains available from BrainWeb (http://brainweb.bic.mni.mcgill.ca/brainweb/). The proposed simulator will include estimated system and modelled physiological noise as well as motion to serve as a reference to measured brain activities. In its current form, STANCE is a MATLAB toolbox with command line functions serving as an open-source add-on to SPM8 (http://www.fil.ion.ucl.ac.uk/spm/software/spm8/). The STANCE simulator has been designed in a modular framework so that the hemodynamic response (HR) and various noise models can be iteratively improved to include evolving knowledge about such models.
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SRD 100 Database for Simulation of Electron Spectra for Surface Analysis (SESSA)Database for Simulation of Electron Spectra for Surface Analysis (SESSA) (PC database for purchase) This database has been designed to facilitate quantitative interpretation of Auger-electron and X-ray photoelectron spectra and to improve the accuracy of quantitation in routine analysis. The database contains all physical data needed to perform quantitative interpretation of an electron spectrum for a thin-film specimen of given composition. A simulation module provides an estimate of peak intensities as well as the energy and angular distributions of the emitted electron flux.
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Learning Computational Models of Video Memorability from fMRI Brain Imaging.
Han, Junwei; Chen, Changyuan; Shao, Ling; Hu, Xintao; Han, Jungong; Liu, Tianming
2015-08-01
Generally, various visual media are unequally memorable by the human brain. This paper looks into a new direction of modeling the memorability of video clips and automatically predicting how memorable they are by learning from brain functional magnetic resonance imaging (fMRI). We propose a novel computational framework by integrating the power of low-level audiovisual features and brain activity decoding via fMRI. Initially, a user study experiment is performed to create a ground truth database for measuring video memorability and a set of effective low-level audiovisual features is examined in this database. Then, human subjects' brain fMRI data are obtained when they are watching the video clips. The fMRI-derived features that convey the brain activity of memorizing videos are extracted using a universal brain reference system. Finally, due to the fact that fMRI scanning is expensive and time-consuming, a computational model is learned on our benchmark dataset with the objective of maximizing the correlation between the low-level audiovisual features and the fMRI-derived features using joint subspace learning. The learned model can then automatically predict the memorability of videos without fMRI scans. Evaluations on publically available image and video databases demonstrate the effectiveness of the proposed framework.
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Oblak, Ethan F; Lewis-Peacock, Jarrod A; Sulzer, James S
2017-07-01
Direct manipulation of brain activity can be used to investigate causal brain-behavior relationships. Current noninvasive neural stimulation techniques are too coarse to manipulate behaviors that correlate with fine-grained spatial patterns recorded by fMRI. However, these activity patterns can be manipulated by having people learn to self-regulate their own recorded neural activity. This technique, known as fMRI neurofeedback, faces challenges as many participants are unable to self-regulate. The causes of this non-responder effect are not well understood due to the cost and complexity of such investigation in the MRI scanner. Here, we investigated the temporal dynamics of the hemodynamic response measured by fMRI as a potential cause of the non-responder effect. Learning to self-regulate the hemodynamic response involves a difficult temporal credit-assignment problem because this signal is both delayed and blurred over time. Two factors critical to this problem are the prescribed self-regulation strategy (cognitive or automatic) and feedback timing (continuous or intermittent). Here, we sought to evaluate how these factors interact with the temporal dynamics of fMRI without using the MRI scanner. We first examined the role of cognitive strategies by having participants learn to regulate a simulated neurofeedback signal using a unidimensional strategy: pressing one of two buttons to rotate a visual grating that stimulates a model of visual cortex. Under these conditions, continuous feedback led to faster regulation compared to intermittent feedback. Yet, since many neurofeedback studies prescribe implicit self-regulation strategies, we created a computational model of automatic reward-based learning to examine whether this result held true for automatic processing. When feedback was delayed and blurred based on the hemodynamics of fMRI, this model learned more reliably from intermittent feedback compared to continuous feedback. These results suggest that different
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Directory of Open Access Journals (Sweden)
Ethan F Oblak
2017-07-01
Full Text Available Direct manipulation of brain activity can be used to investigate causal brain-behavior relationships. Current noninvasive neural stimulation techniques are too coarse to manipulate behaviors that correlate with fine-grained spatial patterns recorded by fMRI. However, these activity patterns can be manipulated by having people learn to self-regulate their own recorded neural activity. This technique, known as fMRI neurofeedback, faces challenges as many participants are unable to self-regulate. The causes of this non-responder effect are not well understood due to the cost and complexity of such investigation in the MRI scanner. Here, we investigated the temporal dynamics of the hemodynamic response measured by fMRI as a potential cause of the non-responder effect. Learning to self-regulate the hemodynamic response involves a difficult temporal credit-assignment problem because this signal is both delayed and blurred over time. Two factors critical to this problem are the prescribed self-regulation strategy (cognitive or automatic and feedback timing (continuous or intermittent. Here, we sought to evaluate how these factors interact with the temporal dynamics of fMRI without using the MRI scanner. We first examined the role of cognitive strategies by having participants learn to regulate a simulated neurofeedback signal using a unidimensional strategy: pressing one of two buttons to rotate a visual grating that stimulates a model of visual cortex. Under these conditions, continuous feedback led to faster regulation compared to intermittent feedback. Yet, since many neurofeedback studies prescribe implicit self-regulation strategies, we created a computational model of automatic reward-based learning to examine whether this result held true for automatic processing. When feedback was delayed and blurred based on the hemodynamics of fMRI, this model learned more reliably from intermittent feedback compared to continuous feedback. These results
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Sulzer, James S.
2017-01-01
Direct manipulation of brain activity can be used to investigate causal brain-behavior relationships. Current noninvasive neural stimulation techniques are too coarse to manipulate behaviors that correlate with fine-grained spatial patterns recorded by fMRI. However, these activity patterns can be manipulated by having people learn to self-regulate their own recorded neural activity. This technique, known as fMRI neurofeedback, faces challenges as many participants are unable to self-regulate. The causes of this non-responder effect are not well understood due to the cost and complexity of such investigation in the MRI scanner. Here, we investigated the temporal dynamics of the hemodynamic response measured by fMRI as a potential cause of the non-responder effect. Learning to self-regulate the hemodynamic response involves a difficult temporal credit-assignment problem because this signal is both delayed and blurred over time. Two factors critical to this problem are the prescribed self-regulation strategy (cognitive or automatic) and feedback timing (continuous or intermittent). Here, we sought to evaluate how these factors interact with the temporal dynamics of fMRI without using the MRI scanner. We first examined the role of cognitive strategies by having participants learn to regulate a simulated neurofeedback signal using a unidimensional strategy: pressing one of two buttons to rotate a visual grating that stimulates a model of visual cortex. Under these conditions, continuous feedback led to faster regulation compared to intermittent feedback. Yet, since many neurofeedback studies prescribe implicit self-regulation strategies, we created a computational model of automatic reward-based learning to examine whether this result held true for automatic processing. When feedback was delayed and blurred based on the hemodynamics of fMRI, this model learned more reliably from intermittent feedback compared to continuous feedback. These results suggest that different
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Resting-state FMRI confounds and cleanup
Murphy, Kevin; Birn, Rasmus M.; Bandettini, Peter A.
2013-01-01
The goal of resting-state functional magnetic resonance imaging (FMRI) is to investigate the brain’s functional connections by using the temporal similarity between blood oxygenation level dependent (BOLD) signals in different regions of the brain “at rest” as an indicator of synchronous neural activity. Since this measure relies on the temporal correlation of FMRI signal changes between different parts of the brain, any non-neural activity-related process that affects the signals will influence the measure of functional connectivity, yielding spurious results. To understand the sources of these resting-state FMRI confounds, this article describes the origins of the BOLD signal in terms of MR physics and cerebral physiology. Potential confounds arising from motion, cardiac and respiratory cycles, arterial CO2 concentration, blood pressure/cerebral autoregulation, and vasomotion are discussed. Two classes of techniques to remove confounds from resting-state BOLD time series are reviewed: 1) those utilising external recordings of physiology and 2) data-based cleanup methods that only use the resting-state FMRI data itself. Further methods that remove noise from functional connectivity measures at a group level are also discussed. For successful interpretation of resting-state FMRI comparisons and results, noise cleanup is an often over-looked but essential step in the analysis pipeline. PMID:23571418
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A Dictionary Learning Approach for Signal Sampling in Task-Based fMRI for Reduction of Big Data
Ge, Bao; Li, Xiang; Jiang, Xi; Sun, Yifei; Liu, Tianming
2018-01-01
The exponential growth of fMRI big data offers researchers an unprecedented opportunity to explore functional brain networks. However, this opportunity has not been fully explored yet due to the lack of effective and efficient tools for handling such fMRI big data. One major challenge is that computing capabilities still lag behind the growth of large-scale fMRI databases, e.g., it takes many days to perform dictionary learning and sparse coding of whole-brain fMRI data for an fMRI database of average size. Therefore, how to reduce the data size but without losing important information becomes a more and more pressing issue. To address this problem, we propose a signal sampling approach for significant fMRI data reduction before performing structurally-guided dictionary learning and sparse coding of whole brain's fMRI data. We compared the proposed structurally guided sampling method with no sampling, random sampling and uniform sampling schemes, and experiments on the Human Connectome Project (HCP) task fMRI data demonstrated that the proposed method can achieve more than 15 times speed-up without sacrificing the accuracy in identifying task-evoked functional brain networks. PMID:29706880
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A Dictionary Learning Approach for Signal Sampling in Task-Based fMRI for Reduction of Big Data.
Ge, Bao; Li, Xiang; Jiang, Xi; Sun, Yifei; Liu, Tianming
2018-01-01
The exponential growth of fMRI big data offers researchers an unprecedented opportunity to explore functional brain networks. However, this opportunity has not been fully explored yet due to the lack of effective and efficient tools for handling such fMRI big data. One major challenge is that computing capabilities still lag behind the growth of large-scale fMRI databases, e.g., it takes many days to perform dictionary learning and sparse coding of whole-brain fMRI data for an fMRI database of average size. Therefore, how to reduce the data size but without losing important information becomes a more and more pressing issue. To address this problem, we propose a signal sampling approach for significant fMRI data reduction before performing structurally-guided dictionary learning and sparse coding of whole brain's fMRI data. We compared the proposed structurally guided sampling method with no sampling, random sampling and uniform sampling schemes, and experiments on the Human Connectome Project (HCP) task fMRI data demonstrated that the proposed method can achieve more than 15 times speed-up without sacrificing the accuracy in identifying task-evoked functional brain networks.
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Using relational databases to collect and store discrete-event simulation results
DEFF Research Database (Denmark)
Poderys, Justas; Soler, José
2016-01-01
, export the results to a data carrier file and then process the results stored in a file using the data processing software. In this work, we propose to save the simulation results directly from a simulation tool to a computer database. We implemented a link between the discrete-even simulation tool...... and the database and performed performance evaluation of 3 different open-source database systems. We show, that with a right choice of a database system, simulation results can be collected and exported up to 2.67 times faster, and use 1.78 times less disk space when compared to using simulation software built...
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International Nuclear Information System (INIS)
Im, Chang-Hwan; Lee, Soo Yeol
2006-01-01
fMRI-constrained EEG/MEG source imaging can be a powerful tool in studying human brain functions with enhanced spatial and temporal resolutions. Recent studies on the combination of fMRI and EEG/MEG have suggested that fMRI prior information could be readily implemented by simply imposing different weighting factors to cortical sources overlapping with the fMRI activations. It has been also reported, however, that such a hard constraint may cause severe distortions or elimination of meaningful EEG/MEG sources when there are distinct mismatches between the fMRI activations and the EEG/MEG sources. If one wants to obtain the actual EEG/MEG source locations and uses the fMRI prior information as just an auxiliary tool to enhance focality of the distributed EEG/MEG sources, it is reasonable to weaken the strength of fMRI constraint when severe mismatches between fMRI and EEG/MEG sources are observed. The present study suggests an efficient technique to automatically adjust the strength of fMRI constraint according to the mismatch level. The use of the proposed technique rarely affects the results of conventional fMRI-constrained EEG/MEG source imaging if no major mismatch between the two modalities is detected; while the new results become similar to those of typical EEG/MEG source imaging without fMRI constraint if the mismatch level is significant. A preliminary simulation study using realistic EEG signals demonstrated that the proposed technique can be a promising tool to selectively apply fMRI prior information to EEG/MEG source imaging
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Feature-space-based FMRI analysis using the optimal linear transformation.
Sun, Fengrong; Morris, Drew; Lee, Wayne; Taylor, Margot J; Mills, Travis; Babyn, Paul S
2010-09-01
The optimal linear transformation (OLT), an image analysis technique of feature space, was first presented in the field of MRI. This paper proposes a method of extending OLT from MRI to functional MRI (fMRI) to improve the activation-detection performance over conventional approaches of fMRI analysis. In this method, first, ideal hemodynamic response time series for different stimuli were generated by convolving the theoretical hemodynamic response model with the stimulus timing. Second, constructing hypothetical signature vectors for different activity patterns of interest by virtue of the ideal hemodynamic responses, OLT was used to extract features of fMRI data. The resultant feature space had particular geometric clustering properties. It was then classified into different groups, each pertaining to an activity pattern of interest; the applied signature vector for each group was obtained by averaging. Third, using the applied signature vectors, OLT was applied again to generate fMRI composite images with high SNRs for the desired activity patterns. Simulations and a blocked fMRI experiment were employed for the method to be verified and compared with the general linear model (GLM)-based analysis. The simulation studies and the experimental results indicated the superiority of the proposed method over the GLM-based analysis in detecting brain activities.
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Simulating fiction: individual differences in literature comprehension revealed with FMRI.
Nijhof, Annabel D; Willems, Roel M
2015-01-01
When we read literary fiction, we are transported to fictional places, and we feel and think along with the characters. Despite the importance of narrative in adult life and during development, the neurocognitive mechanisms underlying fiction comprehension are unclear. We used functional magnetic resonance imaging (fMRI) to investigate how individuals differently employ neural networks important for understanding others' beliefs and intentions (mentalizing), and for sensori-motor simulation while listening to excerpts from literary novels. Localizer tasks were used to localize both the cortical motor network and the mentalizing network in participants after they listened to excerpts from literary novels. Results show that participants who had high activation in anterior medial prefrontal cortex (aMPFC; part of the mentalizing network) when listening to mentalizing content of literary fiction, had lower motor cortex activity when they listened to action-related content of the story, and vice versa. This qualifies how people differ in their engagement with fiction: some people are mostly drawn into a story by mentalizing about the thoughts and beliefs of others, whereas others engage in literature by simulating more concrete events such as actions. This study provides on-line neural evidence for the existence of qualitatively different styles of moving into literary worlds, and adds to a growing body of literature showing the potential to study narrative comprehension with neuroimaging methods.
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Modeling fMRI signals can provide insights into neural processing in the cerebral cortex.
Vanni, Simo; Sharifian, Fariba; Heikkinen, Hanna; Vigário, Ricardo
2015-08-01
Every stimulus or task activates multiple areas in the mammalian cortex. These distributed activations can be measured with functional magnetic resonance imaging (fMRI), which has the best spatial resolution among the noninvasive brain imaging methods. Unfortunately, the relationship between the fMRI activations and distributed cortical processing has remained unclear, both because the coupling between neural and fMRI activations has remained poorly understood and because fMRI voxels are too large to directly sense the local neural events. To get an idea of the local processing given the macroscopic data, we need models to simulate the neural activity and to provide output that can be compared with fMRI data. Such models can describe neural mechanisms as mathematical functions between input and output in a specific system, with little correspondence to physiological mechanisms. Alternatively, models can be biomimetic, including biological details with straightforward correspondence to experimental data. After careful balancing between complexity, computational efficiency, and realism, a biomimetic simulation should be able to provide insight into how biological structures or functions contribute to actual data processing as well as to promote theory-driven neuroscience experiments. This review analyzes the requirements for validating system-level computational models with fMRI. In particular, we study mesoscopic biomimetic models, which include a limited set of details from real-life networks and enable system-level simulations of neural mass action. In addition, we discuss how recent developments in neurophysiology and biophysics may significantly advance the modelling of fMRI signals. Copyright © 2015 the American Physiological Society.
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Network modelling methods for FMRI.
Smith, Stephen M; Miller, Karla L; Salimi-Khorshidi, Gholamreza; Webster, Matthew; Beckmann, Christian F; Nichols, Thomas E; Ramsey, Joseph D; Woolrich, Mark W
2011-01-15
There is great interest in estimating brain "networks" from FMRI data. This is often attempted by identifying a set of functional "nodes" (e.g., spatial ROIs or ICA maps) and then conducting a connectivity analysis between the nodes, based on the FMRI timeseries associated with the nodes. Analysis methods range from very simple measures that consider just two nodes at a time (e.g., correlation between two nodes' timeseries) to sophisticated approaches that consider all nodes simultaneously and estimate one global network model (e.g., Bayes net models). Many different methods are being used in the literature, but almost none has been carefully validated or compared for use on FMRI timeseries data. In this work we generate rich, realistic simulated FMRI data for a wide range of underlying networks, experimental protocols and problematic confounds in the data, in order to compare different connectivity estimation approaches. Our results show that in general correlation-based approaches can be quite successful, methods based on higher-order statistics are less sensitive, and lag-based approaches perform very poorly. More specifically: there are several methods that can give high sensitivity to network connection detection on good quality FMRI data, in particular, partial correlation, regularised inverse covariance estimation and several Bayes net methods; however, accurate estimation of connection directionality is more difficult to achieve, though Patel's τ can be reasonably successful. With respect to the various confounds added to the data, the most striking result was that the use of functionally inaccurate ROIs (when defining the network nodes and extracting their associated timeseries) is extremely damaging to network estimation; hence, results derived from inappropriate ROI definition (such as via structural atlases) should be regarded with great caution. Copyright © 2010 Elsevier Inc. All rights reserved.
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On transferability and contexts when using simulated grasp databases
DEFF Research Database (Denmark)
Jørgensen, Jimmy Alison; Ellekilde, Lars-Peter; Kraft, Dirk
2015-01-01
It has become a common practice to use simulation to generate large databases of good grasps for grasp planning in robotics research. However, the existence of a generic simulation context that enables the generation of high quality grasps that can be used in several different contexts such as bi...
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Design and Establishment of Database on the AtoN Properties for AtoN Simulator
Directory of Open Access Journals (Sweden)
Ji-Min Yeo
2015-12-01
Full Text Available This study investigated the design and establishment of AtoN(Aids to Navigation in the AtoN Simulator. In recent years, IALA(International Association of Lighthouse Authorities has raised the need of a system which could verify whether AtoN is appropriate for the design of AtoN and placement planning. An AtoN Simulator provides simulation circumstances, including the topographical and environmental characteristics of a primary harbor and the characteristics of a navigating ship and the maritime traffic. In the present study, we have developed an AtoN simulator system, including the integrated system design and the construction of an AtoN database. The AtoN Manager was developed as a virtual AtoN to manage the AtoN simulation. However, the data and materials are difficult to manage. Hence, an AtoN Manager and an AtoN simulation system have been needed for an effective managing of the AtoN properties database data. For the database structure design, we have analyzed the database design methodology. The AtoN properties have been analyzed for the effective data management. The AtoN properties designed in the present paper were classified into 19 categories. The status and properties database of AtoN were installed in 14 major ports, those were applied to the AtoN Manager. Designing the AtoN properties database was defined to reduce confusion of the use of English terms and abbreviations. The terms and acronyms have been defined in the AtoN properties and designed to the properties database structure for each AtoN. Before structuring the database for the AtoN Manager, the data of the AtoN properties for each harbor have been organized in accordance with the Excel system. The regulated data were converted into the AtoN properties database in use for the AtoN Manager. The database based on the AtoN properties table structure to each AtoN was designed. The AtoN simulator was implemented by the AtoN Manager applied to the AtoN properties database.
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RETROSPECTIVE DETECTION OF INTERLEAVED SLICE ACQUISITION PARAMETERS FROM FMRI DATA
Parker, David; Rotival, Georges; Laine, Andrew; Razlighi, Qolamreza R.
2015-01-01
To minimize slice excitation leakage to adjacent slices, interleaved slice acquisition is nowadays performed regularly in fMRI scanners. In interleaved slice acquisition, the number of slices skipped between two consecutive slice acquisitions is often referred to as the ‘interleave parameter’; the loss of this parameter can be catastrophic for the analysis of fMRI data. In this article we present a method to retrospectively detect the interleave parameter and the axis in which it is applied. Our method relies on the smoothness of the temporal-distance correlation function, which becomes disrupted along the axis on which interleaved slice acquisition is applied. We examined this method on simulated and real data in the presence of fMRI artifacts such as physiological noise, motion, etc. We also examined the reliability of this method in detecting different types of interleave parameters and demonstrated an accuracy of about 94% in more than 1000 real fMRI scans. PMID:26161244
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Development of a Searchable Database of Cryoablation Simulations for Use in Treatment Planning.
Boas, F Edward; Srimathveeravalli, Govindarajan; Durack, Jeremy C; Kaye, Elena A; Erinjeri, Joseph P; Ziv, Etay; Maybody, Majid; Yarmohammadi, Hooman; Solomon, Stephen B
2017-05-01
To create and validate a planning tool for multiple-probe cryoablation, using simulations of ice ball size and shape for various ablation probe configurations, ablation times, and types of tissue ablated. Ice ball size and shape was simulated using the Pennes bioheat equation. Five thousand six hundred and seventy different cryoablation procedures were simulated, using 1-6 cryoablation probes and 1-2 cm spacing between probes. The resulting ice ball was measured along three perpendicular axes and recorded in a database. Simulated ice ball sizes were compared to gel experiments (26 measurements) and clinical cryoablation cases (42 measurements). The clinical cryoablation measurements were obtained from a HIPAA-compliant retrospective review of kidney and liver cryoablation procedures between January 2015 and February 2016. Finally, we created a web-based cryoablation planning tool, which uses the cryoablation simulation database to look up the probe spacing and ablation time that produces the desired ice ball shape and dimensions. Average absolute error between the simulated and experimentally measured ice balls was 1 mm in gel experiments and 4 mm in clinical cryoablation cases. The simulations accurately predicted the degree of synergy in multiple-probe ablations. The cryoablation simulation database covers a wide range of ice ball sizes and shapes up to 9.8 cm. Cryoablation simulations accurately predict the ice ball size in multiple-probe ablations. The cryoablation database can be used to plan ablation procedures: given the desired ice ball size and shape, it will find the number and type of probes, probe configuration and spacing, and ablation time required.
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A database for human performance under simulated emergencies of nuclear power plants
International Nuclear Information System (INIS)
Park, Jin Kyun; Jung, Won Dea
2005-01-01
Reliable human performance is a prerequisite in securing the safety of complicated process systems such as nuclear power plants. However, the amount of available knowledge that can explain why operators deviate from an expected performance level is so small because of the infrequency of real accidents. Therefore, in this study, a database that contains a set of useful information extracted from simulated emergencies was developed in order to provide important clues for understanding the change of operators' performance under stressful conditions (i.e., real accidents). The database was developed under Microsoft Windows TM environment using Microsoft Access 97 TM and Microsoft Visual Basic 6.0 TM . In the database, operators' performance data obtained from the analysis of over 100 audio-visual records for simulated emergencies were stored using twenty kinds of distinctive data fields. A total of ten kinds of operators' performance data are available from the developed database. Although it is still difficult to predict operators' performance under stressful conditions based on the results of simulated emergencies, simulation studies remain the most feasible way to scrutinize performance. Accordingly, it is expected that the performance data of this study will provide a concrete foundation for understanding the change of operators' performance in emergency situations
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Reading positional codes with fMRI: Problems and solutions.
Directory of Open Access Journals (Sweden)
Kristjan Kalm
Full Text Available Neural mechanisms which bind items into sequences have been investigated in a large body of research in animal neurophysiology and human neuroimaging. However, a major problem in interpreting this data arises from a fact that several unrelated processes, such as memory load, sensory adaptation, and reward expectation, also change in a consistent manner as the sequence unfolds. In this paper we use computational simulations and data from two fMRI experiments to show that a host of unrelated neural processes can masquerade as sequence representations. We show that dissociating such unrelated processes from a dedicated sequence representation is an especially difficult problem for fMRI data, which is almost exclusively the modality used in human experiments. We suggest that such fMRI results must be treated with caution and in many cases the assumed neural representation might actually reflect unrelated processes.
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Development of a Searchable Database of Cryoablation Simulations for Use in Treatment Planning
Energy Technology Data Exchange (ETDEWEB)
Boas, F. Edward, E-mail: boasf@mskcc.org; Srimathveeravalli, Govindarajan, E-mail: srimaths@mskcc.org; Durack, Jeremy C., E-mail: durackj@mskcc.org [Memorial Sloan Kettering Cancer Center, Department of Radiology (United States); Kaye, Elena A., E-mail: kayee@mskcc.org [Memorial Sloan Kettering Cancer Center, Department of Medical Physics (United States); Erinjeri, Joseph P., E-mail: erinjerj@mskcc.org; Ziv, Etay, E-mail: zive@mskcc.org; Maybody, Majid, E-mail: maybodym@mskcc.org; Yarmohammadi, Hooman, E-mail: yarmohah@mskcc.org; Solomon, Stephen B., E-mail: solomons@mskcc.org [Memorial Sloan Kettering Cancer Center, Department of Radiology (United States)
2017-05-15
PurposeTo create and validate a planning tool for multiple-probe cryoablation, using simulations of ice ball size and shape for various ablation probe configurations, ablation times, and types of tissue ablated.Materials and MethodsIce ball size and shape was simulated using the Pennes bioheat equation. Five thousand six hundred and seventy different cryoablation procedures were simulated, using 1–6 cryoablation probes and 1–2 cm spacing between probes. The resulting ice ball was measured along three perpendicular axes and recorded in a database. Simulated ice ball sizes were compared to gel experiments (26 measurements) and clinical cryoablation cases (42 measurements). The clinical cryoablation measurements were obtained from a HIPAA-compliant retrospective review of kidney and liver cryoablation procedures between January 2015 and February 2016. Finally, we created a web-based cryoablation planning tool, which uses the cryoablation simulation database to look up the probe spacing and ablation time that produces the desired ice ball shape and dimensions.ResultsAverage absolute error between the simulated and experimentally measured ice balls was 1 mm in gel experiments and 4 mm in clinical cryoablation cases. The simulations accurately predicted the degree of synergy in multiple-probe ablations. The cryoablation simulation database covers a wide range of ice ball sizes and shapes up to 9.8 cm.ConclusionCryoablation simulations accurately predict the ice ball size in multiple-probe ablations. The cryoablation database can be used to plan ablation procedures: given the desired ice ball size and shape, it will find the number and type of probes, probe configuration and spacing, and ablation time required.
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Development of a Searchable Database of Cryoablation Simulations for Use in Treatment Planning
International Nuclear Information System (INIS)
Boas, F. Edward; Srimathveeravalli, Govindarajan; Durack, Jeremy C.; Kaye, Elena A.; Erinjeri, Joseph P.; Ziv, Etay; Maybody, Majid; Yarmohammadi, Hooman; Solomon, Stephen B.
2017-01-01
PurposeTo create and validate a planning tool for multiple-probe cryoablation, using simulations of ice ball size and shape for various ablation probe configurations, ablation times, and types of tissue ablated.Materials and MethodsIce ball size and shape was simulated using the Pennes bioheat equation. Five thousand six hundred and seventy different cryoablation procedures were simulated, using 1–6 cryoablation probes and 1–2 cm spacing between probes. The resulting ice ball was measured along three perpendicular axes and recorded in a database. Simulated ice ball sizes were compared to gel experiments (26 measurements) and clinical cryoablation cases (42 measurements). The clinical cryoablation measurements were obtained from a HIPAA-compliant retrospective review of kidney and liver cryoablation procedures between January 2015 and February 2016. Finally, we created a web-based cryoablation planning tool, which uses the cryoablation simulation database to look up the probe spacing and ablation time that produces the desired ice ball shape and dimensions.ResultsAverage absolute error between the simulated and experimentally measured ice balls was 1 mm in gel experiments and 4 mm in clinical cryoablation cases. The simulations accurately predicted the degree of synergy in multiple-probe ablations. The cryoablation simulation database covers a wide range of ice ball sizes and shapes up to 9.8 cm.ConclusionCryoablation simulations accurately predict the ice ball size in multiple-probe ablations. The cryoablation database can be used to plan ablation procedures: given the desired ice ball size and shape, it will find the number and type of probes, probe configuration and spacing, and ablation time required.
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Database-driven web interface automating gyrokinetic simulations for validation
Ernst, D. R.
2010-11-01
We are developing a web interface to connect plasma microturbulence simulation codes with experimental data. The website automates the preparation of gyrokinetic simulations utilizing plasma profile and magnetic equilibrium data from TRANSP analysis of experiments, read from MDSPLUS over the internet. This database-driven tool saves user sessions, allowing searches of previous simulations, which can be restored to repeat the same analysis for a new discharge. The website includes a multi-tab, multi-frame, publication quality java plotter Webgraph, developed as part of this project. Input files can be uploaded as templates and edited with context-sensitive help. The website creates inputs for GS2 and GYRO using a well-tested and verified back-end, in use for several years for the GS2 code [D. R. Ernst et al., Phys. Plasmas 11(5) 2637 (2004)]. A centralized web site has the advantage that users receive bug fixes instantaneously, while avoiding the duplicated effort of local compilations. Possible extensions to the database to manage run outputs, toward prototyping for the Fusion Simulation Project, are envisioned. Much of the web development utilized support from the DoE National Undergraduate Fellowship program [e.g., A. Suarez and D. R. Ernst, http://meetings.aps.org/link/BAPS.2005.DPP.GP1.57.
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Functional Decomposition of Modeling and Simulation Terrain Database Generation Process
National Research Council Canada - National Science Library
Yakich, Valerie R; Lashlee, J. D
2008-01-01
.... This report documents the conceptual procedure as implemented by Lockheed Martin Simulation, Training, and Support and decomposes terrain database construction using the Integration Definition for Function Modeling (IDEF...
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Establishment of DNS database in a turbulent channel flow by large-scale simulations
Abe, Hiroyuki; Kawamura, Hiroshi; 阿部 浩幸; 河村 洋
2008-01-01
In the present study, we establish statistical DNS (Direct Numerical Simulation) database in a turbulent channel flow with passive scalar transport at high Reynolds numbers and make the data available at our web site (http://murasun.me.noda.tus.ac.jp/turbulence/). The established database is reported together with the implementation of large-scale simulations, representative DNS results and results on turbulence model testing using the DNS data.
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Extending Local Canonical Correlation Analysis to Handle General Linear Contrasts for fMRI Data
Directory of Open Access Journals (Sweden)
Mingwu Jin
2012-01-01
Full Text Available Local canonical correlation analysis (CCA is a multivariate method that has been proposed to more accurately determine activation patterns in fMRI data. In its conventional formulation, CCA has several drawbacks that limit its usefulness in fMRI. A major drawback is that, unlike the general linear model (GLM, a test of general linear contrasts of the temporal regressors has not been incorporated into the CCA formalism. To overcome this drawback, a novel directional test statistic was derived using the equivalence of multivariate multiple regression (MVMR and CCA. This extension will allow CCA to be used for inference of general linear contrasts in more complicated fMRI designs without reparameterization of the design matrix and without reestimating the CCA solutions for each particular contrast of interest. With the proper constraints on the spatial coefficients of CCA, this test statistic can yield a more powerful test on the inference of evoked brain regional activations from noisy fMRI data than the conventional t-test in the GLM. The quantitative results from simulated and pseudoreal data and activation maps from fMRI data were used to demonstrate the advantage of this novel test statistic.
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Bayesian spatiotemporal model of fMRI data using transfer functions.
Quirós, Alicia; Diez, Raquel Montes; Wilson, Simon P
2010-09-01
This research describes a new Bayesian spatiotemporal model to analyse BOLD fMRI studies. In the temporal dimension, we describe the shape of the hemodynamic response function (HRF) with a transfer function model. The spatial continuity and local homogeneity of the evoked responses are modelled by a Gaussian Markov random field prior on the parameter indicating activations. The proposal constitutes an extension of the spatiotemporal model presented in a previous approach [Quirós, A., Montes Diez, R. and Gamerman, D., 2010. Bayesian spatiotemporal model of fMRI data, Neuroimage, 49: 442-456], offering more flexibility in the estimation of the HRF and computational advantages in the resulting MCMC algorithm. Simulations from the model are performed in order to ascertain the performance of the sampling scheme and the ability of the posterior to estimate model parameters, as well as to check the model sensitivity to signal to noise ratio. Results are shown on synthetic data and on a real data set from a block-design fMRI experiment. Copyright (c) 2010 Elsevier Inc. All rights reserved.
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DoSSiER: Database of Scientific Simulation and Experimental Results
Wenzel, Hans; Genser, Krzysztof; Elvira, Daniel; Pokorski, Witold; Carminati, Federico; Konstantinov, Dmitri; Ribon, Alberto; Folger, Gunter; Dotti, Andrea
2017-01-01
The Geant4, GeantV and GENIE collaborations regularly perform validation and regression tests for simulation results. DoSSiER (Database of Scientific Simulation and Experimental Results) is being developed as a central repository to store the simulation results as well as the experimental data used for validation. DoSSiER can be easily accessed via a web application. In addition, a web service allows for programmatic access to the repository to extract records in json or xml exchange formats. In this article, we describe the functionality and the current status of various components of DoSSiER as well as the technology choices we made.
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Quantifying functional connectivity in multi-subject fMRI data using component models
DEFF Research Database (Denmark)
Madsen, Kristoffer Hougaard; Churchill, Nathan William; Mørup, Morten
2017-01-01
of functional connectivity, evaluated on both simulated and experimental resting-state fMRI data. It was demonstrated that highly flexible subject-specific component subspaces, as well as very constrained average models, are poor predictors of whole-brain functional connectivity, whereas the best...
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Database of Nucleon-Nucleon Scattering Cross Sections by Stochastic Simulation, Phase I
National Aeronautics and Space Administration — A database of nucleon-nucleon elastic differential and total cross sections will be generated by stochastic simulation of the quantum Liouville equation in the...
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Towards open sharing of task-based fMRI data: The OpenfMRI project
Directory of Open Access Journals (Sweden)
Russell A Poldrack
2013-07-01
Full Text Available The large-scale sharing of task-based functional neuroimaging data has the potential to allow novel insights into the organization of mental function in the brain, but the field of neuroimaging has lagged behind other areas of bioscience in the development of data sharing resources. This paper describes the OpenFMRI project (accessible online at http://www.openfmri.org, which aims to provide the neuroimaging community with a resource to support open sharing of task-based fMRI studies. We describe the motivation behind the project, focusing particularly on how this project addresses some of the well-known challenges to sharing of task-based fMRI data. Results from a preliminary analysis of the current database are presented, which demonstrate the ability to classify between task contrasts with high generalization accuracy across subjects, and the ability to identify individual subjects from their activation maps with moderately high accuracy. Clustering analyses show that the similarity relations between statistical maps have a somewhat orderly relation to the mental functions engaged by the relevant tasks. These results highlight the potential of the project to support large-scale multivariate analyses of the relation between mental processes and brain function.
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BIGNASim: a NoSQL database structure and analysis portal for nucleic acids simulation data
Hospital, Adam; Andrio, Pau; Cugnasco, Cesare; Codo, Laia; Becerra, Yolanda; Dans, Pablo D.; Battistini, Federica; Torres, Jordi; Goñi, Ramón; Orozco, Modesto; Gelpí, Josep Ll.
2016-01-01
Molecular dynamics simulation (MD) is, just behind genomics, the bioinformatics tool that generates the largest amounts of data, and that is using the largest amount of CPU time in supercomputing centres. MD trajectories are obtained after months of calculations, analysed in situ, and in practice forgotten. Several projects to generate stable trajectory databases have been developed for proteins, but no equivalence exists in the nucleic acids world. We present here a novel database system to store MD trajectories and analyses of nucleic acids. The initial data set available consists mainly of the benchmark of the new molecular dynamics force-field, parmBSC1. It contains 156 simulations, with over 120 μs of total simulation time. A deposition protocol is available to accept the submission of new trajectory data. The database is based on the combination of two NoSQL engines, Cassandra for storing trajectories and MongoDB to store analysis results and simulation metadata. The analyses available include backbone geometries, helical analysis, NMR observables and a variety of mechanical analyses. Individual trajectories and combined meta-trajectories can be downloaded from the portal. The system is accessible through http://mmb.irbbarcelona.org/BIGNASim/. Supplementary Material is also available on-line at http://mmb.irbbarcelona.org/BIGNASim/SuppMaterial/. PMID:26612862
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OPERA-a human performance database under simulated emergencies of nuclear power plants
International Nuclear Information System (INIS)
Park, Jinkyun; Jung, Wondea
2007-01-01
In complex systems such as the nuclear and chemical industry, the importance of human performance related problems is well recognized. Thus a lot of effort has been spent on this area, and one of the main streams for unraveling human performance related problems is the execution of HRA. Unfortunately a lack of prerequisite information has been pointed out as the most critical problem in conducting HRA. From this necessity, OPERA database that can provide operators' performance data obtained under simulated emergencies has been developed. In this study, typical operators' performance data that are available from OPERA database are briefly explained. After that, in order to ensure the appropriateness of OPERA database, operators' performance data from OPERA database are compared with those of other studies and real events. As a result, it is believed that operators' performance data of OPERA database are fairly comparable to those of other studies and real events. Therefore it is meaningful to expect that OPERA database can be used as a serviceable data source for scrutinizing human performance related problems including HRA
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Imaging gait analysis: An fMRI dual task study.
Bürki, Céline N; Bridenbaugh, Stephanie A; Reinhardt, Julia; Stippich, Christoph; Kressig, Reto W; Blatow, Maria
2017-08-01
In geriatric clinical diagnostics, gait analysis with cognitive-motor dual tasking is used to predict fall risk and cognitive decline. To date, the neural correlates of cognitive-motor dual tasking processes are not fully understood. To investigate these underlying neural mechanisms, we designed an fMRI paradigm to reproduce the gait analysis. We tested the fMRI paradigm's feasibility in a substudy with fifteen young adults and assessed 31 healthy older adults in the main study. First, gait speed and variability were quantified using the GAITRite © electronic walkway. Then, participants lying in the MRI-scanner were stepping on pedals of an MRI-compatible stepping device used to imitate gait during functional imaging. In each session, participants performed cognitive and motor single tasks as well as cognitive-motor dual tasks. Behavioral results showed that the parameters of both gait analyses, GAITRite © and fMRI, were significantly positively correlated. FMRI results revealed significantly reduced brain activation during dual task compared to single task conditions. Functional ROI analysis showed that activation in the superior parietal lobe (SPL) decreased less from single to dual task condition than activation in primary motor cortex and in supplementary motor areas. Moreover, SPL activation was increased during dual tasks in subjects exhibiting lower stepping speed and lower executive control. We were able to simulate walking during functional imaging with valid results that reproduce those from the GAITRite © gait analysis. On the neural level, SPL seems to play a crucial role in cognitive-motor dual tasking and to be linked to divided attention processes, particularly when motor activity is involved.
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Task-related fMRI in hemiplegic cerebral palsy-A systematic review.
Gaberova, Katerina; Pacheva, Iliyana; Ivanov, Ivan
2018-04-27
Functional magnetic resonance imaging (fMRI) is used widely to study reorganization after early brain injuries. Unilateral cerebral palsy (UCP) is an appealing model for studying brain plasticity by fMRI. To summarize the results of task-related fMRI studies in UCP in order to get better understanding of the mechanism of neuroplasticity of the developing brain and its reorganization potential and better translation of this knowledge to clinical practice. A systematic search was conducted on the PubMed database by keywords: "cerebral palsy", "congenital hemiparesis", "unilateral", "Magnetic resonance imaging" , "fMRI", "reorganization", and "plasticity" The exclusion criteria were as follows: case reports; reviews; studies exploring non-UCP patients; and studies with results of rehabilitation. We found 7 articles investigated sensory tasks; 9 studies-motor tasks; 12 studies-speech tasks. Ipsilesional reorganization is dominant in sensory tasks (in 74/77 patients), contralesional-in only 3/77. In motor tasks, bilateral activation is found in 64/83, only contralesional-in 11/83, and only ipsilesional-8/83. Speech perception is bilateral in 35/51, only or dominantly ipsilesional (left-sided) in 8/51, and dominantly contralesional (right-sided) in 8/51. Speech production is only or dominantly contralesional (right-sided) in 88/130, bilateral-26/130, and only or dominantly ipsilesional (left-sided)-in 16/130. The sensory system is the most "rigid" to reorganization probably due to absence of ipsilateral (contralesional) primary somatosensory representation. The motor system is more "flexible" due to ipsilateral (contralesional) motor pathways. The speech perception and production show greater flexibility resulting in more bilateral or contralateral activation. The models of reorganization are variable, depending on the development and function of each neural system and the extent and timing of the damage. The plasticity patterns may guide therapeutic intervention and
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BIGNASim: a NoSQL database structure and analysis portal for nucleic acids simulation data.
Hospital, Adam; Andrio, Pau; Cugnasco, Cesare; Codo, Laia; Becerra, Yolanda; Dans, Pablo D; Battistini, Federica; Torres, Jordi; Goñi, Ramón; Orozco, Modesto; Gelpí, Josep Ll
2016-01-04
Molecular dynamics simulation (MD) is, just behind genomics, the bioinformatics tool that generates the largest amounts of data, and that is using the largest amount of CPU time in supercomputing centres. MD trajectories are obtained after months of calculations, analysed in situ, and in practice forgotten. Several projects to generate stable trajectory databases have been developed for proteins, but no equivalence exists in the nucleic acids world. We present here a novel database system to store MD trajectories and analyses of nucleic acids. The initial data set available consists mainly of the benchmark of the new molecular dynamics force-field, parmBSC1. It contains 156 simulations, with over 120 μs of total simulation time. A deposition protocol is available to accept the submission of new trajectory data. The database is based on the combination of two NoSQL engines, Cassandra for storing trajectories and MongoDB to store analysis results and simulation metadata. The analyses available include backbone geometries, helical analysis, NMR observables and a variety of mechanical analyses. Individual trajectories and combined meta-trajectories can be downloaded from the portal. The system is accessible through http://mmb.irbbarcelona.org/BIGNASim/. Supplementary Material is also available on-line at http://mmb.irbbarcelona.org/BIGNASim/SuppMaterial/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
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Resting state FMRI research in child psychiatric disorders
Oldehinkel, Marianne; Francx, Winke; Beckmann, Christian; Buitelaar, Jan K.; Mennes, Maarten
2013-01-01
Concurring with the shift from linking functions to specific brain areas towards studying network integration, resting state FMRI (R-FMRI) has become an important tool for delineating the functional network architecture of the brain. Fueled by straightforward data collection, R-FMRI analysis methods
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Strappini, Francesca; Gilboa, Elad; Pitzalis, Sabrina; Kay, Kendrick; McAvoy, Mark; Nehorai, Arye; Snyder, Abraham Z
2017-03-01
Temporal and spatial filtering of fMRI data is often used to improve statistical power. However, conventional methods, such as smoothing with fixed-width Gaussian filters, remove fine-scale structure in the data, necessitating a tradeoff between sensitivity and specificity. Specifically, smoothing may increase sensitivity (reduce noise and increase statistical power) but at the cost loss of specificity in that fine-scale structure in neural activity patterns is lost. Here, we propose an alternative smoothing method based on Gaussian processes (GP) regression for single subjects fMRI experiments. This method adapts the level of smoothing on a voxel by voxel basis according to the characteristics of the local neural activity patterns. GP-based fMRI analysis has been heretofore impractical owing to computational demands. Here, we demonstrate a new implementation of GP that makes it possible to handle the massive data dimensionality of the typical fMRI experiment. We demonstrate how GP can be used as a drop-in replacement to conventional preprocessing steps for temporal and spatial smoothing in a standard fMRI pipeline. We present simulated and experimental results that show the increased sensitivity and specificity compared to conventional smoothing strategies. Hum Brain Mapp 38:1438-1459, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
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fMRI. Basics and clinical applications
Energy Technology Data Exchange (ETDEWEB)
Ulmer, Stephan; Jansen, Olav (eds.) [University Hospital of Schleswig-Holstein, Kiel (Germany). Inst. of Neuroradiology, Neurocenter
2010-07-01
Functional MRI (fMRI) and the basic method of BOLD imaging were introduced in 1993 by Seiji Ogawa. From very basic experiments, fMRI has evolved into a clinical application for daily routine brain imaging. There have been various improvements in both the imaging technique as such as well as in the statistical analysis. In this volume, experts in the field share their knowledge and point out possible technical barriers and problems explaining how to solve them. Starting from the very basics on the origin of the BOLD signal, the book covers technical issues, anatomical landmarks, presurgical applications, and special issues in various clinical fields. Other modalities for brain mapping such as PET, TMS, and MEG are also compared with fMRI. This book is intended to give a state-of-the-art overview and to serve as a reference and guide for clinical applications of fMRI. (orig.)
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S-World: A high resolution global soil database for simulation modelling (Invited)
Stoorvogel, J. J.
2013-12-01
There is an increasing call for high resolution soil information at the global level. A good example for such a call is the Global Gridded Crop Model Intercomparison carried out within AgMIP. While local studies can make use of surveying techniques to collect additional techniques this is practically impossible at the global level. It is therefore important to rely on legacy data like the Harmonized World Soil Database. Several efforts do exist that aim at the development of global gridded soil property databases. These estimates of the variation of soil properties can be used to assess e.g., global soil carbon stocks. However, they do not allow for simulation runs with e.g., crop growth simulation models as these models require a description of the entire pedon rather than a few soil properties. This study provides the required quantitative description of pedons at a 1 km resolution for simulation modelling. It uses the Harmonized World Soil Database (HWSD) for the spatial distribution of soil types, the ISRIC-WISE soil profile database to derive information on soil properties per soil type, and a range of co-variables on topography, climate, and land cover to further disaggregate the available data. The methodology aims to take stock of these available data. The soil database is developed in five main steps. Step 1: All 148 soil types are ordered on the basis of their expected topographic position using e.g., drainage, salinization, and pedogenesis. Using the topographic ordering and combining the HWSD with a digital elevation model allows for the spatial disaggregation of the composite soil units. This results in a new soil map with homogeneous soil units. Step 2: The ranges of major soil properties for the topsoil and subsoil of each of the 148 soil types are derived from the ISRIC-WISE soil profile database. Step 3: A model of soil formation is developed that focuses on the basic conceptual question where we are within the range of a particular soil property
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An FMRI-compatible Symbol Search task.
Liebel, Spencer W; Clark, Uraina S; Xu, Xiaomeng; Riskin-Jones, Hannah H; Hawkshead, Brittany E; Schwarz, Nicolette F; Labbe, Donald; Jerskey, Beth A; Sweet, Lawrence H
2015-03-01
Our objective was to determine whether a Symbol Search paradigm developed for functional magnetic resonance imaging (FMRI) is a reliable and valid measure of cognitive processing speed (CPS) in healthy older adults. As all older adults are expected to experience cognitive declines due to aging, and CPS is one of the domains most affected by age, establishing a reliable and valid measure of CPS that can be administered inside an MR scanner may prove invaluable in future clinical and research settings. We evaluated the reliability and construct validity of a newly developed FMRI Symbol Search task by comparing participants' performance in and outside of the scanner and to the widely used and standardized Symbol Search subtest of the Wechsler Adult Intelligence Scale (WAIS). A brief battery of neuropsychological measures was also administered to assess the convergent and discriminant validity of the FMRI Symbol Search task. The FMRI Symbol Search task demonstrated high test-retest reliability when compared to performance on the same task administered out of the scanner (r=.791; pSymbol Search (r=.717; pSymbol Search task were also observed. The FMRI Symbol Search task is a reliable and valid measure of CPS in healthy older adults and exhibits expected sensitivity to the effects of age on CPS performance.
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Matrix-product-state simulation of an extended Brueschweiler bulk-ensemble database search
International Nuclear Information System (INIS)
SaiToh, Akira; Kitagawa, Masahiro
2006-01-01
Brueschweiler's database search in a spin Liouville space can be efficiently simulated on a conventional computer without error as long as the simulation cost of the internal circuit of an oracle function is polynomial, unlike the fact that in true NMR experiments, it suffers from an exponential decrease in the variation of a signal intensity. With the simulation method using the matrix-product-state proposed by Vidal [G. Vidal, Phys. Rev. Lett. 91, 147902 (2003)], we perform such a simulation. We also show the extensions of the algorithm without utilizing the J-coupling or DD-coupling splitting of frequency peaks in observation: searching can be completed with a single query in polynomial postoracle circuit complexities in an extension; multiple solutions of an oracle can be found in another extension whose query complexity is linear in the key length and in the number of solutions (this extension is to find all of marked keys). These extended algorithms are also simulated with the same simulation method
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Automated correction of spin-history related motion artefacts in fMRI : Simulated and phantom data
Muresan, L; Renken, R.; Roerdink, J.B.T.M.; Duifhuis, H.
This paper concerns the problem of correcting spin-history artefacts in fMRI data. We focus on the influence of through-plane motion on the history of magnetization. A change in object position will disrupt the tissue’s steady-state magnetization. The disruption will propagate to the next few
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Amir, Sahar Z.
2013-01-01
expensively simulated data points. The methods reweight and reconstruct previously generated database values of Markov chains at neighboring temperature and density conditions. To investigate the efficiency of these methods, two databases corresponding
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Directory of Open Access Journals (Sweden)
C. Hübler
2017-10-01
Full Text Available For the design and optimisation of offshore wind turbines, the knowledge of realistic environmental conditions and utilisation of well-founded simulation constraints is very important, as both influence the structural behaviour and power output in numerical simulations. However, real high-quality data, especially for research purposes, are scarcely available. This is why, in this work, a comprehensive database of 13 environmental conditions at wind turbine locations in the North and Baltic Sea is derived using data of the FINO research platforms. For simulation constraints, like the simulation length and the time of initial simulation transients, well-founded recommendations in the literature are also rare. Nevertheless, it is known that the choice of simulation lengths and times of initial transients fundamentally affects the quality and computing time of simulations. For this reason, studies of convergence for both parameters are conducted to determine adequate values depending on the type of substructure, the wind speed, and the considered loading (fatigue or ultimate. As the main purpose of both the database and the simulation constraints is to compromise realistic data for probabilistic design approaches and to serve as a guidance for further studies in order to enable more realistic and accurate simulations, all results are freely available and easy to apply.
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Comparison of direct numerical simulation databases of turbulent channel flow at Re = 180
Vreman, A.W.; Kuerten, J.G.M.
2014-01-01
Direct numerical simulation (DNS) databases are compared to assess the accuracy and reproducibility of standard and non-standard turbulence statistics of incompressible plane channel flow at Re t = 180. Two fundamentally different DNS codes are shown to produce maximum relative deviations below 0.2%
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MEG and fMRI fusion for nonlinear estimation of neural and BOLD signal changes
Directory of Open Access Journals (Sweden)
Sergey M Plis
2010-11-01
Full Text Available The combined analysis of MEG/EEG and functional MRI measurements can lead to improvement in the description of the dynamical and spatial properties of brain activity. In this paper we empirically demonstrate this improvement using simulated and recorded task related MEG and fMRI activity. Neural activity estimates were derived using a dynamic Bayesian network with continuous real valued parameters by means of a sequential Monte Carlo technique. In synthetic data, we show that MEG and fMRI fusion improves estimation of the indirectly observed neural activity and smooths tracking of the BOLD response. In recordings of task related neural activity the combination of MEG and fMRI produces a result with greater SNR, that confirms the expectation arising from the nature of the experiment. The highly nonlinear model of the BOLD response poses a difficult inference problem for neural activity estimation; computational requirements are also high due to the time and space complexity. We show that joint analysis of the data improves the system's behavior by stabilizing the differential equations system and by requiring fewer computational resources.
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Motor imagery training: Kinesthetic imagery strategy and inferior parietal fMRI activation.
Lebon, Florent; Horn, Ulrike; Domin, Martin; Lotze, Martin
2018-04-01
Motor imagery (MI) is the mental simulation of action frequently used by professionals in different fields. However, with respect to performance, well-controlled functional imaging studies on MI training are sparse. We investigated changes in fMRI representation going along with performance changes of a finger sequence (error and velocity) after MI training in 48 healthy young volunteers. Before training, we tested the vividness of kinesthetic and visual imagery. During tests, participants were instructed to move or to imagine moving the fingers of the right hand in a specific order. During MI training, participants repeatedly imagined the sequence for 15 min. Imaging analysis was performed using a full-factorial design to assess brain changes due to imagery training. We also used regression analyses to identify those who profited from training (performance outcome and gain) with initial imagery scores (vividness) and fMRI activation magnitude during MI at pre-test (MI pre ). After training, error rate decreased and velocity increased. We combined both parameters into a common performance index. FMRI activation in the left inferior parietal lobe (IPL) was associated with MI and increased over time. In addition, fMRI activation in the right IPL during MI pre was associated with high initial kinesthetic vividness. High kinesthetic imagery vividness predicted a high performance after training. In contrast, occipital activation, associated with visual imagery strategies, showed a negative predictive value for performance. Our data echo the importance of high kinesthetic vividness for MI training outcome and consider IPL as a key area during MI and through MI training. © 2018 Wiley Periodicals, Inc.
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Chiew, Mark; Graedel, Nadine N; Miller, Karla L
2018-07-01
Recent developments in highly accelerated fMRI data acquisition have employed low-rank and/or sparsity constraints for image reconstruction, as an alternative to conventional, time-independent parallel imaging. When under-sampling factors are high or the signals of interest are low-variance, however, functional data recovery can be poor or incomplete. We introduce a method for improving reconstruction fidelity using external constraints, like an experimental design matrix, to partially orient the estimated fMRI temporal subspace. Combining these external constraints with low-rank constraints introduces a new image reconstruction model that is analogous to using a mixture of subspace-decomposition (PCA/ICA) and regression (GLM) models in fMRI analysis. We show that this approach improves fMRI reconstruction quality in simulations and experimental data, focusing on the model problem of detecting subtle 1-s latency shifts between brain regions in a block-design task-fMRI experiment. Successful latency discrimination is shown at acceleration factors up to R = 16 in a radial-Cartesian acquisition. We show that this approach works with approximate, or not perfectly informative constraints, where the derived benefit is commensurate with the information content contained in the constraints. The proposed method extends low-rank approximation methods for under-sampled fMRI data acquisition by leveraging knowledge of expected task-based variance in the data, enabling improvements in the speed and efficiency of fMRI data acquisition without the loss of subtle features. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
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Dang, Shilpa; Chaudhury, Santanu; Lall, Brejesh; Roy, Prasun Kumar
2017-02-15
Effective connectivity (EC) analysis of neuronal groups using fMRI delivers insights about functional-integration. However, fMRI signal has low-temporal resolution due to down-sampling and indirectly measures underlying neuronal activity. The aim is to address above issues for more reliable EC estimates. This paper proposes use of autoregressive hidden Markov model with missing data (AR-HMM-md) in dynamically multi-linked (DML) framework for learning EC using multiple fMRI time series. In our recent work (Dang et al., 2016), we have shown how AR-HMM-md for modelling single fMRI time series outperforms the existing methods. AR-HMM-md models unobserved neuronal activity and lost data over time as variables and estimates their values by joint optimization given fMRI observation sequence. The effectiveness in learning EC is shown using simulated experiments. Also the effects of sampling and noise are studied on EC. Moreover, classification-experiments are performed for Attention-Deficit/Hyperactivity Disorder subjects and age-matched controls for performance evaluation of real data. Using Bayesian model selection, we see that the proposed model converged to higher log-likelihood and demonstrated that group-classification can be performed with higher cross-validation accuracy of above 94% using distinctive network EC which characterizes patients vs. The full data EC obtained from DML-AR-HMM-md is more consistent with previous literature than the classical multivariate Granger causality method. The proposed architecture leads to reliable estimates of EC than the existing latent models. This framework overcomes the disadvantage of low-temporal resolution and improves cross-validation accuracy significantly due to presence of missing data variables and autoregressive process. Copyright © 2016 Elsevier B.V. All rights reserved.
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Sutterer, Matthew J; Tranel, Daniel
2017-11-01
We highlight the past 25 years of cognitive neuroscience and neuropsychology, focusing on the impact to the field of the introduction in 1992 of functional MRI (fMRI). We reviewed the past 25 years of literature in cognitive neuroscience and neuropsychology, focusing on the relation and interplay of fMRI studies and studies utilizing the "lesion method" in human participants with focal brain damage. Our review highlights the state of localist/connectionist research debates in cognitive neuroscience and neuropsychology circa 1992, and details how the introduction of fMRI into the field at that time catalyzed a new wave of efforts to map complex human behavior to specific brain regions. This, in turn, eventually evolved into many studies that focused on networks and connections between brain areas, culminating in recent years with large-scale investigations such as the Human Connectome Project. We argue that throughout the past 25 years, neuropsychology-and more precisely, the "lesion method" in humans-has continued to play a critical role in arbitrating conclusions and theories derived from inferred patterns of local brain activity or wide-spread connectivity from functional imaging approaches. We conclude by highlighting the future for neuropsychology in the context of an increasingly complex methodological armamentarium. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
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Comparison of direct numerical simulation databases of turbulent channel flow at $Re_{\\tau}$ = 180
Vreman, A.W.; Kuerten, Johannes G.M.
2014-01-01
Direct numerical simulation (DNS) databases are compared to assess the accuracy and reproducibility of standard and non-standard turbulence statistics of incompressible plane channel flow at $Re_{\\tau}$ = 180. Two fundamentally different DNS codes are shown to produce maximum relative deviations
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Space-dependent effects of motion on the standard deviation of fMRI signals : a simulation study.
Renken, R; Muresan, L; Duifhuis, H; Roerdink, JBTM; Yaffe, MK; Antonuk, LE
2003-01-01
In fMRI, any fluctuation of signal intensity, not recognized as a result of a specific task, is treated as noise. One source for "noise" is subject motion. Normally, motion effects are reduced by applying realignment. We investigate how apt a realignment procedure is in removing motion-related
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Directory of Open Access Journals (Sweden)
Pierre Lafaye de Micheaux
2011-10-01
Full Text Available For statistical analysis of functional magnetic resonance imaging (fMRI data sets, we propose a data-driven approach based on independent component analysis (ICA implemented in a new version of the AnalyzeFMRI R package. For fMRI data sets, spatial dimension being much greater than temporal dimension, spatial ICA is the computationally tractable approach generally proposed. However, for some neuroscientific applications, temporal independence of source signals can be assumed and temporal ICA becomes then an attractive exploratory technique. In this work, we use a classical linear algebra result ensuring the tractability of temporal ICA. We report several experiments on synthetic data and real MRI data sets that demonstrate the potential interest of our R package.
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Timothy A. Bottomley
2008-01-01
The BLM uses a database, called the Forest Vegetation Information System (FORVIS), to store, retrieve, and analyze forest resource information on a majority of their forested lands. FORVIS also has the capability of easily transferring appropriate data electronically into Forest Vegetation Simulator (FVS) for simulation runs. Only minor additional data inputs or...
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International Nuclear Information System (INIS)
Papadimitroulas, Panagiotis; Efthimiou, Nikos; Nikiforidis, George C.; Kagadis, George C.; Loudos, George; Le Maitre, Amandine; Hatt, Mathieu; Tixier, Florent; Visvikis, Dimitris
2013-01-01
Purpose: The GATE Monte Carlo simulation toolkit is used for the implementation of realistic PET simulations incorporating tumor heterogeneous activity distributions. The reconstructed patient images include noise from the acquisition process, imaging system's performance restrictions and have limited spatial resolution. For those reasons, the measured intensity cannot be simply introduced in GATE simulations, to reproduce clinical data. Investigation of the heterogeneity distribution within tumors applying partial volume correction (PVC) algorithms was assessed. The purpose of the present study was to create a simulated oncology database based on clinical data with realistic intratumor uptake heterogeneity properties.Methods: PET/CT data of seven oncology patients were used in order to create a realistic tumor database investigating the heterogeneity activity distribution of the simulated tumors. The anthropomorphic models (NURBS based cardiac torso and Zubal phantoms) were adapted to the CT data of each patient, and the activity distribution was extracted from the respective PET data. The patient-specific models were simulated with the Monte Carlo Geant4 application for tomography emission (GATE) in three different levels for each case: (a) using homogeneous activity within the tumor, (b) using heterogeneous activity distribution in every voxel within the tumor as it was extracted from the PET image, and (c) using heterogeneous activity distribution corresponding to the clinical image following PVC. The three different types of simulated data in each case were reconstructed with two iterations and filtered with a 3D Gaussian postfilter, in order to simulate the intratumor heterogeneous uptake. Heterogeneity in all generated images was quantified using textural feature derived parameters in 3D according to the ground truth of the simulation, and compared to clinical measurements. Finally, profiles were plotted in central slices of the tumors, across lines with
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Uemachi flexure zone investigated by borehole database and numeical simulation
Inoue, N.; Kitada, N.; Takemura, K.
2014-12-01
The Uemachi fault zone extending north and south, locates in the center of the Osaka City, in Japan. The Uemachi fault is a blind reverse fault and forms the flexure zone. The effects of the Uemachi flexure zone are considered in constructing of lifelines and buildings. In this region, the geomorphological survey is difficult because of the regression of transgression. Many organizations have carried out investigations of fault structures. Various surveys have been conducted, such as seismic reflection survey in and around Osaka. Many borehole data for construction conformations have been collected and the geotechnical borehole database has been constructed. The investigation with several geological borehole data provides the subsurface geological information to the geotechnical borehole database. Various numerical simulations have been carried out to investigate the growth of a blind reverse fault in unconsolidated sediments. The displacement of the basement was given in two ways. One is based on the fault movement, such as dislocation model, the other is a movement of basement block of hanging wall. The Drucker-Prager and elastic model were used for the sediment and basement, respectively. The simulation with low and high angle fault movements, show the good agree with the actual distribution of the marine clay inferred from borehole data in the northern and southern Uemachi fault flexure zone, respectively. This research is partly funded by the Comprehensive Research on the Uemachi Fault Zone (from FY2010 to FY2012) by The Ministry of Education, Culture, Sports, Science and Technology (MEXT).
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Behavior, neuropsychology and fMRI.
Bennett, Maxwell R; Hatton, Sean; Hermens, Daniel F; Lagopoulos, Jim
Cognitive neuroscientists in the late 20th century began the task of identifying the part(s) of the brain concerned with normal behavior as manifest in the psychological capacities as affective powers, reasoning, behaving purposively and the pursuit of goals, following introduction of the 'functional magnetic resonance imaging' (fMRI) method for identifying brain activity. For this research program to be successful two questions require satisfactory answers. First, as the fMRI method can currently only be used on stationary subjects, to what extent can neuropsychological tests applicable to such stationary subjects be correlated with normal behavior. Second, to what extent can correlations between the various neuropsychological tests on the one hand, and sites of brain activity determined with fMRI on the other, be regarded as established. The extent to which these questions have yet received satisfactory answers is reviewed, and suggestions made both for improving correlations of neuropsychological tests with behavior as well as with the results of fMRI-based observations. Copyright © 2016. Published by Elsevier Ltd.
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PARTICLE FILTERING WITH SEQUENTIAL PARAMETER LEARNING FOR NONLINEAR BOLD fMRI SIGNALS.
Xia, Jing; Wang, Michelle Yongmei
Analyzing the blood oxygenation level dependent (BOLD) effect in the functional magnetic resonance imaging (fMRI) is typically based on recent ground-breaking time series analysis techniques. This work represents a significant improvement over existing approaches to system identification using nonlinear hemodynamic models. It is important for three reasons. First, instead of using linearized approximations of the dynamics, we present a nonlinear filtering based on the sequential Monte Carlo method to capture the inherent nonlinearities in the physiological system. Second, we simultaneously estimate the hidden physiological states and the system parameters through particle filtering with sequential parameter learning to fully take advantage of the dynamic information of the BOLD signals. Third, during the unknown static parameter learning, we employ the low-dimensional sufficient statistics for efficiency and avoiding potential degeneration of the parameters. The performance of the proposed method is validated using both the simulated data and real BOLD fMRI data.
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Indian Academy of Sciences (India)
Home; Journals; Journal of Biosciences; Volume 38; Issue 5 ... Alcoholism; brain; fMRI; language processing; lexical; semantic judgment ... alcohol dependence is associated with neurocognitive deficits in tasks requiring memory, perceptual ...
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Advances in fMRI Real-Time Neurofeedback.
Watanabe, Takeo; Sasaki, Yuka; Shibata, Kazuhisa; Kawato, Mitsuo
2017-12-01
Functional magnetic resonance imaging (fMRI) neurofeedback is a type of biofeedback in which real-time online fMRI signals are used to self-regulate brain function. Since its advent in 2003 significant progress has been made in fMRI neurofeedback techniques. Specifically, the use of implicit protocols, external rewards, multivariate analysis, and connectivity analysis has allowed neuroscientists to explore a possible causal involvement of modified brain activity in modified behavior. These techniques have also been integrated into groundbreaking new neurofeedback technologies, specifically decoded neurofeedback (DecNef) and functional connectivity-based neurofeedback (FCNef). By modulating neural activity and behavior, DecNef and FCNef have substantially advanced both basic and clinical research. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
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Nguyen, Thinh; Potter, Thomas; Grossman, Robert; Zhang, Yingchun
2018-06-01
Objective. Neuroimaging has been employed as a promising approach to advance our understanding of brain networks in both basic and clinical neuroscience. Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) represent two neuroimaging modalities with complementary features; EEG has high temporal resolution and low spatial resolution while fMRI has high spatial resolution and low temporal resolution. Multimodal EEG inverse methods have attempted to capitalize on these properties but have been subjected to localization error. The dynamic brain transition network (DBTN) approach, a spatiotemporal fMRI constrained EEG source imaging method, has recently been developed to address these issues by solving the EEG inverse problem in a Bayesian framework, utilizing fMRI priors in a spatial and temporal variant manner. This paper presents a computer simulation study to provide a detailed characterization of the spatial and temporal accuracy of the DBTN method. Approach. Synthetic EEG data were generated in a series of computer simulations, designed to represent realistic and complex brain activity at superficial and deep sources with highly dynamical activity time-courses. The source reconstruction performance of the DBTN method was tested against the fMRI-constrained minimum norm estimates algorithm (fMRIMNE). The performances of the two inverse methods were evaluated both in terms of spatial and temporal accuracy. Main results. In comparison with the commonly used fMRIMNE method, results showed that the DBTN method produces results with increased spatial and temporal accuracy. The DBTN method also demonstrated the capability to reduce crosstalk in the reconstructed cortical time-course(s) induced by neighboring regions, mitigate depth bias and improve overall localization accuracy. Significance. The improved spatiotemporal accuracy of the reconstruction allows for an improved characterization of complex neural activity. This improvement can be
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EEG-Informed fMRI: A Review of Data Analysis Methods
Abreu, Rodolfo; Leal, Alberto; Figueiredo, Patrícia
2018-01-01
The simultaneous acquisition of electroencephalography (EEG) with functional magnetic resonance imaging (fMRI) is a very promising non-invasive technique for the study of human brain function. Despite continuous improvements, it remains a challenging technique, and a standard methodology for data analysis is yet to be established. Here we review the methodologies that are currently available to address the challenges at each step of the data analysis pipeline. We start by surveying methods for pre-processing both EEG and fMRI data. On the EEG side, we focus on the correction for several MR-induced artifacts, particularly the gradient and pulse artifacts, as well as other sources of EEG artifacts. On the fMRI side, we consider image artifacts induced by the presence of EEG hardware inside the MR scanner, and the contamination of the fMRI signal by physiological noise of non-neuronal origin, including a review of several approaches to model and remove it. We then provide an overview of the approaches specifically employed for the integration of EEG and fMRI when using EEG to predict the blood oxygenation level dependent (BOLD) fMRI signal, the so-called EEG-informed fMRI integration strategy, the most commonly used strategy in EEG-fMRI research. Finally, we systematically review methods used for the extraction of EEG features reflecting neuronal phenomena of interest. PMID:29467634
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EEG-Informed fMRI: A Review of Data Analysis Methods
Directory of Open Access Journals (Sweden)
Rodolfo Abreu
2018-02-01
Full Text Available The simultaneous acquisition of electroencephalography (EEG with functional magnetic resonance imaging (fMRI is a very promising non-invasive technique for the study of human brain function. Despite continuous improvements, it remains a challenging technique, and a standard methodology for data analysis is yet to be established. Here we review the methodologies that are currently available to address the challenges at each step of the data analysis pipeline. We start by surveying methods for pre-processing both EEG and fMRI data. On the EEG side, we focus on the correction for several MR-induced artifacts, particularly the gradient and pulse artifacts, as well as other sources of EEG artifacts. On the fMRI side, we consider image artifacts induced by the presence of EEG hardware inside the MR scanner, and the contamination of the fMRI signal by physiological noise of non-neuronal origin, including a review of several approaches to model and remove it. We then provide an overview of the approaches specifically employed for the integration of EEG and fMRI when using EEG to predict the blood oxygenation level dependent (BOLD fMRI signal, the so-called EEG-informed fMRI integration strategy, the most commonly used strategy in EEG-fMRI research. Finally, we systematically review methods used for the extraction of EEG features reflecting neuronal phenomena of interest.
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Monkey cortex through fMRI glasses.
Vanduffel, Wim; Zhu, Qi; Orban, Guy A
2014-08-06
In 1998 several groups reported the feasibility of fMRI experiments in monkeys, with the goal to bridge the gap between invasive nonhuman primate studies and human functional imaging. These studies yielded critical insights in the neuronal underpinnings of the BOLD signal. Furthermore, the technology has been successful in guiding electrophysiological recordings and identifying focal perturbation targets. Finally, invaluable information was obtained concerning human brain evolution. We here provide a comprehensive overview of awake monkey fMRI studies mainly confined to the visual system. We review the latest insights about the topographic organization of monkey visual cortex and discuss the spatial relationships between retinotopy and category- and feature-selective clusters. We briefly discuss the functional layout of parietal and frontal cortex and continue with a summary of some fascinating functional and effective connectivity studies. Finally, we review recent comparative fMRI experiments and speculate about the future of nonhuman primate imaging. Copyright © 2014 Elsevier Inc. All rights reserved.
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Improving fMRI reliability in presurgical mapping for brain tumours.
Stevens, M Tynan R; Clarke, David B; Stroink, Gerhard; Beyea, Steven D; D'Arcy, Ryan Cn
2016-03-01
Functional MRI (fMRI) is becoming increasingly integrated into clinical practice for presurgical mapping. Current efforts are focused on validating data quality, with reliability being a major factor. In this paper, we demonstrate the utility of a recently developed approach that uses receiver operating characteristic-reliability (ROC-r) to: (1) identify reliable versus unreliable data sets; (2) automatically select processing options to enhance data quality; and (3) automatically select individualised thresholds for activation maps. Presurgical fMRI was conducted in 16 patients undergoing surgical treatment for brain tumours. Within-session test-retest fMRI was conducted, and ROC-reliability of the patient group was compared to a previous healthy control cohort. Individually optimised preprocessing pipelines were determined to improve reliability. Spatial correspondence was assessed by comparing the fMRI results to intraoperative cortical stimulation mapping, in terms of the distance to the nearest active fMRI voxel. The average ROC-r reliability for the patients was 0.58±0.03, as compared to 0.72±0.02 in healthy controls. For the patient group, this increased significantly to 0.65±0.02 by adopting optimised preprocessing pipelines. Co-localisation of the fMRI maps with cortical stimulation was significantly better for more reliable versus less reliable data sets (8.3±0.9 vs 29±3 mm, respectively). We demonstrated ROC-r analysis for identifying reliable fMRI data sets, choosing optimal postprocessing pipelines, and selecting patient-specific thresholds. Data sets with higher reliability also showed closer spatial correspondence to cortical stimulation. ROC-r can thus identify poor fMRI data at time of scanning, allowing for repeat scans when necessary. ROC-r analysis provides optimised and automated fMRI processing for improved presurgical mapping. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence
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fMRI. Basics and clinical applications. 2. ed.
Energy Technology Data Exchange (ETDEWEB)
Ulmer, Stephan [Medizinisch Radiologisces Institut (MRI), Zuerich (Switzerland); Universitaetsklinikum Schleswig-Holstein, Kiel (Germany). Inst. fuer Neuroradiologie; Jansen, Olav (eds.) [Universitaetsklinikum Schleswig-Holstein, Kiel (Germany). Inst. fuer Neuroradiologie
2013-11-01
State of the art overview of fMRI. Covers technical issues, methods of statistical analysis, and the full range of clinical applications. Revised and expanded edition including discussion of novel aspects of analysis and further important applications. Includes comparisons with other brain mapping techniques and discussion of potential combined uses. Since functional MRI (fMRI) and the basic method of BOLD imaging were introduced in 1993 by Seiji Ogawa, fMRI has evolved into an invaluable clinical tool for routine brain imaging, and there have been substantial improvements in both the imaging technique itself and the associated statistical analysis. This book provides a state of the art overview of fMRI and its use in clinical practice. Experts in the field share their knowledge and explain how to overcome diverse potential technical barriers and problems. Starting from the very basics on the origin of the BOLD signal, the book covers technical issues, anatomical landmarks, the full range of clinical applications, methods of statistical analysis, and special issues in various clinical fields. Comparisons are made with other brain mapping techniques, such as DTI, PET, TMS, EEG, and MEG, and their combined use with fMRI is also discussed. Since the first edition, original chapters have been updated and new chapters added, covering both novel aspects of analysis and further important clinical applications.
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cudaBayesreg: Parallel Implementation of a Bayesian Multilevel Model for fMRI Data Analysis
Directory of Open Access Journals (Sweden)
Adelino R. Ferreira da Silva
2011-10-01
Full Text Available Graphic processing units (GPUs are rapidly gaining maturity as powerful general parallel computing devices. A key feature in the development of modern GPUs has been the advancement of the programming model and programming tools. Compute Unified Device Architecture (CUDA is a software platform for massively parallel high-performance computing on Nvidia many-core GPUs. In functional magnetic resonance imaging (fMRI, the volume of the data to be processed, and the type of statistical analysis to perform call for high-performance computing strategies. In this work, we present the main features of the R-CUDA package cudaBayesreg which implements in CUDA the core of a Bayesian multilevel model for the analysis of brain fMRI data. The statistical model implements a Gibbs sampler for multilevel/hierarchical linear models with a normal prior. The main contribution for the increased performance comes from the use of separate threads for fitting the linear regression model at each voxel in parallel. The R-CUDA implementation of the Bayesian model proposed here has been able to reduce significantly the run-time processing of Markov chain Monte Carlo (MCMC simulations used in Bayesian fMRI data analyses. Presently, cudaBayesreg is only configured for Linux systems with Nvidia CUDA support.
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High-field fMRI unveils orientation columns in humans.
Yacoub, Essa; Harel, Noam; Ugurbil, Kâmil
2008-07-29
Functional (f)MRI has revolutionized the field of human brain research. fMRI can noninvasively map the spatial architecture of brain function via localized increases in blood flow after sensory or cognitive stimulation. Recent advances in fMRI have led to enhanced sensitivity and spatial accuracy of the measured signals, indicating the possibility of detecting small neuronal ensembles that constitute fundamental computational units in the brain, such as cortical columns. Orientation columns in visual cortex are perhaps the best known example of such a functional organization in the brain. They cannot be discerned via anatomical characteristics, as with ocular dominance columns. Instead, the elucidation of their organization requires functional imaging methods. However, because of insufficient sensitivity, spatial accuracy, and image resolution of the available mapping techniques, thus far, they have not been detected in humans. Here, we demonstrate, by using high-field (7-T) fMRI, the existence and spatial features of orientation- selective columns in humans. Striking similarities were found with the known spatial features of these columns in monkeys. In addition, we found that a larger number of orientation columns are devoted to processing orientations around 90 degrees (vertical stimuli with horizontal motion), whereas relatively similar fMRI signal changes were observed across any given active column. With the current proliferation of high-field MRI systems and constant evolution of fMRI techniques, this study heralds the exciting prospect of exploring unmapped and/or unknown columnar level functional organizations in the human brain.
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Automated selection of brain regions for real-time fMRI brain-computer interfaces
Lührs, Michael; Sorger, Bettina; Goebel, Rainer; Esposito, Fabrizio
2017-02-01
Objective. Brain-computer interfaces (BCIs) implemented with real-time functional magnetic resonance imaging (rt-fMRI) use fMRI time-courses from predefined regions of interest (ROIs). To reach best performances, localizer experiments and on-site expert supervision are required for ROI definition. To automate this step, we developed two unsupervised computational techniques based on the general linear model (GLM) and independent component analysis (ICA) of rt-fMRI data, and compared their performances on a communication BCI. Approach. 3 T fMRI data of six volunteers were re-analyzed in simulated real-time. During a localizer run, participants performed three mental tasks following visual cues. During two communication runs, a letter-spelling display guided the subjects to freely encode letters by performing one of the mental tasks with a specific timing. GLM- and ICA-based procedures were used to decode each letter, respectively using compact ROIs and whole-brain distributed spatio-temporal patterns of fMRI activity, automatically defined from subject-specific or group-level maps. Main results. Letter-decoding performances were comparable to supervised methods. In combination with a similarity-based criterion, GLM- and ICA-based approaches successfully decoded more than 80% (average) of the letters. Subject-specific maps yielded optimal performances. Significance. Automated solutions for ROI selection may help accelerating the translation of rt-fMRI BCIs from research to clinical applications.
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Broadband Electrophysiological Dynamics Contribute to Global Resting-State fMRI Signal.
Wen, Haiguang; Liu, Zhongming
2016-06-01
Spontaneous activity observed with resting-state fMRI is used widely to uncover the brain's intrinsic functional networks in health and disease. Although many networks appear modular and specific, global and nonspecific fMRI fluctuations also exist and both pose a challenge and present an opportunity for characterizing and understanding brain networks. Here, we used a multimodal approach to investigate the neural correlates to the global fMRI signal in the resting state. Like fMRI, resting-state power fluctuations of broadband and arrhythmic, or scale-free, macaque electrocorticography and human magnetoencephalography activity were correlated globally. The power fluctuations of scale-free human electroencephalography (EEG) were coupled with the global component of simultaneously acquired resting-state fMRI, with the global hemodynamic change lagging the broadband spectral change of EEG by ∼5 s. The levels of global and nonspecific fluctuation and synchronization in scale-free population activity also varied across and depended on arousal states. Together, these results suggest that the neural origin of global resting-state fMRI activity is the broadband power fluctuation in scale-free population activity observable with macroscopic electrical or magnetic recordings. Moreover, the global fluctuation in neurophysiological and hemodynamic activity is likely modulated through diffuse neuromodulation pathways that govern arousal states and vigilance levels. This study provides new insights into the neural origin of resting-state fMRI. Results demonstrate that the broadband power fluctuation of scale-free electrophysiology is globally synchronized and directly coupled with the global component of spontaneous fMRI signals, in contrast to modularly synchronized fluctuations in oscillatory neural activity. These findings lead to a new hypothesis that scale-free and oscillatory neural processes account for global and modular patterns of functional connectivity observed
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Real-time functional MR imaging (fMRI) for presurgical evaluation of paediatric epilepsy
Energy Technology Data Exchange (ETDEWEB)
Kesavadas, Chandrasekharan; Thomas, Bejoy; Kumar Gupta, Arun [Sree Chitra Tirunal Institute for Medical Sciences and Technology, Department of Imaging Sciences and Interventional Radiology, Trivandrum (India); Sujesh, Sreedharan [Sree Chitra Tirunal Institute for Medical Sciences and Technology, Biomedical Technology Wing, Trivandrum (India); Ashalata, Radhakrishnan; Radhakrishnan, Kurupath [Sree Chitra Tirunal Institute for Medical Sciences and Technology, Department of Neurology, Trivandrum (India); Abraham, Mathew [Sree Chitra Tirunal Institute for Medical Sciences and Technology, Department of Neurosurgery, Trivandrum (India)
2007-10-15
The role of fMRI in the presurgical evaluation of children with intractable epilepsy is being increasingly recognized. Real-time fMRI allows the clinician to visualize functional brain activation in real time. Since there is no off-line data analysis as in conventional fMRI, the overall time for the procedure is reduced, making it clinically feasible in a busy clinical sitting. (1) To study the accuracy of real-time fMRI in comparison to conventional fMRI with off-line processing; (2) to determine its effectiveness in mapping the eloquent cortex and language lateralization in comparison to invasive procedures such as intraoperative cortical stimulation and Wada testing; and (3) to evaluate the role of fMRI in presurgical decision making in children with epilepsy. A total of 23 patients (age range 6-18 years) underwent fMRI with sensorimotor, visual and language paradigms. Data processing was done in real time using in-line BOLD. The results of real-time fMRI matched those of off-line processing done using the well-accepted standard technique of statistical parametric mapping (SPM) in all the initial ten patients in whom the two techniques were compared. Coregistration of the fMRI data on a 3-D FLAIR sequence rather than a T1-weighted image gave better information regarding the relationship of the lesion to the area of activation. The results of intraoperative cortical stimulation and fMRI matched in six out of six patients, while the Wada test and fMRI had similar results in four out of five patients in whom these techniques were performed. In the majority of patients in this series the technique influenced patient management. Real-time fMRI is an easily performed and reliable technique in the presurgical workup of children with epilepsy. (orig.)
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Real-time functional MR imaging (fMRI) for presurgical evaluation of paediatric epilepsy
International Nuclear Information System (INIS)
Kesavadas, Chandrasekharan; Thomas, Bejoy; Kumar Gupta, Arun; Sujesh, Sreedharan; Ashalata, Radhakrishnan; Radhakrishnan, Kurupath; Abraham, Mathew
2007-01-01
The role of fMRI in the presurgical evaluation of children with intractable epilepsy is being increasingly recognized. Real-time fMRI allows the clinician to visualize functional brain activation in real time. Since there is no off-line data analysis as in conventional fMRI, the overall time for the procedure is reduced, making it clinically feasible in a busy clinical sitting. (1) To study the accuracy of real-time fMRI in comparison to conventional fMRI with off-line processing; (2) to determine its effectiveness in mapping the eloquent cortex and language lateralization in comparison to invasive procedures such as intraoperative cortical stimulation and Wada testing; and (3) to evaluate the role of fMRI in presurgical decision making in children with epilepsy. A total of 23 patients (age range 6-18 years) underwent fMRI with sensorimotor, visual and language paradigms. Data processing was done in real time using in-line BOLD. The results of real-time fMRI matched those of off-line processing done using the well-accepted standard technique of statistical parametric mapping (SPM) in all the initial ten patients in whom the two techniques were compared. Coregistration of the fMRI data on a 3-D FLAIR sequence rather than a T1-weighted image gave better information regarding the relationship of the lesion to the area of activation. The results of intraoperative cortical stimulation and fMRI matched in six out of six patients, while the Wada test and fMRI had similar results in four out of five patients in whom these techniques were performed. In the majority of patients in this series the technique influenced patient management. Real-time fMRI is an easily performed and reliable technique in the presurgical workup of children with epilepsy. (orig.)
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Robust Estimation of HDR in fMRI using H-infinity Filters
DEFF Research Database (Denmark)
Puthusserypady, Sadasivan; Jue, R.; Ratnarajah, T.
2010-01-01
Estimation and detection of the hemodynamic response (HDR) are of great importance in functional MRI (fMRI) data analysis. In this paper, we propose the use of three H-infinity adaptive filters (finite memory, exponentially weighted, and timevarying) for accurate estimation and detection of the HDR......-1487]. Performances of the proposed techniques are compared to the conventional t-test method as well as the well-known LMSs and recursive least squares algorithms. Extensive numerical simulations show that the proposed methods result in better HDR estimations and activation detections....
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Activation Detection in fMRI Using Jeffrey Divergence
Seghouane, Abd-Krim
2009-12-01
A statistical test for detecting activated pixels in functional MRI (fMRI) data is proposed. For the derivation of this test, the fMRI time series measured at each voxel is modeled as the sum of a response signal which arises due to the experimentally controlled activation-baseline pattern, a nuisance component representing effects of no interest, and Gaussian white noise. The test is based on comparing the dimension of the voxels fMRI time series fitted data models with and without controlled activation-baseline pattern. The Jeffrey divergence is used for this comparison. The test has the advantage of not requiring a level of significance or a threshold to be provided.
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Statistical Analysis Methods for the fMRI Data
Directory of Open Access Journals (Sweden)
Huseyin Boyaci
2011-08-01
Full Text Available Functional magnetic resonance imaging (fMRI is a safe and non-invasive way to assess brain functions by using signal changes associated with brain activity. The technique has become a ubiquitous tool in basic, clinical and cognitive neuroscience. This method can measure little metabolism changes that occur in active part of the brain. We process the fMRI data to be able to find the parts of brain that are involve in a mechanism, or to determine the changes that occur in brain activities due to a brain lesion. In this study we will have an overview over the methods that are used for the analysis of fMRI data.
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Adaptation of a haptic robot in a 3T fMRI.
Snider, Joseph; Plank, Markus; May, Larry; Liu, Thomas T; Poizner, Howard
2011-10-04
Functional magnetic resonance imaging (fMRI) provides excellent functional brain imaging via the BOLD signal with advantages including non-ionizing radiation, millimeter spatial accuracy of anatomical and functional data, and nearly real-time analyses. Haptic robots provide precise measurement and control of position and force of a cursor in a reasonably confined space. Here we combine these two technologies to allow precision experiments involving motor control with haptic/tactile environment interaction such as reaching or grasping. The basic idea is to attach an 8 foot end effecter supported in the center to the robot allowing the subject to use the robot, but shielding it and keeping it out of the most extreme part of the magnetic field from the fMRI machine (Figure 1). The Phantom Premium 3.0, 6DoF, high-force robot (SensAble Technologies, Inc.) is an excellent choice for providing force-feedback in virtual reality experiments, but it is inherently non-MR safe, introduces significant noise to the sensitive fMRI equipment, and its electric motors may be affected by the fMRI's strongly varying magnetic field. We have constructed a table and shielding system that allows the robot to be safely introduced into the fMRI environment and limits both the degradation of the fMRI signal by the electrically noisy motors and the degradation of the electric motor performance by the strongly varying magnetic field of the fMRI. With the shield, the signal to noise ratio (SNR: mean signal/noise standard deviation) of the fMRI goes from a baseline of ~380 to ~330, and ~250 without the shielding. The remaining noise appears to be uncorrelated and does not add artifacts to the fMRI of a test sphere (Figure 2). The long, stiff handle allows placement of the robot out of range of the most strongly varying parts of the magnetic field so there is no significant effect of the fMRI on the robot. The effect of the handle on the robot's kinematics is minimal since it is lightweight (~2
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Acoustic fMRI noise : Linear time-invariant system model
Sierra, Carlos V. Rizzo; Versluis, Maarten J.; Hoogduin, Johannes M.; Duifhuis, Hendrikus (Diek)
Functional magnetic resonance imaging (fMRI) enables sites of brain activation to be localized in human subjects. For auditory system studies, however, the acoustic noise generated by the scanner tends to interfere with the assessments of this activation. Understanding and modeling fMRI acoustic
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Ferrazzi, Giulio; Kuklisova Murgasova, Maria; Arichi, Tomoki; Malamateniou, Christina; Fox, Matthew J; Makropoulos, Antonios; Allsop, Joanna; Rutherford, Mary; Malik, Shaihan; Aljabar, Paul; Hajnal, Joseph V
2014-11-01
There is growing interest in exploring fetal functional brain development, particularly with Resting State fMRI. However, during a typical fMRI acquisition, the womb moves due to maternal respiration and the fetus may perform large-scale and unpredictable movements. Conventional fMRI processing pipelines, which assume that brain movements are infrequent or at least small, are not suitable. Previous published studies have tackled this problem by adopting conventional methods and discarding as much as 40% or more of the acquired data. In this work, we developed and tested a processing framework for fetal Resting State fMRI, capable of correcting gross motion. The method comprises bias field and spin history corrections in the scanner frame of reference, combined with slice to volume registration and scattered data interpolation to place all data into a consistent anatomical space. The aim is to recover an ordered set of samples suitable for further analysis using standard tools such as Group Independent Component Analysis (Group ICA). We have tested the approach using simulations and in vivo data acquired at 1.5 T. After full motion correction, Group ICA performed on a population of 8 fetuses extracted 20 networks, 6 of which were identified as matching those previously observed in preterm babies. Copyright © 2014 Elsevier Inc. All rights reserved.
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Energy Technology Data Exchange (ETDEWEB)
Papadimitroulas, Panagiotis; Efthimiou, Nikos; Nikiforidis, George C.; Kagadis, George C. [Department of Medical Physics, School of Medicine, University of Patras, Rion, GR 265 04 (Greece); Loudos, George [Department of Biomedical Engineering, Technological Educational Institute of Athens, Ag. Spyridonos Street, Egaleo GR 122 10, Athens (Greece); Le Maitre, Amandine; Hatt, Mathieu; Tixier, Florent; Visvikis, Dimitris [Medical Information Processing Laboratory (LaTIM), National Institute of Health and Medical Research (INSERM), 29609 Brest (France)
2013-11-15
Purpose: The GATE Monte Carlo simulation toolkit is used for the implementation of realistic PET simulations incorporating tumor heterogeneous activity distributions. The reconstructed patient images include noise from the acquisition process, imaging system's performance restrictions and have limited spatial resolution. For those reasons, the measured intensity cannot be simply introduced in GATE simulations, to reproduce clinical data. Investigation of the heterogeneity distribution within tumors applying partial volume correction (PVC) algorithms was assessed. The purpose of the present study was to create a simulated oncology database based on clinical data with realistic intratumor uptake heterogeneity properties.Methods: PET/CT data of seven oncology patients were used in order to create a realistic tumor database investigating the heterogeneity activity distribution of the simulated tumors. The anthropomorphic models (NURBS based cardiac torso and Zubal phantoms) were adapted to the CT data of each patient, and the activity distribution was extracted from the respective PET data. The patient-specific models were simulated with the Monte Carlo Geant4 application for tomography emission (GATE) in three different levels for each case: (a) using homogeneous activity within the tumor, (b) using heterogeneous activity distribution in every voxel within the tumor as it was extracted from the PET image, and (c) using heterogeneous activity distribution corresponding to the clinical image following PVC. The three different types of simulated data in each case were reconstructed with two iterations and filtered with a 3D Gaussian postfilter, in order to simulate the intratumor heterogeneous uptake. Heterogeneity in all generated images was quantified using textural feature derived parameters in 3D according to the ground truth of the simulation, and compared to clinical measurements. Finally, profiles were plotted in central slices of the tumors, across lines
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A kinetics database and scripts for PHREEQC
Hu, B.; Zhang, Y.; Teng, Y.; Zhu, C.
2017-12-01
Kinetics of geochemical reactions has been increasingly used in numerical models to simulate coupled flow, mass transport, and chemical reactions. However, the kinetic data are scattered in the literature. To assemble a kinetic dataset for a modeling project is an intimidating task for most. In order to facilitate the application of kinetics in geochemical modeling, we assembled kinetics parameters into a database for the geochemical simulation program, PHREEQC (version 3.0). Kinetics data were collected from the literature. Our database includes kinetic data for over 70 minerals. The rate equations are also programmed into scripts with the Basic language. Using the new kinetic database, we simulated reaction path during the albite dissolution process using various rate equations in the literature. The simulation results with three different rate equations gave difference reaction paths at different time scale. Another application involves a coupled reactive transport model simulating the advancement of an acid plume in an acid mine drainage site associated with Bear Creek Uranium tailings pond. Geochemical reactions including calcite, gypsum, and illite were simulated with PHREEQC using the new kinetic database. The simulation results successfully demonstrated the utility of new kinetic database.
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Functional connectivity analysis of the brain network using resting-state fMRI
International Nuclear Information System (INIS)
Hayashi, Toshihiro
2011-01-01
Spatial patterns of spontaneous fluctuations in blood oxygenation level-dependent (BOLD) signals reflect the underlying neural architecture. The study of the brain network based on these self-organized patterns is termed resting-state functional MRI (fMRI). This review article aims at briefly reviewing a basic concept of this technology and discussing its implications for neuropsychological studies. First, the technical aspects of resting-state fMRI, including signal sources, physiological artifacts, image acquisition, and analytical methods such as seed-based correlation analysis and independent component analysis, are explained, followed by a discussion on the major resting-state networks, including the default mode network. In addition, the structure-function correlation studied using diffuse tensor imaging and resting-state fMRI is briefly discussed. Second, I have discussed the reservations and potential pitfalls of 2 major imaging methods: voxel-based lesion-symptom mapping and task fMRI. Problems encountered with voxel-based lesion-symptom mapping can be overcome by using resting-state fMRI and evaluating undamaged brain networks in patients. Regarding task fMRI in patients, I have also emphasized the importance of evaluating the baseline brain activity because the amplitude of activation in BOLD fMRI is hard to interpret as the same baseline cannot be assumed for both patient and normal groups. (author)
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Babajani-Feremi, Abbas; Narayana, Shalini; Rezaie, Roozbeh; Choudhri, Asim F; Fulton, Stephen P; Boop, Frederick A; Wheless, James W; Papanicolaou, Andrew C
2016-03-01
The aim of the present study was to compare localization of the language cortex using cortical stimulation mapping (CSM), high gamma electrocorticography (hgECoG), functional magnetic resonance imaging (fMRI), and transcranial magnetic stimulation (TMS). Language mapping using CSM, hgECoG, fMRI, and TMS were compared in nine patients with epilepsy. Considering CSM as reference, we compared language mapping approaches based on hgECoG, fMRI, and TMS using their sensitivity, specificity, and the results of receiver operating characteristic (ROC) analyses. Our results show that areas involved in language processing can be identified by hgECoG, fMRI, and TMS. The average sensitivity/specificity of hgECoG, fMRI, and TMS across all patients was 100%/85%, 50%/80%, and 67%/66%, respectively. The average area under the ROC curve of hgECoG, fMRI, and TMS across CSM-positive patients was 0.98, 0.76, and 0.68, respectively. There is considerable concordance between CSM, hgECoG, fMRI, and TMS language mapping. Our results reveal that hgECoG, fMRI, and TMS are valuable tools for presurgical language mapping. Language mapping on the basis of hgECoG, fMRI, and TMS can provide important additional information, therefore, these methods can be used in conjunction with CSM or as an alternative, when the latter is deemed impractical. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
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Ruffieux, Jan; Mouthon, Audrey; Keller, Martin; Mouthon, Michaël; Annoni, Jean-Marie; Taube, Wolfgang
2018-01-01
Aging is associated with a shift from an automatic to a more cortical postural control strategy, which goes along with deteriorations in postural stability. Although balance training has been shown to effectively counteract these behavioral deteriorations, little is known about the effect of balance training on brain activity during postural tasks in older adults. We, therefore, assessed postural stability and brain activity using fMRI during motor imagery alone (MI) and in combination with action observation (AO; i.e., AO+MI) of a challenging balance task in older adults before and after 5 weeks of balance training. Results showed a nonsignificant trend toward improvements in postural stability after balance training, accompanied by reductions in brain activity during AO+MI of the balance task in areas relevant for postural control, which have been shown to be over-activated in older adults during (simulation of) motor performance, including motor, premotor, and multisensory vestibular areas. This suggests that balance training may reverse the age-related cortical over-activations and lead to changes in the control of upright posture toward the one observed in young adults.
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Brain functional BOLD perturbation modelling for forward fMRI and inverse mapping
Robinson, Jennifer; Calhoun, Vince
2018-01-01
Purpose To computationally separate dynamic brain functional BOLD responses from static background in a brain functional activity for forward fMRI signal analysis and inverse mapping. Methods A brain functional activity is represented in terms of magnetic source by a perturbation model: χ = χ0 +δχ, with δχ for BOLD magnetic perturbations and χ0 for background. A brain fMRI experiment produces a timeseries of complex-valued images (T2* images), whereby we extract the BOLD phase signals (denoted by δP) by a complex division. By solving an inverse problem, we reconstruct the BOLD δχ dataset from the δP dataset, and the brain χ distribution from a (unwrapped) T2* phase image. Given a 4D dataset of task BOLD fMRI, we implement brain functional mapping by temporal correlation analysis. Results Through a high-field (7T) and high-resolution (0.5mm in plane) task fMRI experiment, we demonstrated in detail the BOLD perturbation model for fMRI phase signal separation (P + δP) and reconstructing intrinsic brain magnetic source (χ and δχ). We also provided to a low-field (3T) and low-resolution (2mm) task fMRI experiment in support of single-subject fMRI study. Our experiments show that the δχ-depicted functional map reveals bidirectional BOLD χ perturbations during the task performance. Conclusions The BOLD perturbation model allows us to separate fMRI phase signal (by complex division) and to perform inverse mapping for pure BOLD δχ reconstruction for intrinsic functional χ mapping. The full brain χ reconstruction (from unwrapped fMRI phase) provides a new brain tissue image that allows to scrutinize the brain tissue idiosyncrasy for the pure BOLD δχ response through an automatic function/structure co-localization. PMID:29351339
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Brain functional BOLD perturbation modelling for forward fMRI and inverse mapping.
Chen, Zikuan; Robinson, Jennifer; Calhoun, Vince
2018-01-01
To computationally separate dynamic brain functional BOLD responses from static background in a brain functional activity for forward fMRI signal analysis and inverse mapping. A brain functional activity is represented in terms of magnetic source by a perturbation model: χ = χ0 +δχ, with δχ for BOLD magnetic perturbations and χ0 for background. A brain fMRI experiment produces a timeseries of complex-valued images (T2* images), whereby we extract the BOLD phase signals (denoted by δP) by a complex division. By solving an inverse problem, we reconstruct the BOLD δχ dataset from the δP dataset, and the brain χ distribution from a (unwrapped) T2* phase image. Given a 4D dataset of task BOLD fMRI, we implement brain functional mapping by temporal correlation analysis. Through a high-field (7T) and high-resolution (0.5mm in plane) task fMRI experiment, we demonstrated in detail the BOLD perturbation model for fMRI phase signal separation (P + δP) and reconstructing intrinsic brain magnetic source (χ and δχ). We also provided to a low-field (3T) and low-resolution (2mm) task fMRI experiment in support of single-subject fMRI study. Our experiments show that the δχ-depicted functional map reveals bidirectional BOLD χ perturbations during the task performance. The BOLD perturbation model allows us to separate fMRI phase signal (by complex division) and to perform inverse mapping for pure BOLD δχ reconstruction for intrinsic functional χ mapping. The full brain χ reconstruction (from unwrapped fMRI phase) provides a new brain tissue image that allows to scrutinize the brain tissue idiosyncrasy for the pure BOLD δχ response through an automatic function/structure co-localization.
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Automatic EEG-assisted retrospective motion correction for fMRI (aE-REMCOR).
Wong, Chung-Ki; Zotev, Vadim; Misaki, Masaya; Phillips, Raquel; Luo, Qingfei; Bodurka, Jerzy
2016-04-01
Head motions during functional magnetic resonance imaging (fMRI) impair fMRI data quality and introduce systematic artifacts that can affect interpretation of fMRI results. Electroencephalography (EEG) recordings performed simultaneously with fMRI provide high-temporal-resolution information about ongoing brain activity as well as head movements. Recently, an EEG-assisted retrospective motion correction (E-REMCOR) method was introduced. E-REMCOR utilizes EEG motion artifacts to correct the effects of head movements in simultaneously acquired fMRI data on a slice-by-slice basis. While E-REMCOR is an efficient motion correction approach, it involves an independent component analysis (ICA) of the EEG data and identification of motion-related ICs. Here we report an automated implementation of E-REMCOR, referred to as aE-REMCOR, which we developed to facilitate the application of E-REMCOR in large-scale EEG-fMRI studies. The aE-REMCOR algorithm, implemented in MATLAB, enables an automated preprocessing of the EEG data, an ICA decomposition, and, importantly, an automatic identification of motion-related ICs. aE-REMCOR has been used to perform retrospective motion correction for 305 fMRI datasets from 16 subjects, who participated in EEG-fMRI experiments conducted on a 3T MRI scanner. Performance of aE-REMCOR has been evaluated based on improvement in temporal signal-to-noise ratio (TSNR) of the fMRI data, as well as correction efficiency defined in terms of spike reduction in fMRI motion parameters. The results show that aE-REMCOR is capable of substantially reducing head motion artifacts in fMRI data. In particular, when there are significant rapid head movements during the scan, a large TSNR improvement and high correction efficiency can be achieved. Depending on a subject's motion, an average TSNR improvement over the brain upon the application of aE-REMCOR can be as high as 27%, with top ten percent of the TSNR improvement values exceeding 55%. The average
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Electrophysiological correlates of the BOLD signal for EEG-informed fMRI
Murta, Teresa; Leite, Marco; Carmichael, David W; Figueiredo, Patrícia; Lemieux, Louis
2015-01-01
Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are important tools in cognitive and clinical neuroscience. Combined EEG–fMRI has been shown to help to characterise brain networks involved in epileptic activity, as well as in different sensory, motor and cognitive functions. A good understanding of the electrophysiological correlates of the blood oxygen level-dependent (BOLD) signal is necessary to interpret fMRI maps, particularly when obtained in combination with EEG. We review the current understanding of electrophysiological–haemodynamic correlates, during different types of brain activity. We start by describing the basic mechanisms underlying EEG and BOLD signals and proceed by reviewing EEG-informed fMRI studies using fMRI to map specific EEG phenomena over the entire brain (EEG–fMRI mapping), or exploring a range of EEG-derived quantities to determine which best explain colocalised BOLD fluctuations (local EEG–fMRI coupling). While reviewing studies of different forms of brain activity (epileptic and nonepileptic spontaneous activity; cognitive, sensory and motor functions), a significant attention is given to epilepsy because the investigation of its haemodynamic correlates is the most common application of EEG-informed fMRI. Our review is focused on EEG-informed fMRI, an asymmetric approach of data integration. We give special attention to the invasiveness of electrophysiological measurements and the simultaneity of multimodal acquisitions because these methodological aspects determine the nature of the conclusions that can be drawn from EEG-informed fMRI studies. We emphasise the advantages of, and need for, simultaneous intracranial EEG–fMRI studies in humans, which recently became available and hold great potential to improve our understanding of the electrophysiological correlates of BOLD fluctuations. PMID:25277370
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Assessment of language lateralization with functional magnetic resonance imaging (fMRI)
International Nuclear Information System (INIS)
Salagierska-Barwinska, A.; Goraj, B.
2004-01-01
fMRI offers powerful methods to delineate which brain regions are engaged in language processing in the intact brain. Until now hemisphere dominance for language has been usually assessed by means of the intraoperative methods: the Wada test or electrocortical stimulation mapping. Recently functional MRI becomes the valuable method in determining hemisphere dominance for language. fMRI study was proved to be concordant with invasive measures. fMRI was carried out in 30 healthy selected participants (15 females: 10 strongly right-handed and 5 strongly left-handed; 15 males: 10 strongly right-handed and 5 strongly left-handed). The subject's handedness was assessed by standardized psychological tests inter alia the 'lateralization inventory'. Two different language tasks were used: a verb generation task and a phonological task. Subjects were scanned,while performing experimental block. The block contained alternately 8 active (language task) and 8 control conditions. Statistical analysis of evoked blood oxygenation level-dependent BOLD) responses, measured with echo planar imagining (1.5 T) were used. During a verb generation task in strongly right or left handed subjects the inferior frontal region was activated on the side opposite to the subject's handedness determined by the psychological test. Our fMRI studies demonstrated no gender effects on brain during these language tasks. Our study suggests that fMRI is a good device for the study of the language organization. The advantage of fMRI is its capacity for exact localization of activated areas. fMRI together with adequate neurolinguistic test could be promising routine preoperative tool in identification hemisphere dominance for language. These results encourage to further investigation for evaluating correlation in patients with brain injuries. (author)
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Petropulos, Dolores; Bittner, David; Murawski, Robert; Golden, Bert
2015-01-01
The SmallSat has an unrealized potential in both the private industry and in the federal government. Currently over 70 companies, 50 universities and 17 governmental agencies are involved in SmallSat research and development. In 1994, the U.S. Army Missile and Defense mapped the moon using smallSat imagery. Since then Smart Phones have introduced this imagery to the people of the world as diverse industries watched this trend. The deployment cost of smallSats is also greatly reduced compared to traditional satellites due to the fact that multiple units can be deployed in a single mission. Imaging payloads have become more sophisticated, smaller and lighter. In addition, the growth of small technology obtained from private industries has led to the more widespread use of smallSats. This includes greater revisit rates in imagery, significantly lower costs, the ability to update technology more frequently and the ability to decrease vulnerability of enemy attacks. The popularity of smallSats show a changing mentality in this fast paced world of tomorrow. What impact has this created on the NASA communication networks now and in future years? In this project, we are developing the SmallSat Relational Database which can support a simulation of smallSats within the NASA SCaN Compatability Environment for Networks and Integrated Communications (SCENIC) Modeling and Simulation Lab. The NASA Space Communications and Networks (SCaN) Program can use this modeling to project required network support needs in the next 10 to 15 years. The SmallSat Rational Database could model smallSats just as the other SCaN databases model the more traditional larger satellites, with a few exceptions. One being that the smallSat Database is designed to be built-to-order. The SmallSat database holds various hardware configurations that can be used to model a smallSat. It will require significant effort to develop as the research material can only be populated by hand to obtain the unique data
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fMRI activation in relation to sound intensity and loudness
Langers, Dave R. M.; van Dijk, Pirn; Schoemaker, Esther S.; Backes, Walter H.
2007-01-01
The aim of this fMRI study was to relate cortical fMRI responses to both physical and perceptual sound level characteristics. Besides subjects with normal hearing, subjects with high-frequency sensorineural hearing loss were included, as distortion of loudness perception is a characteristic of such
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A receptor-based model for dopamine-induced fMRI signal
Mandeville, Joseph. B.; Sander, Christin Y. M.; Jenkins, Bruce G.; Hooker, Jacob M.; Catana, Ciprian; Vanduffel, Wim; Alpert, Nathaniel M.; Rosen, Bruce R.; Normandin, Marc D.
2013-01-01
This report describes a multi-receptor physiological model of the fMRI temporal response and signal magnitude evoked by drugs that elevate synaptic dopamine in basal ganglia. The model is formulated as a summation of dopamine’s effects at D1-like and D2-like receptor families, which produce functional excitation and inhibition, respectively, as measured by molecular indicators like adenylate cyclase or neuroimaging techniques like fMRI. Functional effects within the model are described in terms of relative changes in receptor occupancies scaled by receptor densities and neuro-vascular coupling constants. Using literature parameters, the model reconciles many discrepant observations and interpretations of pre-clinical data. Additionally, we present data showing that amphetamine stimulation produces fMRI inhibition at low doses and a biphasic response at higher doses in the basal ganglia of non-human primates (NHP), in agreement with model predictions based upon the respective levels of evoked dopamine. Because information about dopamine release is required to inform the fMRI model, we simultaneously acquired PET 11C-raclopride data in several studies to evaluate the relationship between raclopride displacement and assumptions about dopamine release. At high levels of dopamine release, results suggest that refinements of the model will be required to consistently describe the PET and fMRI data. Overall, the remarkable success of the model in describing a wide range of preclinical fMRI data indicate that this approach will be useful for guiding the design and analysis of basic science and clinical investigations and for interpreting the functional consequences of dopaminergic stimulation in normal subjects and in populations with dopaminergic neuroadaptations. PMID:23466936
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Nonlinear complexity analysis of brain FMRI signals in schizophrenia.
Directory of Open Access Journals (Sweden)
Moses O Sokunbi
Full Text Available We investigated the differences in brain fMRI signal complexity in patients with schizophrenia while performing the Cyberball social exclusion task, using measures of Sample entropy and Hurst exponent (H. 13 patients meeting diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM IV criteria for schizophrenia and 16 healthy controls underwent fMRI scanning at 1.5 T. The fMRI data of both groups of participants were pre-processed, the entropy characterized and the Hurst exponent extracted. Whole brain entropy and H maps of the groups were generated and analysed. The results after adjusting for age and sex differences together show that patients with schizophrenia exhibited higher complexity than healthy controls, at mean whole brain and regional levels. Also, both Sample entropy and Hurst exponent agree that patients with schizophrenia have more complex fMRI signals than healthy controls. These results suggest that schizophrenia is associated with more complex signal patterns when compared to healthy controls, supporting the increase in complexity hypothesis, where system complexity increases with age or disease, and also consistent with the notion that schizophrenia is characterised by a dysregulation of the nonlinear dynamics of underlying neuronal systems.
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Multivariate linear regression of high-dimensional fMRI data with multiple target variables.
Valente, Giancarlo; Castellanos, Agustin Lage; Vanacore, Gianluca; Formisano, Elia
2014-05-01
Multivariate regression is increasingly used to study the relation between fMRI spatial activation patterns and experimental stimuli or behavioral ratings. With linear models, informative brain locations are identified by mapping the model coefficients. This is a central aspect in neuroimaging, as it provides the sought-after link between the activity of neuronal populations and subject's perception, cognition or behavior. Here, we show that mapping of informative brain locations using multivariate linear regression (MLR) may lead to incorrect conclusions and interpretations. MLR algorithms for high dimensional data are designed to deal with targets (stimuli or behavioral ratings, in fMRI) separately, and the predictive map of a model integrates information deriving from both neural activity patterns and experimental design. Not accounting explicitly for the presence of other targets whose associated activity spatially overlaps with the one of interest may lead to predictive maps of troublesome interpretation. We propose a new model that can correctly identify the spatial patterns associated with a target while achieving good generalization. For each target, the training is based on an augmented dataset, which includes all remaining targets. The estimation on such datasets produces both maps and interaction coefficients, which are then used to generalize. The proposed formulation is independent of the regression algorithm employed. We validate this model on simulated fMRI data and on a publicly available dataset. Results indicate that our method achieves high spatial sensitivity and good generalization and that it helps disentangle specific neural effects from interaction with predictive maps associated with other targets. Copyright © 2013 Wiley Periodicals, Inc.
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Spatially adaptive mixture modeling for analysis of FMRI time series.
Vincent, Thomas; Risser, Laurent; Ciuciu, Philippe
2010-04-01
Within-subject analysis in fMRI essentially addresses two problems, the detection of brain regions eliciting evoked activity and the estimation of the underlying dynamics. In Makni et aL, 2005 and Makni et aL, 2008, a detection-estimation framework has been proposed to tackle these problems jointly, since they are connected to one another. In the Bayesian formalism, detection is achieved by modeling activating and nonactivating voxels through independent mixture models (IMM) within each region while hemodynamic response estimation is performed at a regional scale in a nonparametric way. Instead of IMMs, in this paper we take advantage of spatial mixture models (SMM) for their nonlinear spatial regularizing properties. The proposed method is unsupervised and spatially adaptive in the sense that the amount of spatial correlation is automatically tuned from the data and this setting automatically varies across brain regions. In addition, the level of regularization is specific to each experimental condition since both the signal-to-noise ratio and the activation pattern may vary across stimulus types in a given brain region. These aspects require the precise estimation of multiple partition functions of underlying Ising fields. This is addressed efficiently using first path sampling for a small subset of fields and then using a recently developed fast extrapolation technique for the large remaining set. Simulation results emphasize that detection relying on supervised SMM outperforms its IMM counterpart and that unsupervised spatial mixture models achieve similar results without any hand-tuning of the correlation parameter. On real datasets, the gain is illustrated in a localizer fMRI experiment: brain activations appear more spatially resolved using SMM in comparison with classical general linear model (GLM)-based approaches, while estimating a specific parcel-based HRF shape. Our approach therefore validates the treatment of unsmoothed fMRI data without fixed GLM
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An NMR database for simulations of membrane dynamics.
Leftin, Avigdor; Brown, Michael F
2011-03-01
Computational methods are powerful in capturing the results of experimental studies in terms of force fields that both explain and predict biological structures. Validation of molecular simulations requires comparison with experimental data to test and confirm computational predictions. Here we report a comprehensive database of NMR results for membrane phospholipids with interpretations intended to be accessible by non-NMR specialists. Experimental ¹³C-¹H and ²H NMR segmental order parameters (S(CH) or S(CD)) and spin-lattice (Zeeman) relaxation times (T(1Z)) are summarized in convenient tabular form for various saturated, unsaturated, and biological membrane phospholipids. Segmental order parameters give direct information about bilayer structural properties, including the area per lipid and volumetric hydrocarbon thickness. In addition, relaxation rates provide complementary information about molecular dynamics. Particular attention is paid to the magnetic field dependence (frequency dispersion) of the NMR relaxation rates in terms of various simplified power laws. Model-free reduction of the T(1Z) studies in terms of a power-law formalism shows that the relaxation rates for saturated phosphatidylcholines follow a single frequency-dispersive trend within the MHz regime. We show how analytical models can guide the continued development of atomistic and coarse-grained force fields. Our interpretation suggests that lipid diffusion and collective order fluctuations are implicitly governed by the viscoelastic nature of the liquid-crystalline ensemble. Collective bilayer excitations are emergent over mesoscopic length scales that fall between the molecular and bilayer dimensions, and are important for lipid organization and lipid-protein interactions. Future conceptual advances and theoretical reductions will foster understanding of biomembrane structural dynamics through a synergy of NMR measurements and molecular simulations. Copyright © 2010 Elsevier B.V. All
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Age-Dependent Mesial Temporal Lobe Lateralization in Language FMRI
Sepeta, Leigh N.; Berl, Madison M.; Wilke, Marko; You, Xiaozhen; Mehta, Meera; Xu, Benjamin; Inati, Sara; Dustin, Irene; Khan, Omar; Austermuehle, Alison; Theodore, William H.; Gaillard, William D.
2015-01-01
Objective FMRI activation of the mesial temporal lobe (MTL) may be important for epilepsy surgical planning. We examined MTL activation and lateralization during language fMRI in children and adults with focal epilepsy. Methods 142 controls and patients with left hemisphere focal epilepsy (Pediatric: epilepsy, n = 17, mean age = 9.9 ± 2.0; controls, n = 48; mean age = 9.1 ± 2.6; Adult: epilepsy, n = 20, mean age = 26.7 ± 5.8; controls, n = 57, mean age = 26.2 ± 7.5) underwent 3T fMRI using a language task (auditory description decision task). Image processing and analyses were conducted in SPM8; ROIs included MTL, Broca’s area, and Wernicke’s area. We assessed group and individual MTL activation, and examined degree of lateralization. Results Patients and controls (pediatric and adult) demonstrated group and individual MTL activation during language fMRI. MTL activation was left lateralized for adults but less so in children (p’s < 0.005). Patients did not differ from controls in either age group. Stronger left-lateralized MTL activation was related to older age (p = 0.02). Language lateralization (Broca’s and Wernicke’s) predicted 19% of the variance in MTL lateralization for adults (p = 0.001), but not children. Significance Language fMRI may be used to elicit group and individual MTL activation. The developmental difference in MTL lateralization and its association with language lateralization suggests a developmental shift in lateralization of MTL function, with increased left lateralization across the age span. This shift may help explain why children have better memory outcomes following resection compared to adults. PMID:26696589
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Multivoxel Pattern Analysis for fMRI Data: A Review
Directory of Open Access Journals (Sweden)
Abdelhak Mahmoudi
2012-01-01
Full Text Available Functional magnetic resonance imaging (fMRI exploits blood-oxygen-level-dependent (BOLD contrasts to map neural activity associated with a variety of brain functions including sensory processing, motor control, and cognitive and emotional functions. The general linear model (GLM approach is used to reveal task-related brain areas by searching for linear correlations between the fMRI time course and a reference model. One of the limitations of the GLM approach is the assumption that the covariance across neighbouring voxels is not informative about the cognitive function under examination. Multivoxel pattern analysis (MVPA represents a promising technique that is currently exploited to investigate the information contained in distributed patterns of neural activity to infer the functional role of brain areas and networks. MVPA is considered as a supervised classification problem where a classifier attempts to capture the relationships between spatial pattern of fMRI activity and experimental conditions. In this paper , we review MVPA and describe the mathematical basis of the classification algorithms used for decoding fMRI signals, such as support vector machines (SVMs. In addition, we describe the workflow of processing steps required for MVPA such as feature selection, dimensionality reduction, cross-validation, and classifier performance estimation based on receiver operating characteristic (ROC curves.
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Multivoxel Pattern Analysis for fMRI Data: A Review
Takerkart, Sylvain; Regragui, Fakhita; Boussaoud, Driss; Brovelli, Andrea
2012-01-01
Functional magnetic resonance imaging (fMRI) exploits blood-oxygen-level-dependent (BOLD) contrasts to map neural activity associated with a variety of brain functions including sensory processing, motor control, and cognitive and emotional functions. The general linear model (GLM) approach is used to reveal task-related brain areas by searching for linear correlations between the fMRI time course and a reference model. One of the limitations of the GLM approach is the assumption that the covariance across neighbouring voxels is not informative about the cognitive function under examination. Multivoxel pattern analysis (MVPA) represents a promising technique that is currently exploited to investigate the information contained in distributed patterns of neural activity to infer the functional role of brain areas and networks. MVPA is considered as a supervised classification problem where a classifier attempts to capture the relationships between spatial pattern of fMRI activity and experimental conditions. In this paper , we review MVPA and describe the mathematical basis of the classification algorithms used for decoding fMRI signals, such as support vector machines (SVMs). In addition, we describe the workflow of processing steps required for MVPA such as feature selection, dimensionality reduction, cross-validation, and classifier performance estimation based on receiver operating characteristic (ROC) curves. PMID:23401720
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Energy Technology Data Exchange (ETDEWEB)
Smith, F. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Flach, G. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)
2015-03-30
This report describes work performed by the Savannah River National Laboratory (SRNL) in fiscal year 2014 to develop a new Cementitious Barriers Project (CBP) software module designated as FLOExcel. FLOExcel incorporates a uniform database to capture material characterization data and a GoldSim model to define flow properties for both intact and fractured cementitious materials and estimate Darcy velocity based on specified hydraulic head gradient and matric tension. The software module includes hydraulic parameters for intact cementitious and granular materials in the database and a standalone GoldSim framework to manipulate the data. The database will be updated with new data as it comes available. The software module will later be integrated into the next release of the CBP Toolbox, Version 3.0. This report documents the development efforts for this software module. The FY14 activities described in this report focused on the following two items that form the FLOExcel package; 1) Development of a uniform database to capture CBP data for cementitious materials. In particular, the inclusion and use of hydraulic properties of the materials are emphasized; and 2) Development of algorithms and a GoldSim User Interface to calculate hydraulic flow properties of degraded and fractured cementitious materials. Hydraulic properties are required in a simulation of flow through cementitious materials such as Saltstone, waste tank fill grout, and concrete barriers. At SRNL these simulations have been performed using the PORFLOW code as part of Performance Assessments for salt waste disposal and waste tank closure.
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A new paradigm for individual subject language mapping: Movie-watching fMRI
Tie, Yanmei; Rigolo, Laura; Ovalioglu, Aysegul Ozdemir; Olubiyi, Olutayo; Doolin, Kelly L.; Mukundan, Srinivasan; Golby, Alexandra J.
2015-01-01
Background Functional MRI (fMRI) based on language tasks has been used in pre-surgical language mapping in patients with lesions in or near putative language areas. However, if the patients have difficulty performing the tasks due to neurological deficits, it leads to unreliable or non-interpretable results. In this study, we investigate the feasibility of using a movie-watching fMRI for language mapping. Methods A 7-min movie clip with contrasting speech and non-speech segments was shown to 22 right-handed healthy subjects. Based on all subjects' language functional regions-of-interest, six language response areas were defined, within which a language response model (LRM) was derived by extracting the main temporal activation profile. Using a leave-one-out procedure, individuals' language areas were identified as the areas that expressed highly correlated temporal responses with the LRM derived from an independent group of subjects. Results Compared with an antonym generation task-based fMRI, the movie-watching fMRI generated language maps with more localized activations in the left frontal language area, larger activations in the left temporoparietal language area, and significant activations in their right-hemisphere homologues. Results of two brain tumor patients' movie-watching fMRI using the LRM derived from the healthy subjects indicated its ability to map putative language areas; while their task-based fMRI maps were less robust and noisier. Conclusions These results suggest that it is feasible to use this novel “task-free” paradigm as a complementary tool for fMRI language mapping when patients cannot perform the tasks. Its deployment in more neurosurgical patients and validation against gold-standard techniques need further investigation. PMID:25962953
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Intersession reliability of fMRI activation for heat pain and motor tasks.
Quiton, Raimi L; Keaser, Michael L; Zhuo, Jiachen; Gullapalli, Rao P; Greenspan, Joel D
2014-01-01
As the practice of conducting longitudinal fMRI studies to assess mechanisms of pain-reducing interventions becomes more common, there is a great need to assess the test-retest reliability of the pain-related BOLD fMRI signal across repeated sessions. This study quantitatively evaluated the reliability of heat pain-related BOLD fMRI brain responses in healthy volunteers across 3 sessions conducted on separate days using two measures: (1) intraclass correlation coefficients (ICC) calculated based on signal amplitude and (2) spatial overlap. The ICC analysis of pain-related BOLD fMRI responses showed fair-to-moderate intersession reliability in brain areas regarded as part of the cortical pain network. Areas with the highest intersession reliability based on the ICC analysis included the anterior midcingulate cortex, anterior insula, and second somatosensory cortex. Areas with the lowest intersession reliability based on the ICC analysis also showed low spatial reliability; these regions included pregenual anterior cingulate cortex, primary somatosensory cortex, and posterior insula. Thus, this study found regional differences in pain-related BOLD fMRI response reliability, which may provide useful information to guide longitudinal pain studies. A simple motor task (finger-thumb opposition) was performed by the same subjects in the same sessions as the painful heat stimuli were delivered. Intersession reliability of fMRI activation in cortical motor areas was comparable to previously published findings for both spatial overlap and ICC measures, providing support for the validity of the analytical approach used to assess intersession reliability of pain-related fMRI activation. A secondary finding of this study is that the use of standard ICC alone as a measure of reliability may not be sufficient, as the underlying variance structure of an fMRI dataset can result in inappropriately high ICC values; a method to eliminate these false positive results was used in this
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Intersession reliability of fMRI activation for heat pain and motor tasks
Quiton, Raimi L.; Keaser, Michael L.; Zhuo, Jiachen; Gullapalli, Rao P.; Greenspan, Joel D.
2014-01-01
As the practice of conducting longitudinal fMRI studies to assess mechanisms of pain-reducing interventions becomes more common, there is a great need to assess the test–retest reliability of the pain-related BOLD fMRI signal across repeated sessions. This study quantitatively evaluated the reliability of heat pain-related BOLD fMRI brain responses in healthy volunteers across 3 sessions conducted on separate days using two measures: (1) intraclass correlation coefficients (ICC) calculated based on signal amplitude and (2) spatial overlap. The ICC analysis of pain-related BOLD fMRI responses showed fair-to-moderate intersession reliability in brain areas regarded as part of the cortical pain network. Areas with the highest intersession reliability based on the ICC analysis included the anterior midcingulate cortex, anterior insula, and second somatosensory cortex. Areas with the lowest intersession reliability based on the ICC analysis also showed low spatial reliability; these regions included pregenual anterior cingulate cortex, primary somatosensory cortex, and posterior insula. Thus, this study found regional differences in pain-related BOLD fMRI response reliability, which may provide useful information to guide longitudinal pain studies. A simple motor task (finger-thumb opposition) was performed by the same subjects in the same sessions as the painful heat stimuli were delivered. Intersession reliability of fMRI activation in cortical motor areas was comparable to previously published findings for both spatial overlap and ICC measures, providing support for the validity of the analytical approach used to assess intersession reliability of pain-related fMRI activation. A secondary finding of this study is that the use of standard ICC alone as a measure of reliability may not be sufficient, as the underlying variance structure of an fMRI dataset can result in inappropriately high ICC values; a method to eliminate these false positive results was used in this
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DEFF Research Database (Denmark)
Siebner, Hartwig R.; Herz, Damian
2013-01-01
and reward-related behavior have shown that dopamine replacement can have detrimental effects on non-motor brain functions by altering physiological patterns of dopaminergic signaling. Neuroimaging can also be used to assess preclinical compensation of striatal dopaminergic denervation by studying......In this chapter we review recent advances in functional magnetic resonance imaging (fMRI) in Parkinson’s disease (PD). Covariance patterns of regional resting-state activity in functional brain networks can be used to distinguish Parkinson patients from healthy controls and might play an important...... role as a biomarker in the future. Analyses of motor activity and connectivity have revealed compensatory mechanisms for impaired function of cortico-subcortical feedback loops and have shown how attentional mechanisms modulate the activity in motor loops. Other fMRI studies probing cognitive functions...
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Intrasubject reproducibility of presurgical language lateralization and mapping using fMRI.
Fernandez, G.S.E.; Specht, K.; Weis, S.; Tendolkar, I.; Reuber, M.; Fell, J.; Klaver, P.; Ruhlmann, J.; Reul, J.; Elger, C.E.
2003-01-01
BACKGROUND: fMRI is becoming a standard tool for the presurgical lateralization and mapping of brain areas involved in language processing. However, its within-subject reproducibility has yet to be fully explored. OBJECTIVE: To evaluate within-test and test-retest reliability of language fMRI in
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fMRI Analysis-by-Synthesis Reveals a Dorsal Hierarchy That Extracts Surface Slant.
Ban, Hiroshi; Welchman, Andrew E
2015-07-08
The brain's skill in estimating the 3-D orientation of viewed surfaces supports a range of behaviors, from placing an object on a nearby table, to planning the best route when hill walking. This ability relies on integrating depth signals across extensive regions of space that exceed the receptive fields of early sensory neurons. Although hierarchical selection and pooling is central to understanding of the ventral visual pathway, the successive operations in the dorsal stream are poorly understood. Here we use computational modeling of human fMRI signals to probe the computations that extract 3-D surface orientation from binocular disparity. To understand how representations evolve across the hierarchy, we developed an inference approach using a series of generative models to explain the empirical fMRI data in different cortical areas. Specifically, we simulated the responses of candidate visual processing algorithms and tested how well they explained fMRI responses. Thereby we demonstrate a hierarchical refinement of visual representations moving from the representation of edges and figure-ground segmentation (V1, V2) to spatially extensive disparity gradients in V3A. We show that responses in V3A are little affected by low-level image covariates, and have a partial tolerance to the overall depth position. Finally, we show that responses in V3A parallel perceptual judgments of slant. This reveals a relatively short computational hierarchy that captures key information about the 3-D structure of nearby surfaces, and more generally demonstrates an analysis approach that may be of merit in a diverse range of brain imaging domains. Copyright © 2015 Ban and Welchman.
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The continuing challenge of understanding and modeling hemodynamic variation in fMRI
Handwerker, Daniel A.; Gonzalez-Castillo, Javier; D’Esposito, Mark; Bandettini, Peter A.
2012-01-01
Interpretation of fMRI data depends on our ability to understand or model the shape of the hemodynamic response (HR) to a neural event. Although the HR has been studied almost since the beginning of fMRI, we are still far from having robust methods to account for the full range of known HR variation in typical fMRI analyses. This paper reviews how the authors and others contributed to our understanding of HR variation. We present an overview of studies that describe HR variation across voxels...
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Comparison of PET and fMRI activation patterns during declarative memory processes
International Nuclear Information System (INIS)
Mottaghy, F.M.; Krause, B.J.; Schmidt, D.; Hautzel, H.; Mueller-Gaertner, H.-W.; Herzog, H.; Shah, N.J.; Halsband, U.
2000-01-01
Aim: In this study neuronal correlates of encoding and retrieval in paired association learning were compared using two different neuroimaging methods: Positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). Methods: 6 right-handed normal male volunteers took part in the study. Each subject underwent six 0-15-butanol PET scans and an fMRI study comprising four single epochs on a different day. The subjects had to learn and retrieve 12 word pairs which were visually presented (highly imaginable words, not semantically related). Results: Mean recall accuracy was 93% in the PET as well as in the fMRI experiment. During encoding and retrieval we found anterior cingulate cortex activation, and bilateral prefrontal cortex activation in both imaging modalities. Furthermore, we demonstrate the importance of the precuneus in episodic memory. With PET the results demonstrate frontopolar activations whereas fMRI fails to show activations in this area probably due to susceptibility artifacts. In fMRI we found additionally parahippocampal activation and due to the whole-brain coverage cerebellar activation during encoding. The distance between the center-of-mass activations in both modalities was 7.2±6.5 mm. Conclusion: There is a preponderance of commonalities in the activation patterns yielded with fMRI and PET. However, there are also important differences. The decision to choose one or the other neuroimaging modality should among other aspects depend on the study design (single subject vs. group study) and the task of interest. (orig.) [de
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Bayesian Inference for Functional Dynamics Exploring in fMRI Data
Directory of Open Access Journals (Sweden)
Xuan Guo
2016-01-01
Full Text Available This paper aims to review state-of-the-art Bayesian-inference-based methods applied to functional magnetic resonance imaging (fMRI data. Particularly, we focus on one specific long-standing challenge in the computational modeling of fMRI datasets: how to effectively explore typical functional interactions from fMRI time series and the corresponding boundaries of temporal segments. Bayesian inference is a method of statistical inference which has been shown to be a powerful tool to encode dependence relationships among the variables with uncertainty. Here we provide an introduction to a group of Bayesian-inference-based methods for fMRI data analysis, which were designed to detect magnitude or functional connectivity change points and to infer their functional interaction patterns based on corresponding temporal boundaries. We also provide a comparison of three popular Bayesian models, that is, Bayesian Magnitude Change Point Model (BMCPM, Bayesian Connectivity Change Point Model (BCCPM, and Dynamic Bayesian Variable Partition Model (DBVPM, and give a summary of their applications. We envision that more delicate Bayesian inference models will be emerging and play increasingly important roles in modeling brain functions in the years to come.
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The relation between statistical power and inference in fMRI.
Directory of Open Access Journals (Sweden)
Henk R Cremers
Full Text Available Statistically underpowered studies can result in experimental failure even when all other experimental considerations have been addressed impeccably. In fMRI the combination of a large number of dependent variables, a relatively small number of observations (subjects, and a need to correct for multiple comparisons can decrease statistical power dramatically. This problem has been clearly addressed yet remains controversial-especially in regards to the expected effect sizes in fMRI, and especially for between-subjects effects such as group comparisons and brain-behavior correlations. We aimed to clarify the power problem by considering and contrasting two simulated scenarios of such possible brain-behavior correlations: weak diffuse effects and strong localized effects. Sampling from these scenarios shows that, particularly in the weak diffuse scenario, common sample sizes (n = 20-30 display extremely low statistical power, poorly represent the actual effects in the full sample, and show large variation on subsequent replications. Empirical data from the Human Connectome Project resembles the weak diffuse scenario much more than the localized strong scenario, which underscores the extent of the power problem for many studies. Possible solutions to the power problem include increasing the sample size, using less stringent thresholds, or focusing on a region-of-interest. However, these approaches are not always feasible and some have major drawbacks. The most prominent solutions that may help address the power problem include model-based (multivariate prediction methods and meta-analyses with related synthesis-oriented approaches.
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Position-history and spin-history artifacts in fMRI time-series
Muresan, L; Renken, R; Roerdink, JBTM; Duifhuis, H; Clough, AN; Chen, CT
2002-01-01
What is the impact of the spin history and position history on signal intensity after the alignment of acquired volumes? This question arises in many fMRI studies. We will focus on spin-history artefacts generated by the position-history of the scanned object. In fMRI an object is driven to steady
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Improving decoy databases for protein folding algorithms
Lindsey, Aaron
2014-01-01
Copyright © 2014 ACM. Predicting protein structures and simulating protein folding are two of the most important problems in computational biology today. Simulation methods rely on a scoring function to distinguish the native structure (the most energetically stable) from non-native structures. Decoy databases are collections of non-native structures used to test and verify these functions. We present a method to evaluate and improve the quality of decoy databases by adding novel structures and removing redundant structures. We test our approach on 17 different decoy databases of varying size and type and show significant improvement across a variety of metrics. We also test our improved databases on a popular modern scoring function and show that they contain a greater number of native-like structures than the original databases, thereby producing a more rigorous database for testing scoring functions.
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Smitha, K A; Arun, K M; Rajesh, P G; Thomas, B; Kesavadas, C
2017-06-01
Language is a cardinal function that makes human unique. Preservation of language function poses a great challenge for surgeons during resection. The aim of the study was to assess the efficacy of resting-state fMRI in the lateralization of language function in healthy subjects to permit its further testing in patients who are unable to perform task-based fMRI. Eighteen healthy right-handed volunteers were prospectively evaluated with resting-state fMRI and task-based fMRI to assess language networks. The laterality indices of Broca and Wernicke areas were calculated by using task-based fMRI via a voxel-value approach. We adopted seed-based resting-state fMRI connectivity analysis together with parameters such as amplitude of low-frequency fluctuation and fractional amplitude of low-frequency fluctuation (fALFF). Resting-state fMRI connectivity maps for language networks were obtained from Broca and Wernicke areas in both hemispheres. We performed correlation analysis between the laterality index and the z scores of functional connectivity, amplitude of low-frequency fluctuation, and fALFF. Pearson correlation analysis between signals obtained from the z score of fALFF and the laterality index yielded a correlation coefficient of 0.849 ( P laterality index yielded an R 2 value of 0.721, indicating that 72.1% of the variance in the laterality index of task-based fMRI could be predicted from the fALFF of resting-state fMRI. The present study demonstrates that fALFF can be used as an alternative to task-based fMRI for assessing language laterality. There was a strong positive correlation between the fALFF of the Broca area of resting-state fMRI with the laterality index of task-based fMRI. Furthermore, we demonstrated the efficacy of fALFF for predicting the laterality of task-based fMRI. © 2017 by American Journal of Neuroradiology.
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NLTE4 Plasma Population Kinetics Database
SRD 159 NLTE4 Plasma Population Kinetics Database (Web database for purchase) This database contains benchmark results for simulation of plasma population kinetics and emission spectra. The data were contributed by the participants of the 4th Non-LTE Code Comparison Workshop who have unrestricted access to the database. The only limitation for other users is in hidden labeling of the output results. Guest users can proceed to the database entry page without entering userid and password.
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Mixed-effects and fMRI studies
DEFF Research Database (Denmark)
Friston, K.J; Stephan, K.E; Ellegaard Lund, Torben
2005-01-01
This note concerns mixed-effect (MFX) analyses in multisession functional magnetic resonance imaging (fMRI) studies. It clarifies the relationship between mixed-effect analyses and the two-stage 'summary statistics' procedure (Holmes, A.P., Friston, K.J., 1998. Generalisability, random effects...
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Decoding subjective mental states from fMRI activity patterns
International Nuclear Information System (INIS)
Tamaki, Masako; Kamitani, Yukiyasu
2011-01-01
In recent years, functional magnetic resonance imaging (fMRI) decoding has emerged as a powerful tool to read out detailed stimulus features from multi-voxel brain activity patterns. Moreover, the method has been extended to perform a primitive form of 'mind-reading,' by applying a decoder 'objectively' trained using stimulus features to more 'subjective' conditions. In this paper, we first introduce basic procedures for fMRI decoding based on machine learning techniques. Second, we discuss the source of information used for decoding, in particular, the possibility of extracting information from subvoxel neural structures. We next introduce two experimental designs for decoding subjective mental states: the 'objective-to-subjective design' and the 'subjective-to-subjective design.' Then, we illustrate recent studies on the decoding of a variety of mental states, such as, attention, awareness, decision making, memory, and mental imagery. Finally, we discuss the challenges and new directions of fMRI decoding. (author)
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The influence of FMRI lie detection evidence on juror decision-making.
McCabe, David P; Castel, Alan D; Rhodes, Matthew G
2011-01-01
In the current study, we report on an experiment examining whether functional magnetic resonance imaging (fMRI) lie detection evidence would influence potential jurors' assessment of guilt in a criminal trial. Potential jurors (N = 330) read a vignette summarizing a trial, with some versions of the vignette including lie detection evidence indicating that the defendant was lying about having committed the crime. Lie detector evidence was based on evidence from the polygraph, fMRI (functional brain imaging), or thermal facial imaging. Results showed that fMRI lie detection evidence led to more guilty verdicts than lie detection evidence based on polygraph evidence, thermal facial imaging, or a control condition that did not include lie detection evidence. However, when the validity of the fMRI lie detection evidence was called into question on cross-examination, guilty verdicts were reduced to the level of the control condition. These results provide important information about the influence of lie detection evidence in legal settings. Copyright © 2011 John Wiley & Sons, Ltd.
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Cortical control of gait in healthy humans: an fMRI study
International Nuclear Information System (INIS)
ChiHong, Wang; YauYau, Wai; BoCheng, Kuo; Yei-Yu, Yeh; JiunJie Wang
2008-01-01
This study examined the cortical control of gait in healthy humans using functional magnetic resonance imaging (fMRI). Two block-designed fMRI sessions were conducted during motor imagery of a locomotor-related task. Subjects watched a video clip that showed an actor standing and walking in an egocentric perspective. In a control session, additional fMRI images were collected when participants observed a video clip of the clutch movement of a right hand. In keeping with previous studies using SPECT and NIRS, we detected activation in many motor-related areas including supplementary motor area, bilateral precentral gyrus, left dorsal premotor cortex, and cingulate motor area. Smaller additional activations were observed in the bilateral precuneus, left thalamus, and part of right putamen. Based on these findings, we propose a novel paradigm to study the cortical control of gait in healthy humans using fMRI. Specifically, the task used in this study - involving both mirror neurons and mental imagery - provides a new feasible model to be used in functional neuroimaging studies in this area of research. (author)
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The impact of susceptibility gradients on cartesian and spiral EPI for BOLD fMRI
DEFF Research Database (Denmark)
Sangill, Ryan; Wallentin, Mikkel; Østergaard, Leif
2006-01-01
, with special emphasis on spiral EPI (spiral) and cartesian EPI (EPI) and their performance under influence of induced field gradients (SFGs) and stochastic noise. A numerical method for calculating synthetic MR images is developed and used to simulate BOLD fMRI experiments using EPI and spirals. The data...... is then examined for activation using a pixel-wise t test. Nine subjects are scanned with both techniques while performing a motor task. SPM99 is used for analysing the experimental data. The simulated spirals provide generally higher t scores at low SFGs but lose more strength than EPI at higher SFGs, where EPI...... activation is offset from the true position. In the primary motor area spirals provide significantly higher t scores (P SFG areas spirals provide stronger activation than...
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A Role for the Left Angular Gyrus in Episodic Simulation and Memory
Thakral, Preston P.; Madore, Kevin P.; Schacter, Daniel L.
2017-01-01
Functional magnetic resonance imaging (fMRI) studies indicate that episodic simulation (i.e., imagining specific future experiences) and episodic memory (i.e., remembering specific past experiences) are associated with enhanced activity in a common set of neural regions referred to as the core network. This network comprises the hippocampus, medial prefrontal cortex, and left angular gyrus, among other regions. Because fMRI data are correlational, it is unknown whether activity increases in c...
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Improving language mapping in clinical fMRI through assessment of grammar.
Połczyńska, Monika; Japardi, Kevin; Curtiss, Susan; Moody, Teena; Benjamin, Christopher; Cho, Andrew; Vigil, Celia; Kuhn, Taylor; Jones, Michael; Bookheimer, Susan
2017-01-01
Brain surgery in the language dominant hemisphere remains challenging due to unintended post-surgical language deficits, despite using pre-surgical functional magnetic resonance (fMRI) and intraoperative cortical stimulation. Moreover, patients are often recommended not to undergo surgery if the accompanying risk to language appears to be too high. While standard fMRI language mapping protocols may have relatively good predictive value at the group level, they remain sub-optimal on an individual level. The standard tests used typically assess lexico-semantic aspects of language, and they do not accurately reflect the complexity of language either in comprehension or production at the sentence level. Among patients who had left hemisphere language dominance we assessed which tests are best at activating language areas in the brain. We compared grammar tests (items testing word order in actives and passives, wh -subject and object questions, relativized subject and object clauses and past tense marking) with standard tests (object naming, auditory and visual responsive naming), using pre-operative fMRI. Twenty-five surgical candidates (13 females) participated in this study. Sixteen patients presented with a brain tumor, and nine with epilepsy. All participants underwent two pre-operative fMRI protocols: one including CYCLE-N grammar tests (items testing word order in actives and passives, wh-subject and object questions, relativized subject and object clauses and past tense marking); and a second one with standard fMRI tests (object naming, auditory and visual responsive naming). fMRI activations during performance in both protocols were compared at the group level, as well as in individual candidates. The grammar tests generated more volume of activation in the left hemisphere (left/right angular gyrus, right anterior/posterior superior temporal gyrus) and identified additional language regions not shown by the standard tests (e.g., left anterior
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Using real-time fMRI brain-computer interfacing to treat eating disorders.
Sokunbi, Moses O
2018-05-15
Real-time functional magnetic resonance imaging based brain-computer interfacing (fMRI neurofeedback) has shown encouraging outcomes in the treatment of psychiatric and behavioural disorders. However, its use in the treatment of eating disorders is very limited. Here, we give a brief overview of how to design and implement fMRI neurofeedback intervention for the treatment of eating disorders, considering the basic and essential components. We also attempt to develop potential adaptations of fMRI neurofeedback intervention for the treatment of anorexia nervosa, bulimia nervosa and binge eating disorder. Copyright © 2018 Elsevier B.V. All rights reserved.
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Simulator configuration management system
International Nuclear Information System (INIS)
Faulent, J.; Brooks, J.G.
1990-01-01
The proposed revisions to ANS 3.5-1985 (Section 5) require Utilities to establish a simulator Configuration Management System (CMS). The proposed CMS must be capable of: Establishing and maintaining a simulator design database. Identifying and documenting differences between the simulator and its reference plant. Tracking the resolution of identified differences. Recording data to support simulator certification, testing and maintenance. This paper discusses a CMS capable of meeting the proposed requirements contained in ANS 3.5. The system will utilize a personal computer and a relational database management software to construct a simulator design database. The database will contain records to all reference nuclear plant data used in designing the simulator, as well as records identifying all the software, hardware and documentation making up the simulator. Using the relational powers of the database management software, reports will be generated identifying the impact of reference plant changes on the operation of the simulator. These reports can then be evaluated in terms of training needs to determine if changes are required for the simulator. If a change is authorized, the CMS will track the change through to its resolution and then incorporate the change into the simulator design database
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Spectroscopic databases - A tool for structure elucidation
Energy Technology Data Exchange (ETDEWEB)
Luksch, P [Fachinformationszentrum Karlsruhe, Gesellschaft fuer Wissenschaftlich-Technische Information mbH, Eggenstein-Leopoldshafen (Germany)
1990-05-01
Spectroscopic databases have developed to useful tools in the process of structure elucidation. Besides the conventional library searches, new intelligent programs have been added, that are able to predict structural features from measured spectra or to simulate for a given structure. The example of the C13NMR/IR database developed at BASF and available on STN is used to illustrate the present capabilities of online database. New developments in the field of spectrum simulation and methods for the prediction of complete structures from spectroscopic information are reviewed. (author). 10 refs, 5 figs.
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DEFF Research Database (Denmark)
Charalampaki, Angeliki
2017-01-01
Motor area has a distinct directionality, depending on the stage of the volitional movement. In this study, we were interested in assessing the neuronal mechanism underlying this phenomenon. We therefore performed an fMRI study of Agency, to exploit the high spatial resolution this imaging technique...... displays. For the purposes of our study twenty participants were recruited. The experimental procedure we considered appropriate to study the Sense of Agency, involved participants laying inside the fMRI scanner and while they had no visual feedback of their hand, they were instructed to draw straight...... lines on a tablet with a digital pen. They could only see the consequences of their movement as a cursor’s movement on a screen. After finishing their movement, participants were requested to make a judgment over whether they felt they were the Agent of the observed movement or not. The analysis of our...
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Principal Feature Analysis: A Multivariate Feature Selection Method for fMRI Data
Directory of Open Access Journals (Sweden)
Lijun Wang
2013-01-01
Full Text Available Brain decoding with functional magnetic resonance imaging (fMRI requires analysis of complex, multivariate data. Multivoxel pattern analysis (MVPA has been widely used in recent years. MVPA treats the activation of multiple voxels from fMRI data as a pattern and decodes brain states using pattern classification methods. Feature selection is a critical procedure of MVPA because it decides which features will be included in the classification analysis of fMRI data, thereby improving the performance of the classifier. Features can be selected by limiting the analysis to specific anatomical regions or by computing univariate (voxel-wise or multivariate statistics. However, these methods either discard some informative features or select features with redundant information. This paper introduces the principal feature analysis as a novel multivariate feature selection method for fMRI data processing. This multivariate approach aims to remove features with redundant information, thereby selecting fewer features, while retaining the most information.
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Voluntary Enhancement of Neural Signatures of Affiliative Emotion Using fMRI Neurofeedback
Moll, Jorge; Weingartner, Julie H.; Bado, Patricia; Basilio, Rodrigo; Sato, João R.; Melo, Bruno R.; Bramati, Ivanei E.; de Oliveira-Souza, Ricardo; Zahn, Roland
2014-01-01
In Ridley Scott’s film “Blade Runner”, empathy-detection devices are employed to measure affiliative emotions. Despite recent neurocomputational advances, it is unknown whether brain signatures of affiliative emotions, such as tenderness/affection, can be decoded and voluntarily modulated. Here, we employed multivariate voxel pattern analysis and real-time fMRI to address this question. We found that participants were able to use visual feedback based on decoded fMRI patterns as a neurofeedback signal to increase brain activation characteristic of tenderness/affection relative to pride, an equally complex control emotion. Such improvement was not observed in a control group performing the same fMRI task without neurofeedback. Furthermore, the neurofeedback-driven enhancement of tenderness/affection-related distributed patterns was associated with local fMRI responses in the septohypothalamic area and frontopolar cortex, regions previously implicated in affiliative emotion. This demonstrates that humans can voluntarily enhance brain signatures of tenderness/affection, unlocking new possibilities for promoting prosocial emotions and countering antisocial behavior. PMID:24847819
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Feature-Space Clustering for fMRI Meta-Analysis
DEFF Research Database (Denmark)
Goutte, Cyril; Hansen, Lars Kai; Liptrot, Mathew G.
2001-01-01
MRI sequences containing several hundreds of images, it is sometimes necessary to invoke feature extraction to reduce the dimensionality of the data space. A second interesting application is in the meta-analysis of fMRI experiment, where features are obtained from a possibly large number of single......-voxel analyses. In particular this allows the checking of the differences and agreements between different methods of analysis. Both approaches are illustrated on a fMRI data set involving visual stimulation, and we show that the feature space clustering approach yields nontrivial results and, in particular......, shows interesting differences between individual voxel analysis performed with traditional methods. © 2001 Wiley-Liss, Inc....
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On clustering fMRI time series
DEFF Research Database (Denmark)
Goutte, Cyril; Toft, Peter Aundal; Rostrup, E.
1999-01-01
Analysis of fMRI time series is often performed by extracting one or more parameters for the individual voxels. Methods based, e.g., on various statistical tests are then used to yield parameters corresponding to probability of activation or activation strength. However, these methods do...
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A pooling-LiNGAM algorithm for effective connectivity analysis of fMRI data
Directory of Open Access Journals (Sweden)
Lele eXu
2014-10-01
Full Text Available The Independent Component Analysis - linear non-Gaussian acyclic model (LiNGAM, an algorithm that can be used to estimate the causal relationship among non-Gaussian distributed data, has the potential value to detect the effective connectivity of human brain areas. Under the assumptions that (a: the data generating process is linear, (b there are no unobserved confounders, and (c data have non-Gaussian distributions, LiNGAM can be used to discover the complete causal structure of data. Previous studies reveal that the algorithm could perform well when the data points being analyzed is relatively long. However, there are too few data points in most neuroimaging recordings, especially functional magnetic resonance imaging (fMRI, to allow the algorithm to converge. Smith’s study speculates a method by pooling data points across subjects may be useful to address this issue (Smith et al., 2011. Thus this study focus on validating Smith’s proposal of pooling data points across subjects for the use of LiNGAM, and this method is named as pooling-LiNGAM (pLiNGAM. Using both simulated and real fMRI data, our current study demonstrates the feasibility and efficiency of the pLiNGAM on the effective connectivity estimation.
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Directory of Open Access Journals (Sweden)
S. Khatiwala
2012-04-01
Full Text Available The global ocean has taken up a large fraction of the CO2 released by human activities since the industrial revolution. Quantifying the oceanic anthropogenic carbon (Cant inventory and its variability is important for predicting the future global carbon cycle. The detailed comparison of data-based and model-based estimates is essential for the validation and continued improvement of our prediction capabilities. So far, three global estimates of oceanic Cant inventory that are "data-based" and independent of global ocean circulation models have been produced: one based on the Δ C* method, and two that are based on constraining surface-to-interior transport of tracers, the TTD method and a maximum entropy inversion method (GF. The GF method, in particular, is capable of reconstructing the history of Cant inventory through the industrial era. In the present study we use forward model simulations of the Community Climate System Model (CCSM3.1 to estimate the Cant inventory and compare the results with the data-based estimates. We also use the simulations to test several assumptions of the GF method, including the assumption of constant climate and circulation, which is common to all the data-based estimates. Though the integrated estimates of global Cant inventories are consistent with each other, the regional estimates show discrepancies up to 50 %. The CCSM3 model underestimates the total Cant inventory, in part due to weak mixing and ventilation in the North Atlantic and Southern Ocean. Analyses of different simulation results suggest that key assumptions about ocean circulation and air-sea disequilibrium in the GF method are generally valid on the global scale, but may introduce errors in Cant estimates on regional scales. The GF method should also be used with caution when predicting future oceanic anthropogenic carbon uptake.
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Potential pitfalls when denoising resting state fMRI data using nuisance regression.
Bright, Molly G; Tench, Christopher R; Murphy, Kevin
2017-07-01
In resting state fMRI, it is necessary to remove signal variance associated with noise sources, leaving cleaned fMRI time-series that more accurately reflect the underlying intrinsic brain fluctuations of interest. This is commonly achieved through nuisance regression, in which the fit is calculated of a noise model of head motion and physiological processes to the fMRI data in a General Linear Model, and the "cleaned" residuals of this fit are used in further analysis. We examine the statistical assumptions and requirements of the General Linear Model, and whether these are met during nuisance regression of resting state fMRI data. Using toy examples and real data we show how pre-whitening, temporal filtering and temporal shifting of regressors impact model fit. Based on our own observations, existing literature, and statistical theory, we make the following recommendations when employing nuisance regression: pre-whitening should be applied to achieve valid statistical inference of the noise model fit parameters; temporal filtering should be incorporated into the noise model to best account for changes in degrees of freedom; temporal shifting of regressors, although merited, should be achieved via optimisation and validation of a single temporal shift. We encourage all readers to make simple, practical changes to their fMRI denoising pipeline, and to regularly assess the appropriateness of the noise model used. By negotiating the potential pitfalls described in this paper, and by clearly reporting the details of nuisance regression in future manuscripts, we hope that the field will achieve more accurate and precise noise models for cleaning the resting state fMRI time-series. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
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Analytic programming with FMRI data: a quick-start guide for statisticians using R.
Eloyan, Ani; Li, Shanshan; Muschelli, John; Pekar, Jim J; Mostofsky, Stewart H; Caffo, Brian S
2014-01-01
Functional magnetic resonance imaging (fMRI) is a thriving field that plays an important role in medical imaging analysis, biological and neuroscience research and practice. This manuscript gives a didactic introduction to the statistical analysis of fMRI data using the R project, along with the relevant R code. The goal is to give statisticians who would like to pursue research in this area a quick tutorial for programming with fMRI data. References of relevant packages and papers are provided for those interested in more advanced analysis.
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Probing the brain with molecular fMRI.
Ghosh, Souparno; Harvey, Peter; Simon, Jacob C; Jasanoff, Alan
2018-04-09
One of the greatest challenges of modern neuroscience is to incorporate our growing knowledge of molecular and cellular-scale physiology into integrated, organismic-scale models of brain function in behavior and cognition. Molecular-level functional magnetic resonance imaging (molecular fMRI) is a new technology that can help bridge these scales by mapping defined microscopic phenomena over large, optically inaccessible regions of the living brain. In this review, we explain how MRI-detectable imaging probes can be used to sensitize noninvasive imaging to mechanistically significant components of neural processing. We discuss how a combination of innovative probe design, advanced imaging methods, and strategies for brain delivery can make molecular fMRI an increasingly successful approach for spatiotemporally resolved studies of diverse neural phenomena, perhaps eventually in people. Copyright © 2018 Elsevier Ltd. All rights reserved.
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Signal Sampling for Efficient Sparse Representation of Resting State FMRI Data
Ge, Bao; Makkie, Milad; Wang, Jin; Zhao, Shijie; Jiang, Xi; Li, Xiang; Lv, Jinglei; Zhang, Shu; Zhang, Wei; Han, Junwei; Guo, Lei; Liu, Tianming
2015-01-01
As the size of brain imaging data such as fMRI grows explosively, it provides us with unprecedented and abundant information about the brain. How to reduce the size of fMRI data but not lose much information becomes a more and more pressing issue. Recent literature studies tried to deal with it by dictionary learning and sparse representation methods, however, their computation complexities are still high, which hampers the wider application of sparse representation method to large scale fMRI datasets. To effectively address this problem, this work proposes to represent resting state fMRI (rs-fMRI) signals of a whole brain via a statistical sampling based sparse representation. First we sampled the whole brain’s signals via different sampling methods, then the sampled signals were aggregate into an input data matrix to learn a dictionary, finally this dictionary was used to sparsely represent the whole brain’s signals and identify the resting state networks. Comparative experiments demonstrate that the proposed signal sampling framework can speed-up by ten times in reconstructing concurrent brain networks without losing much information. The experiments on the 1000 Functional Connectomes Project further demonstrate its effectiveness and superiority. PMID:26646924
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Resting-state fMRI and social cognition: An opportunity to connect.
Doruyter, Alex; Groenewold, Nynke A; Dupont, Patrick; Stein, Dan J; Warwick, James M
2017-09-01
Many psychiatric disorders are characterized by altered social cognition. The importance of social cognition has previously been recognized by the National Institute of Mental Health Research Domain Criteria project, in which it features as a core domain. Social task-based functional magnetic resonance imaging (fMRI) currently offers the most direct insight into how the brain processes social information; however, resting-state fMRI may be just as important in understanding the biology and network nature of social processing. Resting-state fMRI allows researchers to investigate the functional relationships between brain regions in a neutral state: so-called resting functional connectivity (RFC). There is evidence that RFC is predictive of how the brain processes information during social tasks. This is important because it shifts the focus from possibly context-dependent aberrations to context-independent aberrations in functional network architecture. Rather than being analysed in isolation, the study of resting-state brain networks shows promise in linking results of task-based fMRI results, structural connectivity, molecular imaging findings, and performance measures of social cognition-which may prove crucial in furthering our understanding of the social brain. Copyright © 2017 John Wiley & Sons, Ltd.
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Amir, Sahar Z.
2013-05-01
We introduce an efficient thermodynamically consistent technique to extrapolate and interpolate normalized Canonical NVT ensemble averages like pressure and energy for Lennard-Jones (L-J) fluids. Preliminary results show promising applicability in oil and gas modeling, where accurate determination of thermodynamic properties in reservoirs is challenging. The thermodynamic interpolation and thermodynamic extrapolation schemes predict ensemble averages at different thermodynamic conditions from expensively simulated data points. The methods reweight and reconstruct previously generated database values of Markov chains at neighboring temperature and density conditions. To investigate the efficiency of these methods, two databases corresponding to different combinations of normalized density and temperature are generated. One contains 175 Markov chains with 10,000,000 MC cycles each and the other contains 3000 Markov chains with 61,000,000 MC cycles each. For such massive database creation, two algorithms to parallelize the computations have been investigated. The accuracy of the thermodynamic extrapolation scheme is investigated with respect to classical interpolation and extrapolation. Finally, thermodynamic interpolation benefiting from four neighboring Markov chains points is implemented and compared with previous schemes. The thermodynamic interpolation scheme using knowledge from the four neighboring points proves to be more accurate than the thermodynamic extrapolation from the closest point only, while both thermodynamic extrapolation and thermodynamic interpolation are more accurate than the classical interpolation and extrapolation. The investigated extrapolation scheme has great potential in oil and gas reservoir modeling.That is, such a scheme has the potential to speed up the MCMC thermodynamic computation to be comparable with conventional Equation of State approaches in efficiency. In particular, this makes it applicable to large-scale optimization of L
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Directory of Open Access Journals (Sweden)
Wenjing Huang
Full Text Available The mechanisms of action underlying acupuncture, including acupuncture point specificity, are not well understood. In the previous decade, an increasing number of studies have applied fMRI to investigate brain response to acupuncture stimulation. Our aim was to provide a systematic overview of acupuncture fMRI research considering the following aspects: 1 differences between verum and sham acupuncture, 2 differences due to various methods of acupuncture manipulation, 3 differences between patients and healthy volunteers, 4 differences between different acupuncture points.We systematically searched English, Chinese, Korean and Japanese databases for literature published from the earliest available up until September 2009, without any language restrictions. We included all studies using fMRI to investigate the effect of acupuncture on the human brain (at least one group that received needle-based acupuncture. 779 papers were identified, 149 met the inclusion criteria for the descriptive analysis, and 34 were eligible for the meta-analyses. From a descriptive perspective, multiple studies reported that acupuncture modulates activity within specific brain areas, including somatosensory cortices, limbic system, basal ganglia, brain stem, and cerebellum. Meta-analyses for verum acupuncture stimuli confirmed brain activity within many of the regions mentioned above. Differences between verum and sham acupuncture were noted in brain response in middle cingulate, while some heterogeneity was noted for other regions depending on how such meta-analyses were performed, such as sensorimotor cortices, limbic regions, and cerebellum.Brain response to acupuncture stimuli encompasses a broad network of regions consistent with not just somatosensory, but also affective and cognitive processing. While the results were heterogeneous, from a descriptive perspective most studies suggest that acupuncture can modulate the activity within specific brain areas, and the
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Application of calibrated fMRI in Alzheimer's disease.
Lajoie, Isabelle; Nugent, Scott; Debacker, Clément; Dyson, Kenneth; Tancredi, Felipe B; Badhwar, AmanPreet; Belleville, Sylvie; Deschaintre, Yan; Bellec, Pierre; Doyon, Julien; Bocti, Christian; Gauthier, Serge; Arnold, Douglas; Kergoat, Marie-Jeanne; Chertkow, Howard; Monchi, Oury; Hoge, Richard D
2017-01-01
Calibrated fMRI based on arterial spin-labeling (ASL) and blood oxygen-dependent contrast (BOLD), combined with periods of hypercapnia and hyperoxia, can provide information on cerebrovascular reactivity (CVR), resting blood flow (CBF), oxygen extraction fraction (OEF), and resting oxidative metabolism (CMRO 2 ). Vascular and metabolic integrity are believed to be affected in Alzheimer's disease (AD), thus, the use of calibrated fMRI in AD may help understand the disease and monitor therapeutic responses in future clinical trials. In the present work, we applied a calibrated fMRI approach referred to as Quantitative O2 (QUO2) in a cohort of probable AD dementia and age-matched control participants. The resulting CBF, OEF and CMRO 2 values fell within the range from previous studies using positron emission tomography (PET) with 15 O labeling. Moreover, the typical parietotemporal pattern of hypoperfusion and hypometabolism in AD was observed, especially in the precuneus, a particularly vulnerable region. We detected no deficit in frontal CBF, nor in whole grey matter CVR, which supports the hypothesis that the effects observed were associated specifically with AD rather than generalized vascular disease. Some key pitfalls affecting both ASL and BOLD methods were encountered, such as prolonged arterial transit times (particularly in the occipital lobe), the presence of susceptibility artifacts obscuring medial temporal regions, and the challenges associated with the hypercapnic manipulation in AD patients and elderly participants. The present results are encouraging and demonstrate the promise of calibrated fMRI measurements as potential biomarkers in AD. Although CMRO 2 can be imaged with 15 O PET, the QUO2 method uses more widely available imaging infrastructure, avoids exposure to ionizing radiation, and integrates with other MRI-based measures of brain structure and function.
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Application of calibrated fMRI in Alzheimer's disease
Directory of Open Access Journals (Sweden)
Isabelle Lajoie
2017-01-01
Full Text Available Calibrated fMRI based on arterial spin-labeling (ASL and blood oxygen-dependent contrast (BOLD, combined with periods of hypercapnia and hyperoxia, can provide information on cerebrovascular reactivity (CVR, resting blood flow (CBF, oxygen extraction fraction (OEF, and resting oxidative metabolism (CMRO2. Vascular and metabolic integrity are believed to be affected in Alzheimer's disease (AD, thus, the use of calibrated fMRI in AD may help understand the disease and monitor therapeutic responses in future clinical trials. In the present work, we applied a calibrated fMRI approach referred to as Quantitative O2 (QUO2 in a cohort of probable AD dementia and age-matched control participants. The resulting CBF, OEF and CMRO2 values fell within the range from previous studies using positron emission tomography (PET with 15O labeling. Moreover, the typical parietotemporal pattern of hypoperfusion and hypometabolism in AD was observed, especially in the precuneus, a particularly vulnerable region. We detected no deficit in frontal CBF, nor in whole grey matter CVR, which supports the hypothesis that the effects observed were associated specifically with AD rather than generalized vascular disease. Some key pitfalls affecting both ASL and BOLD methods were encountered, such as prolonged arterial transit times (particularly in the occipital lobe, the presence of susceptibility artifacts obscuring medial temporal regions, and the challenges associated with the hypercapnic manipulation in AD patients and elderly participants. The present results are encouraging and demonstrate the promise of calibrated fMRI measurements as potential biomarkers in AD. Although CMRO2 can be imaged with 15O PET, the QUO2 method uses more widely available imaging infrastructure, avoids exposure to ionizing radiation, and integrates with other MRI-based measures of brain structure and function.
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Cantini, Federico; Pio Rossi, Angelo; Orosei, Roberto; Baumann, Peter; Misev, Dimitar; Oosthoek, Jelmer; Beccati, Alan; Campalani, Piero; Unnithan, Vikram
2014-05-01
MARSIS is an orbital synthetic aperture radar for both ionosphere and subsurface sounding on board ESA's Mars Express (Picardi et al. 2005). It transmits electromagnetic pulses centered at 1.8, 3, 4 or 5 MHz that penetrate below the surface and are reflected by compositional and/or structural discontinuities in the subsurface of Mars. MARSIS data are available as a collection of single orbit data files. The availability of tools for a more effective access to such data would greatly ease data analysis and exploitation by the community of users. For this purpose, we are developing a database built on the raster database management system RasDaMan (e.g. Baumann et al., 1994), to be populated with MARSIS data and integrated in the PlanetServer/EarthServer (e.g. Oosthoek et al., 2013; Rossi et al., this meeting) project. The data (and related metadata) are stored in the db for each frequency used by MARSIS radar. The capability of retrieving data belonging to a certain orbit or to multiple orbit on the base of latitute/longitude boundaries is a key requirement of the db design, allowing, besides the "classical" radargram representation of the data, and in area with sufficiently hight orbit density, a 3D data extraction, subset and analysis of subsurface structures. Moreover the use of the OGC WCPS (Web Coverage Processing Service) standard can allow calculations on database query results for multiple echoes and/or subsets of a certain data product. Because of the low directivity of its dipole antenna, MARSIS receives echoes from portions of the surface of Mars that are distant from nadir and can be mistakenly interpreted as subsurface echoes. For this reason, methods have been developed to simulate surface echoes (e.g. Nouvel et al., 2004), to reveal the true origin of an echo through comparison with instrument data. These simulations are usually time-consuming, and so far have been performed either on a case-by-case basis or in some simplified form. A code for
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fMRI paradigm designing and post-processing tools
International Nuclear Information System (INIS)
James, Jija S; Rajesh, PG; Chandran, Anuvitha VS; Kesavadas, Chandrasekharan
2014-01-01
In this article, we first review some aspects of functional magnetic resonance imaging (fMRI) paradigm designing for major cognitive functions by using stimulus delivery systems like Cogent, E-Prime, Presentation, etc., along with their technical aspects. We also review the stimulus presentation possibilities (block, event-related) for visual or auditory paradigms and their advantage in both clinical and research setting. The second part mainly focus on various fMRI data post-processing tools such as Statistical Parametric Mapping (SPM) and Brain Voyager, and discuss the particulars of various preprocessing steps involved (realignment, co-registration, normalization, smoothing) in these software and also the statistical analysis principles of General Linear Modeling for final interpretation of a functional activation result
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Test-retest reliability of an fMRI paradigm for studies of cardiovascular reactivity.
Sheu, Lei K; Jennings, J Richard; Gianaros, Peter J
2012-07-01
We examined the reliability of measures of fMRI, subjective, and cardiovascular reactions to standardized versions of a Stroop color-word task and a multisource interference task. A sample of 14 men and 12 women (30-49 years old) completed the tasks on two occasions, separated by a median of 88 days. The reliability of fMRI BOLD signal changes in brain areas engaged by the tasks was moderate, and aggregating fMRI BOLD signal changes across the tasks improved test-retest reliability metrics. These metrics included voxel-wise intraclass correlation coefficients (ICCs) and overlap ratio statistics. Task-aggregated ratings of subjective arousal, valence, and control, as well as cardiovascular reactions evoked by the tasks showed ICCs of 0.57 to 0.87 (ps reliability. These findings support using these tasks as a battery for fMRI studies of cardiovascular reactivity. Copyright © 2012 Society for Psychophysiological Research.
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Optimizing Within-Subject Experimental Designs for jICA of Multi-Channel ERP and fMRI
Mangalathu-Arumana, Jain; Liebenthal, Einat; Beardsley, Scott A.
2018-01-01
Joint independent component analysis (jICA) can be applied within subject for fusion of multi-channel event-related potentials (ERP) and functional magnetic resonance imaging (fMRI), to measure brain function at high spatiotemporal resolution (Mangalathu-Arumana et al., 2012). However, the impact of experimental design choices on jICA performance has not been systematically studied. Here, the sensitivity of jICA for recovering neural sources in individual data was evaluated as a function of imaging SNR, number of independent representations of the ERP/fMRI data, relationship between instantiations of the joint ERP/fMRI activity (linear, non-linear, uncoupled), and type of sources (varying parametrically and non-parametrically across representations of the data), using computer simulations. Neural sources were simulated with spatiotemporal and noise attributes derived from experimental data. The best performance, maximizing both cross-modal data fusion and the separation of brain sources, occurred with a moderate number of representations of the ERP/fMRI data (10–30), as in a mixed block/event related experimental design. Importantly, the type of relationship between instantiations of the ERP/fMRI activity, whether linear, non-linear or uncoupled, did not in itself impact jICA performance, and was accurately recovered in the common profiles (i.e., mixing coefficients). Thus, jICA provides an unbiased way to characterize the relationship between ERP and fMRI activity across brain regions, in individual data, rendering it potentially useful for characterizing pathological conditions in which neurovascular coupling is adversely affected. PMID:29410611
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On the plurality of (methodological worlds: Estimating the analytic flexibility of fMRI experiments.
Directory of Open Access Journals (Sweden)
Joshua eCarp
2012-10-01
Full Text Available How likely are published findings in the functional neuroimaging literature to be false? According to a recent mathematical model, the potential for false positives increases with the flexibility of analysis methods. Functional MRI (fMRI experiments can be analyzed using a large number of commonly used tools, with little consensus on how, when, or whether to apply each one. This situation may lead to substantial variability in analysis outcomes. Thus, the present study sought to estimate the flexibility of neuroimaging analysis by submitting a single event-related fMRI experiment to a large number of unique analysis procedures. Ten analysis steps for which multiple strategies appear in the literature were identified, and two to four strategies were enumerated for each step. Considering all possible combinations of these strategies yielded 6,912 unique analysis pipelines. Activation maps from each pipeline were corrected for multiple comparisons using five thresholding approaches, yielding 34,560 significance maps. While some outcomes were relatively consistent across pipelines, others showed substantial methods-related variability in activation strength, location, and extent. Some analysis decisions contributed to this variability more than others, and different decisions were associated with distinct patterns of variability across the brain. Qualitative outcomes also varied with analysis parameters: many contrasts yielded significant activation under some pipelines but not others. Altogether, these results reveal considerable flexibility in the analysis of fMRI experiments. This observation, when combined with mathematical simulations linking analytic flexibility with elevated false positive rates, suggests that false positive results may be more prevalent than expected in the literature. This risk of inflated false positive rates may be mitigated by constraining the flexibility of analytic choices or by abstaining from selective analysis
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DABAM: an open-source database of X-ray mirrors metrology
Energy Technology Data Exchange (ETDEWEB)
Sanchez del Rio, Manuel, E-mail: srio@esrf.eu [ESRF - The European Synchrotron, 71 Avenue des Martyrs, 38000 Grenoble (France); Bianchi, Davide [AC2T Research GmbH, Viktro-Kaplan-Strasse 2-C, 2700 Wiener Neustadt (Austria); Cocco, Daniele [SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA 94025 (United States); Glass, Mark [ESRF - The European Synchrotron, 71 Avenue des Martyrs, 38000 Grenoble (France); Idir, Mourad [NSLS II, Brookhaven National Laboratory, Upton, NY 11973-5000 (United States); Metz, Jim [InSync Inc., 2511C Broadbent Parkway, Albuquerque, NM 87107 (United States); Raimondi, Lorenzo; Rebuffi, Luca [Elettra-Sincrotrone Trieste SCpA, Basovizza (TS) (Italy); Reininger, Ruben; Shi, Xianbo [Advanced Photon Source, Argonne National Laboratory, Argonne, IL 60439 (United States); Siewert, Frank [BESSY II, Helmholtz Zentrum Berlin, Institute for Nanometre Optics and Technology, Albert-Einstein-Strasse 15, 12489 Berlin (Germany); Spielmann-Jaeggi, Sibylle [Swiss Light Source at Paul Scherrer Institut, CH-5232 Villigen PSI (Switzerland); Takacs, Peter [Instrumentation Division, Brookhaven National Laboratory, Upton, NY 11973-5000 (United States); Tomasset, Muriel [Synchrotron Soleil (France); Tonnessen, Tom [InSync Inc., 2511C Broadbent Parkway, Albuquerque, NM 87107 (United States); Vivo, Amparo [ESRF - The European Synchrotron, 71 Avenue des Martyrs, 38000 Grenoble (France); Yashchuk, Valeriy [Advanced Light Source, Lawrence Berkeley National Laboratory, MS 15-R0317, 1 Cyclotron Road, Berkeley, CA 94720-8199 (United States)
2016-04-20
DABAM, an open-source database of X-ray mirrors metrology to be used with ray-tracing and wave-propagation codes for simulating the effect of the surface errors on the performance of a synchrotron radiation beamline. An open-source database containing metrology data for X-ray mirrors is presented. It makes available metrology data (mirror heights and slopes profiles) that can be used with simulation tools for calculating the effects of optical surface errors in the performances of an optical instrument, such as a synchrotron beamline. A typical case is the degradation of the intensity profile at the focal position in a beamline due to mirror surface errors. This database for metrology (DABAM) aims to provide to the users of simulation tools the data of real mirrors. The data included in the database are described in this paper, with details of how the mirror parameters are stored. An accompanying software is provided to allow simple access and processing of these data, calculate the most usual statistical parameters, and also include the option of creating input files for most used simulation codes. Some optics simulations are presented and discussed to illustrate the real use of the profiles from the database.
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Energy Technology Data Exchange (ETDEWEB)
Mota, Ana [Instituto de Biofísica e Engenharia Biomédica, FC-UL, Lisboa (Portugal); Institute of Nuclear Medicine, UCL, London (United Kingdom); Cuplov, Vesna [Instituto de Biofísica e Engenharia Biomédica, FC-UL, Lisboa (Portugal); Schott, Jonathan; Hutton, Brian; Thielemans, Kris [Institute of Nuclear Medicine, UCL, London (United Kingdom); Drobnjak, Ivana [Centre of Medical Image Computing, UCL, London (United Kingdom); Dickson, John [Institute of Nuclear Medicine, UCL, London (United Kingdom); Bert, Julien [INSERM UMR1101, LaTIM, CHRU de Brest, Brest (France); Burgos, Ninon; Cardoso, Jorge; Modat, Marc; Ourselin, Sebastien [Centre of Medical Image Computing, UCL, London (United Kingdom); Erlandsson, Kjell [Institute of Nuclear Medicine, UCL, London (United Kingdom)
2015-05-18
The Partial Volume (PV) effect in Positron Emission Tomography (PET) imaging leads to loss in quantification accuracy, which manifests in PV effects (small objects occupy partially the sensitive volume of the imaging instrument, resulting in blurred images). Simultaneous acquisition of PET and Magnetic Resonance Imaging (MRI) produces concurrent metabolic and anatomical information. The latter has proved to be very helpful for the correction of PV effects. Currently, there are several techniques used for PV correction. They can be applied directly during the reconstruction process or as a post-processing step after image reconstruction. In order to evaluate the efficacy of the different PV correction techniques in brain- PET, we are constructing a database of simulated data. Here we present the framework and steps involved in constructing this database. Static 18F-FDG epilepsy and 18F-Florbetapir amyloid dementia PET/MR were selected because of their very different characteristics. The methodology followed was based on four main steps: Image pre-processing, Ground Truth (GT) generation, MRI and PET data simulation and reconstruction. All steps used Open Source software and can therefore be repeated at any centre. The framework as well as the database will be freely accessible. Tools used included GIF, FSL, POSSUM, GATE and STIR. The final data obtained after simulation, involving raw or reconstructed PET data together with corresponding MRI datasets, were close to the original patient data. Besides, there is the advantage that data can be compared with the GT. We indicate several parameters that can be improved and optimized.
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International Nuclear Information System (INIS)
Mota, Ana; Cuplov, Vesna; Schott, Jonathan; Hutton, Brian; Thielemans, Kris; Drobnjak, Ivana; Dickson, John; Bert, Julien; Burgos, Ninon; Cardoso, Jorge; Modat, Marc; Ourselin, Sebastien; Erlandsson, Kjell
2015-01-01
The Partial Volume (PV) effect in Positron Emission Tomography (PET) imaging leads to loss in quantification accuracy, which manifests in PV effects (small objects occupy partially the sensitive volume of the imaging instrument, resulting in blurred images). Simultaneous acquisition of PET and Magnetic Resonance Imaging (MRI) produces concurrent metabolic and anatomical information. The latter has proved to be very helpful for the correction of PV effects. Currently, there are several techniques used for PV correction. They can be applied directly during the reconstruction process or as a post-processing step after image reconstruction. In order to evaluate the efficacy of the different PV correction techniques in brain- PET, we are constructing a database of simulated data. Here we present the framework and steps involved in constructing this database. Static 18F-FDG epilepsy and 18F-Florbetapir amyloid dementia PET/MR were selected because of their very different characteristics. The methodology followed was based on four main steps: Image pre-processing, Ground Truth (GT) generation, MRI and PET data simulation and reconstruction. All steps used Open Source software and can therefore be repeated at any centre. The framework as well as the database will be freely accessible. Tools used included GIF, FSL, POSSUM, GATE and STIR. The final data obtained after simulation, involving raw or reconstructed PET data together with corresponding MRI datasets, were close to the original patient data. Besides, there is the advantage that data can be compared with the GT. We indicate several parameters that can be improved and optimized.
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FIACH: A biophysical model for automatic retrospective noise control in fMRI.
Tierney, Tim M; Weiss-Croft, Louise J; Centeno, Maria; Shamshiri, Elhum A; Perani, Suejen; Baldeweg, Torsten; Clark, Christopher A; Carmichael, David W
2016-01-01
Different noise sources in fMRI acquisition can lead to spurious false positives and reduced sensitivity. We have developed a biophysically-based model (named FIACH: Functional Image Artefact Correction Heuristic) which extends current retrospective noise control methods in fMRI. FIACH can be applied to both General Linear Model (GLM) and resting state functional connectivity MRI (rs-fcMRI) studies. FIACH is a two-step procedure involving the identification and correction of non-physiological large amplitude temporal signal changes and spatial regions of high temporal instability. We have demonstrated its efficacy in a sample of 42 healthy children while performing language tasks that include overt speech with known activations. We demonstrate large improvements in sensitivity when FIACH is compared with current methods of retrospective correction. FIACH reduces the confounding effects of noise and increases the study's power by explaining significant variance that is not contained within the commonly used motion parameters. The method is particularly useful in detecting activations in inferior temporal regions which have proven problematic for fMRI. We have shown greater reproducibility and robustness of fMRI responses using FIACH in the context of task induced motion. In a clinical setting this will translate to increasing the reliability and sensitivity of fMRI used for the identification of language lateralisation and eloquent cortex. FIACH can benefit studies of cognitive development in young children, patient populations and older adults. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
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Hattemer, Katja; Plate, Annika; Heverhagen, Johannes T; Haag, Anja; Keil, Boris; Klein, Karl Martin; Hermsen, Anke; Oertel, Wolfgang H; Hamer, Hajo M; Rosenow, Felix; Knake, Susanne
2011-01-01
the aim of this study was to investigate specific activation patterns and potential gender differences during mental rotation and to investigate whether functional magnetic resonance imaging (fMRI) and functional transcranial Doppler sonography (fTCD) lateralize hemispheric dominance concordantly. regional brain activation and hemispheric dominance during mental rotation (cube perspective test) were investigated in 10 female and 10 male healthy subjects using fMRI and fTCD. significant activation was found in the superior parietal lobe, at the parieto-occipital border, in the middle and superior frontal gyrus bilaterally, and the right inferior frontal gyrus using fMRI. Men showed a stronger lateralization to the right hemisphere during fMRI and a tendency toward stronger right-hemispheric activation during fTCD. Furthermore, more activation in frontal and parieto-occipital regions of the right hemisphere was observed using fMRI. Hemispheric dominance for mental rotation determined by the 2 methods correlated well (P= .008), but did not show concordant results in every single subject. the neural basis of mental rotation depends on a widespread bilateral network. Hemispheric dominance for mental rotation determined by fMRI and fTCD, though correlating well, is not always concordant. Hemispheric lateralization of complex cortical functions such as spatial rotation therefore should be investigated using multimodal imaging approaches, especially if used clinically as a tool for the presurgical evaluation of patients undergoing neurosurgery. Copyright © 2009 by the American Society of Neuroimaging.
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Jacquinet-Husson, N.; Lmd Team
The GEISA (Gestion et Etude des Informations Spectroscopiques Atmosphériques: Management and Study of Atmospheric Spectroscopic Information) computer accessible database system, in its former 1997 and 2001 versions, has been updated in 2003 (GEISA-03). It is developed by the ARA (Atmospheric Radiation Analysis) group at LMD (Laboratoire de Météorologie Dynamique, France) since 1974. This early effort implemented the so-called `` line-by-line and layer-by-layer '' approach for forward radiative transfer modelling action. The GEISA 2003 system comprises three databases with their associated management softwares: a database of spectroscopic parameters required to describe adequately the individual spectral lines belonging to 42 molecules (96 isotopic species) and located in a spectral range from the microwave to the limit of the visible. The featured molecules are of interest in studies of the terrestrial as well as the other planetary atmospheres, especially those of the Giant Planets. a database of absorption cross-sections of molecules such as chlorofluorocarbons which exhibit unresolvable spectra. a database of refractive indices of basic atmospheric aerosol components. Illustrations will be given of GEISA-03, data archiving method, contents, management softwares and Web access facilities at: http://ara.lmd.polytechnique.fr The performance of instruments like AIRS (Atmospheric Infrared Sounder; http://www-airs.jpl.nasa.gov) in the USA, and IASI (Infrared Atmospheric Sounding Interferometer; http://smsc.cnes.fr/IASI/index.htm) in Europe, which have a better vertical resolution and accuracy, compared to the presently existing satellite infrared vertical sounders, is directly related to the quality of the spectroscopic parameters of the optically active gases, since these are essential input in the forward models used to simulate recorded radiance spectra. For these upcoming atmospheric sounders, the so-called GEISA/IASI sub-database system has been elaborated
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Energy Technology Data Exchange (ETDEWEB)
Wengenroth, Martina; Blatow, M.; Guenther, J. [University of Heidelberg Medical School, Department of Neuroradiology, Heidelberg (Germany); Akbar, M. [University of Heidelberg Medical School, Department of Orthopaedics, Heidelberg (Germany); Tronnier, V.M. [University of Schleswig-Holstein, Department of Neurosurgery, Luebeck (Germany); Stippich, C. [University Hospital Basle, Department of Diagnostic and Interventional Neuroradiology, Basle (Switzerland)
2011-07-15
Reliable imaging of eloquent tumour-adjacent brain areas is necessary for planning function-preserving neurosurgery. This study evaluates the potential diagnostic benefits of presurgical functional magnetic resonance imaging (fMRI) in comparison to a detailed analysis of morphological MRI data. Standardised preoperative functional and structural neuroimaging was performed on 77 patients with rolandic mass lesions at 1.5 Tesla. The central region of both hemispheres was allocated using six morphological and three functional landmarks. fMRI enabled localisation of the motor hand area in 76/77 patients, which was significantly superior to analysis of structural MRI (confident localisation of motor hand area in 66/77 patients; p < 0.002). FMRI provided additional diagnostic information in 96% (tongue representation) and 97% (foot representation) of patients. FMRI-based presurgical risk assessment correlated in 88% with a positive postoperative clinical outcome. Routine presurgical FMRI allows for superior assessment of the spatial relationship between brain tumour and motor cortex compared with a very detailed analysis of structural 3D MRI, thus significantly facilitating the preoperative risk-benefit assessment and function-preserving surgery. The additional imaging time seems justified. FMRI has the potential to reduce postoperative morbidity and therefore hospitalisation time. (orig.)
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Sair, Haris I; Yahyavi-Firouz-Abadi, Noushin; Calhoun, Vince D; Airan, Raag D; Agarwal, Shruti; Intrapiromkul, Jarunee; Choe, Ann S; Gujar, Sachin K; Caffo, Brian; Lindquist, Martin A; Pillai, Jay J
2016-03-01
To compare language networks derived from resting-state fMRI (rs-fMRI) with task-fMRI in patients with brain tumors and investigate variables that affect rs-fMRI vs task-fMRI concordance. Independent component analysis (ICA) of rs-fMRI was performed with 20, 30, 40, and 50 target components (ICA20 to ICA50) and language networks identified for patients presenting for presurgical fMRI mapping between 1/1/2009 and 7/1/2015. 49 patients were analyzed fulfilling criteria for presence of brain tumors, no prior brain surgery, and adequate task-fMRI performance. Rs-vs-task-fMRI concordance was measured using Dice coefficients across varying fMRI thresholds before and after noise removal. Multi-thresholded Dice coefficient volume under the surface (DiceVUS) and maximum Dice coefficient (MaxDice) were calculated. One-way Analysis of Variance (ANOVA) was performed to determine significance of DiceVUS and MaxDice between the four ICA order groups. Age, Sex, Handedness, Tumor Side, Tumor Size, WHO Grade, number of scrubbed volumes, image intensity root mean square (iRMS), and mean framewise displacement (FD) were used as predictors for VUS in a linear regression. Artificial elevation of rs-fMRI vs task-fMRI concordance is seen at low thresholds due to noise. Noise-removed group-mean DiceVUS and MaxDice improved as ICA order increased, however ANOVA demonstrated no statistically significant difference between the four groups. Linear regression demonstrated an association between iRMS and DiceVUS for ICA30-50, and iRMS and MaxDice for ICA50. Overall there is moderate group level rs-vs-task fMRI language network concordance, however substantial subject-level variability exists; iRMS may be used to determine reliability of rs-fMRI derived language networks. © 2015 Wiley Periodicals, Inc.
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Lin, Hongli; Wang, Weisheng; Luo, Jiawei; Yang, Xuedong
2014-12-01
The aim of this study was to develop a personalized training system using the Lung Image Database Consortium (LIDC) and Image Database resource Initiative (IDRI) Database, because collecting, annotating, and marking a large number of appropriate computed tomography (CT) scans, and providing the capability of dynamically selecting suitable training cases based on the performance levels of trainees and the characteristics of cases are critical for developing a efficient training system. A novel approach is proposed to develop a personalized radiology training system for the interpretation of lung nodules in CT scans using the Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) database, which provides a Content-Boosted Collaborative Filtering (CBCF) algorithm for predicting the difficulty level of each case of each trainee when selecting suitable cases to meet individual needs, and a diagnostic simulation tool to enable trainees to analyze and diagnose lung nodules with the help of an image processing tool and a nodule retrieval tool. Preliminary evaluation of the system shows that developing a personalized training system for interpretation of lung nodules is needed and useful to enhance the professional skills of trainees. The approach of developing personalized training systems using the LIDC/IDRL database is a feasible solution to the challenges of constructing specific training program in terms of cost and training efficiency. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.
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Collective Correlations of Brodmann Areas fMRI Study with RMT-Denoising
Burda, Zdzislaw; Kornelsen, Jennifer; Nowak, Maciej A.; Porebski, Bartosz; Sboto-Frankenstein, Uta; Tomanek, Boguslaw; Tyburczyk, Jacek
2013-01-01
We study collective behavior of Brodmann regions of human cerebral cortex using functional Magnetic Resonance Imaging (fMRI) and Random Matrix Theory (RMT). The raw fMRI data is mapped onto the cortex regions corresponding to the Brodmann areas with the aid of the Talairach coordinates. Principal Component Analysis (PCA) of the Pearson correlation matrix for 41 different Brodmann regions is carried out to determine their collective activity in the idle state and in the active state stimulated...
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Functional Topography of Human Corpus Callosum: An fMRI Mapping Study
Fabri, Mara; Polonara, Gabriele
2013-01-01
The concept of a topographical map of the corpus callosum (CC) has emerged from human lesion studies and from electrophysiological and anatomical tracing investigations in other mammals. Over the last few years a rising number of researchers have been reporting functional magnetic resonance imaging (fMRI) activation in white matter, particularly the CC. In this study the scope for describing CC topography with fMRI was explored by evoking activation through simple sensory stimulation and moto...
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Zhang, Linlin; Guindani, Michele; Versace, Francesco; Vannucci, Marina
2014-07-15
In this paper we present a novel wavelet-based Bayesian nonparametric regression model for the analysis of functional magnetic resonance imaging (fMRI) data. Our goal is to provide a joint analytical framework that allows to detect regions of the brain which exhibit neuronal activity in response to a stimulus and, simultaneously, infer the association, or clustering, of spatially remote voxels that exhibit fMRI time series with similar characteristics. We start by modeling the data with a hemodynamic response function (HRF) with a voxel-dependent shape parameter. We detect regions of the brain activated in response to a given stimulus by using mixture priors with a spike at zero on the coefficients of the regression model. We account for the complex spatial correlation structure of the brain by using a Markov random field (MRF) prior on the parameters guiding the selection of the activated voxels, therefore capturing correlation among nearby voxels. In order to infer association of the voxel time courses, we assume correlated errors, in particular long memory, and exploit the whitening properties of discrete wavelet transforms. Furthermore, we achieve clustering of the voxels by imposing a Dirichlet process (DP) prior on the parameters of the long memory process. For inference, we use Markov Chain Monte Carlo (MCMC) sampling techniques that combine Metropolis-Hastings schemes employed in Bayesian variable selection with sampling algorithms for nonparametric DP models. We explore the performance of the proposed model on simulated data, with both block- and event-related design, and on real fMRI data. Copyright © 2014 Elsevier Inc. All rights reserved.
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International Nuclear Information System (INIS)
Kan, Shigeyuki; Koike, Takahiko; Miyauchi, Satoru; Misaki, Masaya
2009-01-01
Combining functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) allows the investigation of spontaneous activities in the human brain. Recently, by using this technique, increases in fMRI signal accompanying transient EEG activities such as sleep spindles and slow waves were reported. Although these fMRI signal increases appear to arise as a result of the neural activities being reflected in the EEG, when the influence of physiological activities upon fMRI signals are taken into consideration, it is highly controversial that fMRI signal increases accompanying transient EEG activities reflect actual neural activities. In the present study, we conducted simultaneous fMRI and polysomnograph recording of 18 normal adults, to study the effect of transient heart rate changes after a K-complex on fMRI signals. Significant fMRI signal increase was observed in the cerebellum, the ventral thalamus, the dorsal part of the brainstem, the periventricular white matter and the ventricle (quadrigeminal cistern). On the other hand, significant fMRI signal decrease was observed only in the right insula. Moreover, intensities of fMRI signal increase that was accompanied by a K-complex correlated positively with the magnitude of heart rate changes after a K-complex. Previous studies have reported that K-complex is closely related with sympathetic nervous activity and that the attributes of perfusion regulation in the brain differ during wakefulness and sleep. By taking these findings into consideration, our present results indicate that a close relationship exists between a K-complex and the changes in cardio- and neurovascular regulations that are mediated by the autonomic nervous system during sleep; further, these results indicate that transient heart rate changes after a K-complex can affect the fMRI signal generated in certain brain regions. (author)
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Archetypal Analysis for Modeling Multisubject fMRI Data
DEFF Research Database (Denmark)
Hinrich, Jesper Løve; Bardenfleth, Sophia Elizabeth; Røge, Rasmus
2016-01-01
are assumed to be generated by a set of 'prototype' time series. Archetypal analysis (AA) provides a promising alternative, combining the advantages of component-model flexibility with highly interpretable latent 'archetypes' (similar to cluster-model prototypes). To date, AA has not been applied to group......-level fMRI; a major limitation is that it does not generalize to multi-subject datasets, which may have significant variations in blood oxygenation-level-dependent signal and heteroscedastic noise. We develop multi-subject AA (MS-AA), which accounts for group-level data by assuming that archetypal...... performance when modelling archetypes for a motor task experiment. The procedure extracts a 'seed map' across subjects, used to provide brain parcellations with subject-specific temporal profiles. Our approach thus decomposes multisubject fMRI data into distinct interpretable component archetypes that may...
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Fully automated processing of fMRI data in SPM: from MRI scanner to PACS.
Maldjian, Joseph A; Baer, Aaron H; Kraft, Robert A; Laurienti, Paul J; Burdette, Jonathan H
2009-01-01
Here we describe the Wake Forest University Pipeline, a fully automated method for the processing of fMRI data using SPM. The method includes fully automated data transfer and archiving from the point of acquisition, real-time batch script generation, distributed grid processing, interface to SPM in MATLAB, error recovery and data provenance, DICOM conversion and PACS insertion. It has been used for automated processing of fMRI experiments, as well as for the clinical implementation of fMRI and spin-tag perfusion imaging. The pipeline requires no manual intervention, and can be extended to any studies requiring offline processing.
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Bayesian switching factor analysis for estimating time-varying functional connectivity in fMRI.
Taghia, Jalil; Ryali, Srikanth; Chen, Tianwen; Supekar, Kaustubh; Cai, Weidong; Menon, Vinod
2017-07-15
There is growing interest in understanding the dynamical properties of functional interactions between distributed brain regions. However, robust estimation of temporal dynamics from functional magnetic resonance imaging (fMRI) data remains challenging due to limitations in extant multivariate methods for modeling time-varying functional interactions between multiple brain areas. Here, we develop a Bayesian generative model for fMRI time-series within the framework of hidden Markov models (HMMs). The model is a dynamic variant of the static factor analysis model (Ghahramani and Beal, 2000). We refer to this model as Bayesian switching factor analysis (BSFA) as it integrates factor analysis into a generative HMM in a unified Bayesian framework. In BSFA, brain dynamic functional networks are represented by latent states which are learnt from the data. Crucially, BSFA is a generative model which estimates the temporal evolution of brain states and transition probabilities between states as a function of time. An attractive feature of BSFA is the automatic determination of the number of latent states via Bayesian model selection arising from penalization of excessively complex models. Key features of BSFA are validated using extensive simulations on carefully designed synthetic data. We further validate BSFA using fingerprint analysis of multisession resting-state fMRI data from the Human Connectome Project (HCP). Our results show that modeling temporal dependencies in the generative model of BSFA results in improved fingerprinting of individual participants. Finally, we apply BSFA to elucidate the dynamic functional organization of the salience, central-executive, and default mode networks-three core neurocognitive systems with central role in cognitive and affective information processing (Menon, 2011). Across two HCP sessions, we demonstrate a high level of dynamic interactions between these networks and determine that the salience network has the highest temporal
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fMRI of the motor speech center using EPI
International Nuclear Information System (INIS)
Yu, In Kyu; Chang, Kee Hyun; Song, In Chan; Kim, Hong Dae; Seong, Su Ok; Jang, Hyun Jung; Han, Moon Hee; Lee, Sang Kun
1998-01-01
The purpose of this study is to evaluate the feasibility of functional MR imaging (fMRI) using the echo planar imaging (EPI) technique to map the motor speech center and to provide the basic data for motor speech fMRI during internal word generations. This study involved ten young, healthy, right-handed volunteers (M:F=8:2; age: 21-27); a 1.5T whole body scanner with multislice EPI was used. Brain activation was mapped using gradient echo single shot EPI (TR/TE of 3000/40, slice numbers 6, slice thicknesses mm, no interslice gap, matrix numbers 128 x 128, and FOV 30 x 30). The paradigm consisted of a series of alternating rest and activation tasks, repeated eight times. During the rest task, each of ten Korean nouns composed of two to four syllables was shown continuously every 3 seconds. The subjects were required to see the words but not to generate speech, whereas during the activation task, they were asked to internally generate as many words as possible from each of ten non-concrete one-syllabled Korean letters shown on the screen every 3 seconds. During an eight-minute period, a total of 960 axial images were acquired in each subject. Data were analyzed using the Z-score (p<0.05), and following color processing, the activated signals were overlapped on T1-weighted images. The location of the activated area, mean activated signal intensity were evaluated. The results of this study indicate that in most subjects, fMRI using EPI can effectively map the motor speech center. The data obtained may be useful for the clinical application of fMRI. (author). 34 refs., 3 tabs., 5 figs
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Integrating fMRI with psychophysiological measurements in the study of decision-making
Wong, Savio W.H.; Xue, Gui; Bechara, Antoine
2011-01-01
Neuroimaging techniques have recently been used to examine the neural mechanism of decision-making. Nevertheless, most of the neuroimaging studies overlook the importance of emotion and autonomic response in modulating the process of decision-making. In this paper, we discussed how to integrating fMRI with psychophysiological measurements in studying decision-making. We suggested that psychophysiological data would complement with fMRI findings in providing a more comprehensive understanding ...
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fMRI for mapping language networks in neurosurgical cases
International Nuclear Information System (INIS)
Gupta, Santosh S
2014-01-01
Evaluating language has been a long-standing application in functional magnetic resonance imaging (fMRI) studies, both in research and clinical circumstances, and still provides challenges. Localization of eloquent areas is important in neurosurgical cases, so that there is least possible damage to these areas during surgery, maintaining their function postoperatively, therefore providing good quality of life to the patient. Preoperative fMRI study is a non-invasive tool to localize the eloquent areas, including language, with other traditional methods generally used being invasive and at times perilous. In this article, we describe methods and various paradigms to study the language areas, in clinical neurosurgical cases, along with illustrations of cases from our institute
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A SVM-based quantitative fMRI method for resting-state functional network detection.
Song, Xiaomu; Chen, Nan-kuei
2014-09-01
Resting-state functional magnetic resonance imaging (fMRI) aims to measure baseline neuronal connectivity independent of specific functional tasks and to capture changes in the connectivity due to neurological diseases. Most existing network detection methods rely on a fixed threshold to identify functionally connected voxels under the resting state. Due to fMRI non-stationarity, the threshold cannot adapt to variation of data characteristics across sessions and subjects, and generates unreliable mapping results. In this study, a new method is presented for resting-state fMRI data analysis. Specifically, the resting-state network mapping is formulated as an outlier detection process that is implemented using one-class support vector machine (SVM). The results are refined by using a spatial-feature domain prototype selection method and two-class SVM reclassification. The final decision on each voxel is made by comparing its probabilities of functionally connected and unconnected instead of a threshold. Multiple features for resting-state analysis were extracted and examined using an SVM-based feature selection method, and the most representative features were identified. The proposed method was evaluated using synthetic and experimental fMRI data. A comparison study was also performed with independent component analysis (ICA) and correlation analysis. The experimental results show that the proposed method can provide comparable or better network detection performance than ICA and correlation analysis. The method is potentially applicable to various resting-state quantitative fMRI studies. Copyright © 2014 Elsevier Inc. All rights reserved.
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International Nuclear Information System (INIS)
Zhang Ruijie; Jing Tao; Jie Wanqi; Liu Baicheng
2006-01-01
To simulate quantitatively the microstructural evolution in the solidification process of multicomponent alloys, we extend the phase-field model for binary alloys to multicomponent alloys with consideration of the solute interactions between different species. These interactions have a great influence not only on the phase equilibria but also on the solute diffusion behaviors. In the model, the interface region is assumed to be a mixture of solid and liquid with the same chemical potential, but with different compositions. The simulation presented is coupled with thermodynamic and diffusion mobility databases, which can accurately predict the phase equilibria and the solute diffusion transportation in the whole system. The phase equilibria in the interface and other thermodynamic quantities are obtained using Thermo-Calc through the TQ interface. As an example, two-dimensional computations for the dendritic growth in Al-Cu-Mg ternary alloy are performed. The quantitative solute distributions and diffusion matrix are obtained in both solid and liquid phases
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Auditory processing in the brainstem and audiovisual integration in humans studied with fMRI
Slabu, Lavinia Mihaela
2008-01-01
Functional magnetic resonance imaging (fMRI) is a powerful technique because of the high spatial resolution and the noninvasiveness. The applications of the fMRI to the auditory pathway remain a challenge due to the intense acoustic scanner noise of approximately 110 dB SPL. The auditory system
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Henson, Richard N. A.; Tyler, Lorraine K.; Davis, Simon W.; Shafto, Meredith A.; Taylor, Jason R.; Williams, Nitin; Cam‐CAN; Rowe, James B.
2015-01-01
Abstract In functional magnetic resonance imaging (fMRI) research one is typically interested in neural activity. However, the blood‐oxygenation level‐dependent (BOLD) signal is a composite of both neural and vascular activity. As factors such as age or medication may alter vascular function, it is essential to account for changes in neurovascular coupling when investigating neurocognitive functioning with fMRI. The resting‐state fluctuation amplitude (RSFA) in the fMRI signal (rsfMRI) has been proposed as an index of vascular reactivity. The RSFA compares favourably with other techniques such as breath‐hold and hypercapnia, but the latter are more difficult to perform in some populations, such as older adults. The RSFA is therefore a candidate for use in adjusting for age‐related changes in vascular reactivity in fMRI studies. The use of RSFA is predicated on its sensitivity to vascular rather than neural factors; however, the extent to which each of these factors contributes to RSFA remains to be characterized. The present work addressed these issues by comparing RSFA (i.e., rsfMRI variability) to proxy measures of (i) cardiovascular function in terms of heart rate (HR) and heart rate variability (HRV) and (ii) neural activity in terms of resting state magnetoencephalography (rsMEG). We derived summary scores of RSFA, a sensorimotor task BOLD activation, cardiovascular function and rsMEG variability for 335 healthy older adults in the population‐based Cambridge Centre for Ageing and Neuroscience cohort (Cam‐CAN; www.cam-can.com). Mediation analysis revealed that the effects of ageing on RSFA were significantly mediated by vascular factors, but importantly not by the variability in neuronal activity. Furthermore, the converse effects of ageing on the rsMEG variability were not mediated by vascular factors. We then examined the effect of RSFA scaling of task‐based BOLD in the sensorimotor task. The scaling analysis revealed that much of the effects
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Effects of hypoglycemia on human brain activation measured with fMRI.
Anderson, Adam W; Heptulla, Rubina A; Driesen, Naomi; Flanagan, Daniel; Goldberg, Philip A; Jones, Timothy W; Rife, Fran; Sarofin, Hedy; Tamborlane, William; Sherwin, Robert; Gore, John C
2006-07-01
Functional magnetic resonance imaging (fMRI) was used to measure the effects of acute hypoglycemia caused by passive sensory stimulation on brain activation. Visual stimulation was used to generate blood-oxygen-level-dependent (BOLD) contrast, which was monitored during hyperinsulinemic hypoglycemic and euglycemic clamp studies. Hypoglycemia (50 +/- 1 mg glucose/dl) decreased the fMRI signal relative to euglycemia in 10 healthy human subjects: the fractional signal change was reduced by 28 +/- 12% (P variations in blood glucose levels may modulate BOLD signals in the healthy brain.
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Directory of Open Access Journals (Sweden)
G. E. Bodeker
2013-02-01
Full Text Available High vertical resolution ozone measurements from eight different satellite-based instruments have been merged with data from the global ozonesonde network to calculate monthly mean ozone values in 5° latitude zones. These ''Tier 0'' ozone number densities and ozone mixing ratios are provided on 70 altitude levels (1 to 70 km and on 70 pressure levels spaced ~ 1 km apart (878.4 hPa to 0.046 hPa. The Tier 0 data are sparse and do not cover the entire globe or altitude range. To provide a gap-free database, a least squares regression model is fitted to the Tier 0 data and then evaluated globally. The regression model fit coefficients are expanded in Legendre polynomials to account for latitudinal structure, and in Fourier series to account for seasonality. Regression model fit coefficient patterns, which are two dimensional fields indexed by latitude and month of the year, from the N-th vertical level serve as an initial guess for the fit at the N + 1-th vertical level. The initial guess field for the first fit level (20 km/58.2 hPa was derived by applying the regression model to total column ozone fields. Perturbations away from the initial guess are captured through the Legendre and Fourier expansions. By applying a single fit at each level, and using the approach of allowing the regression fits to change only slightly from one level to the next, the regression is less sensitive to measurement anomalies at individual stations or to individual satellite-based instruments. Particular attention is paid to ensuring that the low ozone abundances in the polar regions are captured. By summing different combinations of contributions from different regression model basis functions, four different ''Tier 1'' databases have been compiled for different intended uses. This database is suitable for assessing ozone fields from chemistry-climate model simulations or for providing the ozone boundary conditions for global climate model simulations that do not
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Schonberger, Robert B; Gilbertsen, Todd; Dai, Feng
2013-01-01
Objective(s) Observational database research frequently relies on imperfect administrative markers to determine comorbid status, and it is difficult to infer to what extent the associated misclassification impacts validity in multivariable analyses. The effect that imperfect markers of disease will have on validity in situations where researchers attempt to match populations that have strong baseline health differences is underemphasized as a limitation in some otherwise high-quality observational studies. The present simulations were designed as a quantitative demonstration of the importance of this common and underappreciated issue. Design Two groups of Monte Carlo simulations were performed. The first demonstrated the degree to which controlling for a series of imperfect markers of disease between different populations taking 2 hypothetically harmless drugs would lead to spurious associations between drug assignment and mortality. The second Monte Carlo simulation applied this principle to a recent study in the field of anesthesiology that purported to show increased perioperative mortality in patients taking metoprolol versus atenolol. Setting/Participants/Interventions None. Measurements and Main Results Simulation 1: High type 1 error (ie, false positive findings of an independent association between drug assignment and mortality) was observed as sensitivity and specificity declined and as systematic differences in disease prevalence increased. Simulation 2: Propensity score matching across several imperfect markers was unlikely to eliminate important baseline health disparities in the referenced study. Conclusions In situations where large baseline health disparities exist between populations, matching on imperfect markers of disease may result in strong bias away from the null hypothesis. PMID:23962461
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Variational Bayesian Causal Connectivity Analysis for fMRI
Directory of Open Access Journals (Sweden)
Martin eLuessi
2014-05-01
Full Text Available The ability to accurately estimate effective connectivity among brain regions from neuroimaging data could help answering many open questions in neuroscience. We propose a method which uses causality to obtain a measure of effective connectivity from fMRI data. The method uses a vector autoregressive model for the latent variables describing neuronal activity in combination with a linear observation model based on a convolution with a hemodynamic response function. Due to the employed modeling, it is possible to efficiently estimate all latent variables of the model using a variational Bayesian inference algorithm. The computational efficiency of the method enables us to apply it to large scale problems with high sampling rates and several hundred regions of interest. We use a comprehensive empirical evaluation with synthetic and real fMRI data to evaluate the performance of our method under various conditions.
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Cong, Fengyu; Puoliväli, Tuomas; Alluri, Vinoo; Sipola, Tuomo; Burunat, Iballa; Toiviainen, Petri; Nandi, Asoke K; Brattico, Elvira; Ristaniemi, Tapani
2014-02-15
Independent component analysis (ICA) has been often used to decompose fMRI data mostly for the resting-state, block and event-related designs due to its outstanding advantage. For fMRI data during free-listening experiences, only a few exploratory studies applied ICA. For processing the fMRI data elicited by 512-s modern tango, a FFT based band-pass filter was used to further pre-process the fMRI data to remove sources of no interest and noise. Then, a fast model order selection method was applied to estimate the number of sources. Next, both individual ICA and group ICA were performed. Subsequently, ICA components whose temporal courses were significantly correlated with musical features were selected. Finally, for individual ICA, common components across majority of participants were found by diffusion map and spectral clustering. The extracted spatial maps (by the new ICA approach) common across most participants evidenced slightly right-lateralized activity within and surrounding the auditory cortices. Meanwhile, they were found associated with the musical features. Compared with the conventional ICA approach, more participants were found to have the common spatial maps extracted by the new ICA approach. Conventional model order selection methods underestimated the true number of sources in the conventionally pre-processed fMRI data for the individual ICA. Pre-processing the fMRI data by using a reasonable band-pass digital filter can greatly benefit the following model order selection and ICA with fMRI data by naturalistic paradigms. Diffusion map and spectral clustering are straightforward tools to find common ICA spatial maps. Copyright © 2013 Elsevier B.V. All rights reserved.
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Application Program Interface for the Orion Aerodynamics Database
Robinson, Philip E.; Thompson, James
2013-01-01
The Application Programming Interface (API) for the Crew Exploration Vehicle (CEV) Aerodynamic Database has been developed to provide the developers of software an easily implemented, fully self-contained method of accessing the CEV Aerodynamic Database for use in their analysis and simulation tools. The API is programmed in C and provides a series of functions to interact with the database, such as initialization, selecting various options, and calculating the aerodynamic data. No special functions (file read/write, table lookup) are required on the host system other than those included with a standard ANSI C installation. It reads one or more files of aero data tables. Previous releases of aerodynamic databases for space vehicles have only included data tables and a document of the algorithm and equations to combine them for the total aerodynamic forces and moments. This process required each software tool to have a unique implementation of the database code. Errors or omissions in the documentation, or errors in the implementation, led to a lengthy and burdensome process of having to debug each instance of the code. Additionally, input file formats differ for each space vehicle simulation tool, requiring the aero database tables to be reformatted to meet the tool s input file structure requirements. Finally, the capabilities for built-in table lookup routines vary for each simulation tool. Implementation of a new database may require an update to and verification of the table lookup routines. This may be required if the number of dimensions of a data table exceeds the capability of the simulation tools built-in lookup routines. A single software solution was created to provide an aerodynamics software model that could be integrated into other simulation and analysis tools. The highly complex Orion aerodynamics model can then be quickly included in a wide variety of tools. The API code is written in ANSI C for ease of portability to a wide variety of systems. The
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Non-white noise in fMRI: Does modelling have an impact?
DEFF Research Database (Denmark)
Lund, Torben Ellegaard; Madsen, Kristoffer Hougaard; Sidaros, Karam
2006-01-01
are typically modelled as an autoregressive (AR) process. In this paper, we propose an alternative approach: Nuisance Variable Regression (NVR). By inclusion of confounding effects in a general linear model (GLM), we first confirm that the spatial distribution of the various fMRI noise sources is similar......The sources of non-white noise in Blood Oxygenation Level Dependent (BOLD) functional magnetic resonance imaging (fMRI) are many. Familiar sources include low-frequency drift due to hardware imperfections, oscillatory noise due to respiration and cardiac pulsation and residual movement artefacts...
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Unified ICA-SPM analysis of fMRI experiments
DEFF Research Database (Denmark)
Bjerre, Troels; Henriksen, Jonas; Nielsen, Carsten Haagen
2009-01-01
We present a toolbox for exploratory analysis of functional magnetic resonance imaging (fMRI) data using independent component analysis (ICA) within the widely used SPM analysis pipeline. The toolbox enables dimensional reduction using principal component analysis, ICA using several different ICA...
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Autogenic training alters cerebral activation patterns in fMRI.
Schlamann, Marc; Naglatzki, Ryan; de Greiff, Armin; Forsting, Michael; Gizewski, Elke R
2010-10-01
Cerebral activation patterns during the first three auto-suggestive phases of autogenic training (AT) were investigated in relation to perceived experiences. Nineteen volunteers trained in AT and 19 controls were studied with fMRI during the first steps of autogenic training. FMRI revealed activation of the left postcentral areas during AT in those with experience in AT, which also correlated with the level of AT experience. Activation of prefrontal and insular cortex was significantly higher in the group with experience in AT while insular activation was correlated with number years of simple relaxation exercises. Specific activation in subjects experienced in AT may represent a training effect. Furthermore, the correlation of insular activation suggests that these subjects are different from untrained subjects in emotional processing or self-awareness.
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Directory of Open Access Journals (Sweden)
Marisa Loitfelder
Full Text Available BACKGROUND: Extrapolations from previous cross-sectional fMRI studies suggest cerebral functional changes with progression of Multiple Sclerosis (MS, but longitudinal studies are scarce. We assessed brain activation changes over time in MS patients using a cognitive fMRI paradigm and examined correlations with clinical and cognitive status and brain morphology. METHODS: 13 MS patients and 15 healthy controls (HC underwent MRI including fMRI (go/no-go task, neurological and neuropsychological exams at baseline (BL and follow-up (FU; minimum 12, median 20 months. We assessed estimates of and changes in fMRI activation, total brain and subcortical grey matter volumes, cortical thickness, and T2-lesion load. Bland-Altman (BA plots served to assess fMRI signal variability. RESULTS: Cognitive and disability levels remained largely stable in the patients. With the fMRI task, both at BL and FU, patients compared to HC showed increased activation in the insular cortex, precuneus, cerebellum, posterior cingulate cortex, and occipital cortex. At BL, patients vs. HC also had lower caudate nucleus, thalamus and putamen volumes. Over time, patients (but not HC demonstrated fMRI activity increments in the left inferior parietal lobule. These correlated with worse single-digit-modality test (SDMT performance. BA-plots attested to reproducibility of the fMRI task. In the patients, the right caudate nucleus decreased in volume which again correlated with worsening SDMT performance. CONCLUSIONS: Given preserved cognitive performance, the increased activation at BL in the patients may be viewed as largely adaptive. In contrast, the negative correlation with SDMT performance suggests increasing parietal activation over time to be maladaptive. Several areas with purported relevance for cognition showed decreased volumes at BL and right caudate nucleus volume decline correlated with decreasing SDMT performance. This highlights the dynamics of functional changes and
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Loitfelder, Marisa; Fazekas, Franz; Koschutnig, Karl; Fuchs, Siegrid; Petrovic, Katja; Ropele, Stefan; Pichler, Alexander; Jehna, Margit; Langkammer, Christian; Schmidt, Reinhold; Neuper, Christa; Enzinger, Christian
2014-01-01
Extrapolations from previous cross-sectional fMRI studies suggest cerebral functional changes with progression of Multiple Sclerosis (MS), but longitudinal studies are scarce. We assessed brain activation changes over time in MS patients using a cognitive fMRI paradigm and examined correlations with clinical and cognitive status and brain morphology. 13 MS patients and 15 healthy controls (HC) underwent MRI including fMRI (go/no-go task), neurological and neuropsychological exams at baseline (BL) and follow-up (FU; minimum 12, median 20 months). We assessed estimates of and changes in fMRI activation, total brain and subcortical grey matter volumes, cortical thickness, and T2-lesion load. Bland-Altman (BA) plots served to assess fMRI signal variability. Cognitive and disability levels remained largely stable in the patients. With the fMRI task, both at BL and FU, patients compared to HC showed increased activation in the insular cortex, precuneus, cerebellum, posterior cingulate cortex, and occipital cortex. At BL, patients vs. HC also had lower caudate nucleus, thalamus and putamen volumes. Over time, patients (but not HC) demonstrated fMRI activity increments in the left inferior parietal lobule. These correlated with worse single-digit-modality test (SDMT) performance. BA-plots attested to reproducibility of the fMRI task. In the patients, the right caudate nucleus decreased in volume which again correlated with worsening SDMT performance. Given preserved cognitive performance, the increased activation at BL in the patients may be viewed as largely adaptive. In contrast, the negative correlation with SDMT performance suggests increasing parietal activation over time to be maladaptive. Several areas with purported relevance for cognition showed decreased volumes at BL and right caudate nucleus volume decline correlated with decreasing SDMT performance. This highlights the dynamics of functional changes and the strategic importance of specific brain areas for
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Haller, Sven; Bartsch, Andreas J; Radue, Ernst W; Klarhöfer, Markus; Seifritz, Erich; Scheffler, Klaus
2005-11-01
Conventional blood oxygenation level-dependent (BOLD) based functional magnetic resonance imaging (fMRI) is accompanied by substantial acoustic gradient noise. This noise can influence the performance as well as neuronal activations. Conventional fMRI typically has a pulsed noise component, which is a particularly efficient auditory stimulus. We investigated whether the elimination of this pulsed noise component in a recent modification of continuous-sound fMRI modifies neuronal activations in a cognitively demanding non-auditory working memory task. Sixteen normal subjects performed a letter variant n-back task. Brain activity and psychomotor performance was examined during fMRI with continuous-sound fMRI and conventional fMRI. We found greater BOLD responses in bilateral medial frontal gyrus, left middle frontal gyrus, left middle temporal gyrus, left hippocampus, right superior frontal gyrus, right precuneus and right cingulate gyrus with continuous-sound compared to conventional fMRI. Conversely, BOLD responses were greater in bilateral cingulate gyrus, left middle and superior frontal gyrus and right lingual gyrus with conventional compared to continuous-sound fMRI. There were no differences in psychomotor performance between both scanning protocols. Although behavioral performance was not affected, acoustic gradient noise interferes with neuronal activations in non-auditory cognitive tasks and represents a putative systematic confound.
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Toward brain correlates of natural behavior: fMRI during violent video games.
Mathiak, Klaus; Weber, René
2006-12-01
Modern video games represent highly advanced virtual reality simulations and often contain virtual violence. In a significant amount of young males, playing video games is a quotidian activity, making it an almost natural behavior. Recordings of brain activation with functional magnetic resonance imaging (fMRI) during gameplay may reflect neuronal correlates of real-life behavior. We recorded 13 experienced gamers (18-26 years; average 14 hrs/week playing) while playing a violent first-person shooter game (a violent computer game played in self-perspective) by means of distortion and dephasing reduced fMRI (3 T; single-shot triple-echo echo-planar imaging [EPI]). Content analysis of the video and sound with 100 ms time resolution achieved relevant behavioral variables. These variables explained significant signal variance across large distributed networks. Occurrence of violent scenes revealed significant neuronal correlates in an event-related design. Activation of dorsal and deactivation of rostral anterior cingulate and amygdala characterized the mid-frontal pattern related to virtual violence. Statistics and effect sizes can be considered large at these areas. Optimized imaging strategies allowed for single-subject and for single-trial analysis with good image quality at basal brain structures. We propose that virtual environments can be used to study neuronal processes involved in semi-naturalistic behavior as determined by content analysis. Importantly, the activation pattern reflects brain-environment interactions rather than stimulus responses as observed in classical experimental designs. We relate our findings to the general discussion on social effects of playing first-person shooter games. (c) 2006 Wiley-Liss, Inc.
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Estimating Dynamic Connectivity States in fMRI Using Regime-Switching Factor Models
Ting, Chee-Ming
2017-12-06
We consider the challenges in estimating state-related changes in brain connectivity networks with a large number of nodes. Existing studies use sliding-window analysis or time-varying coefficient models which are unable to capture both smooth and abrupt changes simultaneously, and rely on ad-hoc approaches to the high-dimensional estimation. To overcome these limitations, we propose a Markov-switching dynamic factor model which allows the dynamic connectivity states in functional magnetic resonance imaging (fMRI) data to be driven by lower-dimensional latent factors. We specify a regime-switching vector autoregressive (SVAR) factor process to quantity the time-varying directed connectivity. The model enables a reliable, data-adaptive estimation of change-points of connectivity regimes and the massive dependencies associated with each regime. We develop a three-step estimation procedure: 1) extracting the factors using principal component analysis, 2) identifying connectivity regimes in a low-dimensional subspace based on the factor-based SVAR model, 3) constructing high-dimensional state connectivity metrics based on the subspace estimates. Simulation results show that our estimator outperforms K-means clustering of time-windowed coefficients, providing more accurate estimate of time-evolving connectivity. It achieves percentage of reduction in mean squared error by 60% when the network dimension is comparable to the sample size. When applied to resting-state fMRI data, our method successfully identifies modular organization in resting-state networks in consistency with other studies. It further reveals changes in brain states with variations across subjects and distinct large-scale directed connectivity patterns across states.
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Testing competing hypotheses about single trial fMRI
DEFF Research Database (Denmark)
Hansen, Lars Kai; Purushotham, Archana; Kim, Seong-Ge
2002-01-01
We use a Bayesian framework to compute probabilities of competing hypotheses about functional activation based on single trial fMRI measurements. Within the framework we obtain a complete probabilistic picture of competing hypotheses, hence control of both type I and type II errors....
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Mutschler, Isabella; Wieckhorst, Birgit; Meyer, Andrea H; Schweizer, Tina; Klarhöfer, Markus; Wilhelm, Frank H; Seifritz, Erich; Ball, Tonio
2014-11-07
Experiments using functional magnetic resonance imaging (fMRI) play a fundamental role in affective neuroscience. When placed in an MR scanner, some volunteers feel safe and relaxed in this situation, while others experience uneasiness and fear. Little is known about the basis and consequences of such inter-individually different responses to the general experimental fMRI setting. In this study emotional stimuli were presented during fMRI and subjects' state-anxiety was assessed at the onset and end of the experiment while they were within the scanner. We show that Val/Val but neither Met/Met nor Val/Met carriers of the catechol-O-methyltransferase (COMT) Val(158)Met polymorphism-a prime candidate for anxiety vulnerability-became significantly more anxious during the fMRI experiment (N=97 females: 24 Val/Val, 51 Val/Met, and 22 Met/Met). Met carriers demonstrated brain responses with increased stability over time in the right parietal cortex and significantly better cognitive performances likely mediated by lower levels of anxiety. Val/Val, Val/Met and Met/Met did not significantly differ in state-anxiety at the beginning of the experiment. The exposure of a control group (N=56 females) to the same experiment outside the scanner did not cause a significant increase in state-anxiety, suggesting that the increase we observe in the fMRI experiment may be specific to the fMRI setting. Our findings reveal that genetics may play an important role in shaping inter-individual different emotional, cognitive and neuronal responses during fMRI experiments. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
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Pedersen, Mangor; Omidvarnia, Amir; Zalesky, Andrew; Jackson, Graeme D
2018-06-08
Correlation-based sliding window analysis (CSWA) is the most commonly used method to estimate time-resolved functional MRI (fMRI) connectivity. However, instantaneous phase synchrony analysis (IPSA) is gaining popularity mainly because it offers single time-point resolution of time-resolved fMRI connectivity. We aim to provide a systematic comparison between these two approaches, on both temporal and topological levels. For this purpose, we used resting-state fMRI data from two separate cohorts with different temporal resolutions (45 healthy subjects from Human Connectome Project fMRI data with repetition time of 0.72 s and 25 healthy subjects from a separate validation fMRI dataset with a repetition time of 3 s). For time-resolved functional connectivity analysis, we calculated tapered CSWA over a wide range of different window lengths that were temporally and topologically compared to IPSA. We found a strong association in connectivity dynamics between IPSA and CSWA when considering the absolute values of CSWA. The association between CSWA and IPSA was stronger for a window length of ∼20 s (shorter than filtered fMRI wavelength) than ∼100 s (longer than filtered fMRI wavelength), irrespective of the sampling rate of the underlying fMRI data. Narrow-band filtering of fMRI data (0.03-0.07 Hz) yielded a stronger relationship between IPSA and CSWA than wider-band (0.01-0.1 Hz). On a topological level, time-averaged IPSA and CSWA nodes were non-linearly correlated for both short (∼20 s) and long (∼100 s) windows, mainly because nodes with strong negative correlations (CSWA) displayed high phase synchrony (IPSA). IPSA and CSWA were anatomically similar in the default mode network, sensory cortex, insula and cerebellum. Our results suggest that IPSA and CSWA provide comparable characterizations of time-resolved fMRI connectivity for appropriately chosen window lengths. Although IPSA requires narrow-band fMRI filtering, we recommend the use of
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Motor function deficits in schizophrenia: an fMRI and VBM study
Energy Technology Data Exchange (ETDEWEB)
Singh, Sadhana; Modi, Shilpi; Kumar, Pawan; Singh, Namita; Khushu, Subash [Institute of Nuclear Medicine and Allied Sciences (INMAS), NMR Research Center, Delhi (India); Goyal, Satnam; Bhatia, Triptish; Deshpande, Smita N. [RML Hospital, PGIMER, New Delhi (India)
2014-05-15
To investigate whether the motor functional alterations in schizophrenia (SZ) are also associated with structural changes in the related brain areas using functional magnetic resonance imaging (fMRI) and voxel-based morphometry (VBM). A sample of 14 right-handed SZ patients and 14 right-handed healthy control subjects matched for age, sex, and education were examined with structural high-resolution T1-weighted MRI; fMRI images were obtained during right index finger-tapping task in the same session. fMRI results showed reduced functional activation in the motor areas (contralateral precentral and postcentral gyrus) and ipsilateral cerebellum in SZ subjects as compared to healthy controls (n = 14). VBM analysis also revealed reduced grey matter in motor areas and white matter reduction in cerebellum of SZ subjects as compared to controls. The present study provides an evidence for a possible association between structural alterations in the motor cortex and disturbed functional activation in the motor areas in persons affected with SZ during a simple finger-tapping task. (orig.)
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Motor function deficits in schizophrenia: an fMRI and VBM study
International Nuclear Information System (INIS)
Singh, Sadhana; Modi, Shilpi; Kumar, Pawan; Singh, Namita; Khushu, Subash; Goyal, Satnam; Bhatia, Triptish; Deshpande, Smita N.
2014-01-01
To investigate whether the motor functional alterations in schizophrenia (SZ) are also associated with structural changes in the related brain areas using functional magnetic resonance imaging (fMRI) and voxel-based morphometry (VBM). A sample of 14 right-handed SZ patients and 14 right-handed healthy control subjects matched for age, sex, and education were examined with structural high-resolution T1-weighted MRI; fMRI images were obtained during right index finger-tapping task in the same session. fMRI results showed reduced functional activation in the motor areas (contralateral precentral and postcentral gyrus) and ipsilateral cerebellum in SZ subjects as compared to healthy controls (n = 14). VBM analysis also revealed reduced grey matter in motor areas and white matter reduction in cerebellum of SZ subjects as compared to controls. The present study provides an evidence for a possible association between structural alterations in the motor cortex and disturbed functional activation in the motor areas in persons affected with SZ during a simple finger-tapping task. (orig.)
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EEG-fMRI Bayesian framework for neural activity estimation: a simulation study
Croce, Pierpaolo; Basti, Alessio; Marzetti, Laura; Zappasodi, Filippo; Del Gratta, Cosimo
2016-12-01
Objective. Due to the complementary nature of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), and given the possibility of simultaneous acquisition, the joint data analysis can afford a better understanding of the underlying neural activity estimation. In this simulation study we want to show the benefit of the joint EEG-fMRI neural activity estimation in a Bayesian framework. Approach. We built a dynamic Bayesian framework in order to perform joint EEG-fMRI neural activity time course estimation. The neural activity is originated by a given brain area and detected by means of both measurement techniques. We have chosen a resting state neural activity situation to address the worst case in terms of the signal-to-noise ratio. To infer information by EEG and fMRI concurrently we used a tool belonging to the sequential Monte Carlo (SMC) methods: the particle filter (PF). Main results. First, despite a high computational cost, we showed the feasibility of such an approach. Second, we obtained an improvement in neural activity reconstruction when using both EEG and fMRI measurements. Significance. The proposed simulation shows the improvements in neural activity reconstruction with EEG-fMRI simultaneous data. The application of such an approach to real data allows a better comprehension of the neural dynamics.
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A Specialized Multi-Transmit Head Coil for High Resolution fMRI of the Human Visual Cortex at 7T.
Sengupta, Shubharthi; Roebroeck, Alard; Kemper, Valentin G; Poser, Benedikt A; Zimmermann, Jan; Goebel, Rainer; Adriany, Gregor
2016-01-01
To design, construct and validate radiofrequency (RF) transmit and receive phased array coils for high-resolution visual cortex imaging at 7 Tesla. A 4 channel transmit and 16 channel receive array was constructed on a conformal polycarbonate former. Transmit field efficiency and homogeneity were simulated and validated, along with the Specific Absorption Rate, using [Formula: see text] mapping techniques and electromagnetic simulations. Receiver signal-to-noise ratio (SNR), temporal SNR (tSNR) across EPI time series, g-factors for accelerated imaging and noise correlations were evaluated and compared with a commercial 32 channel whole head coil. The performance of the coil was further evaluated with human subjects through functional MRI (fMRI) studies at standard and submillimeter resolutions of upto 0.8mm isotropic. The transmit and receive sections were characterized using bench tests and showed good interelement decoupling, preamplifier decoupling and sample loading. SNR for the 16 channel coil was ∼ 1.5 times that of the commercial coil in the human occipital lobe, and showed better g-factor values for accelerated imaging. fMRI tests conducted showed better response to Blood Oxygen Level Dependent (BOLD) activation, at resolutions of 1.2mm and 0.8mm isotropic. The 4 channel phased array transmit coil provides homogeneous excitation across the visual cortex, which, in combination with the dual row 16 channel receive array, makes for a valuable research tool for high resolution anatomical and functional imaging of the visual cortex at 7T.
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Large-scale DCMs for resting-state fMRI
Directory of Open Access Journals (Sweden)
Adeel Razi
2017-01-01
Full Text Available This paper considers the identification of large directed graphs for resting-state brain networks based on biophysical models of distributed neuronal activity, that is, effective connectivity. This identification can be contrasted with functional connectivity methods based on symmetric correlations that are ubiquitous in resting-state functional MRI (fMRI. We use spectral dynamic causal modeling (DCM to invert large graphs comprising dozens of nodes or regions. The ensuing graphs are directed and weighted, hence providing a neurobiologically plausible characterization of connectivity in terms of excitatory and inhibitory coupling. Furthermore, we show that the use of Bayesian model reduction to discover the most likely sparse graph (or model from a parent (e.g., fully connected graph eschews the arbitrary thresholding often applied to large symmetric (functional connectivity graphs. Using empirical fMRI data, we show that spectral DCM furnishes connectivity estimates on large graphs that correlate strongly with the estimates provided by stochastic DCM. Furthermore, we increase the efficiency of model inversion using functional connectivity modes to place prior constraints on effective connectivity. In other words, we use a small number of modes to finesse the potentially redundant parameterization of large DCMs. We show that spectral DCM—with functional connectivity priors—is ideally suited for directed graph theoretic analyses of resting-state fMRI. We envision that directed graphs will prove useful in understanding the psychopathology and pathophysiology of neurodegenerative and neurodevelopmental disorders. We will demonstrate the utility of large directed graphs in clinical populations in subsequent reports, using the procedures described in this paper.
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Mapping cerebrovascular reactivity using concurrent fMRI and near infrared spectroscopy
Tong, Yunjie; Bergethon, Peter R.; Frederick, Blaise d.
2011-02-01
Cerebrovascular reactivity (CVR) reflects the compensatory dilatory capacity of cerebral vasculature to a dilatory stimulus and is an important indicator of brain vascular reserve. fMRI has been proven to be an effective imaging technique to obtain the CVR map when the subjects perform CO2 inhalation or the breath holding task (BH). However, the traditional data analysis inaccurately models the BOLD using a boxcar function with fixed time delay. We propose a novel way to process the fMRI data obtained during a blocked BH by using the simultaneously collected near infrared spectroscopy (NIRS) data as regressor1. In this concurrent NIRS and fMRI study, 6 healthy subjects performed a blocked BH (5 breath holds with 20s durations intermitted by 40s of regular breathing). A NIRS probe of two sources and two detectors separated by 3 cm was placed on the right side of prefrontal area of the subjects. The time course of changes in oxy-hemoglobin (Δ[HbO]) was calculated from NIRS data and shifted in time by various amounts, and resampled to the fMRI acquisition rate. Each shifted time course was used as regressor in FEAT (the analysis tool in FSL). The resulting z-statistic maps were concatenated in time and the maximal value was taken along the time for all the voxels to generate a 3-D CVR map. The new method produces more accurate and thorough CVR maps; moreover, it enables us to produce a comparable baseline cerebral vascular map if applied to resting state (RS) data.
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Neuroethics and fMRI: Mapping a fledgling relationship
DEFF Research Database (Denmark)
Garnett, Alex; Whiteley, Louise Emma; Piwowar, Heather
2011-01-01
Human functional magnetic resonance imaging (fMRI) informs the understanding of the neural basis of mental function and is a key domain of ethical enquiry. It raises questions about the practice and implications of research, and reflexively informs ethics through the empirical investigation of mo...
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Yu, Qingbao; Du, Yuhui; Chen, Jiayu; He, Hao; Sui, Jing; Pearlson, Godfrey; Calhoun, Vince D
2017-11-01
A key challenge in building a brain graph using fMRI data is how to define the nodes. Spatial brain components estimated by independent components analysis (ICA) and regions of interest (ROIs) determined by brain atlas are two popular methods to define nodes in brain graphs. It is difficult to evaluate which method is better in real fMRI data. Here we perform a simulation study and evaluate the accuracies of a few graph metrics in graphs with nodes of ICA components, ROIs, or modified ROIs in four simulation scenarios. Graph measures with ICA nodes are more accurate than graphs with ROI nodes in all cases. Graph measures with modified ROI nodes are modulated by artifacts. The correlations of graph metrics across subjects between graphs with ICA nodes and ground truth are higher than the correlations between graphs with ROI nodes and ground truth in scenarios with large overlapped spatial sources. Moreover, moving the location of ROIs would largely decrease the correlations in all scenarios. Evaluating graphs with different nodes is promising in simulated data rather than real data because different scenarios can be simulated and measures of different graphs can be compared with a known ground truth. Since ROIs defined using brain atlas may not correspond well to real functional boundaries, overall findings of this work suggest that it is more appropriate to define nodes using data-driven ICA than ROI approaches in real fMRI data. Copyright © 2017 Elsevier B.V. All rights reserved.
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BROCCOLI: Software for Fast fMRI Analysis on Many-Core CPUs and GPUs
Directory of Open Access Journals (Sweden)
Anders eEklund
2014-03-01
Full Text Available Analysis of functional magnetic resonance imaging (fMRI data is becoming ever more computationally demanding as temporal and spatial resolutions improve, and large, publicly available data sets proliferate. Moreover, methodological improvements in the neuroimaging pipeline, such as non-linear spatial normalization, non-parametric permutation tests and Bayesian Markov Chain Monte Carlo approaches, can dramatically increase the computational burden. Despite these challenges, there do not yet exist any fMRI software packages which leverage inexpensive and powerful graphics processing units (GPUs to perform these analyses. Here, we therefore present BROCCOLI, a free software package written in OpenCL (Open Computing Language that can be used for parallel analysis of fMRI data on a large variety of hardware configurations. BROCCOLI has, for example, been tested with an Intel CPU, an Nvidia GPU and an AMD GPU. These tests show that parallel processing of fMRI data can lead to significantly faster analysis pipelines. This speedup can be achieved on relatively standard hardware, but further, dramatic speed improvements require only a modest investment in GPU hardware. BROCCOLI (running on a GPU can perform non-linear spatial normalization to a 1 mm3 brain template in 4-6 seconds, and run a second level permutation test with 10,000 permutations in about a minute. These non-parametric tests are generally more robust than their parametric counterparts, and can also enable more sophisticated analyses by estimating complicated null distributions. Additionally, BROCCOLI includes support for Bayesian first-level fMRI analysis using a Gibbs sampler. The new software is freely available under GNU GPL3 and can be downloaded from github (https://github.com/wanderine/BROCCOLI/.
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Regional homogeneity changes in prelingually deafened patients: a resting-state fMRI study
Li, Wenjing; He, Huiguang; Xian, Junfang; Lv, Bin; Li, Meng; Li, Yong; Liu, Zhaohui; Wang, Zhenchang
2010-03-01
Resting-state functional magnetic resonance imaging (fMRI) is a technique that measures the intrinsic function of brain and has some advantages over task-induced fMRI. Regional homogeneity (ReHo) assesses the similarity of the time series of a given voxel with its nearest neighbors on a voxel-by-voxel basis, which reflects the temporal homogeneity of the regional BOLD signal. In the present study, we used the resting state fMRI data to investigate the ReHo changes of the whole brain in the prelingually deafened patients relative to normal controls. 18 deaf patients and 22 healthy subjects were scanned. Kendall's coefficient of concordance (KCC) was calculated to measure the degree of regional coherence of fMRI time courses. We found that regional coherence significantly decreased in the left frontal lobe, bilateral temporal lobes and right thalamus, and increased in the postcentral gyrus, cingulate gyrus, left temporal lobe, left thalamus and cerebellum in deaf patients compared with controls. These results show that the prelingually deafened patients have higher degree of regional coherence in the paleocortex, and lower degree in neocortex. Since neocortex plays an important role in the development of auditory, these evidences may suggest that the deaf persons reorganize the paleocortex to offset the loss of auditory.
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Zhang, Jing; Liang, Lichen; Anderson, Jon R; Gatewood, Lael; Rottenberg, David A; Strother, Stephen C
2008-01-01
As functional magnetic resonance imaging (fMRI) becomes widely used, the demands for evaluation of fMRI processing pipelines and validation of fMRI analysis results is increasing rapidly. The current NPAIRS package, an IDL-based fMRI processing pipeline evaluation framework, lacks system interoperability and the ability to evaluate general linear model (GLM)-based pipelines using prediction metrics. Thus, it can not fully evaluate fMRI analytical software modules such as FSL.FEAT and NPAIRS.GLM. In order to overcome these limitations, a Java-based fMRI processing pipeline evaluation system was developed. It integrated YALE (a machine learning environment) into Fiswidgets (a fMRI software environment) to obtain system interoperability and applied an algorithm to measure GLM prediction accuracy. The results demonstrated that the system can evaluate fMRI processing pipelines with univariate GLM and multivariate canonical variates analysis (CVA)-based models on real fMRI data based on prediction accuracy (classification accuracy) and statistical parametric image (SPI) reproducibility. In addition, a preliminary study was performed where four fMRI processing pipelines with GLM and CVA modules such as FSL.FEAT and NPAIRS.CVA were evaluated with the system. The results indicated that (1) the system can compare different fMRI processing pipelines with heterogeneous models (NPAIRS.GLM, NPAIRS.CVA and FSL.FEAT) and rank their performance by automatic performance scoring, and (2) the rank of pipeline performance is highly dependent on the preprocessing operations. These results suggest that the system will be of value for the comparison, validation, standardization and optimization of functional neuroimaging software packages and fMRI processing pipelines.
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Cognitive dissonance induction in everyday life: An fMRI study.
de Vries, Jan; Byrne, Mark; Kehoe, Elizabeth
2015-01-01
This functional magnetic resonance imaging (fMRI) study explored the neural substrates of cognitive dissonance during dissonance "induction." A novel task was developed based on the results of a separate item selection study (n = 125). Items were designed to generate dissonance by prompting participants to reflect on everyday personal experiences that were inconsistent with values they had expressed support for. One experimental condition (dissonance) and three control conditions (justification, consonance, and non-self-related inconsistency) were used for comparison. Items of all four types were presented to each participant (n = 14) in a randomized design. The fMRI analysis used a whole-brain approach focusing on the moments dissonance was induced. Results showed that in comparison with the control conditions the dissonance experience led to higher levels of activation in several brain regions. Specifically dissonance was associated with increased neural activation in key brain regions including the anterior cingulate cortex (ACC), anterior insula, inferior frontal gyrus, and precuneus. This supports current perspectives that emphasize the role of anterior cingulate and insula in dissonance processing. Less extensive activation in the prefrontal cortex than in some previous studies is consistent with this study's emphasis on dissonance induction, rather than reduction. This article also contains a short review and comparison with other fMRI studies of cognitive dissonance.
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Implicit Structured Sequence Learning: An FMRI Study of the Structural Mere-Exposure Effect
Vasiliki eFolia; Vasiliki eFolia; Karl Magnus ePetersson; Karl Magnus ePetersson; Karl Magnus ePetersson
2014-01-01
In this event-related FMRI study we investigated the effect of five days of implicit acquisition on preference classification by means of an artificial grammar learning (AGL) paradigm based on the structural mere-exposure effect and preference classification using a simple right-linear unification grammar. This allowed us to investigate implicit AGL in a proper learning design by including baseline measurements prior to grammar exposure. After 5 days of implicit acquisition, the FMRI results ...
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Directory of Open Access Journals (Sweden)
Toofanny Rudesh D
2011-08-01
Full Text Available Abstract Background Molecular dynamics (MD simulations offer the ability to observe the dynamics and interactions of both whole macromolecules and individual atoms as a function of time. Taken in context with experimental data, atomic interactions from simulation provide insight into the mechanics of protein folding, dynamics, and function. The calculation of atomic interactions or contacts from an MD trajectory is computationally demanding and the work required grows exponentially with the size of the simulation system. We describe the implementation of a spatial indexing algorithm in our multi-terabyte MD simulation database that significantly reduces the run-time required for discovery of contacts. The approach is applied to the Dynameomics project data. Spatial indexing, also known as spatial hashing, is a method that divides the simulation space into regular sized bins and attributes an index to each bin. Since, the calculation of contacts is widely employed in the simulation field, we also use this as the basis for testing compression of data tables. We investigate the effects of compression of the trajectory coordinate tables with different options of data and index compression within MS SQL SERVER 2008. Results Our implementation of spatial indexing speeds up the calculation of contacts over a 1 nanosecond (ns simulation window by between 14% and 90% (i.e., 1.2 and 10.3 times faster. For a 'full' simulation trajectory (51 ns spatial indexing reduces the calculation run-time between 31 and 81% (between 1.4 and 5.3 times faster. Compression resulted in reduced table sizes but resulted in no significant difference in the total execution time for neighbour discovery. The greatest compression (~36% was achieved using page level compression on both the data and indexes. Conclusions The spatial indexing scheme significantly decreases the time taken to calculate atomic contacts and could be applied to other multidimensional neighbor discovery
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Toofanny, Rudesh D; Simms, Andrew M; Beck, David A C; Daggett, Valerie
2011-08-10
Molecular dynamics (MD) simulations offer the ability to observe the dynamics and interactions of both whole macromolecules and individual atoms as a function of time. Taken in context with experimental data, atomic interactions from simulation provide insight into the mechanics of protein folding, dynamics, and function. The calculation of atomic interactions or contacts from an MD trajectory is computationally demanding and the work required grows exponentially with the size of the simulation system. We describe the implementation of a spatial indexing algorithm in our multi-terabyte MD simulation database that significantly reduces the run-time required for discovery of contacts. The approach is applied to the Dynameomics project data. Spatial indexing, also known as spatial hashing, is a method that divides the simulation space into regular sized bins and attributes an index to each bin. Since, the calculation of contacts is widely employed in the simulation field, we also use this as the basis for testing compression of data tables. We investigate the effects of compression of the trajectory coordinate tables with different options of data and index compression within MS SQL SERVER 2008. Our implementation of spatial indexing speeds up the calculation of contacts over a 1 nanosecond (ns) simulation window by between 14% and 90% (i.e., 1.2 and 10.3 times faster). For a 'full' simulation trajectory (51 ns) spatial indexing reduces the calculation run-time between 31 and 81% (between 1.4 and 5.3 times faster). Compression resulted in reduced table sizes but resulted in no significant difference in the total execution time for neighbour discovery. The greatest compression (~36%) was achieved using page level compression on both the data and indexes. The spatial indexing scheme significantly decreases the time taken to calculate atomic contacts and could be applied to other multidimensional neighbor discovery problems. The speed up enables on-the-fly calculation
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Exploring fMRI Data for Periodic Signal Components
DEFF Research Database (Denmark)
Hansen, Lars Kai; Nielsen, Finn Årup; Larsen, Jan
2002-01-01
We use a Bayesian framework to detect periodic components in fMRI data. The resulting detector is sensitive to periodic components with a flexible number of harmonics and with arbitrary amplitude and phases of the harmonics. It is possible to detect the correct number of harmonics in periodic sig...
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Gaussian process based independent analysis for temporal source separation in fMRI
DEFF Research Database (Denmark)
Hald, Ditte Høvenhoff; Henao, Ricardo; Winther, Ole
2017-01-01
Functional Magnetic Resonance Imaging (fMRI) gives us a unique insight into the processes of the brain, and opens up for analyzing the functional activation patterns of the underlying sources. Task-inferred supervised learning with restrictive assumptions in the regression set-up, restricts...... the exploratory nature of the analysis. Fully unsupervised independent component analysis (ICA) algorithms, on the other hand, can struggle to detect clear classifiable components on single-subject data. We attribute this shortcoming to inadequate modeling of the fMRI source signals by failing to incorporate its...
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Functional MRI (fMRI) on lesions in and around the motor and the eloquent cortices
International Nuclear Information System (INIS)
Hara, Yoshie; Nakamura, Mitsugu; Tamura, Shogo; Tamaki, Norihiko; Kitamura, Junji
1999-01-01
From the view point of neurosurgeons, to aim the preoperative localized diagnosis on the motor and the eloquent cortices and postoperative preservation of neurological functions, fMRI was carried for patients with lesions in and around the motor and the eloquent cortices. Even in cases of mechanical oppression or brain edema, the motor and the eloquent cortices are localized on cerebral gyri. In perioperative period, identification and preserving the motor and the eloquent cortices are important for keeping brain function. Twenty six preoperative cases and 3 normal healthy subjects were observed. Exercise enhanced fMRI was performed on 3 normal healthy subjects, fMRI with motor stimulation in 24 cases and fMRI with speech stimulation in 4 cases. The signal intensity increased in all cases responsing to both stimulations. But the signal intensity in 8 cases decreased in some regions by motor stimulation and 1 case by speech stimulation. The decrease of signal intensity in this study seems to be a clinically important finding and it will be required to examine the significance in future. (K.H.)
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A KINETIC DATABASE FOR ASTROCHEMISTRY (KIDA)
International Nuclear Information System (INIS)
Wakelam, V.; Pavone, B.; Hébrard, E.; Hersant, F.; Herbst, E.; Loison, J.-C.; Chandrasekaran, V.; Bergeat, A.; Smith, I. W. M.; Adams, N. G.; Bacchus-Montabonel, M.-C.; Béroff, K.; Bierbaum, V. M.; Chabot, M.; Dalgarno, A.; Van Dishoeck, E. F.; Faure, A.; Geppert, W. D.; Gerlich, D.; Galli, D.
2012-01-01
We present a novel chemical database for gas-phase astrochemistry. Named the KInetic Database for Astrochemistry (KIDA), this database consists of gas-phase reactions with rate coefficients and uncertainties that will be vetted to the greatest extent possible. Submissions of measured and calculated rate coefficients are welcome, and will be studied by experts before inclusion into the database. Besides providing kinetic information for the interstellar medium, KIDA is planned to contain such data for planetary atmospheres and for circumstellar envelopes. Each year, a subset of the reactions in the database (kida.uva) will be provided as a network for the simulation of the chemistry of dense interstellar clouds with temperatures between 10 K and 300 K. We also provide a code, named Nahoon, to study the time-dependent gas-phase chemistry of zero-dimensional and one-dimensional interstellar sources.
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A Versatile Software Package for Inter-subject Correlation Based Analyses of fMRI
Directory of Open Access Journals (Sweden)
Jukka-Pekka eKauppi
2014-01-01
Full Text Available In the inter-subject correlation (ISC based analysis of the functional magnetic resonance imaging (fMRI data, the extent of shared processing across subjects during the experiment is determined by calculating correlation coefficients between the fMRI time series of the subjects in the corresponding brain locations. This implies that ISC can be used to analyze fMRI data without explicitly modelling the stimulus and thus ISC is a potential method to analyze fMRI data acquired under complex naturalistic stimuli. Despite of the suitability of ISC based approach to analyze complex fMRI data, no generic software tools have been made available for this purpose, limiting a widespread use of ISC based analysis techniques among neuroimaging community. In this paper, we present a graphical user interface (GUI based software package, ISC Toolbox, implemented in Matlab for computing various ISC based analyses. Many advanced computations such as comparison of ISCs between different stimuli, time window ISC, and inter-subject phase synchronization are supported by the toolbox. The analyses are coupled with re-sampling based statistical inference. The ISC based analyses are data and computation intensive and the ISC toolbox is equipped with mechanisms to execute the parallel computations in a cluster environment automatically and with an automatic detection of the cluster environment in use. Currently, SGE-based (Oracle Grid Engine, Son of a Grid Engine or Open Grid Scheduler and Slurm environments are supported. In this paper, we present a detailed account on the methods behind the ISC Toolbox, the implementation of the toolbox and demonstrate the possible use of the toolbox by summarizing selected example applications. We also report the computation time experiments both using a single desktop computer and two grid environments demonstrating that parallelization effectively reduces the computing time. The ISC Toolbox is available in https://code.google.com/p/isc-toolbox/.
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A versatile software package for inter-subject correlation based analyses of fMRI.
Kauppi, Jukka-Pekka; Pajula, Juha; Tohka, Jussi
2014-01-01
In the inter-subject correlation (ISC) based analysis of the functional magnetic resonance imaging (fMRI) data, the extent of shared processing across subjects during the experiment is determined by calculating correlation coefficients between the fMRI time series of the subjects in the corresponding brain locations. This implies that ISC can be used to analyze fMRI data without explicitly modeling the stimulus and thus ISC is a potential method to analyze fMRI data acquired under complex naturalistic stimuli. Despite of the suitability of ISC based approach to analyze complex fMRI data, no generic software tools have been made available for this purpose, limiting a widespread use of ISC based analysis techniques among neuroimaging community. In this paper, we present a graphical user interface (GUI) based software package, ISC Toolbox, implemented in Matlab for computing various ISC based analyses. Many advanced computations such as comparison of ISCs between different stimuli, time window ISC, and inter-subject phase synchronization are supported by the toolbox. The analyses are coupled with re-sampling based statistical inference. The ISC based analyses are data and computation intensive and the ISC toolbox is equipped with mechanisms to execute the parallel computations in a cluster environment automatically and with an automatic detection of the cluster environment in use. Currently, SGE-based (Oracle Grid Engine, Son of a Grid Engine, or Open Grid Scheduler) and Slurm environments are supported. In this paper, we present a detailed account on the methods behind the ISC Toolbox, the implementation of the toolbox and demonstrate the possible use of the toolbox by summarizing selected example applications. We also report the computation time experiments both using a single desktop computer and two grid environments demonstrating that parallelization effectively reduces the computing time. The ISC Toolbox is available in https://code.google.com/p/isc-toolbox/
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Norrelgen, Fritjof; Lilja, Anders; Ingvar, Martin; Gisselgård, Jens; Fransson, Peter
2012-01-01
Objective The aims of this study were to develop and assess a method to map language networks in children with two auditory fMRI protocols in combination with a dichotic listening task (DL). The method is intended for pediatric patients prior to epilepsy surgery. To evaluate the potential clinical usefulness of the method we first wanted to assess data from a group of healthy children. Methods In a first step language test materials were developed, intended for subsequent implementation in fMRI protocols. An evaluation of this material was done in 30 children with typical development, 10 from the 1st, 4th and the 7th grade, respectively. The language test material was then adapted and implemented in two fMRI protocols intended to target frontal and posterior language networks. In a second step language lateralization was assessed in 17 typical 10–11 year olds with fMRI and DL. To reach a conclusion about language lateralization, firstly, quantitative analyses of the index data from the two fMRI tasks and the index data from the DL task were done separately. In a second step a set of criteria were applied to these results to reach a conclusion about language lateralization. The steps of these analyses are described in detail. Results The behavioral assessment of the language test material showed that it was well suited for typical children. The results of the language lateralization assessments, based on fMRI data and DL data, showed that for 15 of the 17 subjects (88%) a conclusion could be reached about hemispheric language dominance. In 2 cases (12%) DL provided critical data. Conclusions The employment of DL combined with language mapping using fMRI for assessing hemispheric language dominance is novel and it was deemed valuable since it provided additional information compared to the results gained from each method individually. PMID:23284796
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Directory of Open Access Journals (Sweden)
Fritjof Norrelgen
Full Text Available OBJECTIVE: The aims of this study were to develop and assess a method to map language networks in children with two auditory fMRI protocols in combination with a dichotic listening task (DL. The method is intended for pediatric patients prior to epilepsy surgery. To evaluate the potential clinical usefulness of the method we first wanted to assess data from a group of healthy children. METHODS: In a first step language test materials were developed, intended for subsequent implementation in fMRI protocols. An evaluation of this material was done in 30 children with typical development, 10 from the 1(st, 4(th and the 7(th grade, respectively. The language test material was then adapted and implemented in two fMRI protocols intended to target frontal and posterior language networks. In a second step language lateralization was assessed in 17 typical 10-11 year olds with fMRI and DL. To reach a conclusion about language lateralization, firstly, quantitative analyses of the index data from the two fMRI tasks and the index data from the DL task were done separately. In a second step a set of criteria were applied to these results to reach a conclusion about language lateralization. The steps of these analyses are described in detail. RESULTS: The behavioral assessment of the language test material showed that it was well suited for typical children. The results of the language lateralization assessments, based on fMRI data and DL data, showed that for 15 of the 17 subjects (88% a conclusion could be reached about hemispheric language dominance. In 2 cases (12% DL provided critical data. CONCLUSIONS: The employment of DL combined with language mapping using fMRI for assessing hemispheric language dominance is novel and it was deemed valuable since it provided additional information compared to the results gained from each method individually.
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International Nuclear Information System (INIS)
Wurm, Gabriele; Schnizer, Mathilde; Fellner, Claudia
2008-01-01
Neuronavigation with display of intraoperative structures, instrument locations, orientation and relationships to nearby structures can increase anatomic precision while enhancing the surgeon's confidence and his/her perception of safety. Combination of neuronavigation with functional imaging provides multimodal guidance for surgery of cerebral lesions. We evaluated the impact of functional MRI (fMRI) on surgical decision making and outcome. A neuronavigational device (StealthStation (tm), Medtronic Inc.) was used as platform to merge fMRI data with anatomic images, and to implement intraoperative multimodal guidance. In a 52-month period, where 977 surgical procedures were performed with the aid of neuronavigation, 88 patients underwent image-guided procedures using multimodal guidance. Patient, surgical and outcome data of this series was prospectively collected. Evaluation of 88 procedures on cerebral lesions in complex regions where fMRI data were integrated using the navigation system demonstrated that the additional information was presented in a user-friendly way. Computer assisted fMRI integration was found to be especially helpful in planning the best approach, in assessing alternative approaches, and in defining the extent of the surgical exposure. Furthermore, the surgeons found it more effective to interpret fMRI information when shown in a navigation system as compared to the traditional display on a light board or monitor. Multimodal navigation enhanced by fMRI was judged useful for optimization of surgery of cerebral lesions, especially in and around eloquent regions by experienced neurosurgeons. (orig.)
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International Nuclear Information System (INIS)
Engstroem, Maria; Landtblom, Anne-Marie; Ragnehed, Mattias; Lundberg, Peter; Karlsson, Marie; Crone, Marie; Antepohl, Wolfram
2010-01-01
Background: In fMRI examinations, it is very important to select appropriate paradigms assessing the brain function of interest. In addition, the patients' ability to perform the required cognitive tasks during fMRI must be taken into account. Purpose: To evaluate two language paradigms, word generation and sentence reading for their usefulness in examinations of aphasic patients and to make suggestions for improvements of clinical fMRI. Material and Methods: Five patients with aphasia after stroke or trauma sequelae were examined by fMRI. The patients' language ability was screened by neurolinguistic tests and elementary pre-fMRI language tests. Results: The sentence-reading paradigm succeeded to elicit adequate language-related activation in perilesional areas whereas the word generation paradigm failed. These findings were consistent with results on the behavioral tests in that all patients showed very poor performance in phonemic fluency, but scored well above mean at a reading comprehension task. Conclusion: The sentence-reading paradigm is appropriate to assess language function in this patient group, while the word-generation paradigm seems to be inadequate. In addition, it is crucial to use elementary pre-fMRI language tests to guide the fMRI paradigm decision.
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Seghouane, Abd-Krim; Iqbal, Asif
2017-09-01
Sequential dictionary learning algorithms have been successfully applied to functional magnetic resonance imaging (fMRI) data analysis. fMRI data sets are, however, structured data matrices with the notions of temporal smoothness in the column direction. This prior information, which can be converted into a constraint of smoothness on the learned dictionary atoms, has seldomly been included in classical dictionary learning algorithms when applied to fMRI data analysis. In this paper, we tackle this problem by proposing two new sequential dictionary learning algorithms dedicated to fMRI data analysis by accounting for this prior information. These algorithms differ from the existing ones in their dictionary update stage. The steps of this stage are derived as a variant of the power method for computing the SVD. The proposed algorithms generate regularized dictionary atoms via the solution of a left regularized rank-one matrix approximation problem where temporal smoothness is enforced via regularization through basis expansion and sparse basis expansion in the dictionary update stage. Applications on synthetic data experiments and real fMRI data sets illustrating the performance of the proposed algorithms are provided.
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Energy Technology Data Exchange (ETDEWEB)
Engstroem, Maria; Landtblom, Anne-Marie; Ragnehed, Mattias; Lundberg, Peter (Center for Medical Image Science and Visualization (CMIV), Linkoeping Univ., Linkoeping (Sweden)), e-mail: maria.engstrom@liu.se; Karlsson, Marie; Crone, Marie (Dept. of Clinical and Experimental Medicine/Logopedics, Linkoeping Univ., Linkoeping (Sweden)); Antepohl, Wolfram (Dept. of Clinical and Experimental Medicine/Rehabilitation, Linkoeping Univ., Linkoeping (Sweden))
2010-07-15
Background: In fMRI examinations, it is very important to select appropriate paradigms assessing the brain function of interest. In addition, the patients' ability to perform the required cognitive tasks during fMRI must be taken into account. Purpose: To evaluate two language paradigms, word generation and sentence reading for their usefulness in examinations of aphasic patients and to make suggestions for improvements of clinical fMRI. Material and Methods: Five patients with aphasia after stroke or trauma sequelae were examined by fMRI. The patients' language ability was screened by neurolinguistic tests and elementary pre-fMRI language tests. Results: The sentence-reading paradigm succeeded to elicit adequate language-related activation in perilesional areas whereas the word generation paradigm failed. These findings were consistent with results on the behavioral tests in that all patients showed very poor performance in phonemic fluency, but scored well above mean at a reading comprehension task. Conclusion: The sentence-reading paradigm is appropriate to assess language function in this patient group, while the word-generation paradigm seems to be inadequate. In addition, it is crucial to use elementary pre-fMRI language tests to guide the fMRI paradigm decision.
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Scalable Database Design of End-Game Model with Decoupled Countermeasure and Threat Information
2017-11-01
the Army Modular Active Protection System (MAPS) program to provide end-to-end APS modeling and simulation capabilities. The SSES simulation features...research project of scalable database design was initiated in support of SSES modularization efforts with respect to 4 major software components...Iron Curtain KE kinetic energy MAPS Modular Active Protective System OLE DB object linking and embedding database RDB relational database RPG
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Ready...go: Amplitude of the FMRI signal encodes expectation of cue arrival time.
Directory of Open Access Journals (Sweden)
Xu Cui
2009-08-01
Full Text Available What happens when the brain awaits a signal of uncertain arrival time, as when a sprinter waits for the starting pistol? And what happens just after the starting pistol fires? Using functional magnetic resonance imaging (fMRI, we have discovered a novel correlate of temporal expectations in several brain regions, most prominently in the supplementary motor area (SMA. Contrary to expectations, we found little fMRI activity during the waiting period; however, a large signal appears after the "go" signal, the amplitude of which reflects learned expectations about the distribution of possible waiting times. Specifically, the amplitude of the fMRI signal appears to encode a cumulative conditional probability, also known as the cumulative hazard function. The fMRI signal loses its dependence on waiting time in a "countdown" condition in which the arrival time of the go cue is known in advance, suggesting that the signal encodes temporal probabilities rather than simply elapsed time. The dependence of the signal on temporal expectation is present in "no-go" conditions, demonstrating that the effect is not a consequence of motor output. Finally, the encoding is not dependent on modality, operating in the same manner with auditory or visual signals. This finding extends our understanding of the relationship between temporal expectancy and measurable neural signals.
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Assessment of abstract reasoning abilities in alcohol-dependent subjects: an fMRI study
International Nuclear Information System (INIS)
Bagga, Deepika; Singh, Namita; Singh, Sadhana; Modi, Shilpi; Kumar, Pawan; Bhattacharya, D.; Garg, Mohan L.; Khushu, Subash
2014-01-01
Chronic alcohol abuse has been traditionally associated with impaired cognitive abilities. The deficits are most evident in higher order cognitive functions, such as abstract reasoning, problem solving and visuospatial processing. The present study sought to increase current understanding of the neuropsychological basis of poor abstract reasoning abilities in alcohol-dependent subjects using functional magnetic resonance imaging (fMRI). An abstract reasoning task-based fMRI study was carried out on alcohol-dependent subjects (n = 18) and healthy controls (n = 18) to examine neural activation pattern. The study was carried out using a 3-T whole-body magnetic resonance scanner. Preprocessing and post processing was performed using SPM 8 software. Behavioral data indicated that alcohol-dependent subjects took more time than controls for performing the task but there was no significant difference in their response accuracy. Analysis of the fMRI data indicated that for solving abstract reasoning-based problems, alcohol-dependent subjects showed enhanced right frontoparietal neural activation involving inferior frontal gyrus, post central gyrus, superior parietal lobule, and occipito-temporal gyrus. The extensive activation observed in alcohol dependents as compared to controls suggests that alcohol dependents recruit additional brain areas to meet the behavioral demands for equivalent task performance. The results are consistent with previous fMRI studies suggesting decreased neural efficiency of relevant brain networks or compensatory mechanisms for the execution of task for showing an equivalent performance. (orig.)
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Implicit Structured Sequence Learning: An FMRI Study of the Structural Mere-Exposure Effect
Directory of Open Access Journals (Sweden)
Vasiliki eFolia
2014-02-01
Full Text Available In this event-related FMRI study we investigated the effect of five days of implicit acquisition on preference classification by means of an artificial grammar learning (AGL paradigm based on the structural mere-exposure effect and preference classification using a simple right-linear unification grammar. This allowed us to investigate implicit AGL in a proper learning design by including baseline measurements prior to grammar exposure. After 5 days of implicit acquisition, the FMRI results showed activations in a network of brain regions including the inferior frontal (centered on BA 44/45 and the medial prefrontal regions (centered on BA 8/32. Importantly, and central to this study, the inclusion of a naive preference FMRI baseline measurement allowed us to conclude that these FMRI findings were the intrinsic outcomes of the learning process itself and not a reflection of a preexisting functionality recruited during classification, independent of acquisition. Support for the implicit nature of the knowledge utilized during preference classification on day 5 come from the fact that the basal ganglia, associated with implicit procedural learning, were activated during classification, while the medial temporal lobe system, associated with explicit declarative memory, was consistently deactivated. Thus, preference classification in combination with structural mere-exposure can be used to investigate structural sequence processing (syntax in unsupervised AGL paradigms with proper learning designs.
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Functional brain activation differences in stuttering identified with a rapid fMRI sequence
Kraft, Shelly Jo; Choo, Ai Leen; Sharma, Harish; Ambrose, Nicoline G.
2011-01-01
The purpose of this study was to investigate whether brain activity related to the presence of stuttering can be identified with rapid functional MRI (fMRI) sequences that involved overt and covert speech processing tasks. The long-term goal is to develop sensitive fMRI approaches with developmentally appropriate tasks to identify deviant speech motor and auditory brain activity in children who stutter closer to the age at which recovery from stuttering is documented. Rapid sequences may be preferred for individuals or populations who do not tolerate long scanning sessions. In this report, we document the application of a picture naming and phoneme monitoring task in three minute fMRI sequences with adults who stutter (AWS). If relevant brain differences are found in AWS with these approaches that conform to previous reports, then these approaches can be extended to younger populations. Pairwise contrasts of brain BOLD activity between AWS and normally fluent adults indicated the AWS showed higher BOLD activity in the right inferior frontal gyrus (IFG), right temporal lobe and sensorimotor cortices during picture naming and and higher activity in the right IFG during phoneme monitoring. The right lateralized pattern of BOLD activity together with higher activity in sensorimotor cortices is consistent with previous reports, which indicates rapid fMRI sequences can be considered for investigating stuttering in younger participants. PMID:22133409
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Assessment of abstract reasoning abilities in alcohol-dependent subjects: an fMRI study
Energy Technology Data Exchange (ETDEWEB)
Bagga, Deepika; Singh, Namita; Singh, Sadhana; Modi, Shilpi; Kumar, Pawan [Institute of Nuclear Medicine and Allied Sciences (INMAS), NMR Research Centre, Delhi (India); Bhattacharya, D. [Base Hospital, Department of Psychiatry, Delhi Cantt (India); Garg, Mohan L. [Panjab University, Department of Biophysics, Chandigarh (India); Khushu, Subash [Institute of Nuclear Medicine and Allied Sciences (INMAS), NMR Research Centre, Delhi (India); INMAS, DRDO, NMR Research Centre, Delhi (India)
2014-01-15
Chronic alcohol abuse has been traditionally associated with impaired cognitive abilities. The deficits are most evident in higher order cognitive functions, such as abstract reasoning, problem solving and visuospatial processing. The present study sought to increase current understanding of the neuropsychological basis of poor abstract reasoning abilities in alcohol-dependent subjects using functional magnetic resonance imaging (fMRI). An abstract reasoning task-based fMRI study was carried out on alcohol-dependent subjects (n = 18) and healthy controls (n = 18) to examine neural activation pattern. The study was carried out using a 3-T whole-body magnetic resonance scanner. Preprocessing and post processing was performed using SPM 8 software. Behavioral data indicated that alcohol-dependent subjects took more time than controls for performing the task but there was no significant difference in their response accuracy. Analysis of the fMRI data indicated that for solving abstract reasoning-based problems, alcohol-dependent subjects showed enhanced right frontoparietal neural activation involving inferior frontal gyrus, post central gyrus, superior parietal lobule, and occipito-temporal gyrus. The extensive activation observed in alcohol dependents as compared to controls suggests that alcohol dependents recruit additional brain areas to meet the behavioral demands for equivalent task performance. The results are consistent with previous fMRI studies suggesting decreased neural efficiency of relevant brain networks or compensatory mechanisms for the execution of task for showing an equivalent performance. (orig.)
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Armigliato, Alberto; Pagnoni, Gianluca; Zaniboni, Filippo; Tinti, Stefano
2013-04-01
TRIDEC is a EU-FP7 Project whose main goal is, in general terms, to develop suitable strategies for the management of crises possibly arising in the Earth management field. The general paradigms adopted by TRIDEC to develop those strategies include intelligent information management, the capability of managing dynamically increasing volumes and dimensionality of information in complex events, and collaborative decision making in systems that are typically very loosely coupled. The two areas where TRIDEC applies and tests its strategies are tsunami early warning and industrial subsurface development. In the field of tsunami early warning, TRIDEC aims at developing a Decision Support System (DSS) that integrates 1) a set of seismic, geodetic and marine sensors devoted to the detection and characterisation of possible tsunamigenic sources and to monitoring the time and space evolution of the generated tsunami, 2) large-volume databases of pre-computed numerical tsunami scenarios, 3) a proper overall system architecture. Two test areas are dealt with in TRIDEC: the western Iberian margin and the eastern Mediterranean. In this study, we focus on the western Iberian margin with special emphasis on the Portuguese coasts. The strategy adopted in TRIDEC plans to populate two different databases, called "Virtual Scenario Database" (VSDB) and "Matching Scenario Database" (MSDB), both of which deal only with earthquake-generated tsunamis. In the VSDB we simulate numerically few large-magnitude events generated by the major known tectonic structures in the study area. Heterogeneous slip distributions on the earthquake faults are introduced to simulate events as "realistically" as possible. The members of the VSDB represent the unknowns that the TRIDEC platform must be able to recognise and match during the early crisis management phase. On the other hand, the MSDB contains a very large number (order of thousands) of tsunami simulations performed starting from many different
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Test-retest reliability of evoked BOLD signals from a cognitive-emotive fMRI test battery.
Plichta, Michael M; Schwarz, Adam J; Grimm, Oliver; Morgen, Katrin; Mier, Daniela; Haddad, Leila; Gerdes, Antje B M; Sauer, Carina; Tost, Heike; Esslinger, Christine; Colman, Peter; Wilson, Frederick; Kirsch, Peter; Meyer-Lindenberg, Andreas
2012-04-15
Even more than in cognitive research applications, moving fMRI to the clinic and the drug development process requires the generation of stable and reliable signal changes. The performance characteristics of the fMRI paradigm constrain experimental power and may require different study designs (e.g., crossover vs. parallel groups), yet fMRI reliability characteristics can be strongly dependent on the nature of the fMRI task. The present study investigated both within-subject and group-level reliability of a combined three-task fMRI battery targeting three systems of wide applicability in clinical and cognitive neuroscience: an emotional (face matching), a motivational (monetary reward anticipation) and a cognitive (n-back working memory) task. A group of 25 young, healthy volunteers were scanned twice on a 3T MRI scanner with a mean test-retest interval of 14.6 days. FMRI reliability was quantified using the intraclass correlation coefficient (ICC) applied at three different levels ranging from a global to a localized and fine spatial scale: (1) reliability of group-level activation maps over the whole brain and within targeted regions of interest (ROIs); (2) within-subject reliability of ROI-mean amplitudes and (3) within-subject reliability of individual voxels in the target ROIs. Results showed robust evoked activation of all three tasks in their respective target regions (emotional task=amygdala; motivational task=ventral striatum; cognitive task=right dorsolateral prefrontal cortex and parietal cortices) with high effect sizes (ES) of ROI-mean summary values (ES=1.11-1.44 for the faces task, 0.96-1.43 for the reward task, 0.83-2.58 for the n-back task). Reliability of group level activation was excellent for all three tasks with ICCs of 0.89-0.98 at the whole brain level and 0.66-0.97 within target ROIs. Within-subject reliability of ROI-mean amplitudes across sessions was fair to good for the reward task (ICCs=0.56-0.62) and, dependent on the particular ROI
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Feasibility of using fMRI to study mothers responding to infant cries.
Lorberbaum, J P; Newman, J D; Dubno, J R; Horwitz, A R; Nahas, Z; Teneback, C C; Bloomer, C W; Bohning, D E; Vincent, D; Johnson, M R; Emmanuel, N; Brawman-Mintzer, O; Book, S W; Lydiard, R B; Ballenger, J C; George, M S
1999-01-01
While parenting is a universal human behavior, its neuroanatomic basis is currently unknown. Animal data suggest that the cingulate may play an important function in mammalian parenting behavior. For example, in rodents cingulate lesions impair maternal behavior. Here, in an attempt to understand the brain basis of human maternal behavior, we had mothers listen to recorded infant cries and white noise control sounds while they underwent functional MRI (fMRI) of the brain. We hypothesized that mothers would show significantly greater cingulate activity during the cries compared to the control sounds. Of 7 subjects scanned, 4 had fMRI data suitable for analysis. When fMRI data were averaged for these 4 subjects, the anterior cingulate and right medial prefrontal cortex were the only brain regions showing statistically increased activity with the cries compared to white noise control sounds (cluster analysis with one-tailed z-map threshold of P parent-infant bond and (2) examine whether markers of this bond, such as maternal brain response to infant crying, can predict maternal style (i.e., child neglect), offspring temperament, or offspring depression or anxiety.
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Wall, Matthew B; Mentink, Alexander; Lyons, Georgina; Kowalczyk, Oliwia S; Demetriou, Lysia; Newbould, Rexford D
2017-09-12
Cigarette addiction is driven partly by the physiological effects of nicotine, but also by the distinctive sensory and behavioural aspects of smoking, and understanding the neural effects of such processes is vital. There are many practical difficulties associated with subjects smoking in the modern neuroscientific laboratory environment, however electronic cigarettes obviate many of these issues, and provide a close simulation of smoking tobacco cigarettes. We have examined the neural effects of 'smoking' electronic cigarettes with concurrent functional Magnetic Resonance Imaging (fMRI). The results demonstrate the feasibility of using these devices in the MRI environment, and show brain activation in a network of cortical (motor cortex, insula, cingulate, amygdala) and sub-cortical (putamen, thalamus, globus pallidus, cerebellum) regions. Concomitant relative deactivations were seen in the ventral striatum and orbitofrontal cortex. These results reveal the brain processes involved in (simulated) smoking for the first time, and validate a novel approach to the study of smoking, and addiction more generally.
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Dang, Shilpa; Chaudhury, Santanu; Lall, Brejesh; Roy, Prasun Kumar
2017-06-15
Determination of effective connectivity (EC) among brain regions using fMRI is helpful in understanding the underlying neural mechanisms. Dynamic Bayesian Networks (DBNs) are an appropriate class of probabilistic graphical temporal-models that have been used in past to model EC from fMRI, specifically order-one. High-order DBNs (HO-DBNs) have still not been explored for fMRI data. A fundamental problem faced in the structure-learning of HO-DBN is high computational-burden and low accuracy by the existing heuristic search techniques used for EC detection from fMRI. In this paper, we propose using dynamic programming (DP) principle along with integration of properties of scoring-function in a way to reduce search space for structure-learning of HO-DBNs and finally, for identifying EC from fMRI which has not been done yet to the best of our knowledge. The proposed exact search-&-score learning approach HO-DBN-DP is an extension of the technique which was originally devised for learning a BN's structure from static data (Singh and Moore, 2005). The effectiveness in structure-learning is shown on synthetic fMRI dataset. The algorithm reaches globally-optimal solution in appreciably reduced time-complexity than the static counterpart due to integration of properties. The proof of optimality is provided. The results demonstrate that HO-DBN-DP is comparably more accurate and faster than currently used structure-learning algorithms used for identifying EC from fMRI. The real data EC from HO-DBN-DP shows consistency with previous literature than the classical Granger Causality method. Hence, the DP algorithm can be employed for reliable EC estimates from experimental fMRI data. Copyright © 2017 Elsevier B.V. All rights reserved.
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Toller, Gianina; Adhimoolam, Babu; Grunwald, Thomas; Huppertz, Hans-Jürgen; König, Kristina; Jokeit, Hennric
2015-01-01
Nonvisual spatial navigation functional magnetic resonance imaging (fMRI) may help clinicians determine memory lateralization in blind individuals with refractory mesial temporal lobe epilepsy (MTLE). We report on an exceptional case of a congenitally blind woman with late-onset left MTLE undergoing presurgical memory fMRI. To activate mesial temporal structures despite the lack of visual memory, the patient was requested to recall familiar routes using nonvisual multisensory and verbal cues. Our findings demonstrate the diagnostic value of a nonvisual fMRI task to lateralize MTLE despite congenital blindness and may therefore contribute to the risk assessment for postsurgical amnesia in rare cases with refractory MTLE and accompanying congenital blindness.
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Short- and long-term reliability of language fMRI.
Nettekoven, Charlotte; Reck, Nicola; Goldbrunner, Roland; Grefkes, Christian; Weiß Lucas, Carolin
2018-08-01
When using functional magnetic resonance imaging (fMRI) for mapping important language functions, a high test-retest reliability is mandatory, both in basic scientific research and for clinical applications. We, therefore, systematically tested the short- and long-term reliability of fMRI in a group of healthy subjects using a picture naming task and a sparse-sampling fMRI protocol. We hypothesized that test-retest reliability might be higher for (i) speech-related motor areas than for other language areas and for (ii) the short as compared to the long intersession interval. 16 right-handed subjects (mean age: 29 years) participated in three sessions separated by 2-6 (session 1 and 2, short-term) and 21-34 days (session 1 and 3, long-term). Subjects were asked to perform the same overt picture naming task in each fMRI session (50 black-white images per session). Reliability was tested using the following measures: (i) Euclidean distances (ED) between local activation maxima and Centers of Gravity (CoGs), (ii) overlap volumes and (iii) voxel-wise intraclass correlation coefficients (ICCs). Analyses were performed for three regions of interest which were chosen based on whole-brain group data: primary motor cortex (M1), superior temporal gyrus (STG) and inferior frontal gyrus (IFG). Our results revealed that the activation centers were highly reliable, independent of the time interval, ROI or hemisphere with significantly smaller ED for the local activation maxima (6.45 ± 1.36 mm) as compared to the CoGs (8.03 ± 2.01 mm). In contrast, the extent of activation revealed rather low reliability values with overlaps ranging from 24% (IFG) to 56% (STG). Here, the left hemisphere showed significantly higher overlap volumes than the right hemisphere. Although mean ICCs ranged between poor (ICC0.75) were found for all ROIs. Voxel-wise reliability of the different ROIs was influenced by the intersession interval. Taken together, we could show that, despite of
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Convergence of EEG and fMRI measures of reward anticipation.
Gorka, Stephanie M; Phan, K Luan; Shankman, Stewart A
2015-12-01
Deficits in reward anticipation are putative mechanisms for multiple psychopathologies. Research indicates that these deficits are characterized by reduced left (relative to right) frontal electroencephalogram (EEG) activity and blood oxygenation level-dependent (BOLD) signal abnormalities in mesolimbic and prefrontal neural regions during reward anticipation. Although it is often assumed that these two measures capture similar mechanisms, no study to our knowledge has directly examined the convergence between frontal EEG alpha asymmetry and functional magnetic resonance imaging (fMRI) during reward anticipation in the same sample. Therefore, the aim of the current study was to investigate if and where in the brain frontal EEG alpha asymmetry and fMRI measures were correlated in a sample of 40 adults. All participants completed two analogous reward anticipation tasks--once during EEG data collection and the other during fMRI data collection. Results indicated that the two measures do converge and that during reward anticipation, increased relative left frontal activity is associated with increased left anterior cingulate cortex (ACC)/medial prefrontal cortex (mPFC) and left orbitofrontal cortex (OFC) activation. This suggests that the two measures may similarly capture PFC functioning, which is noteworthy given the role of these regions in reward processing and the pathophysiology of disorders such as depression and schizophrenia. Copyright © 2015 Elsevier B.V. All rights reserved.
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Methodology for functional MRI of simulated driving.
Kan, Karen; Schweizer, Tom A; Tam, Fred; Graham, Simon J
2013-01-01
The developed world faces major socioeconomic and medical challenges associated with motor vehicle accidents caused by risky driving. Functional magnetic resonance imaging (fMRI) of individuals using virtual reality driving simulators may provide an important research tool to assess driving safety, based on brain activity and behavior. A fMRI-compatible driving simulator was developed and evaluated in the context of straight driving, turning, and stopping in 16 young healthy adults. Robust maps of brain activity were obtained, including activation of the primary motor cortex, cerebellum, visual cortex, and parietal lobe, with limited head motion (driving is a feasible undertaking.
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Integration of fMRI, NIROT and ERP for studies of human brain function.
Gore, John C; Horovitz, Silvina G; Cannistraci, Christopher J; Skudlarski, Pavel
2006-05-01
Different methods of assessing human brain function possess specific advantages and disadvantages compared to others, but it is believed that combining different approaches will provide greater information than can be obtained from each alone. For example, functional magnetic resonance imaging (fMRI) has good spatial resolution but poor temporal resolution, whereas the converse is true for electrophysiological recordings (event-related potentials or ERPs). In this review of recent work, we highlight a novel approach to combining these modalities in a manner designed to increase information on the origins and locations of the generators of specific ERPs and the relationship between fMRI and ERP signals. Near infrared imaging techniques have also been studied as alternatives to fMRI and can be readily integrated with simultaneous electrophysiological recordings. Each of these modalities may in principle be also used in so-called steady-state acquisitions in which the correlational structure of signals from the brain may be analyzed to provide new insights into brain function.
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Combining fMRI and behavioral measures to examine the process of human learning.
Karuza, Elisabeth A; Emberson, Lauren L; Aslin, Richard N
2014-03-01
Prior to the advent of fMRI, the primary means of examining the mechanisms underlying learning were restricted to studying human behavior and non-human neural systems. However, recent advances in neuroimaging technology have enabled the concurrent study of human behavior and neural activity. We propose that the integration of behavioral response with brain activity provides a powerful method of investigating the process through which internal representations are formed or changed. Nevertheless, a review of the literature reveals that many fMRI studies of learning either (1) focus on outcome rather than process or (2) are built on the untested assumption that learning unfolds uniformly over time. We discuss here various challenges faced by the field and highlight studies that have begun to address them. In doing so, we aim to encourage more research that examines the process of learning by considering the interrelation of behavioral measures and fMRI recording during learning. Copyright © 2013 Elsevier Inc. All rights reserved.
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Generative embedding for model-based classification of fMRI data.
Directory of Open Access Journals (Sweden)
Kay H Brodersen
2011-06-01
Full Text Available Decoding models, such as those underlying multivariate classification algorithms, have been increasingly used to infer cognitive or clinical brain states from measures of brain activity obtained by functional magnetic resonance imaging (fMRI. The practicality of current classifiers, however, is restricted by two major challenges. First, due to the high data dimensionality and low sample size, algorithms struggle to separate informative from uninformative features, resulting in poor generalization performance. Second, popular discriminative methods such as support vector machines (SVMs rarely afford mechanistic interpretability. In this paper, we address these issues by proposing a novel generative-embedding approach that incorporates neurobiologically interpretable generative models into discriminative classifiers. Our approach extends previous work on trial-by-trial classification for electrophysiological recordings to subject-by-subject classification for fMRI and offers two key advantages over conventional methods: it may provide more accurate predictions by exploiting discriminative information encoded in 'hidden' physiological quantities such as synaptic connection strengths; and it affords mechanistic interpretability of clinical classifications. Here, we introduce generative embedding for fMRI using a combination of dynamic causal models (DCMs and SVMs. We propose a general procedure of DCM-based generative embedding for subject-wise classification, provide a concrete implementation, and suggest good-practice guidelines for unbiased application of generative embedding in the context of fMRI. We illustrate the utility of our approach by a clinical example in which we classify moderately aphasic patients and healthy controls using a DCM of thalamo-temporal regions during speech processing. Generative embedding achieves a near-perfect balanced classification accuracy of 98% and significantly outperforms conventional activation-based and
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A web-based database for EPR centers in semiconductors
International Nuclear Information System (INIS)
Umeda, T.; Hagiwara, S.; Katagiri, M.; Mizuochi, N.; Isoya, J.
2006-01-01
We develop a web-based database system for electron paramagnetic resonance (EPR) centers in semiconductors. This database is available to anyone at http://www.kc.tsukuba.ac.jp/div-media/epr/. It currently has more than 300 records of the spin-Hamiltonian parameters for major known EPR centers. One can upload own new records to the database or can use simulation tools powered by EPR-NMR(C). Here, we describe the features and objectives of this database, and mention some future plans
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Tactile and non-tactile sensory paradigms for fMRI and neurophysiologic studies in rodents
Sanganahalli, Basavaraju G.; Bailey, Christopher J.; Herman, Peter; Hyder, Fahmeed
2009-01-01
Functional magnetic resonance imaging (fMRI) has become a popular functional imaging tool for human studies. Future diagnostic use of fMRI depends, however, on a suitable neurophysiologic interpretation of the blood oxygenation level dependent (BOLD) signal change. This particular goal is best achieved in animal models primarily due to the invasive nature of other methods used and/or pharmacological agents applied to probe different nuances of neuronal (and glial) activity coupled to the BOLD...
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Blood Flow and Brain Function: Investigations of neurovascular coupling using BOLD fMRI at 7 tesla
Siero, J.C.W.
2013-01-01
The advent of ultra high field (7 tesla) MRI systems has opened the possibility to probe biological processes of the human body in great detail. Especially for studying brain function using BOLD fMRI there is a large benefit from the increased magnetic field strength. BOLD fMRI is the working horse
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Functional magnetic resonance imaging (fMRI) of motor deficits in schizophrenia
International Nuclear Information System (INIS)
Wenz, F.; Floemer, F.; Kaick, G. van
1995-01-01
The purpose of this study was to investigate differences in the cerebral activation pattern in ten schizophrenic patients and ten healthy volunteers using functional MRI. fMRI was performed using a modified FLASH sequence (TR/TE/α=100/60/40 ) and a conventional 1.5 T MR scanner. Colorcoded statistical parametric maps based on Student's t-test were calculated. Activation strength was quantified using a 5x6 grid overlay. The volunteers showed a higher activation strength during left hand movement compared to right hand movement. This lateralization effect was reversed in patients who showed overall reduced activation strength. Disturbed interhemispheric balance in schizophrenic patients during motor task performance can be demonstrated using fMRI. (orig.) [de
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International Nuclear Information System (INIS)
Siegel, Andrew M; Culver, Joseph P; Mandeville, Joseph B; Boas, David A
2003-01-01
The time courses of oxyhaemoglobin ([HbO 2 ]), deoxyhaemoglobin ([HbR]) and total haemoglobin ([HbT]) concentration changes following cortical activation in rats by electrical forepaw stimulation were measured using diffuse optical tomography (DOT) and compared to similar measurements performed previously with fMRI at 2.0 T and 4.7 T. We also explored the qualitative effects of varying stimulus parameters on the temporal evolution of the hemodynamic response. DOT images were reconstructed at a depth of 1.5 mm over a 1 cm square area from 2 mm anterior to bregma to 8 mm posterior to bregma. The measurement set included 9 sources and 16 detectors with an imaging frame rate of 10 Hz. Both DOT [HbR] and [HbO 2 ] time courses were compared to the fMRI BOLD time course during stimulation, and the DOT [HbT] time course was compared to the fMRI cerebral plasma volume (CPV) time course. We believe that DOT and fMRI can provide similar temporal information for both blood volume and deoxyhaemoglobin changes, which helps to cross-validate these two techniques and to demonstrate that DOT can be useful as a complementary modality to fMRI for investigating the hemodynamic response to neuronal activity
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Energy Technology Data Exchange (ETDEWEB)
Siegel, Andrew M [Tufts University Bioengineering Center, Medford, MA 02155 (United States); Culver, Joseph P [Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129 (United States); Mandeville, Joseph B [Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129 (United States); Boas, David A [Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129 (United States)
2003-05-21
The time courses of oxyhaemoglobin ([HbO{sub 2}]), deoxyhaemoglobin ([HbR]) and total haemoglobin ([HbT]) concentration changes following cortical activation in rats by electrical forepaw stimulation were measured using diffuse optical tomography (DOT) and compared to similar measurements performed previously with fMRI at 2.0 T and 4.7 T. We also explored the qualitative effects of varying stimulus parameters on the temporal evolution of the hemodynamic response. DOT images were reconstructed at a depth of 1.5 mm over a 1 cm square area from 2 mm anterior to bregma to 8 mm posterior to bregma. The measurement set included 9 sources and 16 detectors with an imaging frame rate of 10 Hz. Both DOT [HbR] and [HbO{sub 2}] time courses were compared to the fMRI BOLD time course during stimulation, and the DOT [HbT] time course was compared to the fMRI cerebral plasma volume (CPV) time course. We believe that DOT and fMRI can provide similar temporal information for both blood volume and deoxyhaemoglobin changes, which helps to cross-validate these two techniques and to demonstrate that DOT can be useful as a complementary modality to fMRI for investigating the hemodynamic response to neuronal activity.
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Biomass Gasifier for Computer Simulation; Biomassa foergasare foer Computer Simulation
Energy Technology Data Exchange (ETDEWEB)
Hansson, Jens; Leveau, Andreas; Hulteberg, Christian [Nordlight AB, Limhamn (Sweden)
2011-08-15
This report is an effort to summarize the existing data on biomass gasifiers as the authors have taken part in various projects aiming at computer simulations of systems that include biomass gasification. Reliable input data is paramount for any computer simulation, but so far there is no easy-accessible biomass gasifier database available for this purpose. This study aims at benchmarking current and past gasifier systems in order to create a comprehensive database for computer simulation purposes. The result of the investigation is presented in a Microsoft Excel sheet, so that the user easily can implement the data in their specific model. In addition to provide simulation data, the technology is described briefly for every studied gasifier system. The primary pieces of information that are sought for are temperatures, pressures, stream compositions and energy consumption. At present the resulting database contains 17 gasifiers, with one or more gasifier within the different gasification technology types normally discussed in this context: 1. Fixed bed 2. Fluidised bed 3. Entrained flow. It also contains gasifiers in the range from 100 kW to 120 MW, with several gasifiers in between these two values. Finally, there are gasifiers representing both direct and indirect heating. This allows for a more qualified and better available choice of starting data sets for simulations. In addition to this, with multiple data sets available for several of the operating modes, sensitivity analysis of various inputs will improve simulations performed. However, there have been fewer answers to the survey than expected/hoped for, which could have improved the database further. However, the use of online sources and other public information has to some extent counterbalanced the low response frequency of the survey. In addition to that, the database is preferred to be a living document, continuously updated with new gasifiers and improved information on existing gasifiers.
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Spatio-temporal models of mental processes from fMRI.
Janoos, Firdaus; Machiraju, Raghu; Singh, Shantanu; Morocz, Istvan Ákos
2011-07-15
Understanding the highly complex, spatially distributed and temporally organized phenomena entailed by mental processes using functional MRI is an important research problem in cognitive and clinical neuroscience. Conventional analysis methods focus on the spatial dimension of the data discarding the information about brain function contained in the temporal dimension. This paper presents a fully spatio-temporal multivariate analysis method using a state-space model (SSM) for brain function that yields not only spatial maps of activity but also its temporal structure along with spatially varying estimates of the hemodynamic response. Efficient algorithms for estimating the parameters along with quantitative validations are given. A novel low-dimensional feature-space for representing the data, based on a formal definition of functional similarity, is derived. Quantitative validation of the model and the estimation algorithms is provided with a simulation study. Using a real fMRI study for mental arithmetic, the ability of this neurophysiologically inspired model to represent the spatio-temporal information corresponding to mental processes is demonstrated. Moreover, by comparing the models across multiple subjects, natural patterns in mental processes organized according to different mental abilities are revealed. Copyright © 2011 Elsevier Inc. All rights reserved.
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Combined fMRI- and eye movement-based decoding of bistable plaid motion perception.
Wilbertz, Gregor; Ketkar, Madhura; Guggenmos, Matthias; Sterzer, Philipp
2018-05-01
The phenomenon of bistable perception, in which perception alternates spontaneously despite constant sensory stimulation, has been particularly useful in probing the neural bases of conscious perception. The study of such bistability requires access to the observer's perceptual dynamics, which is usually achieved via active report. This report, however, constitutes a confounding factor in the study of conscious perception and can also be biased in the context of certain experimental manipulations. One approach to circumvent these problems is to track perceptual alternations using signals from the eyes or the brain instead of observers' reports. Here we aimed to optimize such decoding of perceptual alternations by combining eye and brain signals. Eye-tracking and functional magnetic resonance imaging (fMRI) was performed in twenty participants while they viewed a bistable visual plaid motion stimulus and reported perceptual alternations. Multivoxel pattern analysis (MVPA) for fMRI was combined with eye-tracking in a Support vector machine to decode participants' perceptual time courses from fMRI and eye-movement signals. While both measures individually already yielded high decoding accuracies (on average 86% and 88% correct, respectively) classification based on the two measures together further improved the accuracy (91% correct). These findings show that leveraging on both fMRI and eye movement data may pave the way for optimized no-report paradigms through improved decodability of bistable motion perception and hence for a better understanding of the neural correlates of consciousness. Copyright © 2018 Elsevier Inc. All rights reserved.
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International Nuclear Information System (INIS)
Watanabe, Yukinobu; Kodama, Akihiro; Tukamoto, Yasuyuki; Nakashima, Hideki
2005-01-01
We have developed a cross-section database for neutron-induced reactions on 28Si in the energy range between 2 MeV and 3 GeV in order to analyze single-event upsets (SEUs) phenomena induced by cosmic-ray neutrons in microelectronic devices. A simplified spherical device model is proposed for simulation of the initial processes of SEUs. The model is applied to SEU cross-section calculations for semiconductor memory devices. The calculated results are compared with measured SEU cross sections and the other simulation result. The dependence of SEU cross sections on incident neutron energy and secondary ions having the most important effects on SEUs are discussed
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Hormone effects on fMRI and cognitive measures of encoding: importance of hormone preparation.
Gleason, C E; Schmitz, T W; Hess, T; Koscik, R L; Trivedi, M A; Ries, M L; Carlsson, C M; Sager, M A; Asthana, S; Johnson, S C
2006-12-12
We compared fMRI and cognitive data from nine hormone therapy (HT)-naive women with data from women exposed to either opposed conjugated equine estrogens (CEE) (n = 10) or opposed estradiol (n = 4). Exposure to either form of HT was associated with healthier fMRI response; however, CEE-exposed women exhibited poorer memory performance than either HT-naive or estradiol-exposed subjects. These preliminary findings emphasize the need to characterize differential neural effects of various HTs.
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Machine learning algorithm accurately detects fMRI signature of vulnerability to major depression.
Sato, João R; Moll, Jorge; Green, Sophie; Deakin, John F W; Thomaz, Carlos E; Zahn, Roland
2015-08-30
Standard functional magnetic resonance imaging (fMRI) analyses cannot assess the potential of a neuroimaging signature as a biomarker to predict individual vulnerability to major depression (MD). Here, we use machine learning for the first time to address this question. Using a recently identified neural signature of guilt-selective functional disconnection, the classification algorithm was able to distinguish remitted MD from control participants with 78.3% accuracy. This demonstrates the high potential of our fMRI signature as a biomarker of MD vulnerability. Crown Copyright © 2015. Published by Elsevier Ireland Ltd. All rights reserved.
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Nonparametric modeling of dynamic functional connectivity in fmri data
DEFF Research Database (Denmark)
Nielsen, Søren Føns Vind; Madsen, Kristoffer H.; Røge, Rasmus
2015-01-01
dynamic changes. The existing approaches modeling dynamic connectivity have primarily been based on time-windowing the data and k-means clustering. We propose a nonparametric generative model for dynamic FC in fMRI that does not rely on specifying window lengths and number of dynamic states. Rooted...
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Demertzi, Athena; Gómez, Francisco; Crone, Julia Sophia; Vanhaudenhuyse, Audrey; Tshibanda, Luaba; Noirhomme, Quentin; Thonnard, Marie; Charland-Verville, Vanessa; Kirsch, Murielle; Laureys, Steven; Soddu, Andrea
2014-03-01
In healthy conditions, group-level fMRI resting state analyses identify ten resting state networks (RSNs) of cognitive relevance. Here, we aim to assess the ten-network model in severely brain-injured patients suffering from disorders of consciousness and to identify those networks which will be most relevant to discriminate between patients and healthy subjects. 300 fMRI volumes were obtained in 27 healthy controls and 53 patients in minimally conscious state (MCS), vegetative state/unresponsive wakefulness syndrome (VS/UWS) and coma. Independent component analysis (ICA) reduced data dimensionality. The ten networks were identified by means of a multiple template-matching procedure and were tested on neuronality properties (neuronal vs non-neuronal) in a data-driven way. Univariate analyses detected between-group differences in networks' neuronal properties and estimated voxel-wise functional connectivity in the networks, which were significantly less identifiable in patients. A nearest-neighbor "clinical" classifier was used to determine the networks with high between-group discriminative accuracy. Healthy controls were characterized by more neuronal components compared to patients in VS/UWS and in coma. Compared to healthy controls, fewer patients in MCS and VS/UWS showed components of neuronal origin for the left executive control network, default mode network (DMN), auditory, and right executive control network. The "clinical" classifier indicated the DMN and auditory network with the highest accuracy (85.3%) in discriminating patients from healthy subjects. FMRI multiple-network resting state connectivity is disrupted in severely brain-injured patients suffering from disorders of consciousness. When performing ICA, multiple-network testing and control for neuronal properties of the identified RSNs can advance fMRI system-level characterization. Automatic data-driven patient classification is the first step towards future single-subject objective diagnostics
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fMRI responses to pictures of mutilation and contamination.
Schienle, Anne; Schäfer, Axel; Hermann, Andrea; Walter, Bertram; Stark, Rudolf; Vaitl, Dieter
2006-01-30
Findings from several functional magnetic resonance imaging (fMRI) studies implicate the existence of a distinct neural disgust substrate, whereas others support the idea of distributed and integrative brain systems involved in emotional processing. In the present fMRI experiment 12 healthy females viewed pictures from four emotion categories. Two categories were disgust-relevant and depicted contamination or mutilation. The other scenes showed attacks (fear) or were affectively neutral. The two types of disgust elicitors received comparable ratings for disgust, fear and arousal. Both were associated with activation of the occipitotemporal cortex, the amygdala, and the orbitofrontal cortex; insula activity was nonsignificant in the two disgust conditions. Mutilation scenes induced greater inferior parietal activity than contamination scenes, which might mirror their greater capacity to capture attention. Our results are in disagreement with the idea of selective disgust processing at the insula. They point to a network of brain regions involved in the decoding of stimulus salience and the regulation of attention.
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Brain Activity Associated with Emoticons: An fMRI Study
Yuasa, Masahide; Saito, Keiichi; Mukawa, Naoki
In this paper, we describe that brain activities associated with emoticons by using fMRI. In communication over a computer network, we use abstract faces such as computer graphics (CG) avatars and emoticons. These faces convey users' emotions and enrich their communications. However, the manner in which these faces influence the mental process is as yet unknown. The human brain may perceive the abstract face in an entirely different manner, depending on its level of reality. We conducted an experiment using fMRI in order to investigate the effects of emoticons. The results show that right inferior frontal gyrus, which associated with nonverbal communication, is activated by emoticons. Since the emoticons were created to reflect the real human facial expressions as accurately as possible, we believed that they would activate the right fusiform gyrus. However, this region was not found to be activated during the experiment. This finding is useful in understanding how abstract faces affect our behaviors and decision-making in communication over a computer network.
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Automated testing of arrhythmia monitors using annotated databases.
Elghazzawi, Z; Murray, W; Porter, M; Ezekiel, E; Goodall, M; Staats, S; Geheb, F
1992-01-01
Arrhythmia-algorithm performance is typically tested using the AHA and MIT/BIH databases. The tools for this test are simulation software programs. While these simulations provide rapid results, they neglect hardware and software effects in the monitor. To provide a more accurate measure of performance in the actual monitor, a system has been developed for automated arrhythmia testing. The testing system incorporates an IBM-compatible personal computer, a digital-to-analog converter, an RS232 board, a patient-simulator interface to the monitor, and a multi-tasking software package for data conversion and communication with the monitor. This system "plays" patient data files into the monitor and saves beat classifications in detection files. Tests were performed using the MIT/BIH and AHA databases. Statistics were generated by comparing the detection files with the annotation files. These statistics were marginally different from those that resulted from the simulation. Differences were then examined. As expected, the differences were related to monitor hardware effects.
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Persistency of priors-induced bias in decision behavior and the fMRI signal
Directory of Open Access Journals (Sweden)
Kathleen eHansen
2011-03-01
Full Text Available It is well known that people take advantage of prior knowledge to bias decisions. To investigate this phenomenon behaviorally and in the brain, we acquired fMRI data while human subjects viewed ambiguous abstract shapes and decided whether a shape was of Category A (smoother or B (bumpier. The decision was made in the context of one of two prior knowledge cues, 80/20 and 50/50. The 80/20 cue indicated that upcoming shapes had an 80% probability of being of one category, e.g. B, and a 20% probability of being of the other. The 50/50 cue indicated that upcoming shapes had an equal probability of being of either category. The ideal observer would bias decisions in favor of the indicated alternative at 80/20 and show zero bias at 50/50. We found that subjects did bias their decisions in the predicted direction at 80/20 but did not show zero bias at 50/50. Instead, at 50/50 the subjects retained biases of the same sign as their 80/20 biases, though of diminished magnitude. The signature of a persistent though diminished bias at 50/50 was also evident in fMRI data from frontal and parietal regions previously implicated in decision-making. As a control, we acquired fMRI data from naïve subjects who experienced only the 50/50 stimulus distributions during both the prescan training and the fMRI experiment. The behavioral and fMRI data from the naïve subjects reflected decision biases closer to those of the ideal observer than those of the prior knowledge subjects at 50/50. The results indicate that practice making decisions in the context of non-equal prior probabilities biases decisions made later when prior probabilities are equal. This finding may be related to the anchoring and adjustment strategy described in the psychology, economics and marketing literatures, in which subjects adjust a first approximation response – the anchor – based on additional information, typically applying insufficient adjustment relative to the ideal observer.
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Voss, Frank; Maule, Alec
2013-01-01
A model for simulating daily maximum and mean water temperatures was developed by linking two existing models: one developed by the U.S. Geological Survey and one developed by the Bureau of Reclamation. The study area included the lower Yakima River main stem between the Roza Dam and West Richland, Washington. To automate execution of the labor-intensive models, a database-driven model automation program was developed to decrease operation costs, to reduce user error, and to provide the capability to perform simulations quickly for multiple management and climate change scenarios. Microsoft© SQL Server 2008 R2 Integration Services packages were developed to (1) integrate climate, flow, and stream geometry data from diverse sources (such as weather stations, a hydrologic model, and field measurements) into a single relational database; (2) programmatically generate heavily formatted model input files; (3) iteratively run water temperature simulations; (4) process simulation results for export to other models; and (5) create a database-driven infrastructure that facilitated experimentation with a variety of scenarios, node permutations, weather data, and hydrologic conditions while minimizing costs of running the model with various model configurations. As a proof-of-concept exercise, water temperatures were simulated for a "Current Conditions" scenario, where local weather data from 1980 through 2005 were used as input, and for "Plus 1" and "Plus 2" climate warming scenarios, where the average annual air temperatures used in the Current Conditions scenario were increased by 1degree Celsius (°C) and by 2°C, respectively. Average monthly mean daily water temperatures simulated for the Current Conditions scenario were compared to measured values at the Bureau of Reclamation Hydromet gage at Kiona, Washington, for 2002-05. Differences ranged between 1.9° and 1.1°C for February, March, May, and June, and were less than 0.8°C for the remaining months of the year
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Using fMRI to Investigate Memory in Young Children Born Small for Gestational Age.
Directory of Open Access Journals (Sweden)
Henrica M A de Bie
Full Text Available Intrauterine growth restriction (IUGR can lead to infants being born small for gestational age (SGA. SGA is associated with differences in brain anatomy and impaired cognition. We investigated learning and memory in children born SGA using neuropsychological testing and functional Magnetic Resonance Imaging (fMRI.18 children born appropriate for gestational age (AGA and 34 SGA born children (18 with and 16 without postnatal catch-up growth participated in this study. All children were between 4 and 7 years old. Cognitive functioning was assessed by IQ and memory testing (Digit/Word Span and Location Learning. A newly developed fMRI picture encoding task was completed by all children in order to assess brain regions involved in memory processes.Neuropsychological testing demonstrated that SGA children had IQ's within the normal range but lower than in AGA and poorer performances across measures of memory. Using fMRI, we observed memory related activity in posterior parahippocampal gyrus as well as the hippocampus proper. Additionally, activation was seen bilaterally in the prefrontal gyrus. Children born SGA showed less activation in the left parahippocampal region compared to AGA.This is the first fMRI study demonstrating different brain activation patterns in 4-7 year old children born SGA, suggesting that intrauterine growth restriction continues to affect neural functioning in children later-on.
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Implicit structured sequence learning: an fMRI study of the structural mere-exposure effect.
Folia, Vasiliki; Petersson, Karl Magnus
2014-01-01
In this event-related fMRI study we investigated the effect of 5 days of implicit acquisition on preference classification by means of an artificial grammar learning (AGL) paradigm based on the structural mere-exposure effect and preference classification using a simple right-linear unification grammar. This allowed us to investigate implicit AGL in a proper learning design by including baseline measurements prior to grammar exposure. After 5 days of implicit acquisition, the fMRI results showed activations in a network of brain regions including the inferior frontal (centered on BA 44/45) and the medial prefrontal regions (centered on BA 8/32). Importantly, and central to this study, the inclusion of a naive preference fMRI baseline measurement allowed us to conclude that these fMRI findings were the intrinsic outcomes of the learning process itself and not a reflection of a preexisting functionality recruited during classification, independent of acquisition. Support for the implicit nature of the knowledge utilized during preference classification on day 5 come from the fact that the basal ganglia, associated with implicit procedural learning, were activated during classification, while the medial temporal lobe system, associated with explicit declarative memory, was consistently deactivated. Thus, preference classification in combination with structural mere-exposure can be used to investigate structural sequence processing (syntax) in unsupervised AGL paradigms with proper learning designs.
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Using fMRI to Investigate Memory in Young Children Born Small for Gestational Age.
de Bie, Henrica M A; de Ruiter, Michiel B; Ouwendijk, Mieke; Oostrom, Kim J; Wilke, Marko; Boersma, Maria; Veltman, Dick J; Delemarre-van de Waal, Henriette A
2015-01-01
Intrauterine growth restriction (IUGR) can lead to infants being born small for gestational age (SGA). SGA is associated with differences in brain anatomy and impaired cognition. We investigated learning and memory in children born SGA using neuropsychological testing and functional Magnetic Resonance Imaging (fMRI). 18 children born appropriate for gestational age (AGA) and 34 SGA born children (18 with and 16 without postnatal catch-up growth) participated in this study. All children were between 4 and 7 years old. Cognitive functioning was assessed by IQ and memory testing (Digit/Word Span and Location Learning). A newly developed fMRI picture encoding task was completed by all children in order to assess brain regions involved in memory processes. Neuropsychological testing demonstrated that SGA children had IQ's within the normal range but lower than in AGA and poorer performances across measures of memory. Using fMRI, we observed memory related activity in posterior parahippocampal gyrus as well as the hippocampus proper. Additionally, activation was seen bilaterally in the prefrontal gyrus. Children born SGA showed less activation in the left parahippocampal region compared to AGA. This is the first fMRI study demonstrating different brain activation patterns in 4-7 year old children born SGA, suggesting that intrauterine growth restriction continues to affect neural functioning in children later-on.
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Restoration of fMRI Decodability Does Not Imply Latent Working Memory States
Schneegans, Sebastian; Bays, Paul M.
2018-01-01
Recent imaging studies have challenged the prevailing view that working memory is mediated by sustained neural activity. Using machine learning methods to reconstruct memory content, these studies found that previously diminished representations can be restored by retrospective cueing or other forms of stimulation. These findings have been interpreted as evidence for an activity-silent working memory state that can be reactivated dependent on task demands. Here, we test the validity of this conclusion by formulating a neural process model of working memory based on sustained activity and using this model to emulate a spatial recall task with retrocueing. The simulation reproduces both behavioral and fMRI results previously taken as evidence for latent states, in particular the restoration of spatial reconstruction quality following an informative cue. Our results demonstrate that recovery of the decodability of an imaging signal does not provide compelling evidence for an activity-silent working memory state. PMID:28820674
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Automatic physiological waveform processing for FMRI noise correction and analysis.
Directory of Open Access Journals (Sweden)
Daniel J Kelley
2008-03-01
Full Text Available Functional MRI resting state and connectivity studies of brain focus on neural fluctuations at low frequencies which share power with physiological fluctuations originating from lung and heart. Due to the lack of automated software to process physiological signals collected at high magnetic fields, a gap exists in the processing pathway between the acquisition of physiological data and its use in fMRI software for both physiological noise correction and functional analyses of brain activation and connectivity. To fill this gap, we developed an open source, physiological signal processing program, called PhysioNoise, in the python language. We tested its automated processing algorithms and dynamic signal visualization on resting monkey cardiac and respiratory waveforms. PhysioNoise consistently identifies physiological fluctuations for fMRI noise correction and also generates covariates for subsequent analyses of brain activation and connectivity.
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Simultaneous functional imaging using fPET and fMRI
Energy Technology Data Exchange (ETDEWEB)
Villien, Marjorie [CERMEP (France)
2015-05-18
Brain mapping of task-associated changes in metabolism with PET has been accomplished by subtracting scans acquired during two distinct static states. We have demonstrated that PET can provide truly dynamic information on cerebral energy metabolism using constant infusion of FDG and multiple stimuli in a single experiment. We demonstrate here that the functional PET (fPET-FDG) method accomplished simultaneously with fMRI, can enable the first direct comparisons in time, space and magnitude of hemodynamics and oxygen and glucose consumption. The imaging studies were performed on a 3T Tim-Trio MR scanner modified to support an MR-compatible BrainPET insert. Ten healthy subjects were included. The total PET acquisition and infusion time was 90 minutes. We did 3 blocks of right hand fingers tapping for 10 minutes at 30, 50 and 70 minutes after the beginning of the PET acquisition. ASL and BOLD imaging were acquired simultaneously during the motor paradigm. Changes in glucose utilization are easily observed as changes in the TAC slope of the PET data (FDG utilization rate) and in the derivative signal during motor stimuli in the activated voxels. PET and MRI (ASL, and BOLD) activations are largely colocalized but with very different statistical significance and temporal dynamic, especially in the ipsilateral side of the stimuli. This study demonstrated that motor activation can be measured dynamically during a single FDG PET scan. The complementary nature of fPET-FDG to fMRI capitalizes on the emerging technology of hybrid MR-PET scanners. fPET-FDG, combined with quantitative fMRI methods, allow us to simultaneously measure dynamic changes in glucose utilization and hemodynamic, addressing vital questions about neurovascular coupling.
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Simultaneous functional imaging using fPET and fMRI
International Nuclear Information System (INIS)
Villien, Marjorie
2015-01-01
Brain mapping of task-associated changes in metabolism with PET has been accomplished by subtracting scans acquired during two distinct static states. We have demonstrated that PET can provide truly dynamic information on cerebral energy metabolism using constant infusion of FDG and multiple stimuli in a single experiment. We demonstrate here that the functional PET (fPET-FDG) method accomplished simultaneously with fMRI, can enable the first direct comparisons in time, space and magnitude of hemodynamics and oxygen and glucose consumption. The imaging studies were performed on a 3T Tim-Trio MR scanner modified to support an MR-compatible BrainPET insert. Ten healthy subjects were included. The total PET acquisition and infusion time was 90 minutes. We did 3 blocks of right hand fingers tapping for 10 minutes at 30, 50 and 70 minutes after the beginning of the PET acquisition. ASL and BOLD imaging were acquired simultaneously during the motor paradigm. Changes in glucose utilization are easily observed as changes in the TAC slope of the PET data (FDG utilization rate) and in the derivative signal during motor stimuli in the activated voxels. PET and MRI (ASL, and BOLD) activations are largely colocalized but with very different statistical significance and temporal dynamic, especially in the ipsilateral side of the stimuli. This study demonstrated that motor activation can be measured dynamically during a single FDG PET scan. The complementary nature of fPET-FDG to fMRI capitalizes on the emerging technology of hybrid MR-PET scanners. fPET-FDG, combined with quantitative fMRI methods, allow us to simultaneously measure dynamic changes in glucose utilization and hemodynamic, addressing vital questions about neurovascular coupling.
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Hantke, Nathan; Nielson, Kristy A; Woodard, John L; Breting, Leslie M Guidotti; Butts, Alissa; Seidenberg, Michael; Carson Smith, J; Durgerian, Sally; Lancaster, Melissa; Matthews, Monica; Sugarman, Michael A; Rao, Stephen M
2013-01-01
Previous studies suggest that task-activated functional magnetic resonance imaging (fMRI) can predict future cognitive decline among healthy older adults. The present fMRI study examined the relative sensitivity of semantic memory (SM) versus episodic memory (EM) activation tasks for predicting cognitive decline. Seventy-eight cognitively intact elders underwent neuropsychological testing at entry and after an 18-month interval, with participants classified as cognitively "Stable" or "Declining" based on ≥ 1.0 SD decline in performance. Baseline fMRI scanning involved SM (famous name discrimination) and EM (name recognition) tasks. SM and EM fMRI activation, along with Apolipoprotein E (APOE) ε4 status, served as predictors of cognitive outcome using a logistic regression analysis. Twenty-seven (34.6%) participants were classified as Declining and 51 (65.4%) as Stable. APOE ε4 status alone significantly predicted cognitive decline (R(2) = .106; C index = .642). Addition of SM activation significantly improved prediction accuracy (R(2) = .285; C index = .787), whereas the addition of EM did not (R(2) = .212; C index = .711). In combination with APOE status, SM task activation predicts future cognitive decline better than EM activation. These results have implications for use of fMRI in prevention clinical trials involving the identification of persons at-risk for age-associated memory loss and Alzheimer's disease.
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Current stage of fMRI applications in newborns and children during the first year of life
International Nuclear Information System (INIS)
Boecker, H.; Scheef, L.; Jankowski, J.; Zimmermann, N.; Born, M.; Heep, A.
2008-01-01
Currently, a paradigm shift towards expanded early use of cranial MRI in newborns at risk and infants in the first year of life can be observed in neonatology. Beyond clinical MRI applications, there is progressive use of functional MRI (fMRI) in this age group. On the one hand, fMRI allows monitoring of functional developmental processes depending on maturational stage; on the other hand, this technique may provide the basis for early detection of pathophysiological processes as a prerequisite for functionally guided therapeutic interventions. This article provides a comprehensive review of current fMRI applications in neonates and infants during the first year of life and focuses on the associated methodological issues (e.g. signal physiology, sedation, safety aspects). (orig.)
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SCGICAR: Spatial concatenation based group ICA with reference for fMRI data analysis.
Shi, Yuhu; Zeng, Weiming; Wang, Nizhuan
2017-09-01
With the rapid development of big data, the functional magnetic resonance imaging (fMRI) data analysis of multi-subject is becoming more and more important. As a kind of blind source separation technique, group independent component analysis (GICA) has been widely applied for the multi-subject fMRI data analysis. However, spatial concatenated GICA is rarely used compared with temporal concatenated GICA due to its disadvantages. In this paper, in order to overcome these issues and to consider that the ability of GICA for fMRI data analysis can be improved by adding a priori information, we propose a novel spatial concatenation based GICA with reference (SCGICAR) method to take advantage of the priori information extracted from the group subjects, and then the multi-objective optimization strategy is used to implement this method. Finally, the post-processing means of principal component analysis and anti-reconstruction are used to obtain group spatial component and individual temporal component in the group, respectively. The experimental results show that the proposed SCGICAR method has a better performance on both single-subject and multi-subject fMRI data analysis compared with classical methods. It not only can detect more accurate spatial and temporal component for each subject of the group, but also can obtain a better group component on both temporal and spatial domains. These results demonstrate that the proposed SCGICAR method has its own advantages in comparison with classical methods, and it can better reflect the commonness of subjects in the group. Copyright © 2017 Elsevier B.V. All rights reserved.
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SSC lattice database and graphical interface
International Nuclear Information System (INIS)
Trahern, C.G.; Zhou, J.
1991-11-01
When completed the Superconducting Super Collider will be the world's largest accelerator complex. In order to build this system on schedule, the use of database technologies will be essential. In this paper we discuss one of the database efforts underway at the SSC, the lattice database. The SSC lattice database provides a centralized source for the design of each major component of the accelerator complex. This includes the two collider rings, the High Energy Booster, Medium Energy Booster, Low Energy Booster, and the LINAC as well as transfer and test beam lines. These designs have been created using a menagerie of programs such as SYNCH, DIMAD, MAD, TRANSPORT, MAGIC, TRACE3D AND TEAPOT. However, once a design has been completed, it is entered into a uniform database schema in the database system. In this paper we discuss the reasons for creating the lattice database and its implementation via the commercial database system SYBASE. Each lattice in the lattice database is composed of a set of tables whose data structure can describe any of the SSC accelerator lattices. In order to allow the user community access to the databases, a programmatic interface known as dbsf (for database to several formats) has been written. Dbsf creates ascii input files appropriate to the above mentioned accelerator design programs. In addition it has a binary dataset output using the Self Describing Standard data discipline provided with the Integrated Scientific Tool Kit software tools. Finally we discuss the graphical interfaces to the lattice database. The primary interface, known as OZ, is a simulation environment as well as a database browser
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International Nuclear Information System (INIS)
Spreer, J.; Arnold, S.; Ziyeh, S.; Klisch, J.; Schumacher, M.; Quiske, A.; Altenmueller, D.; Schulze-Bonhage, A.; Wohlfarth, R.; Steinhoff, B.J.; Herpers, M.; Kassubek, J.; Honegger, J.
2002-01-01
The reliability of frontal and temporal fMRI activations for the determination of hemisphere language dominance was evaluated in comparison with intracarotid amytal testing (IAT). Twenty-two patients were studied by IAT (bilateral in 13, unilateral in 9 patients) and fMRI using a paradigm requiring semantic decisions. Global and regional (frontal and temporoparietal) lateralisation indices (LI) were calculated from the number of activated (r>0.4) voxels in both hemispheres. Frontolateral activations associated with the language task were seen in all patients, temporoparietal activations in 20 of 22. Regional LI corresponded better with IAT results than global LI. Frontolateral LI were consistent with IAT in all patients with bilateral IAT (including three patients with right dominant and one patient with bilateral language representation) and were not conflicting in any of the patients with unilateral IAT. Temporoparietal LI were discordant with IAT in two patients with atypical language representation. In the determination of hemisphere dominance for language, regional analysis of fMRI activation is superior to global analysis. In cases with clear-cut fMRI lateralisation, i.e. consistent lateralised activation of frontal and temporoparietal language zones, IAT may be unnecessary. FMRI should be performed prior to IAT in all patients going to be operated in brain regions potentially involved in language. (orig.)
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Cue-Elicited Craving in Heroin Addicts at Different Abstinent Time: An fMRI Pilot Study
Lou, Mingwu; Wang, Erlei; Shen, Yunxia; Wang, Jiping
2012-01-01
Objective: We evaluated the effect of short-term and long-term heroin abstinence on brain responses to heroin-related cues using functional magnetic resonance imaging (fMRI). Methods: Eighteen male heroin addicts following short-term abstinence and 19 male heroin addicts following long-term abstinence underwent fMRI scanning while viewing heroin-related and neutral images. Cue-elicited craving and withdrawal symptoms in the subjects were measured. Results: Following short-term abstinence, gre...
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Applying artificial intelligence to astronomical databases - a surveyof applicable technology.
Rosenthal, D. A.
This paper surveys several emerging technologies which are relevant to astronomical database issues such as interface technology, internal database representation, and intelligent data reduction aids. Among the technologies discussed are natural language understanding, frame and object representations, planning, pattern analysis, machine learning and the nascent study of simulated neural nets. These techniques will become increasingly important for astronomical research, and in particular, for applications with large databases.
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Modeling Powered Aerodynamics for the Orion Launch Abort Vehicle Aerodynamic Database
Chan, David T.; Walker, Eric L.; Robinson, Philip E.; Wilson, Thomas M.
2011-01-01
Modeling the aerodynamics of the Orion Launch Abort Vehicle (LAV) has presented many technical challenges to the developers of the Orion aerodynamic database. During a launch abort event, the aerodynamic environment around the LAV is very complex as multiple solid rocket plumes interact with each other and the vehicle. It is further complicated by vehicle separation events such as between the LAV and the launch vehicle stack or between the launch abort tower and the crew module. The aerodynamic database for the LAV was developed mainly from wind tunnel tests involving powered jet simulations of the rocket exhaust plumes, supported by computational fluid dynamic simulations. However, limitations in both methods have made it difficult to properly capture the aerodynamics of the LAV in experimental and numerical simulations. These limitations have also influenced decisions regarding the modeling and structure of the aerodynamic database for the LAV and led to compromises and creative solutions. Two database modeling approaches are presented in this paper (incremental aerodynamics and total aerodynamics), with examples showing strengths and weaknesses of each approach. In addition, the unique problems presented to the database developers by the large data space required for modeling a launch abort event illustrate the complexities of working with multi-dimensional data.
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Applying independent component analysis to clinical fMRI at 7 T
Directory of Open Access Journals (Sweden)
Simon Daniel Robinson
2013-09-01
Full Text Available Increased BOLD sensitivity at 7 T offers the possibility to increase the reliability of fMRI, but ultra-high field is also associated with an increase in artifacts related to head motion, Nyquist ghosting and parallel imaging reconstruction errors. In this study, the ability of Independent Component Analysis (ICA to separate activation from these artifacts was assessed in a 7 T study of neurological patients performing chin and hand motor tasks. ICA was able to isolate primary motor activation with negligible contamination by motion effects. The results of General Linear Model (GLM analysis of these data were, in contrast, heavily contaminated by motion. Secondary motor areas, basal ganglia and thalamus involvement were apparent in ICA results, but there was low capability to isolate activation in the same brain regions in the GLM analysis, indicating that ICA was more sensitive as well as more specific. A method was developed to simplify the assessment of the large number of independent components. Task-related activation components could be automatically identified via intuitive and effective features. These findings demonstrate that ICA is a practical and sensitive analysis approach in high field fMRI studies, particularly where motion is evoked. Promising applications of ICA in clinical fMRI include presurgical planning and the study of pathologies affecting subcortical brain areas.
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Hayes, Scott M.; Hayes, Jasmeet P.; Williams, Victoria J.; Liu, Huiting; Verfaellie, Mieke
2017-01-01
Older adults (OA), relative to young adults (YA), exhibit age-related alterations in functional Magnetic Resonance Imaging (fMRI) activity during associative encoding, which contributes to deficits in source memory. Yet, there are remarkable individual differences in brain health and memory performance among OA. Cardiorespiratory fitness (CRF) is one individual difference factor that may attenuate brain aging, and thereby contribute to enhanced source memory in OA. To examine this possibility, 26 OA and 31 YA completed a treadmill-based exercise test to evaluate CRF (peak VO2) and fMRI to examine brain activation during a face-name associative encoding task. Our results indicated that in OA, peak VO2 was positively associated with fMRI activity during associative encoding in multiple regions including bilateral prefrontal cortex, medial frontal cortex, bilateral thalamus and left hippocampus. Next, a conjunction analysis was conducted to assess whether CRF influenced age-related differences in fMRI activation. We classified OA as high or low CRF and compared their activation to YA. High fit OA (HFOA) showed fMRI activation more similar to YA than low fit OA (LFOA) (i.e., reduced age-related differences) in multiple regions including thalamus, posterior and prefrontal cortex. Conversely, in other regions, primarily in prefrontal cortex, HFOA, but not LFOA, demonstrated greater activation than YA (i.e., increased age-related differences). Further, fMRI activity in these brain regions was positively associated with source memory among OA, with a mediation model demonstrating that associative encoding activation in medial frontal cortex indirectly influenced the relationship between peak VO2 and subsequent source memory performance. These results indicate that CRF may contribute to neuroplasticity among OA, reducing age-related differences in some brain regions, consistent with the brain maintenance hypothesis, but accentuating age-differences in other regions
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Low-dimensional morphospace of topological motifs in human fMRI brain networks
Directory of Open Access Journals (Sweden)
Sarah E. Morgan
2018-06-01
Full Text Available We present a low-dimensional morphospace of fMRI brain networks, where axes are defined in a data-driven manner based on the network motifs. The morphospace allows us to identify the key variations in healthy fMRI networks in terms of their underlying motifs, and we observe that two principal components (PCs can account for 97% of the motif variability. The first PC of the motif distribution is correlated with efficiency and inversely correlated with transitivity. Hence this axis approximately conforms to the well-known economical small-world trade-off between integration and segregation in brain networks. Finally, we show that the economical clustering generative model proposed by Vértes et al. (2012 can approximately reproduce the motif morphospace of the real fMRI brain networks, in contrast to other generative models. Overall, the motif morphospace provides a powerful way to visualize the relationships between network properties and to investigate generative or constraining factors in the formation of complex human brain functional networks. Motifs have been described as the building blocks of complex networks. Meanwhile, a morphospace allows networks to be placed in a common space and can reveal the relationships between different network properties and elucidate the driving forces behind network topology. We combine the concepts of motifs and morphospaces to create the first motif morphospace of fMRI brain networks. Crucially, the morphospace axes are defined by the motifs, in a data-driven manner. We observe strong correlations between the networks’ positions in morphospace and their global topological properties, suggesting that motif morphospaces are a powerful way to capture the topology of networks in a low-dimensional space and to compare generative models of brain networks. Motif morphospaces could also be used to study other complex networks’ topologies.
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Directory of Open Access Journals (Sweden)
Klaudius eKalcher
2015-12-01
Full Text Available Identifying venous voxels in fMRI datasets is important to increase the specificity of fMRI analyses to microvasculature in the vicinity of the neural processes triggering the BOLD response. This is, however, difficult to achieve in particular in typical studies where magnitude images of BOLD EPI are the only data available. In this study, voxelwise functional connectivity graphs were computed on minimally preprocessed low TR (333 ms multiband resting-state fMRI data, using both high positive and negative correlations to define edges between nodes (voxels. A high correlation threshold for binarization ensures that most edges in the resulting sparse graph reflect the high coherence of signals in medium to large veins. Graph clustering based on the optimization of modularity was then employed to identify clusters of coherent voxels in this graph, and all clusters of 50 or more voxels were then interpreted as corresponding to medium to large veins. Indeed, a comparison with SWI reveals that 75.6 ± 5.9% of voxels within these large clusters overlap with veins visible in the SWI image or lie outside the brain parenchyma. Some of the remainingdifferences between the two modalities can be explained by imperfect alignment or geometric distortions between the two images. Overall, the graph clustering based method for identifying venous voxels has a high specificity as well as the additional advantages of being computed in the same voxel grid as the fMRI dataset itself and not needingany additional data beyond what is usually acquired (and exported in standard fMRI experiments.
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Wu, Ruiqi; Yang, Pai-Feng; Chen, Li Min
2017-11-15
This study aims to understand how functional connectivity (FC) between areas 3b and S2 alters following input deprivation and the neuronal basis of disrupted FC of resting-state fMRI signals. We combined submillimeter fMRI with microelectrode recordings to localize the deafferented digit regions in areas 3b and S2 by mapping tactile stimulus-evoked fMRI activations before and after cervical dorsal column lesion in each male monkey. An average afferent disruption of 97% significantly reduced fMRI, local field potential (LFP), and spike responses to stimuli in both areas. Analysis of resting-state fMRI signal correlation, LFP coherence, and spike cross-correlation revealed significantly reduced functional connectivity between deafferented areas 3b and S2. The degrees of reductions in stimulus responsiveness and FC after deafferentation differed across fMRI, LFP, and spiking signals. The reduction of FC was much weaker than that of stimulus-evoked responses. Whereas the largest stimulus-evoked signal drop (∼80%) was observed in LFP signals, the greatest FC reduction was detected in the spiking activity (∼30%). fMRI signals showed mild reductions in stimulus responsiveness (∼25%) and FC (∼20%). The overall deafferentation-induced changes were quite similar in areas 3b and S2 across signals. Here we demonstrated that FC strength between areas 3b and S2 was much weakened by dorsal column lesion, and stimulus response reduction and FC disruption in fMRI covary with those of LFP and spiking signals in deafferented areas 3b and S2. These findings have important implications for fMRI studies aiming to probe FC alterations in pathological conditions involving deafferentation in humans. SIGNIFICANCE STATEMENT By directly comparing fMRI, local field potential, and spike signals in both tactile stimulation and resting states before and after severe disruption of dorsal column afferent, we demonstrated that reduction in fMRI responses to stimuli is accompanied by weakened
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Brain correlates of aesthetic expertise: A parametric fMRI study
DEFF Research Database (Denmark)
Kirk, Ulrich; Skov, Martin; Christensen, Mark Schram
2009-01-01
Several studies have demonstrated that acquired expertise influences aesthetic judgments. In this paradigm we used functional magnetic resonance imaging (fMRI) to study aesthetic judgments of visually presented architectural stimuli and control-stimuli (faces) for a group of architects and a grou...
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Bayesian Modelling of fMRI Time Series
DEFF Research Database (Denmark)
Højen-Sørensen, Pedro; Hansen, Lars Kai; Rasmussen, Carl Edward
2000-01-01
We present a Hidden Markov Model (HMM) for inferring the hidden psychological state (or neural activity) during single trial fMRI activation experiments with blocked task paradigms. Inference is based on Bayesian methodology, using a combination of analytical and a variety of Markov Chain Monte...... Carlo (MCMC) sampling techniques. The advantage of this method is that detection of short time learning effects between repeated trials is possible since inference is based only on single trial experiments....
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Hemodynamic modelling of BOLD fMRI - A machine learning approach
DEFF Research Database (Denmark)
Jacobsen, Danjal Jakup
2007-01-01
This Ph.D. thesis concerns the application of machine learning methods to hemodynamic models for BOLD fMRI data. Several such models have been proposed by different researchers, and they have in common a basis in physiological knowledge of the hemodynamic processes involved in the generation...... of the BOLD signal. The BOLD signal is modelled as a non-linear function of underlying, hidden (non-measurable) hemodynamic state variables. The focus of this thesis work has been to develop methods for learning the parameters of such models, both in their traditional formulation, and in a state space...... formulation. In the latter, noise enters at the level of the hidden states, as well as in the BOLD measurements themselves. A framework has been developed to allow approximate posterior distributions of model parameters to be learned from real fMRI data. This is accomplished with Markov chain Monte Carlo...
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Bansal, Ravi; Peterson, Bradley S
2018-06-01
Identifying regional effects of interest in MRI datasets usually entails testing a priori hypotheses across many thousands of brain voxels, requiring control for false positive findings in these multiple hypotheses testing. Recent studies have suggested that parametric statistical methods may have incorrectly modeled functional MRI data, thereby leading to higher false positive rates than their nominal rates. Nonparametric methods for statistical inference when conducting multiple statistical tests, in contrast, are thought to produce false positives at the nominal rate, which has thus led to the suggestion that previously reported studies should reanalyze their fMRI data using nonparametric tools. To understand better why parametric methods may yield excessive false positives, we assessed their performance when applied both to simulated datasets of 1D, 2D, and 3D Gaussian Random Fields (GRFs) and to 710 real-world, resting-state fMRI datasets. We showed that both the simulated 2D and 3D GRFs and the real-world data contain a small percentage (<6%) of very large clusters (on average 60 times larger than the average cluster size), which were not present in 1D GRFs. These unexpectedly large clusters were deemed statistically significant using parametric methods, leading to empirical familywise error rates (FWERs) as high as 65%: the high empirical FWERs were not a consequence of parametric methods failing to model spatial smoothness accurately, but rather of these very large clusters that are inherently present in smooth, high-dimensional random fields. In fact, when discounting these very large clusters, the empirical FWER for parametric methods was 3.24%. Furthermore, even an empirical FWER of 65% would yield on average less than one of those very large clusters in each brain-wide analysis. Nonparametric methods, in contrast, estimated distributions from those large clusters, and therefore, by construct rejected the large clusters as false positives at the nominal
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Brain fMRI study of crave induced by cue pictures in online game addicts (male adolescents).
Sun, Yueji; Ying, Huang; Seetohul, Ravi M; Xuemei, Wang; Ya, Zheng; Qian, Li; Guoqing, Xu; Ye, Sun
2012-08-01
To study crave-related cerebral regions induced by game figure cues in online game addicts. fMRI brain imaging was done when the subjects were shown picture cues of the WoW (World of Warcraft, Version: 4.1.014250) game. 10 male addicts of WoW were selected as addicts' group, and 10 other healthy male non-addicts who were matched by age, were used as non-game addicts' group. All volunteers participated in fMRI paradigms. WoW associated cue pictures and neutral pictures were shown. We examined functional cerebral regions activated by the pictures with 3.0 T Philips MRI. The imaging signals' database was analyzed by SPM5. The correlation between game craving scores and different image results were assessed. When the game addicts watch the pictures, some brain areas show increased signal activity namely: dorsolateral prefrontal cortex, bilateral temporal cortex, cerebellum, right inferior parietal lobule, right cuneus, right hippocampus, parahippocampal gyrus, left caudate nucleus. But in these same brain regions we did not observe remarkable activities in the control group. Differential image signal densities of the addict group were subtracted from the health control group, results of which were expressed in the bilateral dorsolateral prefrontal cortex, anterior cingulate cortex, inferior parietal lobe and inferior temporal gyrus, cerebellum, right insular and the right angular gyrus. The increased imaging signal densities were significant and positively correlated with the craving scale scores in the bilateral prefrontal cortex, anterior cingulate cortex and right inferior parietal lobe. Craving of online game addicts was successfully induced by game cue pictures. Crave related brain areas are: dorsolateral prefrontal cortex, anterior cingulate cortex, and right inferior parietal lobe. The brain regions are overlapped with cognitive and emotion related processing brain areas. Copyright © 2012 Elsevier B.V. All rights reserved.
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Brain Activity Unique to Orgasm in Women: An fMRI Analysis.
Wise, Nan J; Frangos, Eleni; Komisaruk, Barry R
2017-11-01
Although the literature on imaging of regional brain activity during sexual arousal in women and men is extensive and largely consistent, that on orgasm is relatively limited and variable, owing in part to the methodologic challenges posed by variability in latency to orgasm in participants and head movement. To compare brain activity at orgasm (self- and partner-induced) with that at the onset of genital stimulation, immediately before the onset of orgasm, and immediately after the cessation of orgasm and to upgrade the methodology for obtaining and analyzing functional magnetic resonance imaging (fMRI) findings. Using fMRI, we sampled equivalent time points across female participants' variable durations of stimulation and orgasm in response to self- and partner-induced clitoral stimulation. The first 20-second epoch of orgasm was contrasted with the 20-second epochs at the beginning of stimulation and immediately before and after orgasm. Separate analyses were conducted for whole-brain and brainstem regions of interest. For a finer-grained analysis of the peri-orgasm phase, we conducted a time-course analysis on regions of interest. Head movement was minimized to a mean less than 1.3 mm using a custom-fitted thermoplastic whole-head and neck brace stabilizer. Ten women experienced orgasm elicited by self- and partner-induced genital stimulation in a Siemens 3-T Trio fMRI scanner. Brain activity gradually increased leading up to orgasm, peaked at orgasm, and then decreased. We found no evidence of deactivation of brain regions leading up to or during orgasm. The activated brain regions included sensory, motor, reward, frontal cortical, and brainstem regions (eg, nucleus accumbens, insula, anterior cingulate cortex, orbitofrontal cortex, operculum, right angular gyrus, paracentral lobule, cerebellum, hippocampus, amygdala, hypothalamus, ventral tegmental area, and dorsal raphe). Insight gained from the present findings could provide guidance toward a rational basis
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Comparison of fMRI paradigms assessing visuospatial processing: Robustness and reproducibility.
Directory of Open Access Journals (Sweden)
Verena Schuster
Full Text Available The development of brain imaging techniques, in particular functional magnetic resonance imaging (fMRI, made it possible to non-invasively study the hemispheric lateralization of cognitive brain functions in large cohorts. Comprehensive models of hemispheric lateralization are, however, still missing and should not only account for the hemispheric specialization of individual brain functions, but also for the interactions among different lateralized cognitive processes (e.g., language and visuospatial processing. This calls for robust and reliable paradigms to study hemispheric lateralization for various cognitive functions. While numerous reliable imaging paradigms have been developed for language, which represents the most prominent left-lateralized brain function, the reliability of imaging paradigms investigating typically right-lateralized brain functions, such as visuospatial processing, has received comparatively less attention. In the present study, we aimed to establish an fMRI paradigm that robustly and reliably identifies right-hemispheric activation evoked by visuospatial processing in individual subjects. In a first study, we therefore compared three frequently used paradigms for assessing visuospatial processing and evaluated their utility to robustly detect right-lateralized brain activity on a single-subject level. In a second study, we then assessed the test-retest reliability of the so-called Landmark task-the paradigm that yielded the most robust results in study 1. At the single-voxel level, we found poor reliability of the brain activation underlying visuospatial attention. This suggests that poor signal-to-noise ratios can become a limiting factor for test-retest reliability. This represents a common detriment of fMRI paradigms investigating visuospatial attention in general and therefore highlights the need for careful considerations of both the possibilities and limitations of the respective fMRI paradigm-in particular
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Database for radiation therapy images
International Nuclear Information System (INIS)
Shalev, S.; Cosby, S.; Leszczynski, K.; Chu, T.
1989-01-01
The authors have developed a database for images acquired during simulation and verification of radiation treatments. Simulation images originate as planning films that are digitized with a video camera, or through direct digitization of fluoroscopic images. Verification images may also be digitized from portal films or acquired with an on-line portal imaging system. Images are classified by the patient, the fraction, the field direction, static or dynamic (movie) sequences, and the type of processing applied. Additional parameters indicate whether the source is a simulation or treatment, whether images are digitized film or real-time acquisitions, and whether treatment is portal or double exposure for beam localization. Examples are presented for images acquired, processed, stored, and displayed with on-line portal imaging system (OPIUM) and digital simulation system (FLIP)
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Database Description - Trypanosomes Database | LSDB Archive [Life Science Database Archive metadata
Lifescience Database Archive (English)
Full Text Available List Contact us Trypanosomes Database Database Description General information of database Database name Trypanosomes Database...stitute of Genetics Research Organization of Information and Systems Yata 1111, Mishima, Shizuoka 411-8540, JAPAN E mail: Database...y Name: Trypanosoma Taxonomy ID: 5690 Taxonomy Name: Homo sapiens Taxonomy ID: 9606 Database description The... Article title: Author name(s): Journal: External Links: Original website information Database maintenance s...DB (Protein Data Bank) KEGG PATHWAY Database DrugPort Entry list Available Query search Available Web servic
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Gravel, Nicolás G; Harvey, Ben M; Renken, Remco K; Dumoulin, Serge O; Cornelissen, Frans W
2018-01-01
Resting-state fMRI is widely used to study brain function and connectivity. However, interpreting patterns of resting state (RS) fMRI activity remains challenging as they may arise from different neuronal mechanisms than those triggered by exogenous events. Currently, this limits the use of RS-fMRI
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Multilingualism and fMRI: Longitudinal Study of Second Language Acquisition
Andrews, Edna; Frigau, Luca; Voyvodic-Casabo, Clara; Voyvodic, James; Wright, John
2013-01-01
BOLD fMRI is often used for the study of human language. However, there are still very few attempts to conduct longitudinal fMRI studies in the study of language acquisition by measuring auditory comprehension and reading. The following paper is the first in a series concerning a unique longitudinal study devoted to the analysis of bi- and multilingual subjects who are: (1) already proficient in at least two languages; or (2) are acquiring Russian as a second/third language. The focus of the current analysis is to present data from the auditory sections of a set of three scans acquired from April, 2011 through April, 2012 on a five-person subject pool who are learning Russian during the study. All subjects were scanned using the same protocol for auditory comprehension on the same General Electric LX 3T Signa scanner in Duke University Hospital. Using a multivariate analysis of covariance (MANCOVA) for statistical analysis, proficiency measurements are shown to correlate significantly with scan results in the Russian conditions over time. The importance of both the left and right hemispheres in language processing is discussed. Special attention is devoted to the importance of contextualizing imaging data with corresponding behavioral and empirical testing data using a multivariate analysis of variance. This is the only study to date that includes: (1) longitudinal fMRI data with subject-based proficiency and behavioral data acquired in the same time frame; and (2) statistical modeling that demonstrates the importance of covariate language proficiency data for understanding imaging results of language acquisition. PMID:24961428
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Support vector machine learning-based fMRI data group analysis.
Wang, Ze; Childress, Anna R; Wang, Jiongjiong; Detre, John A
2007-07-15
To explore the multivariate nature of fMRI data and to consider the inter-subject brain response discrepancies, a multivariate and brain response model-free method is fundamentally required. Two such methods are presented in this paper by integrating a machine learning algorithm, the support vector machine (SVM), and the random effect model. Without any brain response modeling, SVM was used to extract a whole brain spatial discriminance map (SDM), representing the brain response difference between the contrasted experimental conditions. Population inference was then obtained through the random effect analysis (RFX) or permutation testing (PMU) on the individual subjects' SDMs. Applied to arterial spin labeling (ASL) perfusion fMRI data, SDM RFX yielded lower false-positive rates in the null hypothesis test and higher detection sensitivity for synthetic activations with varying cluster size and activation strengths, compared to the univariate general linear model (GLM)-based RFX. For a sensory-motor ASL fMRI study, both SDM RFX and SDM PMU yielded similar activation patterns to GLM RFX and GLM PMU, respectively, but with higher t values and cluster extensions at the same significance level. Capitalizing on the absence of temporal noise correlation in ASL data, this study also incorporated PMU in the individual-level GLM and SVM analyses accompanied by group-level analysis through RFX or group-level PMU. Providing inferences on the probability of being activated or deactivated at each voxel, these individual-level PMU-based group analysis methods can be used to threshold the analysis results of GLM RFX, SDM RFX or SDM PMU.
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Multilingualism and fMRI: Longitudinal Study of Second Language Acquisition
Directory of Open Access Journals (Sweden)
John Wright
2013-05-01
Full Text Available BOLD fMRI is often used for the study of human language. However, there are still very few attempts to conduct longitudinal fMRI studies in the study of language acquisition by measuring auditory comprehension and reading. The following paper is the first in a series concerning a unique longitudinal study devoted to the analysis of bi- and multilingual subjects who are: (1 already proficient in at least two languages; or (2 are acquiring Russian as a second/third language. The focus of the current analysis is to present data from the auditory sections of a set of three scans acquired from April, 2011 through April, 2012 on a five-person subject pool who are learning Russian during the study. All subjects were scanned using the same protocol for auditory comprehension on the same General Electric LX 3T Signa scanner in Duke University Hospital. Using a multivariate analysis of covariance (MANCOVA for statistical analysis, proficiency measurements are shown to correlate significantly with scan results in the Russian conditions over time. The importance of both the left and right hemispheres in language processing is discussed. Special attention is devoted to the importance of contextualizing imaging data with corresponding behavioral and empirical testing data using a multivariate analysis of variance. This is the only study to date that includes: (1 longitudinal fMRI data with subject-based proficiency and behavioral data acquired in the same time frame; and (2 statistical modeling that demonstrates the importance of covariate language proficiency data for understanding imaging results of language acquisition.
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Functional brain segmentation using inter-subject correlation in fMRI.
Kauppi, Jukka-Pekka; Pajula, Juha; Niemi, Jari; Hari, Riitta; Tohka, Jussi
2017-05-01
The human brain continuously processes massive amounts of rich sensory information. To better understand such highly complex brain processes, modern neuroimaging studies are increasingly utilizing experimental setups that better mimic daily-life situations. A new exploratory data-analysis approach, functional segmentation inter-subject correlation analysis (FuSeISC), was proposed to facilitate the analysis of functional magnetic resonance (fMRI) data sets collected in these experiments. The method provides a new type of functional segmentation of brain areas, not only characterizing areas that display similar processing across subjects but also areas in which processing across subjects is highly variable. FuSeISC was tested using fMRI data sets collected during traditional block-design stimuli (37 subjects) as well as naturalistic auditory narratives (19 subjects). The method identified spatially local and/or bilaterally symmetric clusters in several cortical areas, many of which are known to be processing the types of stimuli used in the experiments. The method is not only useful for spatial exploration of large fMRI data sets obtained using naturalistic stimuli, but also has other potential applications, such as generation of a functional brain atlases including both lower- and higher-order processing areas. Finally, as a part of FuSeISC, a criterion-based sparsification of the shared nearest-neighbor graph was proposed for detecting clusters in noisy data. In the tests with synthetic data, this technique was superior to well-known clustering methods, such as Ward's method, affinity propagation, and K-means ++. Hum Brain Mapp 38:2643-2665, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
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Multilingualism and fMRI: Longitudinal Study of Second Language Acquisition.
Andrews, Edna; Frigau, Luca; Voyvodic-Casabo, Clara; Voyvodic, James; Wright, John
2013-05-28
BOLD fMRI is often used for the study of human language. However, there are still very few attempts to conduct longitudinal fMRI studies in the study of language acquisition by measuring auditory comprehension and reading. The following paper is the first in a series concerning a unique longitudinal study devoted to the analysis of bi- and multilingual subjects who are: (1) already proficient in at least two languages; or (2) are acquiring Russian as a second/third language. The focus of the current analysis is to present data from the auditory sections of a set of three scans acquired from April, 2011 through April, 2012 on a five-person subject pool who are learning Russian during the study. All subjects were scanned using the same protocol for auditory comprehension on the same General Electric LX 3T Signa scanner in Duke University Hospital. Using a multivariate analysis of covariance (MANCOVA) for statistical analysis, proficiency measurements are shown to correlate significantly with scan results in the Russian conditions over time. The importance of both the left and right hemispheres in language processing is discussed. Special attention is devoted to the importance of contextualizing imaging data with corresponding behavioral and empirical testing data using a multivariate analysis of variance. This is the only study to date that includes: (1) longitudinal fMRI data with subject-based proficiency and behavioral data acquired in the same time frame; and (2) statistical modeling that demonstrates the importance of covariate language proficiency data for understanding imaging results of language acquisition.
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Directory of Open Access Journals (Sweden)
Lucy Hannah Glasspool
2013-03-01
Full Text Available Japanese video games have been characterized as typifying contemporary postmodernity in the form of simulacra, both as a media form and in terms of their extensive localization for international markets, which creates user fantasies of Japaneseness that are not linked to an authentic or original Japan. These simulations are reappropriated by fans to create new content, in this case boys' love dōjinshi, which are in turn disseminated and consumed in an English-speaking online context. Fantasy role-playing video games, which often privilege heteronormativity and binary gender norms in their goals, narratives, and aesthetics, are among the most popular texts reimagined in this way. This study considers the concepts of simulation and database societies through an examination of the ways in which artificial contours of Japaneseness are constructed in the role-playing game series Final Fantasy VII's boys' love dōjinshi fandoms, how far these fan texts develop possibilities for the deconstruction of heteronormativity, and how transnational digitized consumption methods facilitate the intersection of these phenomena.
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Database mirroring in fault-tolerant continuous technological process control
Directory of Open Access Journals (Sweden)
R. Danel
2015-10-01
Full Text Available This paper describes the implementations of mirroring technology of the selected database systems – Microsoft SQL Server, MySQL and Caché. By simulating critical failures the systems behavior and their resilience against failure were tested. The aim was to determine whether the database mirroring is suitable to use in continuous metallurgical processes for ensuring the fault-tolerant solution at affordable cost. The present day database systems are characterized by high robustness and are resistant to sudden system failure. Database mirroring technologies are reliable and even low-budget projects can be provided with a decent fault-tolerant solution. The database system technologies available for low-budget projects are not suitable for use in real-time systems.
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FMRI connectivity analysis of acupuncture effects on an amygdala-associated brain network
Directory of Open Access Journals (Sweden)
Zhao Baixiao
2008-11-01
Full Text Available Abstract Background Recently, increasing evidence has indicated that the primary acupuncture effects are mediated by the central nervous system. However, specific brain networks underpinning these effects remain unclear. Results In the present study using fMRI, we employed a within-condition interregional covariance analysis method to investigate functional connectivity of brain networks involved in acupuncture. The fMRI experiment was performed before, during and after acupuncture manipulations on healthy volunteers at an acupuncture point, which was previously implicated in a neural pathway for pain modulation. We first identified significant fMRI signal changes during acupuncture stimulation in the left amygdala, which was subsequently selected as a functional reference for connectivity analyses. Our results have demonstrated that there is a brain network associated with the amygdala during a resting condition. This network encompasses the brain structures that are implicated in both pain sensation and pain modulation. We also found that such a pain-related network could be modulated by both verum acupuncture and sham acupuncture. Furthermore, compared with a sham acupuncture, the verum acupuncture induced a higher level of correlations among the amygdala-associated network. Conclusion Our findings indicate that acupuncture may change this amygdala-specific brain network into a functional state that underlies pain perception and pain modulation.
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Mapping of cognitive functions in chronic intractable epilepsy: Role of fMRI
International Nuclear Information System (INIS)
Chaudhary, Kapil; Kumaran, S Senthil; Chandra, Sarat P; Wadhawan, Ashima Nehra; Tripathi, Manjari
2014-01-01
Functional magnetic resonance imaging (fMRI), a non-invasive technique with high spatial resolution and blood oxygen level dependent (BOLD) contrast, has been applied to localize and map cognitive functions in the clinical condition of chronic intractable epilepsy. fMRI was used to map the language and memory network in patients of chronic intractable epilepsy pre- and post-surgery. After obtaining approval from the institutional ethics committee, six patients with intractable epilepsy with an equal number of age-matched controls were recruited in the study. A 1.5 T MR scanner with 12-channel head coil, integrated with audio-visual fMRI accessories was used. Echo planar imaging sequence was used for BOLD studies. There were two sessions in TLE (pre- and post-surgery). In TLE patients, BOLD activation increased post-surgery in comparison of pre-surgery in inferior frontal gyrus (IFG), middle frontal gyrus (MFG), and superior temporal gyrus (STG), during semantic lexical, judgment, comprehension, and semantic memory tasks. Functional MRI is useful to study the basic concepts related to language and memory lateralization in TLE and guide surgeons for preservation of important brain areas during ATLR. This will help in understanding future directions for the diagnosis and treatment of such disease
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Mapping of cognitive functions in chronic intractable epilepsy: Role of fMRI
Directory of Open Access Journals (Sweden)
Kapil Chaudhary
2014-01-01
Full Text Available Background: Functional magnetic resonance imaging (fMRI, a non-invasive technique with high spatial resolution and blood oxygen level dependent (BOLD contrast, has been applied to localize and map cognitive functions in the clinical condition of chronic intractable epilepsy. Purpose: fMRI was used to map the language and memory network in patients of chronic intractable epilepsy pre- and post-surgery. Materials and Methods: After obtaining approval from the institutional ethics committee, six patients with intractable epilepsy with an equal number of age-matched controls were recruited in the study. A 1.5 T MR scanner with 12-channel head coil, integrated with audio-visual fMRI accessories was used. Echo planar imaging sequence was used for BOLD studies. There were two sessions in TLE (pre- and post-surgery. Results: In TLE patients, BOLD activation increased post-surgery in comparison of pre-surgery in inferior frontal gyrus (IFG, middle frontal gyrus (MFG, and superior temporal gyrus (STG, during semantic lexical, judgment, comprehension, and semantic memory tasks. Conclusion: Functional MRI is useful to study the basic concepts related to language and memory lateralization in TLE and guide surgeons for preservation of important brain areas during ATLR. This will help in understanding future directions for the diagnosis and treatment of such disease.
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Single-trial EEG-informed fMRI analysis of emotional decision problems in hot executive function.
Guo, Qian; Zhou, Tiantong; Li, Wenjie; Dong, Li; Wang, Suhong; Zou, Ling
2017-07-01
Executive function refers to conscious control in psychological process which relates to thinking and action. Emotional decision is a part of hot executive function and contains emotion and logic elements. As a kind of important social adaptation ability, more and more attention has been paid in recent years. Gambling task can be well performed in the study of emotional decision. As fMRI researches focused on gambling task show not completely consistent brain activation regions, this study adopted EEG-fMRI fusion technology to reveal brain neural activity related with feedback stimuli. In this study, an EEG-informed fMRI analysis was applied to process simultaneous EEG-fMRI data. First, relative power-spectrum analysis and K-means clustering method were performed separately to extract EEG-fMRI features. Then, Generalized linear models were structured using fMRI data and using different EEG features as regressors. The results showed that in the win versus loss stimuli, the activated regions almost covered the caudate, the ventral striatum (VS), the orbital frontal cortex (OFC), and the cingulate. Wide activation areas associated with reward and punishment were revealed by the EEG-fMRI integration analysis than the conventional fMRI results, such as the posterior cingulate and the OFC. The VS and the medial prefrontal cortex (mPFC) were found when EEG power features were performed as regressors of GLM compared with results entering the amplitudes of feedback-related negativity (FRN) as regressors. Furthermore, the brain region activation intensity was the strongest when theta-band power was used as a regressor compared with the other two fusion results. The EEG-based fMRI analysis can more accurately depict the whole-brain activation map and analyze emotional decision problems.
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Directory of Open Access Journals (Sweden)
Simon Benjaminsson
2010-08-01
Full Text Available Non-parametric data-driven analysis techniques can be used to study datasets with few assumptions about the data and underlying experiment. Variations of Independent Component Analysis (ICA have been the methods mostly used on fMRI data, e.g. in finding resting-state networks thought to reflect the connectivity of the brain. Here we present a novel data analysis technique and demonstrate it on resting-state fMRI data. It is a generic method with few underlying assumptions about the data. The results are built from the statistical relations between all input voxels, resulting in a whole-brain analysis on a voxel level. It has good scalability properties and the parallel implementation is capable of handling large datasets and databases. From the mutual information between the activities of the voxels over time, a distance matrix is created for all voxels in the input space. Multidimensional scaling is used to put the voxels in a lower-dimensional space reflecting the dependency relations based on the distance matrix. By performing clustering in this space we can find the strong statistical regularities in the data, which for the resting-state data turns out to be the resting-state networks. The decomposition is performed in the last step of the algorithm and is computationally simple. This opens up for rapid analysis and visualization of the data on different spatial levels, as well as automatically finding a suitable number of decomposition components.
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Moerel, Michelle; De Martino, Federico; Kemper, Valentin G; Schmitter, Sebastian; Vu, An T; Uğurbil, Kâmil; Formisano, Elia; Yacoub, Essa
2018-01-01
Following rapid technological advances, ultra-high field functional MRI (fMRI) enables exploring correlates of neuronal population activity at an increasing spatial resolution. However, as the fMRI blood-oxygenation-level-dependent (BOLD) contrast is a vascular signal, the spatial specificity of fMRI data is ultimately determined by the characteristics of the underlying vasculature. At 7T, fMRI measurement parameters determine the relative contribution of the macro- and microvasculature to the acquired signal. Here we investigate how these parameters affect relevant high-end fMRI analyses such as encoding, decoding, and submillimeter mapping of voxel preferences in the human auditory cortex. Specifically, we compare a T 2 * weighted fMRI dataset, obtained with 2D gradient echo (GE) EPI, to a predominantly T 2 weighted dataset obtained with 3D GRASE. We first investigated the decoding accuracy based on two encoding models that represented different hypotheses about auditory cortical processing. This encoding/decoding analysis profited from the large spatial coverage and sensitivity of the T 2 * weighted acquisitions, as evidenced by a significantly higher prediction accuracy in the GE-EPI dataset compared to the 3D GRASE dataset for both encoding models. The main disadvantage of the T 2 * weighted GE-EPI dataset for encoding/decoding analyses was that the prediction accuracy exhibited cortical depth dependent vascular biases. However, we propose that the comparison of prediction accuracy across the different encoding models may be used as a post processing technique to salvage the spatial interpretability of the GE-EPI cortical depth-dependent prediction accuracy. Second, we explored the mapping of voxel preferences. Large-scale maps of frequency preference (i.e., tonotopy) were similar across datasets, yet the GE-EPI dataset was preferable due to its larger spatial coverage and sensitivity. However, submillimeter tonotopy maps revealed biases in assigned frequency
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Database Description - SKIP Stemcell Database | LSDB Archive [Life Science Database Archive metadata
Lifescience Database Archive (English)
Full Text Available List Contact us SKIP Stemcell Database Database Description General information of database Database name SKIP Stemcell Database...rsity Journal Search: Contact address http://www.skip.med.keio.ac.jp/en/contact/ Database classification Human Genes and Diseases Dat...abase classification Stemcell Article Organism Taxonomy Name: Homo sapiens Taxonomy ID: 9606 Database...ks: Original website information Database maintenance site Center for Medical Genetics, School of medicine, ...lable Web services Not available URL of Web services - Need for user registration Not available About This Database Database
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Target simulations with SCROLL non-LTE opacity/emissivity databases.
Klapisch, M.; Colombant, D.; Bar-Shalom, A.
2001-10-01
SCROLL[1], a collisional radiative model and code based on superconfigurations, is able to compute high Z non-LTE opacities and emissivities accurately and efficiently. It was used to create opacity/emissivity databases for Pd, Lu, Au on a 50 temperatures/80 densities grid. Incident radiation field was shown to have no effect on opacities in the case of interest, and was not taken into account. These databases were introduced in the hydrocode FAST1D[2]. SCROLL also gives an ionization temperature Tz which is used in FAST1D to obtain non-LTE corrections to the equation of state. Results will be compared to those of a previous version using Busquet’s algorithm[3]. Work supported by USDOE under a contract with NRL. [1] A. Bar-Shalom, J. Oreg and M. Klapisch, J. Quant. Spectrosc. Radiat. Transfer, 65, 43(2000). [2] J. H. Gardner, A. J. Schmitt, J. P. Dahlburg, C. J. Pawley, S. E. Bodner, S. P. Obenschain, V. Serlin and Y. Aglitskiy, Phys. Plasmas, 5, 1935 (1998). [3] M. Busquet, Phys. Fluids B, 5, 4191 (1993).
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[fMRI study of the dominant hemisphere for language in patients with brain tumor].
Buklina, S B; Podoprigora, A E; Pronin, I N; Shishkina, L V; Boldyreva, G N; Bondarenko, A A; Fadeeva, L M; Kornienko, V N; Zhukov, V Iu
2013-01-01
Paper describes a study of language lateralization of patients with brain tumors, measured by preoperative functional magnetic resonance imaging (fMRI) and comparison results with tumor histology and profile of functional asymmetry. During the study 21 patient underwent fMRI scan. 15 patients had a tumor in the left and 6 in the right hemisphere. Tumors were localized mainly in the frontal, temporal and fronto-temporal regions. Histological diagnosis in 8 cases was malignant Grade IV, in 13 cases--Grade I-III. fMRI study was perfomed on scanner "Signa Exite" with a field strength of 1.5 As speech test reciting the months of the year in reverse order was used. fMRI scan results were compared with the profile of functional asymmetry, which was received with the results of questionnaire Annette and dichotic listening test. Broca's area was found in 7 cases in the left hemisphere, 6 had a tumor Grade I-III. And one patient with glioblastoma had a tumor of the right hemisphere. Broca's area in the right hemisphere was found in 3 patients (2 patients with left sided tumor, and one with right-sided tumor). One patient with left-sided tumor had mild motor aphasia. Bilateral activation in both hemispheres of the brain was observed in 6 patients. All of them had tumor Grade II-III of the left hemisphere. Signs of left-handedness were revealed only in half of these patients. Broca's area was not found in 4 cases. All of them had large malignant tumors Grade IV. One patient couldn't handle program of the research. Results of fMRI scans, questionnaire Annette and dichotic listening test frequently were not the same, which is significant. Bilateral activation in speech-loads may be a reflection of brain plasticity in cases of long-growing tumors. Thus it's important to consider the full range of clinical data in studying the problem of the dominant hemisphere for language.
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Lifescience Database Archive (English)
Full Text Available List Contact us Arabidopsis Phenome Database Database Description General information of database Database n... BioResource Center Hiroshi Masuya Database classification Plant databases - Arabidopsis thaliana Organism T...axonomy Name: Arabidopsis thaliana Taxonomy ID: 3702 Database description The Arabidopsis thaliana phenome i...heir effective application. We developed the new Arabidopsis Phenome Database integrating two novel database...seful materials for their experimental research. The other, the “Database of Curated Plant Phenome” focusing
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Identifying patients with Alzheimer's disease using resting-state fMRI and graph theory.
Khazaee, Ali; Ebrahimzadeh, Ata; Babajani-Feremi, Abbas
2015-11-01
Study of brain network on the basis of resting-state functional magnetic resonance imaging (fMRI) has provided promising results to investigate changes in connectivity among different brain regions because of diseases. Graph theory can efficiently characterize different aspects of the brain network by calculating measures of integration and segregation. In this study, we combine graph theoretical approaches with advanced machine learning methods to study functional brain network alteration in patients with Alzheimer's disease (AD). Support vector machine (SVM) was used to explore the ability of graph measures in diagnosis of AD. We applied our method on the resting-state fMRI data of twenty patients with AD and twenty age and gender matched healthy subjects. The data were preprocessed and each subject's graph was constructed by parcellation of the whole brain into 90 distinct regions using the automated anatomical labeling (AAL) atlas. The graph measures were then calculated and used as the discriminating features. Extracted network-based features were fed to different feature selection algorithms to choose most significant features. In addition to the machine learning approach, statistical analysis was performed on connectivity matrices to find altered connectivity patterns in patients with AD. Using the selected features, we were able to accurately classify patients with AD from healthy subjects with accuracy of 100%. Results of this study show that pattern recognition and graph of brain network, on the basis of the resting state fMRI data, can efficiently assist in the diagnosis of AD. Classification based on the resting-state fMRI can be used as a non-invasive and automatic tool to diagnosis of Alzheimer's disease. Copyright © 2015 International Federation of Clinical Neurophysiology. All rights reserved.
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Directory of Open Access Journals (Sweden)
Jesse A. Brown
2012-11-01
Full Text Available Brain connectomics research has rapidly expanded using functional MRI (fMRI and diffusion-weighted MRI (dwMRI. A common product of these varied analyses is a connectivity matrix (CM. A CM stores the connection strength between any two regions (nodes in a brain network. This format is useful for several reasons: 1 it is highly distilled, with minimal data size and complexity, 2 graph theory can be applied to characterize the network’s topology, and 3 it retains sufficient information to capture individual differences such as age, gender, intelligence quotient, or disease state. Here we introduce the UCLA Multimodal Connectivity Database (http://umcd.humanconnectomeproject.org, an openly available website for brain network analysis and data sharing. The site is a repository for researchers to publicly share CMs derived from their data. The site also allows users to select any CM shared by another user, compute graph theoretical metrics on the site, visualize a report of results, or download the raw CM. To date, users have contributed over 2000 individual CMs, spanning different imaging modalities (fMRI, dwMRI and disorders (Alzheimer’s, autism, Attention Deficit Hyperactive Disorder. To demonstrate the site’s functionality, whole brain functional and structural connectivity matrices are derived from 60 subjects’ (ages 26-45 resting state fMRI (rs-fMRI and dwMRI data and uploaded to the site. The site is utilized to derive graph theory global and regional measures for the rs-fMRI and dwMRI networks. Global and nodal graph theoretical measures between functional and structural networks exhibit low correspondence. This example demonstrates how this tool can enhance the comparability of brain networks from different imaging modalities and studies. The existence of this connectivity-based repository should foster broader data sharing and enable larger-scale meta analyses comparing networks across imaging modality, age group, and disease state.
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Distributed database kriging for adaptive sampling (D2KAS)
International Nuclear Information System (INIS)
Roehm, Dominic; Pavel, Robert S.; Barros, Kipton; Rouet-Leduc, Bertrand; McPherson, Allen L.; Germann, Timothy C.; Junghans, Christoph
2015-01-01
We present an adaptive sampling method supplemented by a distributed database and a prediction method for multiscale simulations using the Heterogeneous Multiscale Method. A finite-volume scheme integrates the macro-scale conservation laws for elastodynamics, which are closed by momentum and energy fluxes evaluated at the micro-scale. In the original approach, molecular dynamics (MD) simulations are launched for every macro-scale volume element. Our adaptive sampling scheme replaces a large fraction of costly micro-scale MD simulations with fast table lookup and prediction. The cloud database Redis provides the plain table lookup, and with locality aware hashing we gather input data for our prediction scheme. For the latter we use kriging, which estimates an unknown value and its uncertainty (error) at a specific location in parameter space by using weighted averages of the neighboring points. We find that our adaptive scheme significantly improves simulation performance by a factor of 2.5 to 25, while retaining high accuracy for various choices of the algorithm parameters
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Sub-Millimeter T2 Weighted fMRI at 7 T: Comparison of 3D-GRASE and 2D SE-EPI
Directory of Open Access Journals (Sweden)
Valentin G. Kemper
2015-05-01
Full Text Available Functional magnetic resonance imaging (fMRI allows studying human brain function non-invasively up to the spatial resolution of cortical columns and layers. Most fMRI acquisitions rely on the blood oxygenation level dependent (BOLD contrast employing T2* weighted 2D multi-slice echo-planar imaging (EPI. At ultra-high magnetic field (i.e. 7 T and above, it has been shown experimentally and by simulation, that T2 weighted acquisitions yield a signal that is spatially more specific to the site of neuronal activity at the cost of functional sensitivity. This study compared two T2 weighted imaging sequences, inner-volume 3D Gradient-and-Spin-Echo (3D-GRASE and 2D Spin-Echo EPI (SE-EPI, with evaluation of their imaging point-spread function, functional specificity, and functional sensitivity at sub-millimeter resolution. Simulations and measurements of the imaging point-spread function revealed that the strongest anisotropic blurring in 3D-GRASE (along the second phase-encoding direction was about 60 % higher than the strongest anisotropic blurring in 2D SE-EPI (along the phase-encoding direction In a visual paradigm, the BOLD sensitivity of 3D-GRASE was found to be superior due to its higher temporal signal-to-noise ratio. High resolution cortical depth profiles suggested that the contrast mechanisms are similar between the two sequences, however, 2D SE-EPI had a higher surface bias owing to the higher T2* contribution of the longer in-plane EPI echo-train for full field of view compared to the reduced field of view of zoomed 3D-GRASE.
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Statistical Analysis of fMRI Time-Series: A Critical Review of the GLM Approach
Directory of Open Access Journals (Sweden)
Martin M Monti
2011-03-01
Full Text Available Functional Magnetic Resonance Imaging (fMRI is one of the most widely used tools to study the neural underpinnings of human cognition. Standard analysis of fMRI data relies on a General Linear Model (GLM approach to separate stimulus induced signals from noise. Crucially, this approach relies on a number of assumptions about the data which, for inferences to be valid, must be met. The current paper reviews the GLM approach to analysis of fMRI time-series, focusing in particular on the degree to which such data abides by the assumptions of the GLM framework, and on the methods that have been developed to correct for any violation of those assumptions. Rather than biasing estimates of effect size, the major consequence of non-conformity to the assumptions is to introduce bias into estimates of the variance, thus affecting test statistics, power and false positive rates. Furthermore, this bias can have pervasive effects on both individual subject and group-level statistics, potentially yielding qualitatively different results across replications, especially after the thresholding procedures commonly used for inference-making.
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The Mars Climate Database (MCD version 5.2)
Millour, E.; Forget, F.; Spiga, A.; Navarro, T.; Madeleine, J.-B.; Montabone, L.; Pottier, A.; Lefevre, F.; Montmessin, F.; Chaufray, J.-Y.; Lopez-Valverde, M. A.; Gonzalez-Galindo, F.; Lewis, S. R.; Read, P. L.; Huot, J.-P.; Desjean, M.-C.; MCD/GCM development Team
2015-10-01
The Mars Climate Database (MCD) is a database of meteorological fields derived from General Circulation Model (GCM) numerical simulations of the Martian atmosphere and validated using available observational data. The MCD includes complementary post-processing schemes such as high spatial resolution interpolation of environmental data and means of reconstructing the variability thereof. We have just completed (March 2015) the generation of a new version of the MCD, MCD version 5.2
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Directory of Open Access Journals (Sweden)
Adrienne C. Lahti
2013-06-01
Full Text Available Schizophrenia is a complex chronic mental illness that is characterized by positive, negative and cognitive symptoms. Cognitive deficits are most predictive of long-term outcomes, with abnormalities in memory being the most robust finding. The advent of functional magnetic resonance imaging (fMRI has allowed exploring neural correlates of memory deficits in vivo. In this article, we will give a selective review of fMRI studies probing brain regions and functional networks that are thought to be related to abnormal memory performance in two memory systems prominently affected in schizophrenia; working memory and episodic memory. We revisit the classic “hypofrontality” hypothesis of working memory deficits and explore evidence for frontotemporal dysconnectivity underlying episodic memory abnormalities. We conclude that fMRI studies of memory deficits in schizophrenia are far from universal. However, the current literature does suggest that alterations are not isolated to a few brain regions, but are characterized by abnormalities within large-scale brain networks.
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DEFF Research Database (Denmark)
Hartwigsen, G.; Siebner, Hartwig R.; Stippich, C.
2010-01-01
Neurosurgical resection of brain lesions aims to maximize excision while minimizing the risk of permanent injury to the surrounding intact brain tissue and resulting neurological deficits. While direct electrical cortical stimulation at the time of surgery allows the precise identification...... of essential cortex, it cannot provide information preoperatively for surgical planning.Brain imaging techniques such as functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG) and transcranial magnetic stimulation (TMS) are increasingly being used to localize functionally critical cortical......, if the stimulated cortex makes a critical contribution to the brain functions subserving the task. While the relationship between task and functional activation as revealed by fMRI is correlative in nature, the neurodisruptive effect of TMS reflects a causal effect on brain activity.The use of preoperative f...
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Collective Correlations of Brodmann Areas fMRI Study with RMT-Denoising
Burda, Z.; Kornelsen, J.; Nowak, M. A.; Porebski, B.; Sboto-Frankenstein, U.; Tomanek, B.; Tyburczyk, J.
We study collective behavior of Brodmann regions of human cerebral cortex using functional Magnetic Resonance Imaging (fMRI) and Random Matrix Theory (RMT). The raw fMRI data is mapped onto the cortex regions corresponding to the Brodmann areas with the aid of the Talairach coordinates. Principal Component Analysis (PCA) of the Pearson correlation matrix for 41 different Brodmann regions is carried out to determine their collective activity in the idle state and in the active state stimulated by tapping. The collective brain activity is identified through the statistical analysis of the eigenvectors to the largest eigenvalues of the Pearson correlation matrix. The leading eigenvectors have a large participation ratio. This indicates that several Broadmann regions collectively give rise to the brain activity associated with these eigenvectors. We apply random matrix theory to interpret the underlying multivariate data.
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The power of using functional fMRI on small rodents to study brain pharmacology and disease
Jonckers, Elisabeth; Shah, Disha; Hamaide, Julie; Verhoye, Marleen; Van der Linden, Annemie
2015-01-01
Abstract: Functional magnetic resonance imaging (fMRI) is an excellent tool to study the effect of pharmacological modulations on brain function in a non-invasive and longitudinal manner. We introduce several blood oxygenation level dependent (BOLD) fMRI techniques, including resting state (rsfMRI), stimulus-evoked (st-fMRI), and pharmacological MRI (phMRI). Respectively, these techniques permit the assessment of functional connectivity during rest as well as brain activation triggered by sen...
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A step-by-step tutorial on using the cognitive architecture ACT-R in combination with fMRI data
Borst, Jelmer P.; Anderson, John R.
The cognitive architecture ACT-R is at the same time a psychological theory and a modeling framework for constructing cognitive models that adhere to the principles of the theory. ACT-R can be used in combination with fMRI data in two different ways: (1) fMRI data can be used to evaluate and
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Autobiographical Memory in Semantic Dementia: A Longitudinal fMRI Study
Maguire, Eleanor A.; Kumaran, Dharshan; Hassabis, Demis; Kopelman, Michael D.
2010-01-01
Whilst patients with semantic dementia (SD) are known to suffer from semantic memory and language impairments, there is less agreement about whether memory for personal everyday experiences, autobiographical memory, is compromised. In healthy individuals, functional MRI (fMRI) has helped to delineate a consistent and distributed brain network…
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Item Memory, Context Memory and the Hippocampus: fMRI Evidence
Rugg, Michael D.; Vilberg, Kaia L.; Mattson, Julia T.; Yu, Sarah S.; Johnson, Jeffrey D.; Suzuki, Maki
2012-01-01
Dual-process models of recognition memory distinguish between the retrieval of qualitative information about a prior event (recollection), and judgments of prior occurrence based on an acontextual sense of familiarity. fMRI studies investigating the neural correlates of memory encoding and retrieval conducted within the dual-process framework have…
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International Nuclear Information System (INIS)
Thyreau, Benjamin; Schwartz, Yannick; Thirion, Bertrand; Frouin, Vincent; Loth, Eva; Conrod, Patricia J.; Schumann, Gunter; Vollstadt-Klein, Sabine; Paus, Tomas; Artiges, Eric; Whelan, Robert; Poline, Jean-Baptiste
2012-01-01
In this paper we investigate the use of classical fMRI Random Effect (RFX) group statistics when analyzing a very large cohort and the possible improvement brought from anatomical information. Using 1326 subjects from the IMAGEN study, we first give a global picture of the evolution of the group effect t-value from a simple face-watching contrast with increasing cohort size. We obtain a wide activated pattern, far from being limited to the reasonably expected brain areas, illustrating the difference between statistical significance and practical significance. This motivates us to inject tissue-probability information into the group estimation, we model the BOLD contrast using a matter-weighted mixture of Gaussians and compare it to the common, single-Gaussian model. In both cases, the model parameters are estimated per-voxel for one subgroup, and the likelihood of both models is computed on a second, separate subgroup to reflect model generalization capacity. Various group sizes are tested, and significance is asserted using a 10-fold cross-validation scheme. We conclude that adding matter information consistently improves the quantitative analysis of BOLD responses in some areas of the brain, particularly those where accurate inter-subject registration remains challenging. (authors)
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Armigliato, Alberto; Pagnoni, Gianluca; Tinti, Stefano
2014-05-01
The general idea that pre-computed simulated scenario databases can play a key role in conceiving tsunami early warning systems is commonly accepted by now. But it was only in the last decade that it started to be applied to the Mediterranean region, taking special impulse from initiatives like the GDACS and from recently concluded EU-funded projects such as TRIDEC and NearToWarn. With reference to these two projects and with the possibility of further developing this research line in the frame of the FP7 ASTARTE project, we discuss some results we obtained regarding two major topics, namely the strategies applicable to the tsunami scenario database building and the design and performance assessment of a timely and "reliable" elementary-scenario combination algorithm to be run in real-time. As for the first theme, we take advantage of the experience gained in the test areas of Western Iberia, Rhodes (Greece) and Cyprus to illustrate the criteria with which a "Matching Scenario Database" (MSDB) can be built. These involve 1) the choice of the main tectonic tsunamigenic sources (or areas), 2) their tessellation with matrices of elementary faults whose dimension heavily depend on the particular studied area and must be a compromise between the needs to represent the tsunamigenic area in sufficient detail and of limiting the number of scenarios to be simulated, 3) the computation of the scenarios themselves, 4) the choice of the relevant simulation outputs and the standardisation of their formats. Regarding the matching/forecast algorithm, we want it to select and combine the MSDB elements based on the initial earthquake magnitude and location estimate, and to produce a forecast of (at least) the tsunami arrival time, amplitude and period at the closest tide-level sensors and in all needed forecast points. We discuss the performance of the algorithm in terms of the time needed to produce the forecast after the earthquake is detected. In particular, we analyse the
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Cerebral somatic pain modulation during autogenic training in fMRI.
Naglatzki, R P; Schlamann, M; Gasser, T; Ladd, M E; Sure, U; Forsting, M; Gizewski, E R
2012-10-01
Functional magnetic resonance imaging (fMRI) studies are increasingly employed in different conscious states. Autogenic training (AT) is a common clinically used relaxation method. The purpose of this study was to investigate the cerebral modulation of pain activity patterns due to AT and to correlate the effects to the degree of experience with AT and strength of stimuli. Thirteen volunteers familiar with AT were studied with fMRI during painful electrical stimulation in a block design alternating between resting state and electrical stimulation, both without AT and while employing the same paradigm when utilizing their AT abilities. The subjective rating of painful stimulation and success in modulation during AT was assessed. During painful electrical stimulation without AT, fMRI revealed activation of midcingulate, right secondary sensory, right supplementary motor, and insular cortices, the right thalamus and left caudate nucleus. In contrast, utilizing AT only activation of left insular and supplementary motor cortices was revealed. The paired t-test revealed pain-related activation in the midcingulate, posterior cingulate and left anterior insular cortices for the condition without AT, and activation in the left ventrolateral prefrontal cortex under AT. Activation of the posterior cingulate cortex and thalamus correlated with the amplitude of electrical stimulation. This study revealed an effect on cerebral pain processing while performing AT. This might represent the cerebral correlate of different painful stimulus processing by subjects who are trained in performing relaxation techniques. However, due to the absence of a control group, further studies are needed to confirm this theory. © 2012 European Federation of International Association for the Study of Pain Chapters.
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International Nuclear Information System (INIS)
Smits, Marion; Peeters, Ronald R.; Hecke, Paul van; Sunaert, Stefan
2007-01-01
It is known that taste is centrally represented in the insula, frontal and parietal operculum, as well as in the orbitofrontal cortex (secondary gustatory cortex). In functional MRI (fMRI) experiments activation in the insula has been confirmed, but activation in the orbitofrontal cortex is only infrequently found, especially at higher field strengths (3 T). Due to large susceptibility artefacts, the orbitofrontal cortex is a difficult region to examine with fMRI. Our aim was to localize taste in the human cortex at 3 T, specifically in the orbitofrontal cortex as well as in the primary gustatory cortex. Event-related fMRI was performed at 3 T in seven healthy volunteers. Taste stimuli consisted of lemon juice and chocolate. To visualize activation in the orbitofrontal cortex a dedicated 3D SENSE EPI fMRI sequence was used, in addition to a 2D SENSE EPI fMRI sequence for imaging the entire brain. Data were analyzed using a perception-based model. The dedicated 3D SENSE EPI sequence successfully reduced susceptibility artefacts in the orbitofrontal area. Significant taste-related activation was found in the orbitofrontal and insular cortices. fMRI of the orbitofrontal cortex is feasible at 3 T, using a dedicated sequence. Our results corroborate findings from previous studies. (orig.)
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Energy Technology Data Exchange (ETDEWEB)
Smits, Marion [Erasmus MC, University Medical Center Rotterdam, Department of Radiology, P.O. Box 2040, CA Rotterdam (Netherlands); K.U.Leuven, Department of Radiology, University Hospitals, Leuven (Belgium); Peeters, Ronald R.; Hecke, Paul van; Sunaert, Stefan [K.U.Leuven, Department of Radiology, University Hospitals, Leuven (Belgium)
2007-01-15
It is known that taste is centrally represented in the insula, frontal and parietal operculum, as well as in the orbitofrontal cortex (secondary gustatory cortex). In functional MRI (fMRI) experiments activation in the insula has been confirmed, but activation in the orbitofrontal cortex is only infrequently found, especially at higher field strengths (3 T). Due to large susceptibility artefacts, the orbitofrontal cortex is a difficult region to examine with fMRI. Our aim was to localize taste in the human cortex at 3 T, specifically in the orbitofrontal cortex as well as in the primary gustatory cortex. Event-related fMRI was performed at 3 T in seven healthy volunteers. Taste stimuli consisted of lemon juice and chocolate. To visualize activation in the orbitofrontal cortex a dedicated 3D SENSE EPI fMRI sequence was used, in addition to a 2D SENSE EPI fMRI sequence for imaging the entire brain. Data were analyzed using a perception-based model. The dedicated 3D SENSE EPI sequence successfully reduced susceptibility artefacts in the orbitofrontal area. Significant taste-related activation was found in the orbitofrontal and insular cortices. fMRI of the orbitofrontal cortex is feasible at 3 T, using a dedicated sequence. Our results corroborate findings from previous studies. (orig.)
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Disentangling reward anticipation with simultaneous pupillometry / fMRI.
Schneider, Max; Leuchs, Laura; Czisch, Michael; Sämann, Philipp G; Spoormaker, Victor I
2018-05-05
The reward system may provide an interesting intermediate phenotype for anhedonia in affective disorders. Reward anticipation is characterized by an increase in arousal, and previous studies have linked the anterior cingulate cortex (ACC) to arousal responses such as dilation of the pupil. Here, we examined pupil dynamics during a reward anticipation task in forty-six healthy human subjects and evaluated its neural correlates using functional magnetic resonance imaging (fMRI). Pupil size showed a strong increase during monetary reward anticipation, a moderate increase during verbal reward anticipation and a decrease during control trials. For fMRI analyses, average pupil size and pupil change were computed in 1-s time bins during the anticipation phase. Activity in the ventral striatum was inversely related to the pupil size time course, indicating an early onset of activation and a role in reward prediction processing. Pupil dilations were linked to increased activity in the salience network (dorsal ACC and bilateral insula), which likely triggers an increase in arousal to enhance task performance. Finally, increased pupil size preceding the required motor response was associated with activity in the ventral attention network. In sum, pupillometry provides an effective tool for disentangling different phases of reward anticipation, with relevance for affective symptomatology. Copyright © 2018 Elsevier Inc. All rights reserved.
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Directory of Open Access Journals (Sweden)
Hendrik eMandelkow
2016-03-01
Full Text Available Naturalistic stimuli like movies evoke complex perceptual processes, which are of great interest in the study of human cognition by functional MRI (fMRI. However, conventional fMRI analysis based on statistical parametric mapping (SPM and the general linear model (GLM is hampered by a lack of accurate parametric models of the BOLD response to complex stimuli. In this situation, statistical machine-learning methods, a.k.a. multivariate pattern analysis (MVPA, have received growing attention for their ability to generate stimulus response models in a data-driven fashion. However, machine-learning methods typically require large amounts of training data as well as computational resources. In the past this has largely limited their application to fMRI experiments involving small sets of stimulus categories and small regions of interest in the brain. By contrast, the present study compares several classification algorithms known as Nearest Neighbour (NN, Gaussian Naïve Bayes (GNB, and (regularised Linear Discriminant Analysis (LDA in terms of their classification accuracy in discriminating the global fMRI response patterns evoked by a large number of naturalistic visual stimuli presented as a movie.Results show that LDA regularised by principal component analysis (PCA achieved high classification accuracies, above 90% on average for single fMRI volumes acquired 2s apart during a 300s movie (chance level 0.7% = 2s/300s. The largest source of classification errors were autocorrelations in the BOLD signal compounded by the similarity of consecutive stimuli. All classifiers performed best when given input features from a large region of interest comprising around 25% of the voxels that responded significantly to the visual stimulus. Consistent with this, the most informative principal components represented widespread distributions of co-activated brain regions that were similar between subjects and may represent functional networks. In light of these
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Effect of scanner acoustic background noise on strict resting-state fMRI
Directory of Open Access Journals (Sweden)
C. Rondinoni
2013-04-01
Full Text Available Functional MRI (fMRI resting-state experiments are aimed at identifying brain networks that support basal brain function. Although most investigators consider a ‘resting-state' fMRI experiment with no specific external stimulation, subjects are unavoidably under heavy acoustic noise produced by the equipment. In the present study, we evaluated the influence of auditory input on the resting-state networks (RSNs. Twenty-two healthy subjects were scanned using two similar echo-planar imaging sequences in the same 3T MRI scanner: a default pulse sequence and a reduced “silent” pulse sequence. Experimental sessions consisted of two consecutive 7-min runs with noise conditions (default or silent counterbalanced across subjects. A self-organizing group independent component analysis was applied to fMRI data in order to recognize the RSNs. The insula, left middle frontal gyrus and right precentral and left inferior parietal lobules showed significant differences in the voxel-wise comparison between RSNs depending on noise condition. In the presence of low-level noise, these areas Granger-cause oscillations in RSNs with cognitive implications (dorsal attention and entorhinal, while during high noise acquisition, these connectivities are reduced or inverted. Applying low noise MR acquisitions in research may allow the detection of subtle differences of the RSNs, with implications in experimental planning for resting-state studies, data analysis, and ergonomic factors.
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Test-retest and between-site reliability in a multicenter fMRI study.
Friedman, Lee; Stern, Hal; Brown, Gregory G; Mathalon, Daniel H; Turner, Jessica; Glover, Gary H; Gollub, Randy L; Lauriello, John; Lim, Kelvin O; Cannon, Tyrone; Greve, Douglas N; Bockholt, Henry Jeremy; Belger, Aysenil; Mueller, Bryon; Doty, Michael J; He, Jianchun; Wells, William; Smyth, Padhraic; Pieper, Steve; Kim, Seyoung; Kubicki, Marek; Vangel, Mark; Potkin, Steven G
2008-08-01
In the present report, estimates of test-retest and between-site reliability of fMRI assessments were produced in the context of a multicenter fMRI reliability study (FBIRN Phase 1, www.nbirn.net). Five subjects were scanned on 10 MRI scanners on two occasions. The fMRI task was a simple block design sensorimotor task. The impulse response functions to the stimulation block were derived using an FIR-deconvolution analysis with FMRISTAT. Six functionally-derived ROIs covering the visual, auditory and motor cortices, created from a prior analysis, were used. Two dependent variables were compared: percent signal change and contrast-to-noise-ratio. Reliability was assessed with intraclass correlation coefficients derived from a variance components analysis. Test-retest reliability was high, but initially, between-site reliability was low, indicating a strong contribution from site and site-by-subject variance. However, a number of factors that can markedly improve between-site reliability were uncovered, including increasing the size of the ROIs, adjusting for smoothness differences, and inclusion of additional runs. By employing multiple steps, between-site reliability for 3T scanners was increased by 123%. Dropping one site at a time and assessing reliability can be a useful method of assessing the sensitivity of the results to particular sites. These findings should provide guidance toothers on the best practices for future multicenter studies.
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Effect of scanner acoustic background noise on strict resting-state fMRI.
Rondinoni, C; Amaro, E; Cendes, F; dos Santos, A C; Salmon, C E G
2013-04-01
Functional MRI (fMRI) resting-state experiments are aimed at identifying brain networks that support basal brain function. Although most investigators consider a 'resting-state' fMRI experiment with no specific external stimulation, subjects are unavoidably under heavy acoustic noise produced by the equipment. In the present study, we evaluated the influence of auditory input on the resting-state networks (RSNs). Twenty-two healthy subjects were scanned using two similar echo-planar imaging sequences in the same 3T MRI scanner: a default pulse sequence and a reduced "silent" pulse sequence. Experimental sessions consisted of two consecutive 7-min runs with noise conditions (default or silent) counterbalanced across subjects. A self-organizing group independent component analysis was applied to fMRI data in order to recognize the RSNs. The insula, left middle frontal gyrus and right precentral and left inferior parietal lobules showed significant differences in the voxel-wise comparison between RSNs depending on noise condition. In the presence of low-level noise, these areas Granger-cause oscillations in RSNs with cognitive implications (dorsal attention and entorhinal), while during high noise acquisition, these connectivities are reduced or inverted. Applying low noise MR acquisitions in research may allow the detection of subtle differences of the RSNs, with implications in experimental planning for resting-state studies, data analysis, and ergonomic factors.
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Probing the Interoceptive Network by Listening to Heartbeats: An fMRI Study.
Directory of Open Access Journals (Sweden)
Nina I Kleint
Full Text Available Exposure to cues of homeostatic relevance (i.e. heartbeats is supposed to increase the allocation of attentional resources towards the cue, due to its importance for self-regulatory, interoceptive processes. This functional magnetic resonance imaging (fMRI study aimed at determining whether listening to heartbeats is accompanied by activation in brain areas associated with interoception, particularly the insular cortex. Brain activity was measured with fMRI during cue-exposure in 36 subjects while listening to heartbeats vs. sinus tones. Autonomic markers (skin conductance and subjective measures of state and trait anxiety were assessed. Stimulation with heartbeat sounds triggered activation in brain areas commonly associated with the processing of interoceptive information, including bilateral insular cortices, the inferior frontal operculum, and the middle frontal gyrus. A psychophysiological interaction analysis indicated a functional connectivity between the middle frontal gyrus (seed region and bilateral insular cortices, the left amygdala and the supplementary motor area. The magnitude of neural activation in the right anterior insular cortex was positively associated with autonomic arousal. The present findings indicate that listening to heartbeats induced activity in areas of the interoception network as well as changes in psychophysiological arousal and subjective emotional experience. As this approach constitutes a promising method for studying interoception in the fMRI environment, a clinical application in anxiety prone populations should be addressed by future studies.
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Combining task-evoked and spontaneous activity to improve pre-operative brain mapping with fMRI
Fox, Michael D.; Qian, Tianyi; Madsen, Joseph R.; Wang, Danhong; Li, Meiling; Ge, Manling; Zuo, Huan-cong; Groppe, David M.; Mehta, Ashesh D.; Hong, Bo; Liu, Hesheng
2016-01-01
Noninvasive localization of brain function is used to understand and treat neurological disease, exemplified by pre-operative fMRI mapping prior to neurosurgical intervention. The principal approach for generating these maps relies on brain responses evoked by a task and, despite known limitations, has dominated clinical practice for over 20 years. Recently, pre-operative fMRI mapping based on correlations in spontaneous brain activity has been demonstrated, however this approach has its own limitations and has not seen widespread clinical use. Here we show that spontaneous and task-based mapping can be performed together using the same pre-operative fMRI data, provide complimentary information relevant for functional localization, and can be combined to improve identification of eloquent motor cortex. Accuracy, sensitivity, and specificity of our approach are quantified through comparison with electrical cortical stimulation mapping in eight patients with intractable epilepsy. Broad applicability and reproducibility of our approach is demonstrated through prospective replication in an independent dataset of six patients from a different center. In both cohorts and every individual patient, we see a significant improvement in signal to noise and mapping accuracy independent of threshold, quantified using receiver operating characteristic curves. Collectively, our results suggest that modifying the processing of fMRI data to incorporate both task-based and spontaneous activity significantly improves functional localization in pre-operative patients. Because this method requires no additional scan time or modification to conventional pre-operative data acquisition protocols it could have widespread utility. PMID:26408860
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Brain Correlates of Aesthetic Expertise: A Parametric fMRI Study
Kirk, Ulrich; Skov, Martin; Christensen, Mark Schram; Nygaard, Niels
2009-01-01
Several studies have demonstrated that acquired expertise influences aesthetic judgments. In this paradigm we used functional magnetic resonance imaging (fMRI) to study aesthetic judgments of visually presented architectural stimuli and control-stimuli (faces) for a group of architects and a group of non-architects. This design allowed us to test…
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A wavelet method for modeling and despiking motion artifacts from resting-state fMRI time series
Patel, Ameera X.; Kundu, Prantik; Rubinov, Mikail; Jones, P. Simon; Vértes, Petra E.; Ersche, Karen D.; Suckling, John; Bullmore, Edward T.
2014-01-01
The impact of in-scanner head movement on functional magnetic resonance imaging (fMRI) signals has long been established as undesirable. These effects have been traditionally corrected by methods such as linear regression of head movement parameters. However, a number of recent independent studies have demonstrated that these techniques are insufficient to remove motion confounds, and that even small movements can spuriously bias estimates of functional connectivity. Here we propose a new data-driven, spatially-adaptive, wavelet-based method for identifying, modeling, and removing non-stationary events in fMRI time series, caused by head movement, without the need for data scrubbing. This method involves the addition of just one extra step, the Wavelet Despike, in standard pre-processing pipelines. With this method, we demonstrate robust removal of a range of different motion artifacts and motion-related biases including distance-dependent connectivity artifacts, at a group and single-subject level, using a range of previously published and new diagnostic measures. The Wavelet Despike is able to accommodate the substantial spatial and temporal heterogeneity of motion artifacts and can consequently remove a range of high and low frequency artifacts from fMRI time series, that may be linearly or non-linearly related to physical movements. Our methods are demonstrated by the analysis of three cohorts of resting-state fMRI data, including two high-motion datasets: a previously published dataset on children (N = 22) and a new dataset on adults with stimulant drug dependence (N = 40). We conclude that there is a real risk of motion-related bias in connectivity analysis of fMRI data, but that this risk is generally manageable, by effective time series denoising strategies designed to attenuate synchronized signal transients induced by abrupt head movements. The Wavelet Despiking software described in this article is freely available for download at www
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Li, Yuanqing; Wang, Fangyi; Chen, Yongbin; Cichocki, Andrzej; Sejnowski, Terrence
2017-09-25
At cocktail parties, our brains often simultaneously receive visual and auditory information. Although the cocktail party problem has been widely investigated under auditory-only settings, the effects of audiovisual inputs have not. This study explored the effects of audiovisual inputs in a simulated cocktail party. In our fMRI experiment, each congruent audiovisual stimulus was a synthesis of 2 facial movie clips, each of which could be classified into 1 of 2 emotion categories (crying and laughing). Visual-only (faces) and auditory-only stimuli (voices) were created by extracting the visual and auditory contents from the synthesized audiovisual stimuli. Subjects were instructed to selectively attend to 1 of the 2 objects contained in each stimulus and to judge its emotion category in the visual-only, auditory-only, and audiovisual conditions. The neural representations of the emotion features were assessed by calculating decoding accuracy and brain pattern-related reproducibility index based on the fMRI data. We compared the audiovisual condition with the visual-only and auditory-only conditions and found that audiovisual inputs enhanced the neural representations of emotion features of the attended objects instead of the unattended objects. This enhancement might partially explain the benefits of audiovisual inputs for the brain to solve the cocktail party problem. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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Lessons Learned From Developing Reactor Pressure Vessel Steel Embrittlement Database
Energy Technology Data Exchange (ETDEWEB)
Wang, Jy-An John [ORNL
2010-08-01
Materials behaviors caused by neutron irradiation under fission and/or fusion environments can be little understood without practical examination. Easily accessible material information system with large material database using effective computers is necessary for design of nuclear materials and analyses or simulations of the phenomena. The developed Embrittlement Data Base (EDB) at ORNL is this comprehensive collection of data. EDB database contains power reactor pressure vessel surveillance data, the material test reactor data, foreign reactor data (through bilateral agreements authorized by NRC), and the fracture toughness data. The lessons learned from building EDB program and the associated database management activity regarding Material Database Design Methodology, Architecture and the Embedded QA Protocol are described in this report. The development of IAEA International Database on Reactor Pressure Vessel Materials (IDRPVM) and the comparison of EDB database and IAEA IDRPVM database are provided in the report. The recommended database QA protocol and database infrastructure are also stated in the report.
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Modality Specific Cerebro-Cerebellar Activations in Verbal Working Memory: An fMRI Study
Directory of Open Access Journals (Sweden)
Matthew P. Kirschen
2010-01-01
Full Text Available Verbal working memory (VWM engages frontal and temporal/parietal circuits subserving the phonological loop, as well as, superior and inferior cerebellar regions which have projections from these neocortical areas. Different cerebro-cerebellar circuits may be engaged for integrating aurally- and visually-presented information for VWM. The present fMRI study investigated load (2, 4, or 6 letters and modality (auditory and visual dependent cerebro-cerebellar VWM activation using a Sternberg task. FMRI revealed modality-independent activations in left frontal (BA 6/9/44, insular, cingulate (BA 32, and bilateral inferior parietal/supramarginal (BA 40 regions, as well as in bilateral superior (HVI and right inferior (HVIII cerebellar regions. Visual presentation evoked prominent activations in right superior (HVI/CrusI cerebellum, bilateral occipital (BA19 and left parietal (BA7/40 cortex while auditory presentation showed robust activations predominately in bilateral temporal regions (BA21/22. In the cerebellum, we noted a visual to auditory emphasis of function progressing from superior to inferior and from lateral to medial regions. These results extend our previous findings of fMRI activation in cerebro-cerebellar networks during VWM, and demonstrate both modality dependent commonalities and differences in activations with increasing memory load.
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PyMVPA: A python toolbox for multivariate pattern analysis of fMRI data.
Hanke, Michael; Halchenko, Yaroslav O; Sederberg, Per B; Hanson, Stephen José; Haxby, James V; Pollmann, Stefan
2009-01-01
Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. Here we introduce a Python-based, cross-platform, and open-source software toolbox, called PyMVPA, for the application of classifier-based analysis techniques to fMRI datasets. PyMVPA makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine learning packages. We present the framework in this paper and provide illustrative examples on its usage, features, and programmability.
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Reducing task-based fMRI scanning time using simultaneous multislice echo planar imaging
Energy Technology Data Exchange (ETDEWEB)
Kiss, Mate [Hungarian Academy of Sciences, Brain Imaging Centre, Research Centre for Natural Sciences, Budapest (Hungary); Janos Szentagothai PhD School, MR Research Centre, Budapest (Hungary); National Institute of Clinical Neuroscience, Department of Neuroradiology, Budapest (Hungary); Hermann, Petra; Vidnyanszky, Zoltan; Gal, Viktor [Hungarian Academy of Sciences, Brain Imaging Centre, Research Centre for Natural Sciences, Budapest (Hungary)
2018-03-15
To maintain alertness and to remain motionless during scanning represent a substantial challenge for patients/subjects involved in both clinical and research functional magnetic resonance imaging (fMRI) examinations. Therefore, availability and application of new data acquisition protocols allowing the shortening of scan time without compromising the data quality and statistical power are of major importance. Higher order category-selective visual cortical areas were identified individually, and rapid event-related fMRI design was used to compare three different sampling rates (TR = 2000, 1000, and 410 ms, using state-of-the-art simultaneous multislice imaging) and four different scanning lengths to match the statistical power of the traditional scanning methods to high sampling-rate design. The results revealed that ∝ 4 min of the scan time with 1 Hz (TR = 1000 ms) sampling rate and ∝ 2 min scanning at ∝ 2.5 Hz (TR = 410 ms) sampling rate provide similar localization sensitivity and selectivity to that obtained with 11-min session at conventional, 0.5 Hz (TR = 2000 ms) sampling rate. Our findings suggest that task-based fMRI examination of clinical population prone to distress such as presurgical mapping experiments might substantially benefit from the reduced (20-40%) scanning time that can be achieved by the application of simultaneous multislice sequences. (orig.)
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Modality Specific Cerebro-Cerebellar Activations in Verbal Working Memory: An fMRI Study
Kirschen, Matthew P.; Chen, S. H. Annabel; Desmond, John E.
2010-01-01
Verbal working memory (VWM) engages frontal and temporal/parietal circuits subserving the phonological loop, as well as, superior and inferior cerebellar regions which have projections from these neocortical areas. Different cerebro-cerebellar circuits may be engaged for integrating aurally- and visually-presented information for VWM. The present fMRI study investigated load (2, 4, or 6 letters) and modality (auditory and visual) dependent cerebro-cerebellar VWM activation using a Sternberg task. FMRI revealed modality-independent activations in left frontal (BA 6/9/44), insular, cingulate (BA 32), and bilateral inferior parietal/supramarginal (BA 40) regions, as well as in bilateral superior (HVI) and right inferior (HVIII) cerebellar regions. Visual presentation evoked prominent activations in right superior (HVI/CrusI) cerebellum, bilateral occipital (BA19) and left parietal (BA7/40) cortex while auditory presentation showed robust activations predominately in bilateral temporal regions (BA21/22). In the cerebellum, we noted a visual to auditory emphasis of function progressing from superior to inferior and from lateral to medial regions. These results extend our previous findings of fMRI activation in cerebro-cerebellar networks during VWM, and demonstrate both modality dependent commonalities and differences in activations with increasing memory load. PMID:20714061
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Conjunction analysis and propositional logic in fMRI data analysis using Bayesian statistics.
Rudert, Thomas; Lohmann, Gabriele
2008-12-01
To evaluate logical expressions over different effects in data analyses using the general linear model (GLM) and to evaluate logical expressions over different posterior probability maps (PPMs). In functional magnetic resonance imaging (fMRI) data analysis, the GLM was applied to estimate unknown regression parameters. Based on the GLM, Bayesian statistics can be used to determine the probability of conjunction, disjunction, implication, or any other arbitrary logical expression over different effects or contrast. For second-level inferences, PPMs from individual sessions or subjects are utilized. These PPMs can be combined to a logical expression and its probability can be computed. The methods proposed in this article are applied to data from a STROOP experiment and the methods are compared to conjunction analysis approaches for test-statistics. The combination of Bayesian statistics with propositional logic provides a new approach for data analyses in fMRI. Two different methods are introduced for propositional logic: the first for analyses using the GLM and the second for common inferences about different probability maps. The methods introduced extend the idea of conjunction analysis to a full propositional logic and adapt it from test-statistics to Bayesian statistics. The new approaches allow inferences that are not possible with known standard methods in fMRI. (c) 2008 Wiley-Liss, Inc.
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Directory of Open Access Journals (Sweden)
Chi Wah Wong
Full Text Available In the real world, learning often proceeds in an unsupervised manner without explicit instructions or feedback. In this study, we employed an experimental paradigm in which subjects explored an immersive virtual reality environment on each of two days. On day 1, subjects implicitly learned the location of 39 objects in an unsupervised fashion. On day 2, the locations of some of the objects were changed, and object location recall performance was assessed and found to vary across subjects. As prior work had shown that functional magnetic resonance imaging (fMRI measures of resting-state brain activity can predict various measures of brain performance across individuals, we examined whether resting-state fMRI measures could be used to predict object location recall performance. We found a significant correlation between performance and the variability of the resting-state fMRI signal in the basal ganglia, hippocampus, amygdala, thalamus, insula, and regions in the frontal and temporal lobes, regions important for spatial exploration, learning, memory, and decision making. In addition, performance was significantly correlated with resting-state fMRI connectivity between the left caudate and the right fusiform gyrus, lateral occipital complex, and superior temporal gyrus. Given the basal ganglia's role in exploration, these findings suggest that tighter integration of the brain systems responsible for exploration and visuospatial processing may be critical for learning in a complex environment.
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Nuclear integrated database and design advancement system
International Nuclear Information System (INIS)
Ha, Jae Joo; Jeong, Kwang Sub; Kim, Seung Hwan; Choi, Sun Young.
1997-01-01
The objective of NuIDEAS is to computerize design processes through an integrated database by eliminating the current work style of delivering hardcopy documents and drawings. The major research contents of NuIDEAS are the advancement of design processes by computerization, the establishment of design database and 3 dimensional visualization of design data. KSNP (Korea Standard Nuclear Power Plant) is the target of legacy database and 3 dimensional model, so that can be utilized in the next plant design. In the first year, the blueprint of NuIDEAS is proposed, and its prototype is developed by applying the rapidly revolutionizing computer technology. The major results of the first year research were to establish the architecture of the integrated database ensuring data consistency, and to build design database of reactor coolant system and heavy components. Also various softwares were developed to search, share and utilize the data through networks, and the detailed 3 dimensional CAD models of nuclear fuel and heavy components were constructed, and walk-through simulation using the models are developed. This report contains the major additions and modifications to the object oriented database and associated program, using methods and Javascript.. (author). 36 refs., 1 tab., 32 figs
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Real time fMRI: a tool for the routine presurgical localisation of the motor cortex
Energy Technology Data Exchange (ETDEWEB)
Moeller, M.; Freund, M.; Schwindt, W.; Gaus, C.; Heindel, W. [University of Muenster, Department of Clinical Radiology, Munster (Germany); Greiner, C. [University of Muenster, Department of Neurosurgery, Munster (Germany)
2005-02-01
In patients with brain lesions adjacent to the central area, exact preoperative knowledge of the spatial relation of the tumour to the motor cortex is of major importance. Many studies have shown that functional magnetic resonance imaging (fMRI) is a reliable tool to identify the motor cortex. However, fMRI data acquisition and data processing are time-consuming procedures, and this prevents general routine clinical application. We report a new application of real time fMRI that allows immediate access to fMRI results by automatic on-line data processing. Prior to surgery we examined ten patients with a brain tumour adjacent to the central area. Three measurements were performed at a 1.5-T Magnetom Vision Scanner (Siemens, Forchheim, Germany) on seven patients and at a 1.5-T Intera Scanner (Philips, Best, The Netherlands) on three patients using a sequential finger-tapping paradigm for motor cortex activation versus at rest condition. Blood oxygen level-dependant (BOLD) images were acquired using a multislice EPI sequence (16 slices, TE 60, TR 6000, FOV 210 x 210, matrix 64 x 64). The central sulcus of the left hemisphere could be clearly identified by a maximum of cortical activity after finger tapping of the right hand in all investigated patients. In eight of ten patients the right central sulcus was localised by a signal maximum, whereas in two patients the central sulcus could not be identified due to a hemiparesis in one and strong motion artefacts in the second patient. Finger tapping with one side versus rest condition seems to result in more motion artefacts, while finger tapping of the right versus the left hand yielded the strongest signal in the central area. Real time fMRI is a quick and reliable method to identify the central sulcus and has the potential to become a clinical tool to assess patients non-invasively before neurosurgical treatment. (orig.)
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Increasing fMRI sampling rate improves Granger causality estimates.
Directory of Open Access Journals (Sweden)
Fa-Hsuan Lin
Full Text Available Estimation of causal interactions between brain areas is necessary for elucidating large-scale functional brain networks underlying behavior and cognition. Granger causality analysis of time series data can quantitatively estimate directional information flow between brain regions. Here, we show that such estimates are significantly improved when the temporal sampling rate of functional magnetic resonance imaging (fMRI is increased 20-fold. Specifically, healthy volunteers performed a simple visuomotor task during blood oxygenation level dependent (BOLD contrast based whole-head inverse imaging (InI. Granger causality analysis based on raw InI BOLD data sampled at 100-ms resolution detected the expected causal relations, whereas when the data were downsampled to the temporal resolution of 2 s typically used in echo-planar fMRI, the causality could not be detected. An additional control analysis, in which we SINC interpolated additional data points to the downsampled time series at 0.1-s intervals, confirmed that the improvements achieved with the real InI data were not explainable by the increased time-series length alone. We therefore conclude that the high-temporal resolution of InI improves the Granger causality connectivity analysis of the human brain.
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Investigating Inhibitory Control in Children with Epilepsy: An fMRI Study
Triplett, Regina L.; Velanova, Katerina; Luna, Beatriz; Padmanabhan, Aarthi; Gaillard, William D.; Asato, Miya R.
2014-01-01
SUMMARY Objective Deficits in executive function are increasingly noted in children with epilepsy and have been associated with poor academic and psychosocial outcomes. Impaired inhibitory control contributes to executive dysfunction in children with epilepsy; however, its neuroanatomic basis has not yet been investigated. We used functional Magnetic Resonance Imaging (fMRI) to probe the integrity of activation in brain regions underlying inhibitory control in children with epilepsy. Methods This cross-sectional study consisted of 34 children aged 8 to 17 years: 17 with well-controlled epilepsy and 17 age-and sex-matched controls. Participants performed the antisaccade (AS) task, representative of inhibitory control, during fMRI scanning. We compared AS performance during neutral and reward task conditions and evaluated task-related blood-oxygen level dependent (BOLD) activation. Results Children with epilepsy demonstrated impaired AS performance compared to controls during both neutral (non-reward) and reward trials, but exhibited significant task improvement during reward trials. Post-hoc analysis revealed that younger patients made more errors than older patients and all controls. fMRI results showed preserved activation in task-relevant regions in patients and controls, with the exception of increased activation in the left posterior cingulate gyrus in patients specifically with generalized epilepsy across neutral and reward trials. Significance Despite impaired inhibitory control, children with epilepsy accessed typical neural pathways as did their peers without epilepsy. Children with epilepsy showed improved behavioral performance in response to the reward condition, suggesting potential benefits of the use of incentives in cognitive remediation. PMID:25223606
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Brünner, Yvonne F; Rodriguez-Raecke, Rea; Mutic, Smiljana; Benedict, Christian; Freiherr, Jessica
2016-10-01
This fMRI study intended to establish 3D-simulated mazes with olfactory and visual cues and examine the effect of intranasally applied insulin on memory performance in healthy subjects. The effect of insulin on hippocampus-dependent brain activation was explored using a double-blind and placebo-controlled design. Following intranasal administration of either insulin (40IU) or placebo, 16 male subjects participated in two experimental MRI sessions with olfactory and visual mazes. Each maze included two separate runs. The first was an encoding maze during which subjects learned eight olfactory or eight visual cues at different target locations. The second was a recall maze during which subjects were asked to remember the target cues at spatial locations. For eleven included subjects in the fMRI analysis we were able to validate brain activation for odor perception and visuospatial tasks. However, we did not observe an enhancement of declarative memory performance in our behavioral data or hippocampal activity in response to insulin application in the fMRI analysis. It is therefore possible that intranasal insulin application is sensitive to the methodological variations e.g. timing of task execution and dose of application. Findings from this study suggest that our method of 3D-simulated mazes is feasible for studying neural correlates of olfactory and visual memory performance. Copyright © 2016 Elsevier Inc. All rights reserved.
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Reddy, Rajiv M; Panahi, Issa M S
2008-01-01
The performance of FIR feedforward, IIR feedforward, FIR feedback, hybrid FIR feedforward--FIR feedback, and hybrid IIR feedforward - FIR feedback structures for active noise control (ANC) are compared for an fMRI noise application. The filtered-input normalized least squares (FxNLMS) algorithm is used to update the coefficients of the adaptive filters in all these structures. Realistic primary and secondary paths of an fMRI bore are used by estimating them on a half cylindrical acrylic bore of 0.76 m (D)x1.52 m (L). Detailed results of the performance of the ANC system are presented in the paper for each of these structures. We find that the IIR feedforward structure produces most of the performance improvement in the hybrid IIR feedforward - FIR feedback structure and adding the feedback structure becomes almost redundant in the case of fMRI noise.
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Optimistic protocol for partitioned distributed database systems
International Nuclear Information System (INIS)
Davidson, S.B.
1982-01-01
A protocol for transaction processing during partition failures is presented which guarantees mutual consistency between copies of data-items after repair is completed. The protocol is optimistic in that transactions are processed without restrictions during the failure; conflicts are detected at repair time using a precedence graph and are resolved by backing out transactions according to some backout strategy. The protocol is then evaluated using simulation and probabilistic modeling. In the simulation, several parameters are varied such as the number of transactions processed in a group, the type of transactions processed, the number of data-items present in the database, and the distribution of references to data-items. The simulation also uses different backout strategies. From these results we note conditions under which the protocol performs well, i.e., conditions under which the protocol backs out a small percentage of the transaction run. A probabilistic model is developed to estimate the expected number of transactions backed out using most of the above database and transaction parameters, and is shown to agree with simulation results. Suggestions are then made on how to improve the performance of the protocol. Insights gained from the simulation and probabilistic modeling are used to develop a backout strategy which takes into account individual transaction costs and attempts to minimize total backout cost. Although the problem of choosing transactions to minimize total backout cost is, in general, NP-complete, the backout strategy is efficient and produces very good results
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Modeling the hemodynamic response in fMRI using smooth FIR filters
DEFF Research Database (Denmark)
Goutte, Cyril; Nielsen, Finn Årup; Hansen, Lars Kai
2000-01-01
Modeling the hemodynamic response in functional magnetic resonance (fMRI) experiments is an important aspect of the analysis of functional neuroimages. This has been done in the past using parametric response function, from a limited family. In this contribution, the authors adopt a semi...
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Poplawsky, Alexander John; Fukuda, Mitsuhiro; Kang, Bok-Man; Kim, Jae Hwan; Suh, Minah; Kim, Seong-Gi
2017-08-16
Contrast-enhanced cerebral blood volume-weighted (CBVw) fMRI response peaks are specific to the layer of evoked synaptic activity (Poplawsky et al., 2015), but the spatial resolution limit of CBVw fMRI is unknown. In this study, we measured the laminar spread of the CBVw fMRI evoked response in the external plexiform layer (EPL, 265 ± 65 μm anatomical thickness, mean ± SD, n = 30 locations from 5 rats) of the rat olfactory bulb during electrical stimulation of the lateral olfactory tract and examined its potential vascular source. First, we obtained the evoked CBVw fMRI responses with a 55 × 55 μm 2 in-plane resolution and a 500-μm thickness at 9.4 T, and found that the fMRI signal peaked predominantly in the inner half of EPL (136 ± 54 μm anatomical thickness). The mean full-width at half-maximum of these fMRI peaks was 347 ± 102 μm and the functional spread was approximately 100 or 200 μm when the effects of the laminar thicknesses of EPL or inner EPL were removed, respectively. Second, we visualized the vascular architecture of EPL from a different rat using a Clear Lipid-exchanged Anatomically Rigid Imaging/immunostaining-compatible Tissue hYdrogel (CLARITY)-based tissue preparation method and confocal microscopy. Microvascular segments with an outer diameter of limit of the fMRI spatial resolution is approximately the average length of 1-2 microvessel segments, which may be sufficient for examining sublaminar circuits. Copyright © 2017 Elsevier Inc. All rights reserved.
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Hames, Elizabeth’ C.; Murphy, Brandi; Rajmohan, Ravi; Anderson, Ronald C.; Baker, Mary; Zupancic, Stephen; O’Boyle, Michael; Richman, David
2016-01-01
Electroencephalography (EEG) and blood oxygen level dependent functional magnetic resonance imagining (BOLD fMRI) assessed the neurocorrelates of sensory processing of visual and auditory stimuli in 11 adults with autism (ASD) and 10 neurotypical (NT) controls between the ages of 20–28. We hypothesized that ASD performance on combined audiovisual trials would be less accurate with observable decreased EEG power across frontal, temporal, and occipital channels and decreased BOLD fMRI activity in these same regions; reflecting deficits in key sensory processing areas. Analysis focused on EEG power, BOLD fMRI, and accuracy. Lower EEG beta power and lower left auditory cortex fMRI activity were seen in ASD compared to NT when they were presented with auditory stimuli as demonstrated by contrasting the activity from the second presentation of an auditory stimulus in an all auditory block vs. the second presentation of a visual stimulus in an all visual block (AA2-VV2).We conclude that in ASD, combined audiovisual processing is more similar than unimodal processing to NTs. PMID:27148020
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Directory of Open Access Journals (Sweden)
Elizabeth C Hames
2016-04-01
Full Text Available Electroencephalography (EEG and Blood Oxygen Level Dependent Functional Magnetic Resonance Imagining (BOLD fMRI assessed the neurocorrelates of sensory processing of visual and auditory stimuli in 11 adults with autism (ASD and 10 neurotypical (NT controls between the ages of 20-28. We hypothesized that ASD performance on combined audiovisual trials would be less accurate with observable decreased EEG power across frontal, temporal, and occipital channels and decreased BOLD fMRI activity in these same regions; reflecting deficits in key sensory processing areas. Analysis focused on EEG power, BOLD fMRI, and accuracy. Lower EEG beta power and lower left auditory cortex fMRI activity were seen in ASD compared to NT when they were presented with auditory stimuli as demonstrated by contrasting the activity from the second presentation of an auditory stimulus in an all auditory block versus the second presentation of a visual stimulus in an all visual block (AA2VV2. We conclude that in ASD, combined audiovisual processing is more similar than unimodal processing to NTs.
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Classification of fMRI resting-state maps using machine learning techniques: A comparative study
Gallos, Ioannis; Siettos, Constantinos
2017-11-01
We compare the efficiency of Principal Component Analysis (PCA) and nonlinear learning manifold algorithms (ISOMAP and Diffusion maps) for classifying brain maps between groups of schizophrenia patients and healthy from fMRI scans during a resting-state experiment. After a standard pre-processing pipeline, we applied spatial Independent component analysis (ICA) to reduce (a) noise and (b) spatial-temporal dimensionality of fMRI maps. On the cross-correlation matrix of the ICA components, we applied PCA, ISOMAP and Diffusion Maps to find an embedded low-dimensional space. Finally, support-vector-machines (SVM) and k-NN algorithms were used to evaluate the performance of the algorithms in classifying between the two groups.
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19F-MRI of stomach and intestine using 50% FTPA emulsion under 2T MRI system
International Nuclear Information System (INIS)
Shimizu, Masahiro; Kobayashi, Teturou; Mishima, Hideyuki
1991-01-01
1 H-MRI is of clinical value in many lesions, but imaging of gastrointestinal lesions is still difficult by 1 H-MRI. To overcome this weak point of 1 H-MRI, rabbit stomachs were examined by 19 F-MRI using 50% FTPA emulsion. We also examined the stability of 50% FTPA emulsion in the stomach and its absorption from the gastrointestinal tract. We found that 50% FTPA emulsion was very stable at pH 1.5, and only a very small amount was absorbed. A rabbit (weighing 2 kg) was anesthetized, and 100 ml of 50% FTPA emulsion was infused into the stomach by catheter. 19 F-MRI was performed in this rabbit using a 2 T superconducting MRI system designed for human use, and clear pictures of the stomach were obtained. From our results we conclude that 19 F-MRI of the stomach using 50% FTPA emulsion is of practical value. (author)
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Meszlényi, Regina J; Buza, Krisztian; Vidnyánszky, Zoltán
2017-01-01
Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classification called connectome-convolutional neural network (CCNN). Our results on simulated datasets and a publicly available dataset for amnestic mild cognitive impairment classification demonstrate that our CCNN model can efficiently distinguish between subject groups. We also show that the connectome-convolutional network is capable to combine information from diverse functional connectivity metrics and that models using a combination of different connectivity descriptors are able to outperform classifiers using only one metric. From this flexibility follows that our proposed CCNN model can be easily adapted to a wide range of connectome based classification or regression tasks, by varying which connectivity descriptor combinations are used to train the network.
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Khoram, Nafiseh
2014-08-01
We propose an efficient numerical technique for calibrating the mathematical model that describes the singleevent related brain response when fMRI measurements are given. This method employs a regularized Newton technique in conjunction with a Kalman filtering procedure. We have applied this method to estimate the biophysiological parameters of the Balloon model that describes the hemodynamic brain responses. Illustrative results obtained with both synthetic and real fMRI measurements are presented. © 2014 IEEE.
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Singh, Sadhana; Modi, Shilpi; Goyal, Satnam; Kaur, Prabhjot; Singh, Namita; Bhatia, Triptish; Deshpande, Smita N; Khushu, Subash
2015-01-01
Empathy deficit is a core feature of schizophrenia which may lead to social dysfunction. The present study was carried out to investigate functional and structural abnormalities associated with empathy in patients with schizophrenia using functional magnetic resonance imaging (fMRI) and voxel-based morphometry (VBM). A sample of 14 schizophrenia patients and 14 healthy control subjects matched for age, sex and education were examined with structural high-resolution T1-weighted MRI; fMRI image...
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Molina, Juliana; Amaro, Edson; da Rocha, Liana Guerra Sanches; Jorge, Liliana; Santos, Flavia Heloisa; Len, Claudio A.
2017-01-01
Background Studies on functional magnetic resonance imaging (fMRI) have shown that adults with musculoskeletal pain syndromes tolerate smaller amount of pressure (pain) as well as differences in brain activation patterns in areas related to pain.The objective of this study was to evaluate, through fMRI, the brain activation in adolescents with idiopathic musculoskeletal pain (IMP) while performing an experimental paradigm of pain. Methods The study included 10 consecutive adolescents with idi...
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Controlling an avatar by thought using real-time fMRI
Cohen, Ori; Koppel, Moshe; Malach, Rafael; Friedman, Doron
2014-06-01
Objective. We have developed a brain-computer interface (BCI) system based on real-time functional magnetic resonance imaging (fMRI) with virtual reality feedback. The advantage of fMRI is the relatively high spatial resolution and the coverage of the whole brain; thus we expect that it may be used to explore novel BCI strategies, based on new types of mental activities. However, fMRI suffers from a low temporal resolution and an inherent delay, since it is based on a hemodynamic response rather than electrical signals. Thus, our objective in this paper was to explore whether subjects could perform a BCI task in a virtual environment using our system, and how their performance was affected by the delay. Approach. The subjects controlled an avatar by left-hand, right-hand and leg motion or imagery. The BCI classification is based on locating the regions of interest (ROIs) related with each of the motor classes, and selecting the ROI with maximum average values online. The subjects performed a cue-based task and a free-choice task, and the analysis includes evaluation of the performance as well as subjective reports. Main results. Six subjects performed the task with high accuracy when allowed to move their fingers and toes, and three subjects achieved high accuracy using imagery alone. In the cue-based task the accuracy was highest 8-12 s after the trigger, whereas in the free-choice task the subjects performed best when the feedback was provided 6 s after the trigger. Significance. We show that subjects are able to perform a navigation task in a virtual environment using an fMRI-based BCI, despite the hemodynamic delay. The same approach can be extended to other mental tasks and other brain areas.
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Hallquist, Michael N.; Hwang, Kai; Luna, Beatriz
2013-01-01
Recent resting-state functional connectivity fMRI (RS-fcMRI) research has demonstrated that head motion during fMRI acquisition systematically influences connectivity estimates despite bandpass filtering and nuisance regression, which are intended to reduce such nuisance variability. We provide evidence that the effects of head motion and other nuisance signals are poorly controlled when the fMRI time series are bandpass-filtered but the regressors are unfiltered, resulting in the inadvertent...
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Directory of Open Access Journals (Sweden)
Shanshan eLi
2016-01-01
Full Text Available Independent Component analysis (ICA is a widely used technique for separating signals that have been mixed together. In this manuscript, we propose a novel ICA algorithm using density estimation and maximum likelihood, where the densities of the signals are estimated via p-spline based histogram smoothing and the mixing matrix is simultaneously estimated using an optimization algorithm. The algorithm is exceedingly simple, easy to implement and blind to the underlying distributions of the source signals. To relax the identically distributed assumption in the density function, a modified algorithm is proposed to allow for different density functions on different regions. The performance of the proposed algorithm is evaluated in different simulation settings. For illustration, the algorithm is applied to a research investigation with a large collection of resting state fMRI datasets. The results show that the algorithm successfully recovers the established brain networks.
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Power, Jonathan D; Plitt, Mark; Gotts, Stephen J; Kundu, Prantik; Voon, Valerie; Bandettini, Peter A; Martin, Alex
2018-02-27
"Functional connectivity" techniques are commonplace tools for studying brain organization. A critical element of these analyses is to distinguish variance due to neurobiological signals from variance due to nonneurobiological signals. Multiecho fMRI techniques are a promising means for making such distinctions based on signal decay properties. Here, we report that multiecho fMRI techniques enable excellent removal of certain kinds of artifactual variance, namely, spatially focal artifacts due to motion. By removing these artifacts, multiecho techniques reveal frequent, large-amplitude blood oxygen level-dependent (BOLD) signal changes present across all gray matter that are also linked to motion. These whole-brain BOLD signals could reflect widespread neural processes or other processes, such as alterations in blood partial pressure of carbon dioxide (pCO 2 ) due to ventilation changes. By acquiring multiecho data while monitoring breathing, we demonstrate that whole-brain BOLD signals in the resting state are often caused by changes in breathing that co-occur with head motion. These widespread respiratory fMRI signals cannot be isolated from neurobiological signals by multiecho techniques because they occur via the same BOLD mechanism. Respiratory signals must therefore be removed by some other technique to isolate neurobiological covariance in fMRI time series. Several methods for removing global artifacts are demonstrated and compared, and were found to yield fMRI time series essentially free of motion-related influences. These results identify two kinds of motion-associated fMRI variance, with different physical mechanisms and spatial profiles, each of which strongly and differentially influences functional connectivity patterns. Distance-dependent patterns in covariance are nearly entirely attributable to non-BOLD artifacts.
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Directory of Open Access Journals (Sweden)
Chelsea eEkstrand
2016-03-01
Full Text Available Herein we report on a patient with a WHO Grade III astrocytoma in the right insular region in close proximity to the internal capsule who underwent a right frontotemporal craniotomy. Total gross resection of insular gliomas remains surgically challenging based on the possibility of damage to the corticospinal tracts. However, maximizing the extent of resection has been shown to decrease future adverse outcomes. Thus, the goal of such surgeries should focus on maximizing extent of resection while minimizing possible adverse outcomes. In this case, pre-surgical planning included integration of functional magnetic resonance imaging (fMRI and diffusion tensor imaging (DTI, to localize motor and sensory pathways. Novel fMRI tasks were individually developed for the patient to maximize both somatosensory and motor activation simultaneously in areas in close proximity to the tumor. Information obtained was used to optimize resection trajectory and extent, facilitating gross total resection of the astrocytoma. Across all three motor-sensory tasks administered, fMRI revealed an area of interest just superior and lateral to the astrocytoma. Further, DTI analyses showed displacement of the corona radiata around the superior dorsal surface of the astrocytoma, extending in the direction of the activation found using fMRI. Taking into account these results, a transcortical superior temporal gyrus surgical approach was chosen in order to avoid the area of interest identified by fMRI and DTI. Total gross resection was achieved and minor post-surgical motor and sensory deficits were temporary. This case highlights the utility of comprehensive pre-surgical planning, including fMRI and DTI, to maximize surgical outcomes on a case-by-case basis.
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Combining task-evoked and spontaneous activity to improve pre-operative brain mapping with fMRI.
Fox, Michael D; Qian, Tianyi; Madsen, Joseph R; Wang, Danhong; Li, Meiling; Ge, Manling; Zuo, Huan-Cong; Groppe, David M; Mehta, Ashesh D; Hong, Bo; Liu, Hesheng
2016-01-01
Noninvasive localization of brain function is used to understand and treat neurological disease, exemplified by pre-operative fMRI mapping prior to neurosurgical intervention. The principal approach for generating these maps relies on brain responses evoked by a task and, despite known limitations, has dominated clinical practice for over 20years. Recently, pre-operative fMRI mapping based on correlations in spontaneous brain activity has been demonstrated, however this approach has its own limitations and has not seen widespread clinical use. Here we show that spontaneous and task-based mapping can be performed together using the same pre-operative fMRI data, provide complimentary information relevant for functional localization, and can be combined to improve identification of eloquent motor cortex. Accuracy, sensitivity, and specificity of our approach are quantified through comparison with electrical cortical stimulation mapping in eight patients with intractable epilepsy. Broad applicability and reproducibility of our approach are demonstrated through prospective replication in an independent dataset of six patients from a different center. In both cohorts and every individual patient, we see a significant improvement in signal to noise and mapping accuracy independent of threshold, quantified using receiver operating characteristic curves. Collectively, our results suggest that modifying the processing of fMRI data to incorporate both task-based and spontaneous activity significantly improves functional localization in pre-operative patients. Because this method requires no additional scan time or modification to conventional pre-operative data acquisition protocols it could have widespread utility. Copyright © 2015. Published by Elsevier Inc.
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Evidence for bilateral involvement in idiom comprehension : An fMRI study
Zempleni, Monika-Zita; Haverkort, Marco; Renken, Remco; Stowe, Laurie A.
2007-01-01
The goal of the current study was to identify the neural substrate of idiom comprehension using fMRI. Idioms are familiar, fixed expressions whose meaning is not dependent on the literal interpretation of the component words. We presented literally plausible idioms in a sentence forcing a figurative
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The insula is not specifically involved in disgust processing: an fMRI study.
Schienle, A; Stark, R; Walter, B; Blecker, C; Ott, U; Kirsch, P; Sammer, G; Vaitl, D
2002-11-15
fMRI studies have shown that the perception of facial disgust expressions specifically activates the insula. The present fMRI study investigated whether this structure is also involved in the processing of visual stimuli depicting non-mimic disgust elicitors compared to fear-inducing and neutral scenes. Twelve female subjects were scanned while viewing alternating blocks of 40 disgust-inducing, 40 fear-inducing and 40 affectively neutral pictures, shown for 1.5 s each. Afterwards, affective ratings were assessed. The disgust pictures, rated as highly repulsive, induced activation in the insula, the amygdala, the orbitofrontal and occipito-temporal cortex. Since during the fear condition the insula was also involved, our findings do not fit the idea of the insula as a specific disgust processor.
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De Angelis, Vittoria; De Martino, Federico; Moerel, Michelle; Santoro, Roberta; Hausfeld, Lars; Formisano, Elia
2017-11-13
Pitch is a perceptual attribute related to the fundamental frequency (or periodicity) of a sound. So far, the cortical processing of pitch has been investigated mostly using synthetic sounds. However, the complex harmonic structure of natural sounds may require different mechanisms for the extraction and analysis of pitch. This study investigated the neural representation of pitch in human auditory cortex using model-based encoding and decoding analyses of high field (7 T) functional magnetic resonance imaging (fMRI) data collected while participants listened to a wide range of real-life sounds. Specifically, we modeled the fMRI responses as a function of the sounds' perceived pitch height and salience (related to the fundamental frequency and the harmonic structure respectively), which we estimated with a computational algorithm of pitch extraction (de Cheveigné and Kawahara, 2002). First, using single-voxel fMRI encoding, we identified a pitch-coding region in the antero-lateral Heschl's gyrus (HG) and adjacent superior temporal gyrus (STG). In these regions, the pitch representation model combining height and salience predicted the fMRI responses comparatively better than other models of acoustic processing and, in the right hemisphere, better than pitch representations based on height/salience alone. Second, we assessed with model-based decoding that multi-voxel response patterns of the identified regions are more informative of perceived pitch than the remainder of the auditory cortex. Further multivariate analyses showed that complementing a multi-resolution spectro-temporal sound representation with pitch produces a small but significant improvement to the decoding of complex sounds from fMRI response patterns. In sum, this work extends model-based fMRI encoding and decoding methods - previously employed to examine the representation and processing of acoustic sound features in the human auditory system - to the representation and processing of a relevant
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Lifescience Database Archive (English)
Full Text Available List Contact us Yeast Interacting Proteins Database Database Description General information of database Database... name Yeast Interacting Proteins Database Alternative name - DOI 10.18908/lsdba.nbdc00742-000 Creator C...-ken 277-8561 Tel: +81-4-7136-3989 FAX: +81-4-7136-3979 E-mail : Database classif...s cerevisiae Taxonomy ID: 4932 Database description Information on interactions and related information obta...l Acad Sci U S A. 2001 Apr 10;98(8):4569-74. Epub 2001 Mar 13. External Links: Original website information Database
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Yoo, Do Hyeon; Shin, Wook-Geun; Lee, Jaekook; Yeom, Yeon Soo; Kim, Chan Hyeong; Chang, Byung-Uck; Min, Chul Hee
2017-11-01
After the Fukushima accident in Japan, the Korean Government implemented the "Act on Protective Action Guidelines Against Radiation in the Natural Environment" to regulate unnecessary radiation exposure to the public. However, despite the law which came into effect in July 2012, an appropriate method to evaluate the equivalent and effective doses from naturally occurring radioactive material (NORM) in consumer products is not available. The aim of the present study is to develop and validate an effective dose coefficient database enabling the simple and correct evaluation of the effective dose due to the usage of NORM-added consumer products. To construct the database, we used a skin source method with a computational human phantom and Monte Carlo (MC) simulation. For the validation, the effective dose was compared between the database using interpolation method and the original MC method. Our result showed a similar equivalent dose across the 26 organs and a corresponding average dose between the database and the MC calculations of database with sufficient accuracy. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Directory of Open Access Journals (Sweden)
Cristina Rosazza
2018-06-01
Full Text Available Objective: Mechanisms of motor plasticity are critical to maintain motor functions after cerebral damage. This study explores the mechanisms of motor reorganization occurring before and after surgery in four patients with drug-refractory epilepsy candidate to disconnective surgery.Methods: We studied four patients with early damage, who underwent tailored hemispheric surgery in adulthood, removing the cortical motor areas and disconnecting the corticospinal tract (CST from the affected hemisphere. Motor functions were assessed clinically, with functional MRI (fMRI tasks of arm and leg movement and Diffusion Tensor Imaging (DTI before and after surgery with assessments of up to 3 years. Quantifications of fMRI motor activations and DTI fractional anisotropy (FA color maps were performed to assess the lateralization of motor network. We hypothesized that lateralization of motor circuits assessed preoperatively with fMRI and DTI was useful to evaluate the motor outcome in these patients.Results: In two cases preoperative DTI-tractography did not reconstruct the CST, and FA-maps were strongly asymmetric. In the other two cases, the affected CST appeared reduced compared to the contralateral one, with modest asymmetry in the FA-maps. fMRI showed different degrees of lateralization of the motor network and the SMA of the intact hemisphere was mostly engaged in all cases. After surgery, patients with a strongly lateralized motor network showed a stable performance. By contrast, a patient with a more bilateral pattern showed worsening of the upper limb function. For all cases, fMRI activations shifted to the intact hemisphere. Structural alterations of motor circuits, observed with FA values, continued beyond 1 year after surgery.Conclusion: In our case series fMRI and DTI could track the longitudinal reorganization of motor functions. In these four patients the more the paretic limbs recruited the intact hemisphere in primary motor and associative
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Rosazza, Cristina; Deleo, Francesco; D'Incerti, Ludovico; Antelmi, Luigi; Tringali, Giovanni; Didato, Giuseppe; Bruzzone, Maria G; Villani, Flavio; Ghielmetti, Francesco
2018-01-01
Objective: Mechanisms of motor plasticity are critical to maintain motor functions after cerebral damage. This study explores the mechanisms of motor reorganization occurring before and after surgery in four patients with drug-refractory epilepsy candidate to disconnective surgery. Methods: We studied four patients with early damage, who underwent tailored hemispheric surgery in adulthood, removing the cortical motor areas and disconnecting the corticospinal tract (CST) from the affected hemisphere. Motor functions were assessed clinically, with functional MRI (fMRI) tasks of arm and leg movement and Diffusion Tensor Imaging (DTI) before and after surgery with assessments of up to 3 years. Quantifications of fMRI motor activations and DTI fractional anisotropy (FA) color maps were performed to assess the lateralization of motor network. We hypothesized that lateralization of motor circuits assessed preoperatively with fMRI and DTI was useful to evaluate the motor outcome in these patients. Results: In two cases preoperative DTI-tractography did not reconstruct the CST, and FA-maps were strongly asymmetric. In the other two cases, the affected CST appeared reduced compared to the contralateral one, with modest asymmetry in the FA-maps. fMRI showed different degrees of lateralization of the motor network and the SMA of the intact hemisphere was mostly engaged in all cases. After surgery, patients with a strongly lateralized motor network showed a stable performance. By contrast, a patient with a more bilateral pattern showed worsening of the upper limb function. For all cases, fMRI activations shifted to the intact hemisphere. Structural alterations of motor circuits, observed with FA values, continued beyond 1 year after surgery. Conclusion: In our case series fMRI and DTI could track the longitudinal reorganization of motor functions. In these four patients the more the paretic limbs recruited the intact hemisphere in primary motor and associative areas, the
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Lifescience Database Archive (English)
Full Text Available List Contact us Trypanosomes Database Update History of This Database Date Update contents 2014/05/07 The co...ntact information is corrected. The features and manner of utilization of the database are corrected. 2014/02/04 Trypanosomes Databas...e English archive site is opened. 2011/04/04 Trypanosomes Database ( http://www.tan...paku.org/tdb/ ) is opened. About This Database Database Description Download Lice...nse Update History of This Database Site Policy | Contact Us Update History of This Database - Trypanosomes Database | LSDB Archive ...
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LHCb Conditions Database Operation Assistance Systems
Shapoval, Illya
2012-01-01
The Conditions Database of the LHCb experiment (CondDB) provides versioned, time dependent geometry and conditions data for all LHCb data processing applications (simulation, high level trigger, reconstruction, analysis) in a heterogeneous computing environment ranging from user laptops to the HLT farm and the Grid. These different use cases impose front-end support for multiple database technologies (Oracle and SQLite are used). Sophisticated distribution tools are required to ensure timely and robust delivery of updates to all environments. The content of the database has to be managed to ensure that updates are internally consistent and externally compatible with multiple versions of the physics application software. In this paper we describe three systems that we have developed to address these issues: - an extension to the automatic content validation done by the “Oracle Streams” replication technology, to trap cases when the replication was unsuccessful; - an automated distribution process for the S...
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A Transactional Asynchronous Replication Scheme for Mobile Database Systems
Institute of Scientific and Technical Information of China (English)
丁治明; 孟小峰; 王珊
2002-01-01
In mobile database systems, mobility of users has a significant impact on data replication. As a result, the various replica control protocols that exist today in traditional distributed and multidatabase environments are no longer suitable. To solve this problem, a new mobile database replication scheme, the Transaction-Level Result-Set Propagation (TLRSP)model, is put forward in this paper. The conflict detection and resolution strategy based on TLRSP is discussed in detail, and the implementation algorithm is proposed. In order to compare the performance of the TLRSP model with that of other mobile replication schemes, we have developed a detailed simulation model. Experimental results show that the TLRSP model provides an efficient support for replicated mobile database systems by reducing reprocessing overhead and maintaining database consistency.
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Alink, Arjen; Krugliak, Alexandra; Walther, Alexander; Kriegeskorte, Nikolaus
2013-01-01
The orientation of a large grating can be decoded from V1 functional magnetic resonance imaging (fMRI) data, even at low resolution (3-mm isotropic voxels). This finding has suggested that columnar-level neuronal information might be accessible to fMRI at 3T. However, orientation decodability might alternatively arise from global orientation-preference maps. Such global maps across V1 could result from bottom-up processing, if the preferences of V1 neurons were biased toward particular orientations (e.g., radial from fixation, or cardinal, i.e., vertical or horizontal). Global maps could also arise from local recurrent or top-down processing, reflecting pre-attentive perceptual grouping, attention spreading, or predictive coding of global form. Here we investigate whether fMRI orientation decoding with 2-mm voxels requires (a) globally coherent orientation stimuli and/or (b) global-scale patterns of V1 activity. We used opposite-orientation gratings (balanced about the cardinal orientations) and spirals (balanced about the radial orientation), along with novel patch-swapped variants of these stimuli. The two stimuli of a patch-swapped pair have opposite orientations everywhere (like their globally coherent parent stimuli). However, the two stimuli appear globally similar, a patchwork of opposite orientations. We find that all stimulus pairs are robustly decodable, demonstrating that fMRI orientation decoding does not require globally coherent orientation stimuli. Furthermore, decoding remained robust after spatial high-pass filtering for all stimuli, showing that fine-grained components of the fMRI patterns reflect visual orientations. Consistent with previous studies, we found evidence for global radial and vertical preference maps in V1. However, these were weak or absent for patch-swapped stimuli, suggesting that global preference maps depend on globally coherent orientations and might arise through recurrent or top-down processes related to the perception of
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Hayes, Scott M; Hayes, Jasmeet P; Williams, Victoria J; Liu, Huiting; Verfaellie, Mieke
2017-06-01
Older adults (OA), relative to young adults (YA), exhibit age-related alterations in functional Magnetic Resonance Imaging (fMRI) activity during associative encoding, which contributes to deficits in source memory. Yet, there are remarkable individual differences in brain health and memory performance among OA. Cardiorespiratory fitness (CRF) is one individual difference factor that may attenuate brain aging, and thereby contribute to enhanced source memory in OA. To examine this possibility, 26 OA and 31 YA completed a treadmill-based exercise test to evaluate CRF (peak VO 2 ) and fMRI to examine brain activation during a face-name associative encoding task. Our results indicated that in OA, peak VO 2 was positively associated with fMRI activity during associative encoding in multiple regions including bilateral prefrontal cortex, medial frontal cortex, bilateral thalamus and left hippocampus. Next, a conjunction analysis was conducted to assess whether CRF influenced age-related differences in fMRI activation. We classified OA as high or low CRF and compared their activation to YA. High fit OA (HFOA) showed fMRI activation more similar to YA than low fit OA (LFOA) (i.e., reduced age-related differences) in multiple regions including thalamus, posterior and prefrontal cortex. Conversely, in other regions, primarily in prefrontal cortex, HFOA, but not LFOA, demonstrated greater activation than YA (i.e., increased age-related differences). Further, fMRI activity in these brain regions was positively associated with source memory among OA, with a mediation model demonstrating that associative encoding activation in medial frontal cortex indirectly influenced the relationship between peak VO 2 and subsequent source memory performance. These results indicate that CRF may contribute to neuroplasticity among OA, reducing age-related differences in some brain regions, consistent with the brain maintenance hypothesis, but accentuating age-differences in other regions
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Malfait, D; Tucholka, A; Mendizabal, S; Tremblay, J; Poulin, C; Oskoui, M; Srour, M; Carmant, L; Major, P; Lippé, S
2015-11-01
Children with benign epilepsy with centro-temporal spikes (BECTS) often have language problems. Abnormal epileptic activity is found in central and temporal brain regions, which are involved in reading and semantic and syntactic comprehension. Using functional magnetic resonance imaging (fMRI), we examined reading networks in BECTS children with a new sentence reading comprehension task involving semantic and syntactic processing. Fifteen children with BECTS (age=11y 1m ± 16 m; 12 boys) and 18 healthy controls (age=11 y 8m ± 20 m; 11 boys) performed an fMRI reading comprehension task in which they read a pair of syntactically complex sentences and decided whether the target sentence (the second sentence in the pair) was true or false with respect to the first sentence. All children also underwent an exhaustive neuropsychological assessment. We demonstrated weaknesses in several cognitive domains in BECTS children. During the sentence reading fMRI task, left inferior frontal regions and bilateral temporal areas were activated in BECTS children and healthy controls. However, additional brain regions such as the left hippocampus and precuneus were activated in BECTS children. Moreover, specific activation was found in the left caudate and putamen in BECTS children but not in healthy controls. Cognitive results and accuracy during the fMRI task were associated with specific brain activation patterns. BECTS children recruited a wider network to perform the fMRI sentence reading comprehension task, with specific activation in the left dorsal striatum. BECTS cognitive performance differently predicted functional activation in frontal and temporal regions compared to controls, suggesting differences in brain network organisation that contribute to reading comprehension. Crown Copyright © 2015. Published by Elsevier B.V. All rights reserved.
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Directory of Open Access Journals (Sweden)
Castagna A
2011-10-01
Full Text Available Salvatore Rinaldi1,2, Vania Fontani1, Alessandro Castagna1 1Department of Neuro-Psycho-Physio Pathology, Rinaldi Fontani Institute, Florence, Italy; 2Medical School of Occupational Medicine, University of Florence, Florence, Italy Purpose: Radioelectric asymmetric brain stimulation technology with its treatment protocols has shown efficacy in various psychiatric disorders. The aim of this work was to highlight the mechanisms by which these positive effects are achieved. The current study was conducted to determine whether a single 500-millisecond radioelectric asymmetric conveyor (REAC brain stimulation pulse (BSP, applied to the ear, can effect a modification of brain activity that is detectable using functional magnetic resonance imaging (fMRI. Methods: Ten healthy volunteers, six females and four males, underwent fMRI during a simple finger-tapping motor task before and after receiving a single 500-millisecond REAC-BSP. Results: The fMRI results indicate that the average variation in task-induced encephalic activation patterns is lower in subjects following the single REAC pulse. Conclusion: The current report demonstrates that a single REAC-BSP is sufficient to modulate brain activity in awake subjects, able to be measured using fMRI. These initial results open new perspectives into the understanding of the effects of weak and brief radio pulses upon brain activity, and provide the basis for further indepth studies using REAC-BSP and fMRI. Keywords: fMRI, brain stimulation, brain modulation, REAC, neuropsychiatric treatments
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Unsupervised segmentation of task activated regions in fmRI
DEFF Research Database (Denmark)
Røge, Rasmus; Madsen, Kristoffer Hougaard; Schmidt, Mikkel Nørgaard
2015-01-01
Functional Magnetic Resonance Imaging has become a central measuring modality to quantify functional activiation of the brain in both task and rest. Most analysis used to quantify functional activation requires supervised approaches as employed in statistical parametric mapping (SPM) to extract...... framework for the analysis of task fMRI and resting-state data in general where strong knowledge of how the task induces a BOLD response is missing....
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Directory of Open Access Journals (Sweden)
Guillaume Chanel
2016-01-01
Full Text Available Multivariate pattern analysis (MVPA has been applied successfully to task-based and resting-based fMRI recordings to investigate which neural markers distinguish individuals with autistic spectrum disorders (ASD from controls. While most studies have focused on brain connectivity during resting state episodes and regions of interest approaches (ROI, a wealth of task-based fMRI datasets have been acquired in these populations in the last decade. This calls for techniques that can leverage information not only from a single dataset, but from several existing datasets that might share some common features and biomarkers. We propose a fully data-driven (voxel-based approach that we apply to two different fMRI experiments with social stimuli (faces and bodies. The method, based on Support Vector Machines (SVMs and Recursive Feature Elimination (RFE, is first trained for each experiment independently and each output is then combined to obtain a final classification output. Second, this RFE output is used to determine which voxels are most often selected for classification to generate maps of significant discriminative activity. Finally, to further explore the clinical validity of the approach, we correlate phenotypic information with obtained classifier scores. The results reveal good classification accuracy (range between 69% and 92.3%. Moreover, we were able to identify discriminative activity patterns pertaining to the social brain without relying on a priori ROI definitions. Finally, social motivation was the only dimension which correlated with classifier scores, suggesting that it is the main dimension captured by the classifiers. Altogether, we believe that the present RFE method proves to be efficient and may help identifying relevant biomarkers by taking advantage of acquired task-based fMRI datasets in psychiatric populations.
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Chanel, Guillaume; Pichon, Swann; Conty, Laurence; Berthoz, Sylvie; Chevallier, Coralie; Grèzes, Julie
2015-01-01
Multivariate pattern analysis (MVPA) has been applied successfully to task-based and resting-based fMRI recordings to investigate which neural markers distinguish individuals with autistic spectrum disorders (ASD) from controls. While most studies have focused on brain connectivity during resting state episodes and regions of interest approaches (ROI), a wealth of task-based fMRI datasets have been acquired in these populations in the last decade. This calls for techniques that can leverage information not only from a single dataset, but from several existing datasets that might share some common features and biomarkers. We propose a fully data-driven (voxel-based) approach that we apply to two different fMRI experiments with social stimuli (faces and bodies). The method, based on Support Vector Machines (SVMs) and Recursive Feature Elimination (RFE), is first trained for each experiment independently and each output is then combined to obtain a final classification output. Second, this RFE output is used to determine which voxels are most often selected for classification to generate maps of significant discriminative activity. Finally, to further explore the clinical validity of the approach, we correlate phenotypic information with obtained classifier scores. The results reveal good classification accuracy (range between 69% and 92.3%). Moreover, we were able to identify discriminative activity patterns pertaining to the social brain without relying on a priori ROI definitions. Finally, social motivation was the only dimension which correlated with classifier scores, suggesting that it is the main dimension captured by the classifiers. Altogether, we believe that the present RFE method proves to be efficient and may help identifying relevant biomarkers by taking advantage of acquired task-based fMRI datasets in psychiatric populations. PMID:26793434
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Task and task-free fMRI reproducibility comparison for motor network identification
Kristo, G.; Rutten, G.J.; Raemaekers, M.; de Gelder, B.; Rombouts, S.A.R.B.; Ramsey, N.F.
2014-01-01
Test-retest reliability of individual functional magnetic resonance imaging (fMRI) results is of importance in clinical practice and longitudinal experiments. While several studies have investigated reliability of task-induced motor network activation, less is known about the reliability of the
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DEFF Research Database (Denmark)
Henningsson, S.; Madsen, Kristoffer Hougaard; Pinborg, A.
2015-01-01
resonance imaging (fMRI) to investigate if sex-steroid hormone manipulation with a gonadotropin-releasing hormone agonist (GnRHa) influences emotional processing. Fifty-six healthy women were investigated twice: at baseline (follicular phase of menstrual cycle) and 16 +/- 3 days post intervention. At both...... sessions, fMRI-scans during exposure to faces expressing fear, anger, happiness or no emotion, depressive symptom scores and estradiol levels were acquired. The fMRI analyses focused on regions of interest for emotional processing. As expected, GnRHa initially increased and subsequently reduced estradiol...
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Directory of Open Access Journals (Sweden)
Kirsten Labudda
2010-01-01
Full Text Available We aimed to study whether previously described impairment in decision making under risky conditions in patients with Parkinson's disease (PD is affected by deficits in using information about potential incentives or by processing feedback (in terms of fictitious gains and losses following each decision. Additionally, we studied whether the neural correlates of using explicit information in decision making under risk differ between PD patients and healthy subjects. We investigated ten cognitively intact PD patients and twelve healthy subjects with the Game of Dice Task (GDT to assess risky decision making, and with an fMRI paradigm to analyse the neural correlates of information integration in the deliberative decision phase. Behaviourally, PD patients showed selective impairment in the GDT but not on the fMRI task that did not include a feedback component. Healthy subjects exhibited lateral prefrontal, anterior cingulate and parietal activations when integrating decision-relevant information. Despite similar behavioural patterns on the fMRI task, patients exhibited reduced parietal activation. Behavioural results suggest that PD patients’ deficits in risky decision making are dominated by impaired feedback utilization not compensable by intact cognitive functions. Our fMRI results suggest similarities but also differences in neural correlates when using explicit information for the decision process, potentially indicating different strategy application even if the interfering feedback component is excluded.
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A wavelet method for modeling and despiking motion artifacts from resting-state fMRI time series.
Patel, Ameera X; Kundu, Prantik; Rubinov, Mikail; Jones, P Simon; Vértes, Petra E; Ersche, Karen D; Suckling, John; Bullmore, Edward T
2014-07-15
The impact of in-scanner head movement on functional magnetic resonance imaging (fMRI) signals has long been established as undesirable. These effects have been traditionally corrected by methods such as linear regression of head movement parameters. However, a number of recent independent studies have demonstrated that these techniques are insufficient to remove motion confounds, and that even small movements can spuriously bias estimates of functional connectivity. Here we propose a new data-driven, spatially-adaptive, wavelet-based method for identifying, modeling, and removing non-stationary events in fMRI time series, caused by head movement, without the need for data scrubbing. This method involves the addition of just one extra step, the Wavelet Despike, in standard pre-processing pipelines. With this method, we demonstrate robust removal of a range of different motion artifacts and motion-related biases including distance-dependent connectivity artifacts, at a group and single-subject level, using a range of previously published and new diagnostic measures. The Wavelet Despike is able to accommodate the substantial spatial and temporal heterogeneity of motion artifacts and can consequently remove a range of high and low frequency artifacts from fMRI time series, that may be linearly or non-linearly related to physical movements. Our methods are demonstrated by the analysis of three cohorts of resting-state fMRI data, including two high-motion datasets: a previously published dataset on children (N=22) and a new dataset on adults with stimulant drug dependence (N=40). We conclude that there is a real risk of motion-related bias in connectivity analysis of fMRI data, but that this risk is generally manageable, by effective time series denoising strategies designed to attenuate synchronized signal transients induced by abrupt head movements. The Wavelet Despiking software described in this article is freely available for download at www
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Introducing Alternative-Based Thresholding for Defining Functional Regions of Interest in fMRI
Directory of Open Access Journals (Sweden)
Jasper Degryse
2017-04-01
Full Text Available In fMRI research, one often aims to examine activation in specific functional regions of interest (fROIs. Current statistical methods tend to localize fROIs inconsistently, focusing on avoiding detection of false activation. Not missing true activation is however equally important in this context. In this study, we explored the potential of an alternative-based thresholding (ABT procedure, where evidence against the null hypothesis of no effect and evidence against a prespecified alternative hypothesis is measured to control both false positives and false negatives directly. The procedure was validated in the context of localizer tasks on simulated brain images and using a real data set of 100 runs per subject. Voxels categorized as active with ABT can be confidently included in the definition of the fROI, while inactive voxels can be confidently excluded. Additionally, the ABT method complements classic null hypothesis significance testing with valuable information by making a distinction between voxels that show evidence against both the null and alternative and voxels for which the alternative hypothesis cannot be rejected despite lack of evidence against the null.
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State-Space Analysis of Granger-Geweke Causality Measures with Application to fMRI.
Solo, Victor
2016-05-01
The recent interest in the dynamics of networks and the advent, across a range of applications, of measuring modalities that operate on different temporal scales have put the spotlight on some significant gaps in the theory of multivariate time series. Fundamental to the description of network dynamics is the direction of interaction between nodes, accompanied by a measure of the strength of such interactions. Granger causality and its associated frequency domain strength measures (GEMs) (due to Geweke) provide a framework for the formulation and analysis of these issues. In pursuing this setup, three significant unresolved issues emerge. First, computing GEMs involves computing submodels of vector time series models, for which reliable methods do not exist. Second, the impact of filtering on GEMs has never been definitively established. Third, the impact of downsampling on GEMs has never been established. In this work, using state-space methods, we resolve all these issues and illustrate the results with some simulations. Our analysis is motivated by some problems in (fMRI) brain imaging, to which we apply it, but it is of general applicability.
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Intrusive Memories of Distressing Information: An fMRI Study.
Directory of Open Access Journals (Sweden)
Eva Battaglini
Full Text Available Although intrusive memories are characteristic of many psychological disorders, the neurobiological underpinning of these involuntary recollections are largely unknown. In this study we used functional magentic resonance imaging (fMRI to identify the neural networks associated with encoding of negative stimuli that are subsequently experienced as intrusive memories. Healthy partipants (N = 42 viewed negative and neutral images during a visual/verbal processing task in an fMRI context. Two days later they were assessed on the Impact of Event Scale for occurrence of intrusive memories of the encoded images. A sub-group of participants who reported significant intrusions (n = 13 demonstrated stronger activation in the amygdala, bilateral ACC and parahippocampal gyrus during verbal encoding relative to a group who reported no intrusions (n = 13. Within-group analyses also revealed that the high intrusion group showed greater activity in the dorsomedial (dmPFC and dorsolateral prefrontal cortex (dlPFC, inferior frontal gyrus and occipital regions during negative verbal processing compared to neutral verbal processing. These results do not accord with models of intrusions that emphasise visual processing of information at encoding but are consistent with models that highlight the role of inhibitory and suppression processes in the formation of subsequent intrusive memories.
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POBE: A Computer Program for Optimal Design of Multi-Subject Blocked fMRI Experiments
Directory of Open Access Journals (Sweden)
Bärbel Maus
2014-01-01
Full Text Available For functional magnetic resonance imaging (fMRI studies, researchers can use multi-subject blocked designs to identify active brain regions for a certain stimulus type of interest. Before performing such an experiment, careful planning is necessary to obtain efficient stimulus effect estimators within the available financial resources. The optimal number of subjects and the optimal scanning time for a multi-subject blocked design with fixed experimental costs can be determined using optimal design methods. In this paper, the user-friendly computer program POBE 1.2 (program for optimal design of blocked experiments, version 1.2 is presented. POBE provides a graphical user interface for fMRI researchers to easily and efficiently design their experiments. The computer program POBE calculates the optimal number of subjects and the optimal scanning time for user specified experimental factors and model parameters so that the statistical efficiency is maximised for a given study budget. POBE can also be used to determine the minimum budget for a given power. Furthermore, a maximin design can be determined as efficient design for a possible range of values for the unknown model parameters. In this paper, the computer program is described and illustrated with typical experimental factors for a blocked fMRI experiment.
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fMRI responses to Jung's Word Association Test: implications for theory, treatment and research.
Petchkovsky, Leon; Petchkovsky, Michael; Morris, Philip; Dickson, Paul; Montgomery, Danielle; Dwyer, Jonathan; Burnett, Patrick
2013-06-01
Jung's Word Association Test was performed under fMRI conditions by 12 normal subjects. Pooled complexed responses were contrasted against pooled neutral ones. The fMRI activation pattern of this generic 'complexed response' was very strong (corrected Z scores ranging from 4.90 to 5.69). The activation pattern in each hemisphere includes mirror neurone areas that track 'otherness' (perspectival empathy), anterior insula (both self-awareness and emotional empathy), and cingulated gyrus (self-awareness and conflict-monitoring). These are the sites described by Siegel and colleagues as the 'resonance circuitry' in the brain which is central to mindfulness (awareness of self) and empathy (sense of the other), negotiations between self awareness and the 'internal other'. But there is also an interhemispheric dialogue. Within 3 seconds, the left hemisphere over-rides the right (at least in our normal subjects). Mindfulness and empathy are central to good psychotherapy, and complexes can be windows of opportunity if left-brain hegemony is resisted. This study sets foundations for further research: (i) QEEG studies (with their finer temporal resolution) of complexed responses in normal subjects (ii) QEEG and fMRI studies of complexed responses in other conditions, like schizophrenia, PTSD, disorders of self organization. © 2013, The Society of Analytical Psychology.
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National Geo-Database for Biofuel Simulations and Regional Analysis
Energy Technology Data Exchange (ETDEWEB)
Izaurralde, Roberto C.; Zhang, Xuesong; Sahajpal, Ritvik; Manowitz, David H.
2012-04-01
The goal of this project undertaken by GLBRC (Great Lakes Bioenergy Research Center) Area 4 (Sustainability) modelers is to develop a national capability to model feedstock supply, ethanol production, and biogeochemical impacts of cellulosic biofuels. The results of this project contribute to sustainability goals of the GLBRC; i.e. to contribute to developing a sustainable bioenergy economy: one that is profitable to farmers and refiners, acceptable to society, and environmentally sound. A sustainable bioenergy economy will also contribute, in a fundamental way, to meeting national objectives on energy security and climate mitigation. The specific objectives of this study are to: (1) develop a spatially explicit national geodatabase for conducting biofuel simulation studies; (2) model biomass productivity and associated environmental impacts of annual cellulosic feedstocks; (3) simulate production of perennial biomass feedstocks grown on marginal lands; and (4) locate possible sites for the establishment of cellulosic ethanol biorefineries. To address the first objective, we developed SENGBEM (Spatially Explicit National Geodatabase for Biofuel and Environmental Modeling), a 60-m resolution geodatabase of the conterminous USA containing data on: (1) climate, (2) soils, (3) topography, (4) hydrography, (5) land cover/ land use (LCLU), and (6) ancillary data (e.g., road networks, federal and state lands, national and state parks, etc.). A unique feature of SENGBEM is its 2008-2010 crop rotation data, a crucially important component for simulating productivity and biogeochemical cycles as well as land-use changes associated with biofuel cropping. We used the EPIC (Environmental Policy Integrated Climate) model to simulate biomass productivity and environmental impacts of annual and perennial cellulosic feedstocks across much of the USA on both croplands and marginal lands. We used data from LTER and eddy-covariance experiments within the study region to test the
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Switching the Fermilab Accelerator Control System to a relational database
International Nuclear Information System (INIS)
Shtirbu, S.
1993-01-01
The accelerator control system (open-quotes ACNETclose quotes) at Fermilab is using a made-in-house, Assembly language, database. The database holds device information, which is mostly used for finding out how to read/set devices and how to interpret alarms. This is a very efficient implementation, but it lacks the needed flexibility and forces applications to store data in private/shared files. This database is being replaced by an off-the-shelf relational database (Sybase 2 ). The major constraints on switching are the necessity to maintain/improve response time and to minimize changes to existing applications. Innovative methods are used to help achieve the required performance, and a layer seven gateway simulates the old database for existing programs. The new database is running on a DEC ALPHA/VMS platform, and provides better performance. The switch is also exposing problems with the data currently stored in the database, and is helping in cleaning up erroneous data. The flexibility of the new relational database is going to facilitate many new applications in the future (e.g. a 3D presentation of device location). The new database is expected to fully replace the old database during this summer's shutdown
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Hypercapnic normalization of BOLD fMRI: comparison across field strengths and pulse sequences
DEFF Research Database (Denmark)
Cohen, Eric R.; Rostrup, Egill; Sidaros, Karam
2004-01-01
to be more accurately localized and quantified based on changes in venous blood oxygenation alone. The normalized BOLD signal induced by the motor task was consistent across different magnetic fields and pulse sequences, and corresponded well with cerebral blood flow measurements. Our data suggest...... size, as well as experimental, such as pulse sequence and static magnetic field strength (B(0)). Thus, it is difficult to compare task-induced fMRI signals across subjects, field strengths, and pulse sequences. This problem can be overcome by normalizing the neural activity-induced BOLD fMRI response...... for global stimulation, subjects breathed a 5% CO(2) gas mixture. Under all conditions, voxels containing primarily large veins and those containing primarily active tissue (i.e., capillaries and small veins) showed distinguishable behavior after hypercapnic normalization. This allowed functional activity...
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An investigation of fMRI time series stationarity during motor sequence learning foot tapping tasks.
Muhei-aldin, Othman; VanSwearingen, Jessie; Karim, Helmet; Huppert, Theodore; Sparto, Patrick J; Erickson, Kirk I; Sejdić, Ervin
2014-04-30
Understanding complex brain networks using functional magnetic resonance imaging (fMRI) is of great interest to clinical and scientific communities. To utilize advanced analysis methods such as graph theory for these investigations, the stationarity of fMRI time series needs to be understood as it has important implications on the choice of appropriate approaches for the analysis of complex brain networks. In this paper, we investigated the stationarity of fMRI time series acquired from twelve healthy participants while they performed a motor (foot tapping sequence) learning task. Since prior studies have documented that learning is associated with systematic changes in brain activation, a sequence learning task is an optimal paradigm to assess the degree of non-stationarity in fMRI time-series in clinically relevant brain areas. We predicted that brain regions involved in a "learning network" would demonstrate non-stationarity and may violate assumptions associated with some advanced analysis approaches. Six blocks of learning, and six control blocks of a foot tapping sequence were performed in a fixed order. The reverse arrangement test was utilized to investigate the time series stationarity. Our analysis showed some non-stationary signals with a time varying first moment as a major source of non-stationarity. We also demonstrated a decreased number of non-stationarities in the third block as a result of priming and repetition. Most of the current literature does not examine stationarity prior to processing. The implication of our findings is that future investigations analyzing complex brain networks should utilize approaches robust to non-stationarities, as graph-theoretical approaches can be sensitive to non-stationarities present in data. Copyright © 2014 Elsevier B.V. All rights reserved.
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Buckner, R L; Koutstaal, W; Schacter, D L; Wagner, A D; Rosen, B R
1998-04-01
A number of recent functional imaging studies have identified brain areas activated during tasks involving episodic memory retrieval. The identification of such areas provides a foundation for targeted hypotheses regarding the more specific contributions that these areas make to episodic retrieval. As a beginning effort toward such an endeavor, whole-brain functional magnetic resonance imaging (fMRI) was used to examine 14 subjects during episodic word recognition in a block-designed fMRI experiment. Study conditions were manipulated by presenting either shallow or deep encoding tasks. This manipulation yielded two recognition conditions that differed with regard to retrieval effort and retrieval success: shallow encoding yielded low levels of recognition success with high levels of retrieval effort, and deep encoding yielded high levels of recognition success with low levels of effort. Many brain areas were activated in common by these two recognition conditions compared to a low-level fixation condition, including left and right prefrontal regions often detected during PET episodic retrieval paradigms (e.g., R. L. Buckner et al., 1996, J. Neurosci. 16, 6219-6235) thereby generalizing these findings to fMRI. Characterization of the activated regions in relation to the separate recognition conditions showed (1) bilateral anterior insular regions and a left dorsal prefrontal region were more active after shallow encoding, when retrieval demanded greatest effort, and (2) right anterior prefrontal cortex, which has been implicated in episodic retrieval, was most active during successful retrieval after deep encoding. We discuss these findings in relation to component processes involved in episodic retrieval and in the context of a companion study using event-related fMRI.
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Modelling large motion events in fMRI studies of patients with epilepsy
DEFF Research Database (Denmark)
Lemieux, Louis; Salek-Haddadi, Afraim; Lund, Torben E
2007-01-01
-positive activation. Head motion can lead to severe image degradation and result in false-positive activation and is usually worse in patients than in healthy subjects. We performed general linear model fMRI data analysis on simultaneous EEG-fMRI data acquired in 34 cases with focal epilepsy. Signal changes...... associated with large inter-scan motion events (head jerks) were modelled using modified design matrices that include 'scan nulling' regressors. We evaluated the efficacy of this approach by mapping the proportion of the brain for which F-tests across the additional regressors were significant. In 95......% of cases, there was a significant effect of motion in 50% of the brain or greater; for the scan nulling effect, the proportion was 36%; this effect was predominantly in the neocortex. We conclude that careful consideration of the motion-related effects in fMRI studies of patients with epilepsy is essential...
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Lin, Xiao; Zhou, Hongli; Dong, Guangheng; Du, Xiaoxia
2015-01-02
This study examined how Internet gaming disorder (IGD) subjects modulating reward and risk at a neural level under a probability-discounting task with functional magnetic resonance imaging (fMRI). Behavioral and imaging data were collected from 19 IGD subjects (22.2 ± 3.08 years) and 21 healthy controls (HC, 22.8 ± 3.5 years). Behavior results showed that IGD subjects prefer the probabilistic options to fixed ones and were associated with shorter reaction time, when comparing to HC. The fMRI results revealed that IGD subjects show decreased activation in the inferior frontal gyrus and the precentral gyrus when choosing the probabilistic options than HC. Correlations were also calculated between behavioral performances and brain activities in relevant brain regions. Both of the behavioral performance and fMRI results indicate that people with IGD show impaired risk evaluation, which might be the reason why IGD subjects continue playing online games despite the risks of widely known negative consequence. Copyright © 2014 Elsevier Inc. All rights reserved.
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Lifescience Database Archive (English)
Full Text Available List Contact us Arabidopsis Phenome Database Update History of This Database Date Update contents 2017/02/27 Arabidopsis Phenome Data...base English archive site is opened. - Arabidopsis Phenome Database (http://jphenom...e.info/?page_id=95) is opened. About This Database Database Description Download License Update History of This Database... Site Policy | Contact Us Update History of This Database - Arabidopsis Phenome Database | LSDB Archive ...
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International Nuclear Information System (INIS)
Yoshikawa, H.; Nakaya, K.; Wakabayashi, J.
1986-01-01
A new conversational simulation system is proposed which aims at effective re-utilization of software resources as module database, and conducting versatile simulations easily by automatic module integration with the help of user-friendly interfaces. The whole simulation system is composed of the four parts: master module library and pre-compiler system as the core system, while module database management system and simulation execution support system for the user interfaces. Basic methods employed in the system are mentioned with their knowledge representation and the relationship with the human information processing. An example practice of an LMFBR reactor dynamic simulation by the system demonstrated its capability to integrate a large simulation program and the related input/output files automatically by a single user
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Tensor-based fusion of EEG and FMRI to understand neurological changes in Schizophrenia
DEFF Research Database (Denmark)
Evrim, Acar Ataman; Levin-Schwartz, Yuri; Calhoun, Vince D.
2016-01-01
Neuroimaging modalities such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) provide information about neurological functions in complementary spatiotemporal resolutions; therefore, fusion of these modalities is expected to provide better understanding of brain...
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Estimation of the neuronal activation using fMRI data: An observer-based approach
Laleg-Kirati, Taous-Meriem; Arabi, Hossein; Tadjine, Mohamed; Zayane, Chadia
2013-01-01
This paper deals with the estimation of the neuronal activation and some unmeasured physiological information using the Blood Oxygenation Level Dependent (BOLD) signal measured using functional Magnetic Resonance Imaging (fMRI). We propose to use
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Reimann, Henning Matthias; Todiras, Mihail; Hodge, Russ; Huelnhagen, Till; Millward, Jason Michael; Turner, Robert; Seeliger, Erdmann; Bader, Michael; Pohlmann, Andreas; Niendorf, Thoralf
2018-05-15
The neuromatrix, or "pain matrix", is a network of cortical brain areas which is activated by noxious as well as salient somatosensory stimulation. This has been studied in mice and humans using blood oxygenation level-dependent (BOLD) fMRI. Here we demonstrate that BOLD effects observed in the murine neuromatrix in response to salient somatosensory stimuli are prone to reflect mean arterial blood pressure (MABP) changes, rather than neural activity. We show that a standard electrostimulus typically used in murine somatosensory fMRI can induce substantial elevations in MABP. Equivalent drug-induced MABP changes - without somatosensory stimulation - evoked BOLD patterns in the neuromatrix strikingly similar to those evoked by electrostimulation. This constitutes a serious caveat for murine fMRI. The regional specificity of these BOLD patterns can be attributed to the co-localization of the neuromatrix with large draining veins. Based on these findings we propose a cardiovascular support mechanism whereby abrupt elevations in MABP provide additional energy supply to the neuromatrix and other essential brain areas in fight-or-flight situations. Copyright © 2018 Elsevier Inc. All rights reserved.
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Refactoring databases evolutionary database design
Ambler, Scott W
2006-01-01
Refactoring has proven its value in a wide range of development projects–helping software professionals improve system designs, maintainability, extensibility, and performance. Now, for the first time, leading agile methodologist Scott Ambler and renowned consultant Pramodkumar Sadalage introduce powerful refactoring techniques specifically designed for database systems. Ambler and Sadalage demonstrate how small changes to table structures, data, stored procedures, and triggers can significantly enhance virtually any database design–without changing semantics. You’ll learn how to evolve database schemas in step with source code–and become far more effective in projects relying on iterative, agile methodologies. This comprehensive guide and reference helps you overcome the practical obstacles to refactoring real-world databases by covering every fundamental concept underlying database refactoring. Using start-to-finish examples, the authors walk you through refactoring simple standalone databas...
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Lifescience Database Archive (English)
Full Text Available List Contact us SKIP Stemcell Database Update History of This Database Date Update contents 2017/03/13 SKIP Stemcell Database... English archive site is opened. 2013/03/29 SKIP Stemcell Database ( https://www.skip.med.k...eio.ac.jp/SKIPSearch/top?lang=en ) is opened. About This Database Database Description Download License Update History of This Databa...se Site Policy | Contact Us Update History of This Database - SKIP Stemcell Database | LSDB Archive ...
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Andoh, J; Ferreira, M; Leppert, I R; Matsushita, R; Pike, B; Zatorre, R J
2017-02-15
Resting-state fMRI studies have become very important in cognitive neuroscience because they are able to identify BOLD fluctuations in brain circuits involved in motor, cognitive, or perceptual processes without the use of an explicit task. Such approaches have been fruitful when applied to various disordered populations, or to children or the elderly. However, insufficient attention has been paid to the consequences of the loud acoustic scanner noise associated with conventional fMRI acquisition, which could be an important confounding factor affecting auditory and/or cognitive networks in resting-state fMRI. Several approaches have been developed to mitigate the effects of acoustic noise on fMRI signals, including sparse sampling protocols and interleaved silent steady state (ISSS) acquisition methods, the latter being used only for task-based fMRI. Here, we developed an ISSS protocol for resting-state fMRI (rs-ISSS) consisting of rapid acquisition of a set of echo planar imaging volumes following each silent period, during which the steady state longitudinal magnetization was maintained with a train of relatively silent slice-selective excitation pulses. We evaluated the test-retest reliability of intensity and spatial extent of connectivity networks of fMRI BOLD signal across three different days for rs-ISSS and compared it with a standard resting-state fMRI (rs-STD). We also compared the strength and distribution of connectivity networks between rs-ISSS and rs-STD. We found that both rs-ISSS and rs-STD showed high reproducibility of fMRI signal across days. In addition, rs-ISSS showed a more robust pattern of functional connectivity within the somatosensory and motor networks, as well as an auditory network compared with rs-STD. An increased connectivity between the default mode network and the language network and with the anterior cingulate cortex (ACC) network was also found for rs-ISSS compared with rs-STD. Finally, region of interest analysis showed
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The GIOD Project-Globally Interconnected Object Databases
Bunn, J J; Newman, H B; Wilkinson, R P
2001-01-01
The GIOD (Globally Interconnected Object Databases) Project, a joint effort between Caltech and CERN, funded by Hewlett Packard Corporation, has investigated the use of WAN-distributed Object Databases and Mass Storage systems for LHC data. A prototype small- scale LHC data analysis center has been constructed using computing resources at Caltechs Centre for advanced Computing Research (CACR). These resources include a 256 CPU HP Exemplar of ~4600 SPECfp95, a 600 TByte High Performance Storage System (HPSS), and local/wide area links based on OC3 ATM. Using the exemplar, a large number of fully simulated CMS events were produced, and used to populate an object database with a complete schema for raw, reconstructed and analysis objects. The reconstruction software used for this task was based on early codes developed in preparation for the current CMS reconstruction program, ORCA. (6 refs).
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International Nuclear Information System (INIS)
Harrington, Greg S.; Tomaszewski Farias, Sarah; Buonocore, Michael H.; Yonelinas, Andrew P.
2006-01-01
The goal of the present study was to evaluate the inter- and intrasubject reproducibility of FMRI activation for three memory encoding tasks previously used in the context of presurgical functional mapping. The primary region of interest (ROI) was the medial temporal lobe (MTL). Comparative ROIs included the inferior frontal and fusiform gyri which are less affected by susceptibility-induced signal losses than the MTL regions. Eighteen subjects were scanned using three memory encoding paradigms: word-pair, pattern, and scene encoding. Nine subjects underwent repeat scanning. Intersubject reproducibility of FMRI activation was evaluated by examining the percent of subjects who showed activation within a given ROI and the range to which individual laterality indices (LIs) varied from the mean. Intrasubject test-retest reproducibility was evaluated by examining the LI test-retest correlation, the average difference between LIs from two separate imaging sessions, and concordance ratios of activation volumes (R volume and R overlap ). For scene encoding the reproducibility of activation volume and LIs within the MTL were as good as or better than the reproducibility within the fusiform and inferior frontal ROIs. For pattern encoding and word-pair encoding, the reproducibility of activation volume and LIs within the MTL tended to be worse compared to the fusiform and inferior frontal ROIs. The differences in FMRI reproducibility appeared more dependent on the task than the susceptibility effects. The results of this study suggest that FMRI-based assessment of the neural substrates of memory using a scene encoding task may be a useful clinical tool. (orig.)
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Energy Technology Data Exchange (ETDEWEB)
Harrington, Greg S. [Virginia Commonwealth University, Department of Radiology, Richmond, VA (United States); Tomaszewski Farias, Sarah [University of California at Davis, Department of Neurology, Sacramento (United States); Buonocore, Michael H. [University of California at Davis, Department of Radiology, Sacramento (United States); Yonelinas, Andrew P. [University of California at Davis, Department of Psychology, Davis (United States)
2006-07-15
The goal of the present study was to evaluate the inter- and intrasubject reproducibility of FMRI activation for three memory encoding tasks previously used in the context of presurgical functional mapping. The primary region of interest (ROI) was the medial temporal lobe (MTL). Comparative ROIs included the inferior frontal and fusiform gyri which are less affected by susceptibility-induced signal losses than the MTL regions. Eighteen subjects were scanned using three memory encoding paradigms: word-pair, pattern, and scene encoding. Nine subjects underwent repeat scanning. Intersubject reproducibility of FMRI activation was evaluated by examining the percent of subjects who showed activation within a given ROI and the range to which individual laterality indices (LIs) varied from the mean. Intrasubject test-retest reproducibility was evaluated by examining the LI test-retest correlation, the average difference between LIs from two separate imaging sessions, and concordance ratios of activation volumes (R{sub volume} and R{sub overlap}). For scene encoding the reproducibility of activation volume and LIs within the MTL were as good as or better than the reproducibility within the fusiform and inferior frontal ROIs. For pattern encoding and word-pair encoding, the reproducibility of activation volume and LIs within the MTL tended to be worse compared to the fusiform and inferior frontal ROIs. The differences in FMRI reproducibility appeared more dependent on the task than the susceptibility effects. The results of this study suggest that FMRI-based assessment of the neural substrates of memory using a scene encoding task may be a useful clinical tool. (orig.)
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Suzuki, Hideaki; Sumiyoshi, Akira; Kawashima, Ryuta; Shimokawa, Hiroaki
2013-01-01
Myocardial ischemia in the anterior wall of the left ventricule (LV) and in the inferior wall and/or right ventricle (RV) shows different manifestations that can be explained by the different innervations of cardiac afferent nerves. However, it remains unclear whether information from different areas of the heart, such as the LV and RV, are differently processed in the brain. In this study, we investigated the brain regions that process information from the LV or RV using cardiac electrical stimulation and functional magnetic resonance imaging (fMRI) in anesthetized rats because the combination of these two approaches cannot be used in humans. An electrical stimulation catheter was inserted into the LV or RV (n = 12 each). Brain fMRI scans were recorded during LV or RV stimulation (9 Hz and 0.3 ms width) over 10 blocks consisting of alternating periods of 2 mA for 30 sec followed by 0.2 mA for 60 sec. The validity of fMRI signals was confirmed by first and second-level analyses and temporal profiles. Increases in fMRI signals were observed in the anterior cingulate cortex and the right somatosensory cortex under LV stimulation. In contrast, RV stimulation activated the right somatosensory cortex, which was identified more anteriorly compared with LV stimulation but did not activate the anterior cingulate cortex. This study provides the first evidence for differences in brain activation under LV and RV stimulation. These different brain processes may be associated with different clinical manifestations between anterior wall and inferoposterior wall and/or RV myocardial ischemia.
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Brain Activities Associated with Graphic Emoticons: An fMRI Study
Yuasa, Masahide; Saito, Keiichi; Mukawa, Naoki
In this paper, we describe the brain activities that are associated with graphic emoticons by using functional MRI (fMRI). We use various types of faces from abstract to photorealistic in computer network applications. A graphics emoticon is an abstract face in communication over computer network. In this research, we created various graphic emoticons for the fMRI study and the graphic emoticons were classified according to friendliness and level of arousal. We investigated the brain activities of participants who were required to evaluate the emotional valence of the graphic emoticons (happy or sad). The experimental results showed that not only the right inferior frontal gyrus and the cingulate gyrus, but also the inferior and middle temporal gyrus and the fusiform gyrus, were found to be activated during the experiment. Forthermore, it is possible that the activation of the right inferior frontal gyrus and the cingulate gyrus is related to the type of abstract face. Since the inferior and middle temporal gyrus were activated, even though the graphic emoticons are static, we may perceive graphic emoticons as dynamic and living agents. Moreover, it is believed that text and graphics emoticons play an important role in enriching communication among users.
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Benchmarking the CEMDATA07 database to model chemical degradation of concrete using GEMS and PHREEQC
International Nuclear Information System (INIS)
Jacques, Diederik; Wang, Lian; Martens, Evelien; Mallants, Dirk
2012-01-01
Thermodynamic equilibrium modelling of degradation of cement and concrete systems by chemically detrimental reactions as carbonation, sulphate attack and decalcification or leaching processes requires a consistent thermodynamic database with the relevant aqueous species, cement minerals and hydrates. The recent and consistent database CEMDATA07 is used as the basis in the studies of the Belgian near-surface disposal concept being developed by ONDRAF/NIRAS. The database is consistent with the thermodynamic data in the Nagra/PSI-Thermodynamic Database. When used with the GEMS thermodynamic code, thermodynamic modelling can be performed at temperatures different from the standard temperature of 25 C. GEMS calculates thermodynamic equilibrium by minimizing the Gibbs free energy of the system. Alternatively, thermodynamic equilibrium can also be calculated by solving a nonlinear system of mass balance equations and mass action equations, as is done in PHREEQC. A PHREEQC-database for the cement systems at temperatures different from 25 C is derived from the thermodynamic parameters and models from GEMS. A number of benchmark simulations using PHREEQC and GEM-Selektor were done to verify the implementation of the CEMDATA07 database in PHREEQC-databases. Simulations address a series of reactions that are relevant to the assessment of long-term cement and concrete durability. Verification calculations were performed for different systems with increasing complexity: CaO-SiO 2 -CO 2 , CaO-Al 2 O 3 -SO 3 -CO 2 , and CaO-SiO 2 -Al 2 O 3 -Fe 2 O 3 -MgO-SO 3 -CO 2 . Three types of chemical degradation processes were simulated: (1) carbonation by adding CO 2 to the bulk composition, (2) sulphate attack by adding SO 3 to the bulk composition, and (3) decalcification/leaching by putting the cement solid phase sequentially in contact with pure water. An excellent agreement between the simulations with GEMS and PHREEQC was obtained
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Advanced technologies for scalable ATLAS conditions database access on the grid
Basset, R; Dimitrov, G; Girone, M; Hawkings, R; Nevski, P; Valassi, A; Vaniachine, A; Viegas, F; Walker, R; Wong, A
2010-01-01
During massive data reprocessing operations an ATLAS Conditions Database application must support concurrent access from numerous ATLAS data processing jobs running on the Grid. By simulating realistic work-flow, ATLAS database scalability tests provided feedback for Conditions Db software optimization and allowed precise determination of required distributed database resources. In distributed data processing one must take into account the chaotic nature of Grid computing characterized by peak loads, which can be much higher than average access rates. To validate database performance at peak loads, we tested database scalability at very high concurrent jobs rates. This has been achieved through coordinated database stress tests performed in series of ATLAS reprocessing exercises at the Tier-1 sites. The goal of database stress tests is to detect scalability limits of the hardware deployed at the Tier-1 sites, so that the server overload conditions can be safely avoided in a production environment. Our analysi...
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Database design and database administration for a kindergarten
Vítek, Daniel
2009-01-01
The bachelor thesis deals with creation of database design for a standard kindergarten, installation of the designed database into the database system Oracle Database 10g Express Edition and demonstration of the administration tasks in this database system. The verification of the database was proved by a developed access application.
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N-back Working Memory Task: Meta-analysis of Normative fMRI Studies With Children.
Yaple, Zachary; Arsalidou, Marie
2018-05-07
The n-back task is likely the most popular measure of working memory for functional magnetic resonance imaging (fMRI) studies. Despite accumulating neuroimaging studies with the n-back task and children, its neural representation is still unclear. fMRI studies that used the n-back were compiled, and data from children up to 15 years (n = 260) were analyzed using activation likelihood estimation. Results show concordance in frontoparietal regions recognized for their role in working memory as well as regions not typically highlighted as part of the working memory network, such as the insula. Findings are discussed in terms of developmental methodology and potential contribution to developmental theories of cognition. © 2018 Society for Research in Child Development.
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HATCHES - a thermodynamic database and management system
International Nuclear Information System (INIS)
Cross, J.E.; Ewart, F.T.
1990-03-01
The Nirex Safety Assessment Research Programme has been compiling the thermodynamic data necessary to allow simulations of the aqueous behaviour of the elements important to radioactive waste disposal to be made. These data have been obtained from the literature, when available, and validated for the conditions of interest by experiment. In order to maintain these data in an accessible form and to satisfy quality assurance on all data used for assessments, a database has been constructed which resides on a personal computer operating under MS-DOS using the Ashton-Tate dBase III program. This database contains all the input data fields required by the PHREEQE program and, in addition, a body of text which describes the source of the data and the derivation of the PHREEQE input parameters from the source data. The HATCHES system consists of this database, a suite of programs to facilitate the searching and listing of data and a further suite of programs to convert the dBase III files to PHREEQE database format. (Author)
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An fMRI Study of the Social Competition in Healthy Subjects
Polosan, M.; Baciu, M.; Cousin, E.; Perrone, M.; Pichat, C.; Bougerol, T.
2011-01-01
Social interaction requires the ability to infer another person's mental state (Theory of Mind, ToM) and also executive functions. This fMRI study aimed to identify the cerebral correlates activated by ToM during a specific social interaction, the human-human competition. In this framework, we tested a conflict resolution task (Stroop) adapted to…
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Correlates of figure-ground segregation in fMRI.
Skiera, G; Petersen, D; Skalej, M; Fahle, M
2000-01-01
We investigated which correlates of figure-ground-segregation can be detected by means of functional magnetic resonance imaging (fMRI). Five subjects were scanned with a Siemens Vision 1.5 T system. Motion, colour, and luminance-defined checkerboards were presented with alternating control conditions containing one of the two features of the checkerboard. We find a segregation-specific activation in V1 for all subjects and all stimuli and conclude that neural mechanisms exist as early as in the primary visual cortex that are sensitive to figure-ground segregation.
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International Nuclear Information System (INIS)
Lenz, Michael; Linke, Yannick; Timmer, Jens; Schelter, Björn; Musso, Mariachristina; Weiller, Cornelius; Tüscher, Oliver
2011-01-01
An often addressed challenge in neuroscience research is the assignment of different tasks to specific brain regions. In many cases several brain regions are activated during a single task. Therefore, one is also interested in the temporal evolution of brain activity to infer causal relations between activated brain regions. These causal relations may be described by a directed, task specific network which consists of activated brain regions as vertices and directed edges. The edges describe the causal relations. Inference of the task specific brain network from measurements like electroencephalography (EEG) or functional magnetic resonance imaging (fMRI) is challenging, due to the low spatial resolution of the former and the low temporal resolution of the latter. Here, we present a simulation study investigating a possible combined analysis of simultaneously measured EEG and fMRI data to address the challenge specified above. A nonlinear state space model is used to distinguish between the underlying brain states and the (simulated) EEG/fMRI measurements. We make use of a modified unscented Kalman filter and a corresponding unscented smoother for the estimation of the underlying neural activity. Model parameters are estimated using an expectation-maximization algorithm, which exploits the partial linearity of our model. Inference of the brain network structure is then achieved using directed partial correlation, a measure for Granger causality. The results indicate that the convolution effect of the fMRI forward model imposes a big challenge for the parameter estimation and reduces the influence of the fMRI in combined EEG–fMRI models. It remains to be investigated whether other models or similar combinations of other modalities such as, e.g., EEG and magnetoencephalography can increase the profit of the promising idea of combining various modalities
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Cerebellar induced differential polyglot aphasia: A neurolinguistic and fMRI study.
Mariën, Peter; van Dun, Kim; Van Dormael, Johanna; Vandenborre, Dorien; Keulen, Stefanie; Manto, Mario; Verhoeven, Jo; Abutalebi, Jubin
2017-12-01
Research has shown that linguistic functions in the bilingual brain are subserved by similar neural circuits as in monolinguals, but with extra-activity associated with cognitive and attentional control. Although a role for the right cerebellum in multilingual language processing has recently been acknowledged, a potential role of the left cerebellum remains largely unexplored. This paper reports the clinical and fMRI findings in a strongly right-handed (late) multilingual patient who developed differential polyglot aphasia, ataxic dysarthria and a selective decrease in executive function due to an ischemic stroke in the left cerebellum. fMRI revealed that lexical-semantic retrieval in the unaffected L1 was predominantly associated with activations in the left cortical areas (left prefrontal area and left postcentral gyrus), while naming in two affected non-native languages recruited a significantly larger bilateral functional network, including the cerebellum. It is hypothesized that the left cerebellar insult resulted in decreased right prefrontal hemisphere functioning due to a loss of cerebellar impulses through the cerebello-cerebral pathways. Copyright © 2017 Elsevier Inc. All rights reserved.
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Adjudicating between face-coding models with individual-face fMRI responses.
Directory of Open Access Journals (Sweden)
Johan D Carlin
2017-07-01
Full Text Available The perceptual representation of individual faces is often explained with reference to a norm-based face space. In such spaces, individuals are encoded as vectors where identity is primarily conveyed by direction and distinctiveness by eccentricity. Here we measured human fMRI responses and psychophysical similarity judgments of individual face exemplars, which were generated as realistic 3D animations using a computer-graphics model. We developed and evaluated multiple neurobiologically plausible computational models, each of which predicts a representational distance matrix and a regional-mean activation profile for 24 face stimuli. In the fusiform face area, a face-space coding model with sigmoidal ramp tuning provided a better account of the data than one based on exemplar tuning. However, an image-processing model with weighted banks of Gabor filters performed similarly. Accounting for the data required the inclusion of a measurement-level population averaging mechanism that approximates how fMRI voxels locally average distinct neuronal tunings. Our study demonstrates the importance of comparing multiple models and of modeling the measurement process in computational neuroimaging.
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Resting-state fMRI study of patients with fragile X syndrome
Isanova, E.; Petrovskiy, E.; Savelov, A.; Yudkin, D.; Tulupov, A.
2017-08-01
The study aimed to assess the neural activity of different brain regions in patients with fragile X syndrome (FXS) and the healthy volunteers by resting-state functional magnetic resonance imaging (fMRI) on a 1.5 T MRI Achieva scanner (Philips). Results: The fMRI study showed a DMN of brain function in patients with FXS, as well as in the healthy volunteers. Furthermore, it was found that a default mode network of the brain in patients with FXS and healthy volunteers does not have statistically significant differences (p>0.05), which may indicate that the basal activity of neurons in patients with FXS is not reduced. In addition, we have found a significant (pright inferior parietal and right angular gyrus in the resting state in patients with FXS. Conclusion: New data of functional status of the brain in patients with FXS were received. The significant increase in the resting state functional connectivity within the right inferior parietal and right angular gyrus (p<0.001) in patients with FXS was found.
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Lifescience Database Archive (English)
Full Text Available List Contact us Open TG-GATEs Pathological Image Database Database Description General information of database Database... name Open TG-GATEs Pathological Image Database Alternative name - DOI 10.18908/lsdba.nbdc00954-0...iomedical Innovation 7-6-8, Saito-asagi, Ibaraki-city, Osaka 567-0085, Japan TEL:81-72-641-9826 Email: Database... classification Toxicogenomics Database Organism Taxonomy Name: Rattus norvegi... Article title: Author name(s): Journal: External Links: Original website information Database
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Functional connectivity analysis of fMRI data using parameterized regions-of-interest.
Weeda, W.D.; Waldorp, L.J.; Grasman, R.P.P.P.; van Gaal, S.; Huizenga, H.M.
2011-01-01
Connectivity analysis of fMRI data requires correct specification of regions-of-interest (ROIs). Selection of ROIs based on outcomes of a GLM analysis may be hindered by conservativeness of the multiple comparison correction, while selection based on brain anatomy may be biased due to inconsistent
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The olfactory deficit and fMRI in the Alzheimer's disease
International Nuclear Information System (INIS)
Yin Jianzhong; Wang Jianli; Yang Qingxian; Qi Ji
2008-01-01
Olfactory deficit is a common symptom occurring at the early stage of Alzheimer's disease, the purpose of this review is to summarize MRI research on olfactory deficit in the Alzheimer's disease and potential clinical relevance of fMRI in this area. (authors)
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Soddu, Andrea; Gómez, Francisco; Heine, Lizette; Di Perri, Carol; Bahri, Mohamed Ali; Voss, Henning U; Bruno, Marie-Aurélie; Vanhaudenhuyse, Audrey; Phillips, Christophe; Demertzi, Athena; Chatelle, Camille; Schrouff, Jessica; Thibaut, Aurore; Charland-Verville, Vanessa; Noirhomme, Quentin; Salmon, Eric; Tshibanda, Jean-Flory Luaba; Schiff, Nicholas D; Laureys, Steven
2016-01-01
The mildly invasive 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is a well-established imaging technique to measure 'resting state' cerebral metabolism. This technique made it possible to assess changes in metabolic activity in clinical applications, such as the study of severe brain injury and disorders of consciousness. We assessed the possibility of creating functional MRI activity maps, which could estimate the relative levels of activity in FDG-PET cerebral metabolic maps. If no metabolic absolute measures can be extracted, our approach may still be of clinical use in centers without access to FDG-PET. It also overcomes the problem of recognizing individual networks of independent component selection in functional magnetic resonance imaging (fMRI) resting state analysis. We extracted resting state fMRI functional connectivity maps using independent component analysis and combined only components of neuronal origin. To assess neuronality of components a classification based on support vector machine (SVM) was used. We compared the generated maps with the FDG-PET maps in 16 healthy controls, 11 vegetative state/unresponsive wakefulness syndrome patients and four locked-in patients. The results show a significant similarity with ρ = 0.75 ± 0.05 for healthy controls and ρ = 0.58 ± 0.09 for vegetative state/unresponsive wakefulness syndrome patients between the FDG-PET and the fMRI based maps. FDG-PET, fMRI neuronal maps, and the conjunction analysis show decreases in frontoparietal and medial regions in vegetative patients with respect to controls. Subsequent analysis in locked-in syndrome patients produced also consistent maps with healthy controls. The constructed resting state fMRI functional connectivity map points toward the possibility for fMRI resting state to estimate relative levels of activity in a metabolic map.
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Reliability database development for use with an object-oriented fault tree evaluation program
Heger, A. Sharif; Harringtton, Robert J.; Koen, Billy V.; Patterson-Hine, F. Ann
1989-01-01
A description is given of the development of a fault-tree analysis method using object-oriented programming. In addition, the authors discuss the programs that have been developed or are under development to connect a fault-tree analysis routine to a reliability database. To assess the performance of the routines, a relational database simulating one of the nuclear power industry databases has been constructed. For a realistic assessment of the results of this project, the use of one of existing nuclear power reliability databases is planned.
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Scale-Free Brain-Wave Music from Simultaneously EEG and fMRI Recordings
Lu, Jing; Wu, Dan; Yang, Hua; Luo, Cheng; Li, Chaoyi; Yao, Dezhong
2012-01-01
In the past years, a few methods have been developed to translate human EEG to music. In 2009, PloS One 4 e5915, we developed a method to generate scale-free brainwave music where the amplitude of EEG was translated to music pitch according to the power law followed by both of them, the period of an EEG waveform is translated directly to the duration of a note, and the logarithm of the average power change of EEG is translated to music intensity according to the Fechner's law. In this work, we proposed to adopt simultaneously-recorded fMRI signal to control the intensity of the EEG music, thus an EEG-fMRI music is generated by combining two different and simultaneous brain signals. And most importantly, this approach further realized power law for music intensity as fMRI signal follows it. Thus the EEG-fMRI music makes a step ahead in reflecting the physiological process of the scale-free brain. PMID:23166768
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Scale-free brain-wave music from simultaneously EEG and fMRI recordings.
Lu, Jing; Wu, Dan; Yang, Hua; Luo, Cheng; Li, Chaoyi; Yao, Dezhong
2012-01-01
In the past years, a few methods have been developed to translate human EEG to music. In 2009, PloS One 4 e5915, we developed a method to generate scale-free brainwave music where the amplitude of EEG was translated to music pitch according to the power law followed by both of them, the period of an EEG waveform is translated directly to the duration of a note, and the logarithm of the average power change of EEG is translated to music intensity according to the Fechner's law. In this work, we proposed to adopt simultaneously-recorded fMRI signal to control the intensity of the EEG music, thus an EEG-fMRI music is generated by combining two different and simultaneous brain signals. And most importantly, this approach further realized power law for music intensity as fMRI signal follows it. Thus the EEG-fMRI music makes a step ahead in reflecting the physiological process of the scale-free brain.
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Boichard, Jean-Luc; Brissebrat, Guillaume; Cloche, Sophie; Eymard, Laurence; Fleury, Laurence; Mastrorillo, Laurence; Moulaye, Oumarou; Ramage, Karim
2010-05-01
The AMMA project includes aircraft, ground-based and ocean measurements, an intensive use of satellite data and diverse modelling studies. Therefore, the AMMA database aims at storing a great amount and a large variety of data, and at providing the data as rapidly and safely as possible to the AMMA research community. In order to stimulate the exchange of information and collaboration between researchers from different disciplines or using different tools, the database provides a detailed description of the products and uses standardized formats. The AMMA database contains: - AMMA field campaigns datasets; - historical data in West Africa from 1850 (operational networks and previous scientific programs); - satellite products from past and future satellites, (re-)mapped on a regular latitude/longitude grid and stored in NetCDF format (CF Convention); - model outputs from atmosphere or ocean operational (re-)analysis and forecasts, and from research simulations. The outputs are processed as the satellite products are. Before accessing the data, any user has to sign the AMMA data and publication policy. This chart only covers the use of data in the framework of scientific objectives and categorically excludes the redistribution of data to third parties and the usage for commercial applications. Some collaboration between data producers and users, and the mention of the AMMA project in any publication is also required. The AMMA database and the associated on-line tools have been fully developed and are managed by two teams in France (IPSL Database Centre, Paris and OMP, Toulouse). Users can access data of both data centres using an unique web portal. This website is composed of different modules : - Registration: forms to register, read and sign the data use chart when an user visits for the first time - Data access interface: friendly tool allowing to build a data extraction request by selecting various criteria like location, time, parameters... The request can
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Jiménez, César; Carbonel, Carlos; Rojas, Joel
2018-04-01
We have implemented a numerical procedure to forecast the parameters of a tsunami, such as the arrival time of the front of the first wave and the maximum wave height in real and virtual tidal stations along the Peruvian coast, with this purpose a database of pre-computed synthetic tsunami waveforms (or Green functions) was obtained from numerical simulation of seismic unit sources (dimension: 50 × 50 km2) for subduction zones from southern Chile to northern Mexico. A bathymetry resolution of 30 arc-sec (approximately 927 m) was used. The resulting tsunami waveform is obtained from the superposition of synthetic waveforms corresponding to several seismic unit sources contained within the tsunami source geometry. The numerical procedure was applied to the Chilean tsunami of April 1, 2014. The results show a very good correlation for stations with wave amplitude greater than 1 m, in the case of the Arica tide station an error (from the maximum height of the observed and simulated waveform) of 3.5% was obtained, for Callao station the error was 12% and the largest error was in Chimbote with 53.5%, however, due to the low amplitude of the Chimbote wave (<1 m), the overestimated error, in this case, is not important for evacuation purposes. The aim of the present research is tsunami early warning, where speed is required rather than accuracy, so the results should be taken as preliminary.
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Primary Numbers Database for ATLAS Detector Description Parameters
Vaniachine, A; Malon, D; Nevski, P; Wenaus, T
2003-01-01
We present the design and the status of the database for detector description parameters in ATLAS experiment. The ATLAS Primary Numbers are the parameters defining the detector geometry and digitization in simulations, as well as certain reconstruction parameters. Since the detailed ATLAS detector description needs more than 10,000 such parameters, a preferred solution is to have a single verified source for all these data. The database stores the data dictionary for each parameter collection object, providing schema evolution support for object-based retrieval of parameters. The same Primary Numbers are served to many different clients accessing the database: the ATLAS software framework Athena, the Geant3 heritage framework Atlsim, the Geant4 developers framework FADS/Goofy, the generator of XML output for detector description, and several end-user clients for interactive data navigation, including web-based browsers and ROOT. The choice of the MySQL database product for the implementation provides addition...
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Khachaturian, Mark Haig
2010-01-01
Awake monkey fMRI and diffusion MRI combined with conventional neuroscience techniques has the potential to study the structural and functional neural network. The majority of monkey fMRI and diffusion MRI experiments are performed with single coils which suffer from severe EPI distortions which limit resolution. By constructing phased array coils for monkey MRI studies, gains in SNR and anatomical accuracy (i.e., reduction of EPI distortions) can be achieved using parallel imaging. The major challenges associated with constructing phased array coils for monkeys are the variation in head size and space constraints. Here, we apply phased array technology to a 4-channel phased array coil capable of improving the resolution and image quality of full brain awake monkey fMRI and diffusion MRI experiments. The phased array coil is that can adapt to different rhesus monkey head sizes (ages 4-8) and fits in the limited space provided by monkey stereotactic equipment and provides SNR gains in primary visual cortex and anatomical accuracy in conjunction with parallel imaging and improves resolution in fMRI experiments by a factor of 2 (1.25 mm to 1.0 mm isotropic) and diffusion MRI experiments by a factor of 4 (1.5 mm to 0.9 mm isotropic).
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Directory of Open Access Journals (Sweden)
Jacob Westfall
2017-03-01
Full Text Available Most functional magnetic resonance imaging (fMRI experiments record the brain’s responses to samples of stimulus materials (e.g., faces or words. Yet the statistical modeling approaches used in fMRI research universally fail to model stimulus variability in a manner that affords population generalization, meaning that researchers’ conclusions technically apply only to the precise stimuli used in each study, and cannot be generalized to new stimuli. A direct consequence of this stimulus-as-fixed-effect fallacy is that the majority of published fMRI studies have likely overstated the strength of the statistical evidence they report. Here we develop a Bayesian mixed model (the random stimulus model; RSM that addresses this problem, and apply it to a range of fMRI datasets. Results demonstrate considerable inflation (50-200% in most of the studied datasets of test statistics obtained from standard “summary statistics”-based approaches relative to the corresponding RSM models. We demonstrate how RSMs can be used to improve parameter estimates, properly control false positive rates, and test novel research hypotheses about stimulus-level variability in human brain responses.
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The neural basis for simulated drawing and the semantic implications.
Harrington, Greg S; Farias, Dana; Davis, Christine H
2009-03-01
This functional magnetic resonance imaging (fMRI) study of the mental simulation of drawing (1) investigated the neural substrates of drawing and (2) delineated the semantic aspects of drawing. The goal was to advance our understanding of how drawing a familiar object is linked to lexical semantics and therefore a viable method to use to rehabilitate aphasia. We hypothesized that the semantic aspects of drawing familiar objects compared to drawing non-objects would yield greater activation in the inferior temporal cortex and the inferior frontal cortex of the left hemisphere. To test this hypothesis, eight right-handed subjects performed an fMRI experiment that directly contrasted drawing familiar objects to non-objects using mental imagery. Simulated drawing recruited a large, distributed network of frontal, parietal, and temporal structures. In the contrast comparing drawing familiar objects to non-objects there was stronger activation in the left hemisphere within the inferior temporal, anterior inferior frontal, inferior parietal and superior frontal cortices. The activation within the inferior temporal cortex was associated with visual semantic processing and semantic mediated naming. We suggest that the anterior inferior frontal activation is linked to the inferior temporal cortex and is involved in the selection of specific semantic features of the object as well as retrieval of information regarding the perceptual aspects of the object.
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Functional connectivity in resting-state fMRI: Is linear correlation sufficient?
Czech Academy of Sciences Publication Activity Database
Hlinka, Jaroslav; Paluš, Milan; Vejmelka, Martin; Mantini, D.; Corbetta, M.
2011-01-01
Roč. 54, č. 3 (2011), s. 2218-2225 ISSN 1053-8119 R&D Projects: GA MŠk 7E08027 EU Projects: European Commission(XE) 200728 - BRAINSYNC Institutional research plan: CEZ:AV0Z10300504 Keywords : fMRI * functional connectivity * Gaussianity * nonlinearity * correlation * mutual information Subject RIV: FH - Neurology Impact factor: 5.895, year: 2011
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Protein Simulation Data in the Relational Model.
Simms, Andrew M; Daggett, Valerie
2012-10-01
High performance computing is leading to unprecedented volumes of data. Relational databases offer a robust and scalable model for storing and analyzing scientific data. However, these features do not come without a cost-significant design effort is required to build a functional and efficient repository. Modeling protein simulation data in a relational database presents several challenges: the data captured from individual simulations are large, multi-dimensional, and must integrate with both simulation software and external data sites. Here we present the dimensional design and relational implementation of a comprehensive data warehouse for storing and analyzing molecular dynamics simulations using SQL Server.
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Material specific lateralization of medial temporal lobe function: An fMRI investigation.
Dalton, Marshall A; Hornberger, Michael; Piguet, Olivier
2016-03-01
The theory of material specific lateralization of memory function posits that left and right MTL regions are asymmetrically involved in mnemonic processing of verbal and nonverbal material respectively. Lesion and functional imaging (fMRI) studies provide robust evidence for a left MTL asymmetry in the verbal memory domain. Evidence for a right MTL/nonverbal asymmetry is not as robust. A handful of fMRI studies have investigated this issue but have generally utilised nonverbal stimuli which are amenable to semantic elaboration. This fMRI study aimed to investigate the neural correlates of recognition memory processing in 20 healthy young adults (mean age = 26 years) for verbal stimuli and nonverbal stimuli that were specifically designed to minimize verbalisation. Analyses revealed that the neural correlates of recognition memory processing for verbal and nonverbal stimuli were differentiable and asymmetrically recruited the left and right MTL respectively. The right perirhinal cortex and hippocampus were preferentially involved in successful recognition memory of items devoid of semantic information. In contrast, the left anterior hippocampus was preferentially involved in successful recognition memory of stimuli which contained semantic meaning. These results suggest that the left MTL is preferentially involved in mnemonic processing of verbal/semantic information. In contrast, the right MTL is preferentially involved in visual/non-semantic mnemonic processing. We propose that during development, the left MTL becomes specialised for verbal mnemonic processing due to its proximity with left lateralised cortical language processing areas while visual/non-semantic mnemonic processing gets 'crowded out' to become predominantly, but not completely, the domain of the right MTL. © 2015 Wiley Periodicals, Inc.
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A novel approach to analyzing fMRI and SNP data via parallel independent component analysis
Liu, Jingyu; Pearlson, Godfrey; Calhoun, Vince; Windemuth, Andreas
2007-03-01
There is current interest in understanding genetic influences on brain function in both the healthy and the disordered brain. Parallel independent component analysis, a new method for analyzing multimodal data, is proposed in this paper and applied to functional magnetic resonance imaging (fMRI) and a single nucleotide polymorphism (SNP) array. The method aims to identify the independent components of each modality and the relationship between the two modalities. We analyzed 92 participants, including 29 schizophrenia (SZ) patients, 13 unaffected SZ relatives, and 50 healthy controls. We found a correlation of 0.79 between one fMRI component and one SNP component. The fMRI component consists of activations in cingulate gyrus, multiple frontal gyri, and superior temporal gyrus. The related SNP component is contributed to significantly by 9 SNPs located in sets of genes, including those coding for apolipoprotein A-I, and C-III, malate dehydrogenase 1 and the gamma-aminobutyric acid alpha-2 receptor. A significant difference in the presences of this SNP component is found between the SZ group (SZ patients and their relatives) and the control group. In summary, we constructed a framework to identify the interactions between brain functional and genetic information; our findings provide new insight into understanding genetic influences on brain function in a common mental disorder.
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Lifescience Database Archive (English)
Full Text Available List Contact us Yeast Interacting Proteins Database Update History of This Database Date Update contents 201...0/03/29 Yeast Interacting Proteins Database English archive site is opened. 2000/12/4 Yeast Interacting Proteins Database...( http://itolab.cb.k.u-tokyo.ac.jp/Y2H/ ) is released. About This Database Database Description... Download License Update History of This Database Site Policy | Contact Us Update History of This Database... - Yeast Interacting Proteins Database | LSDB Archive ...
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Yang, Lei; Tian, Jie; Wang, Xiaoxiang; Hu, Jin
2005-04-01
The comprehensive understanding of human emotion processing needs consideration both in the spatial distribution and the temporal sequencing of neural activity. The aim of our work is to identify brain regions involved in emotional recognition as well as to follow the time sequence in the millisecond-range resolution. The effect of activation upon visual stimuli in different gender by International Affective Picture System (IAPS) has been examined. Hemodynamic and electrophysiological responses were measured in the same subjects. Both fMRI and ERP study were employed in an event-related study. fMRI have been obtained with 3.0 T Siemens Magnetom whole-body MRI scanner. 128-channel ERP data were recorded using an EGI system. ERP is sensitive to millisecond changes in mental activity, but the source localization and timing is limited by the ill-posed 'inversed' problem. We try to investigate the ERP source reconstruction problem in this study using fMRI constraint. We chose ICA as a pre-processing step of ERP source reconstruction to exclude the artifacts and provide a prior estimate of the number of dipoles. The results indicate that male and female show differences in neural mechanism during emotion visual stimuli.
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Database Description - RMOS | LSDB Archive [Life Science Database Archive metadata
Lifescience Database Archive (English)
Full Text Available base Description General information of database Database name RMOS Alternative nam...arch Unit Shoshi Kikuchi E-mail : Database classification Plant databases - Rice Microarray Data and other Gene Expression Database...s Organism Taxonomy Name: Oryza sativa Taxonomy ID: 4530 Database description The Ric...19&lang=en Whole data download - Referenced database Rice Expression Database (RED) Rice full-length cDNA Database... (KOME) Rice Genome Integrated Map Database (INE) Rice Mutant Panel Database (Tos17) Rice Genome Annotation Database
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Linear mixed-effects modeling approach to FMRI group analysis.
Chen, Gang; Saad, Ziad S; Britton, Jennifer C; Pine, Daniel S; Cox, Robert W
2013-06-01
Conventional group analysis is usually performed with Student-type t-test, regression, or standard AN(C)OVA in which the variance-covariance matrix is presumed to have a simple structure. Some correction approaches are adopted when assumptions about the covariance structure is violated. However, as experiments are designed with different degrees of sophistication, these traditional methods can become cumbersome, or even be unable to handle the situation at hand. For example, most current FMRI software packages have difficulty analyzing the following scenarios at group level: (1) taking within-subject variability into account when there are effect estimates from multiple runs or sessions; (2) continuous explanatory variables (covariates) modeling in the presence of a within-subject (repeated measures) factor, multiple subject-grouping (between-subjects) factors, or the mixture of both; (3) subject-specific adjustments in covariate modeling; (4) group analysis with estimation of hemodynamic response (HDR) function by multiple basis functions; (5) various cases of missing data in longitudinal studies; and (6) group studies involving family members or twins. Here we present a linear mixed-effects modeling (LME) methodology that extends the conventional group analysis approach to analyze many complicated cases, including the six prototypes delineated above, whose analyses would be otherwise either difficult or unfeasible under traditional frameworks such as AN(C)OVA and general linear model (GLM). In addition, the strength of the LME framework lies in its flexibility to model and estimate the variance-covariance structures for both random effects and residuals. The intraclass correlation (ICC) values can be easily obtained with an LME model with crossed random effects, even at the presence of confounding fixed effects. The simulations of one prototypical scenario indicate that the LME modeling keeps a balance between the control for false positives and the sensitivity
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fMRI activation patterns in an analytic reasoning task: consistency with EEG source localization
Li, Bian; Vasanta, Kalyana C.; O'Boyle, Michael; Baker, Mary C.; Nutter, Brian; Mitra, Sunanda
2010-03-01
Functional magnetic resonance imaging (fMRI) is used to model brain activation patterns associated with various perceptual and cognitive processes as reflected by the hemodynamic (BOLD) response. While many sensory and motor tasks are associated with relatively simple activation patterns in localized regions, higher-order cognitive tasks may produce activity in many different brain areas involving complex neural circuitry. We applied a recently proposed probabilistic independent component analysis technique (PICA) to determine the true dimensionality of the fMRI data and used EEG localization to identify the common activated patterns (mapped as Brodmann areas) associated with a complex cognitive task like analytic reasoning. Our preliminary study suggests that a hybrid GLM/PICA analysis may reveal additional regions of activation (beyond simple GLM) that are consistent with electroencephalography (EEG) source localization patterns.
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Energy Technology Data Exchange (ETDEWEB)
Setyawan, Wahyu [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Nandipati, Giridhar [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Roche, Kenneth J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Univ. of Washington, Seattle, WA (United States); Heinisch, Howard L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Wirth, Brian D. [Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab., Oak Ridge, TN (United States); Kurtz, Richard J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
2015-07-01
Molecular dynamics simulations have been used to generate a comprehensive database of surviving defects due to displacement cascades in bulk tungsten. Twenty-one data points of primary knock-on atom (PKA) energies ranging from 100 eV (sub-threshold energy) to 100 keV (~780×Ed, where Ed = 128 eV is the average displacement threshold energy) have been completed at 300 K, 1025 K and 2050 K. Within this range of PKA energies, two regimes of power-law energy-dependence of the defect production are observed. A distinct power-law exponent characterizes the number of Frenkel pairs produced within each regime. The two regimes intersect at a transition energy which occurs at approximately 250×Ed. The transition energy also marks the onset of the formation of large self-interstitial atom (SIA) clusters (size 14 or more). The observed defect clustering behavior is asymmetric, with SIA clustering increasing with temperature, while the vacancy clustering decreases. This asymmetry increases with temperature such that at 2050 K (~0.5Tm) practically no large vacancy clusters are formed, meanwhile large SIA clusters appear in all simulations. The implication of such asymmetry on the long-term defect survival and damage accumulation is discussed. In addition, <100> {110} SIA loops are observed to form directly in the highest energy cascades, while vacancy <100> loops are observed to form at the lowest temperature and highest PKA energies, although the appearance of both the vacancy and SIA loops with Burgers vector of <100> type is relatively rare.
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Decoding Complex Cognitive States Online by Manifold Regularization in Real-Time fMRI
DEFF Research Database (Denmark)
Hansen, Toke Jansen; Hansen, Lars Kai; Madsen, Kristoffer Hougaard
2011-01-01
Human decision making is complex and influenced by many factors on multiple time scales, reflected in the numerous brain networks and connectivity patterns involved as revealed by fMRI. We address mislabeling issues in paradigms involving complex cognition, by considering a manifold regularizing...
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KALIMER database development (database configuration and design methodology)
International Nuclear Information System (INIS)
Jeong, Kwan Seong; Kwon, Young Min; Lee, Young Bum; Chang, Won Pyo; Hahn, Do Hee
2001-10-01
KALIMER Database is an advanced database to utilize the integration management for Liquid Metal Reactor Design Technology Development using Web Applicatins. KALIMER Design database consists of Results Database, Inter-Office Communication (IOC), and 3D CAD database, Team Cooperation system, and Reserved Documents, Results Database is a research results database during phase II for Liquid Metal Reactor Design Technology Develpment of mid-term and long-term nuclear R and D. IOC is a linkage control system inter sub project to share and integrate the research results for KALIMER. 3D CAD Database is s schematic design overview for KALIMER. Team Cooperation System is to inform team member of research cooperation and meetings. Finally, KALIMER Reserved Documents is developed to manage collected data and several documents since project accomplishment. This report describes the features of Hardware and Software and the Database Design Methodology for KALIMER
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Nakagawa, Y.; Kawahara, S.; Araki, F.; Matsuoka, D.; Ishikawa, Y.; Fujita, M.; Sugimoto, S.; Okada, Y.; Kawazoe, S.; Watanabe, S.; Ishii, M.; Mizuta, R.; Murata, A.; Kawase, H.
2017-12-01
Analyses of large ensemble data are quite useful in order to produce probabilistic effect projection of climate change. Ensemble data of "+2K future climate simulations" are currently produced by Japanese national project "Social Implementation Program on Climate Change Adaptation Technology (SI-CAT)" as a part of a database for Policy Decision making for Future climate change (d4PDF; Mizuta et al. 2016) produced by Program for Risk Information on Climate Change. Those data consist of global warming simulations and regional downscaling simulations. Considering that those data volumes are too large (a few petabyte) to download to a local computer of users, a user-friendly system is required to search and download data which satisfy requests of the users. We develop "a database system for near-future climate change projections" for providing functions to find necessary data for the users under SI-CAT. The database system for near-future climate change projections mainly consists of a relational database, a data download function and user interface. The relational database using PostgreSQL is a key function among them. Temporally and spatially compressed data are registered on the relational database. As a first step, we develop the relational database for precipitation, temperature and track data of typhoon according to requests by SI-CAT members. The data download function using Open-source Project for a Network Data Access Protocol (OPeNDAP) provides a function to download temporally and spatially extracted data based on search results obtained by the relational database. We also develop the web-based user interface for using the relational database and the data download function. A prototype of the database system for near-future climate change projections are currently in operational test on our local server. The database system for near-future climate change projections will be released on Data Integration and Analysis System Program (DIAS) in fiscal year 2017
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Hueschen, Richard M.
2011-01-01
A six degree-of-freedom, flat-earth dynamics, non-linear, and non-proprietary aircraft simulation was developed that is representative of a generic mid-sized twin-jet transport aircraft. The simulation was developed from a non-proprietary, publicly available, subscale twin-jet transport aircraft simulation using scaling relationships and a modified aerodynamic database. The simulation has an extended aerodynamics database with aero data outside the normal transport-operating envelope (large angle-of-attack and sideslip values). The simulation has representative transport aircraft surface actuator models with variable rate-limits and generally fixed position limits. The simulation contains a generic 40,000 lb sea level thrust engine model. The engine model is a first order dynamic model with a variable time constant that changes according to simulation conditions. The simulation provides a means for interfacing a flight control system to use the simulation sensor variables and to command the surface actuators and throttle position of the engine model.
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Specificity of Esthetic Experience for Artworks: An fMRI Study
Di Dio, Cinzia; Canessa, Nicola; Cappa, Stefano F.; Rizzolatti, Giacomo
2011-01-01
In a previous functional magnetic resonance imaging (fMRI) study, where we investigated the neural correlates of esthetic experience, we found that observing canonical sculptures, relative to sculptures whose proportions had been modified, produced the activation of a network that included the lateral occipital gyrus, precuneus, prefrontal areas, and, most interestingly, the right anterior insula. We interpreted this latter activation as the neural signature underpinning hedonic response during esthetic experience. With the aim of exploring whether this specific hedonic response is also present during the observation of non-art biological stimuli, in the present fMRI study we compared the activations associated with viewing masterpieces of classical sculpture with those produced by the observation of pictures of young athletes. The two stimulus-categories were matched on various factors, including body postures, proportion, and expressed dynamism. The stimuli were presented in two conditions: observation and esthetic judgment. The two stimulus-categories produced a rather similar global activation pattern. Direct comparisons between sculpture and real-body images revealed, however, relevant differences, among which the activation of right antero-dorsal insula during sculptures viewing only. Along with our previous data, this finding suggests that the hedonic state associated with activation of right dorsal anterior insula underpins esthetic experience for artworks. PMID:22121344
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Residual fMRI sensitivity for identity changes in acquired prosopagnosia.
Fox, Christopher J; Iaria, Giuseppe; Duchaine, Bradley C; Barton, Jason J S
2013-01-01
While a network of cortical regions contribute to face processing, the lesions in acquired prosopagnosia are highly variable, and likely result in different combinations of spared and affected regions of this network. To assess the residual functional sensitivities of spared regions in prosopagnosia, we designed a rapid event-related functional magnetic resonance imaging (fMRI) experiment that included pairs of faces with same or different identities and same or different expressions. By measuring the release from adaptation to these facial changes we determined the residual sensitivity of face-selective regions-of-interest. We tested three patients with acquired prosopagnosia, and all three of these patients demonstrated residual sensitivity for facial identity changes in surviving fusiform and occipital face areas of either the right or left hemisphere, but not in the right posterior superior temporal sulcus. The patients also showed some residual capabilities for facial discrimination with normal performance on the Benton Facial Recognition Test, but impaired performance on more complex tasks of facial discrimination. We conclude that fMRI can demonstrate residual processing of facial identity in acquired prosopagnosia, that this adaptation can occur in the same structures that show similar processing in healthy subjects, and further, that this adaptation may be related to behavioral indices of face perception.
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Residual fMRI sensitivity for identity changes in acquired prosopagnosia
Directory of Open Access Journals (Sweden)
Christopher J Fox
2013-10-01
Full Text Available While a network of cortical regions contribute to face processing, the lesions in acquired prosopagnosia are highly variable, and likely result in different combinations of spared and affected regions of this network. To assess the residual functional sensitivities of spared regions in prosopagnosia, we designed a rapid event-related functional magnetic resonance imaging (fMRI experiment that included pairs of faces with same or different identities and same or different expressions. By measuring the release from adaptation to these facial changes we determined the residual sensitivity of face-selective regions-of-interest. We tested three patients with acquired prosopagnosia, and all three of these patients demonstrated residual sensitivity for facial identity changes in surviving fusiform and occipital face areas of either the right or left hemisphere, but not in the right posterior superior temporal sulcus. The patients also showed some residual capabilities for facial discrimination with normal performance on the Benton Facial Recognition Test, but impaired performance on more complex tasks of facial discrimination. We conclude that fMRI can demonstrate residual processing of facial identity in acquired prosopagnosia, that this adaptation can occur in the same structures that show similar processing in healthy subjects, and further, that this adaptation may be related to behavioral indices of face perception.
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Time course based artifact identification for independent components of resting state fMRI
Directory of Open Access Journals (Sweden)
Christian eRummel
2013-05-01
Full Text Available In functional magnetic resonance imaging (fMRI coherent oscillations of the blood oxygen level dependent (BOLD signal can be detected. These arise when brain regions respond to external stimuli or are activated by tasks. The same networks have been characterized during wakeful rest when functional connectivity of the human brain is organized in generic resting state networks (RSN. Alterations of RSN emerge as neurobiological markers of pathological conditions such as altered mental state. In single-subject fMRI data the coherent components can be identified by blind source separation of the pre-processed BOLD data using spatial independent component analysis (ICA and related approaches. The resulting maps may represent physiological RSNs or may be due to various artifacts. In this methodological study, we propose a conceptually simple and fully automatic time course based filtering procedure to detect obvious artifacts in the ICA output for resting state fMRI. The filter is trained on six and tested on 29 healthy subjects, yielding mean filter accuracy, sensitivity and specificity of 0.80, 0.82 and 0.75 in out-of-sample tests. To estimate the impact of clearly artifactual single-subject components on group resting state studies we analyze unfiltered and filtered output with a second level ICA procedure. Although the automated filter does not reach performance values of visual analysis by human raters, we propose that resting state compatible analysis of ICA time courses could be very useful to complement the existing map or task/event oriented artifact classification algorithms.
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fMRI and brain activation after sport concussion: a tale of two cases
Directory of Open Access Journals (Sweden)
Michael G Hutchison
2014-04-01
Full Text Available Sport-related concussions are now recognized as a major public health concern: The number of participants in sport and recreation is growing, possibly playing their games faster, and there is heightened public awareness of injuries to some high-profile athletes. However, many clinicians still rely on subjective symptom reports for the clinical determination of recovery. Relying on subjective symptom reports can be dangerous, as it has been shown that some concussed athletes may downplay their symptoms. The use of neuropsychological (NP testing tools has enabled clinicians to measure the effects and extent of impairment following concussion more precisely, providing more objective metrics for determining recovery after concussion. Nevertheless, there is a remaining concern that brain abnormalities may exist beyond the point at which individuals achieve recovery in self-reported symptoms and cognition measured by NP testing. Our understanding of brain recovery after concussion is important not only from a neuroscience perspective, but also from the perspective of clinical decision making for safe return-to-play (RTP. A number of advanced neuroimaging tools, including blood oxygen level dependent (BOLD functional magnetic resonance imaging (fMRI, have independently yielded early information on these abnormal brain functions. In the two cases presented in this article, we report contrasting brain activation patterns and recovery profiles using fMRI. Importantly, fMRI was conducted using adapted versions of the most sensitive computerized NP tests administered in current clinical practice to determine impairments and recovery after sport-related concussion. One of the cases is consistent with the concept of lagging brain recovery.
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Directory of Open Access Journals (Sweden)
Honghui Yang
2010-10-01
Full Text Available We demonstrate a hybrid machine learning method to classify schizophrenia patients and healthy controls, using functional magnetic resonance imaging (fMRI and single nucleotide polymorphism (SNP data. The method consists of four stages: (1 SNPs with the most discriminating information between the healthy controls and schizophrenia patients are selected to construct a support vector machine ensemble (SNP-SVME. (2 Voxels in the fMRI map contributing to classification are selected to build another SVME (Voxel-SVME. (3 Components of fMRI activation obtained with independent component analysis (ICA are used to construct a single SVM classifier (ICA-SVMC. (4 The above three models are combined into a single module using a majority voting approach to make a final decision (Combined SNP-fMRI. The method was evaluated by a fully-validated leave-one-out method using 40 subjects (20 patients and 20 controls. The classification accuracy was: 0.74 for SNP-SVME, 0.82 for Voxel-SVME, 0.83 for ICA-SVMC, and 0.87 for Combined SNP-fMRI. Experimental results show that better classification accuracy was achieved by combining genetic and fMRI data than using either alone, indicating that genetic and brain function representing different, but partially complementary aspects, of schizophrenia etiopathology. This study suggests an effective way to reassess biological classification of individuals with schizophrenia, which is also potentially useful for identifying diagnostically important markers for the disorder.
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Database Description - SAHG | LSDB Archive [Life Science Database Archive metadata
Lifescience Database Archive (English)
Full Text Available base Description General information of database Database name SAHG Alternative nam...h: Contact address Chie Motono Tel : +81-3-3599-8067 E-mail : Database classification Structure Databases - ...e databases - Protein properties Organism Taxonomy Name: Homo sapiens Taxonomy ID: 9606 Database description... Links: Original website information Database maintenance site The Molecular Profiling Research Center for D...stration Not available About This Database Database Description Download License Update History of This Database Site Policy | Contact Us Database Description - SAHG | LSDB Archive ...
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Hjelmervik, Helene; Hausmann, Markus; Osnes, Berge; Westerhausen, René; Specht, Karsten
2014-01-01
To what degree resting state fMRI is stable or susceptible to internal mind states of the individual is currently an issue of debate. To address this issue, the present study focuses on sex differences and investigates whether resting state fMRI is stable in men and women or changes within relative short-term periods (i.e., across the menstrual cycle). Due to the fact that we recently reported menstrual cycle effects on cognitive control based on data collected during the same sessions, the current study is particularly interested in fronto-parietal resting state networks. Resting state fMRI was measured in sixteen women during three different cycle phases (menstrual, follicular, and luteal). Fifteen men underwent three sessions in corresponding time intervals. We used independent component analysis to identify four fronto-parietal networks. The results showed sex differences in two of these networks with women exhibiting higher functional connectivity in general, including the prefrontal cortex. Menstrual cycle effects on resting states were non-existent. It is concluded that sex differences in resting state fMRI might reflect sexual dimorphisms in the brain rather than transitory activating effects of sex hormones on the functional connectivity in the resting brain.
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Nuclear Data and Reaction Rate Databases in Nuclear Astrophysics
Lippuner, Jonas
2018-06-01
Astrophysical simulations and models require a large variety of micro-physics data, such as equation of state tables, atomic opacities, properties of nuclei, and nuclear reaction rates. Some of the required data is experimentally accessible, but the extreme conditions present in many astrophysical scenarios cannot be reproduced in the laboratory and thus theoretical models are needed to supplement the empirical data. Collecting data from various sources and making them available as a database in a unified format is a formidable task. I will provide an overview of the data requirements in astrophysics with an emphasis on nuclear astrophysics. I will then discuss some of the existing databases, the science they enable, and their limitations. Finally, I will offer some thoughts on how to design a useful database.
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Jang, Hojin; Plis, Sergey M; Calhoun, Vince D; Lee, Jong-Hwan
2017-01-15
Feedforward deep neural networks (DNNs), artificial neural networks with multiple hidden layers, have recently demonstrated a record-breaking performance in multiple areas of applications in computer vision and speech processing. Following the success, DNNs have been applied to neuroimaging modalities including functional/structural magnetic resonance imaging (MRI) and positron-emission tomography data. However, no study has explicitly applied DNNs to 3D whole-brain fMRI volumes and thereby extracted hidden volumetric representations of fMRI that are discriminative for a task performed as the fMRI volume was acquired. Our study applied fully connected feedforward DNN to fMRI volumes collected in four sensorimotor tasks (i.e., left-hand clenching, right-hand clenching, auditory attention, and visual stimulus) undertaken by 12 healthy participants. Using a leave-one-subject-out cross-validation scheme, a restricted Boltzmann machine-based deep belief network was pretrained and used to initialize weights of the DNN. The pretrained DNN was fine-tuned while systematically controlling weight-sparsity levels across hidden layers. Optimal weight-sparsity levels were determined from a minimum validation error rate of fMRI volume classification. Minimum error rates (mean±standard deviation; %) of 6.9 (±3.8) were obtained from the three-layer DNN with the sparsest condition of weights across the three hidden layers. These error rates were even lower than the error rates from the single-layer network (9.4±4.6) and the two-layer network (7.4±4.1). The estimated DNN weights showed spatial patterns that are remarkably task-specific, particularly in the higher layers. The output values of the third hidden layer represented distinct patterns/codes of the 3D whole-brain fMRI volume and encoded the information of the tasks as evaluated from representational similarity analysis. Our reported findings show the ability of the DNN to classify a single fMRI volume based on the
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Database Description - PSCDB | LSDB Archive [Life Science Database Archive metadata
Lifescience Database Archive (English)
Full Text Available abase Description General information of database Database name PSCDB Alternative n...rial Science and Technology (AIST) Takayuki Amemiya E-mail: Database classification Structure Databases - Protein structure Database...554-D558. External Links: Original website information Database maintenance site Graduate School of Informat...available URL of Web services - Need for user registration Not available About This Database Database Descri...ption Download License Update History of This Database Site Policy | Contact Us Database Description - PSCDB | LSDB Archive ...
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Database Description - ASTRA | LSDB Archive [Life Science Database Archive metadata
Lifescience Database Archive (English)
Full Text Available abase Description General information of database Database name ASTRA Alternative n...tics Journal Search: Contact address Database classification Nucleotide Sequence Databases - Gene structure,...3702 Taxonomy Name: Oryza sativa Taxonomy ID: 4530 Database description The database represents classified p...(10):1211-6. External Links: Original website information Database maintenance site National Institute of Ad... for user registration Not available About This Database Database Description Dow
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2010-11-01
subsections discuss the design of the simulations. 3.12.1 Lanchester5D Simulation A Lanchester simulation was developed to conduct performance...benchmarks using the WarpIV Kernel and HyperWarpSpeed. The Lanchester simulation contains a user-definable number of grid cells in which blue and red...forces engage in battle using Lanchester equations. Having a user-definable number of grid cells enables the simulation to be stressed with high entity
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The neural basis of event simulation: an FMRI study.
Directory of Open Access Journals (Sweden)
Yukihito Yomogida
Full Text Available Event simulation (ES is the situational inference process in which perceived event features such as objects, agents, and actions are associated in the brain to represent the whole situation. ES provides a common basis for various cognitive processes, such as perceptual prediction, situational understanding/prediction, and social cognition (such as mentalizing/trait inference. Here, functional magnetic resonance imaging was used to elucidate the neural substrates underlying important subdivisions within ES. First, the study investigated whether ES depends on different neural substrates when it is conducted explicitly and implicitly. Second, the existence of neural substrates specific to the future-prediction component of ES was assessed. Subjects were shown contextually related object pictures implying a situation and performed several picture-word-matching tasks. By varying task goals, subjects were made to infer the implied situation implicitly/explicitly or predict the future consequence of that situation. The results indicate that, whereas implicit ES activated the lateral prefrontal cortex and medial/lateral parietal cortex, explicit ES activated the medial prefrontal cortex, posterior cingulate cortex, and medial/lateral temporal cortex. Additionally, the left temporoparietal junction plays an important role in the future-prediction component of ES. These findings enrich our understanding of the neural substrates of the implicit/explicit/predictive aspects of ES-related cognitive processes.
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Calibrated fMRI for mapping absolute CMRO2: Practicalities and prospects.
Germuska, M; Wise, R G
2018-03-29
Functional magnetic resonance imaging (fMRI) is an essential workhorse of modern neuroscience, providing valuable insight into the functional organisation of the brain. The physiological mechanisms underlying the blood oxygenation level dependent (BOLD) effect are complex and preclude a straightforward interpretation of the signal. However, by employing appropriate calibration of the BOLD signal, quantitative measurements can be made of important physiological parameters including the absolute rate of cerebral metabolic oxygen consumption or oxygen metabolism (CMRO 2 ) and oxygen extraction (OEF). The ability to map such fundamental parameters has the potential to greatly expand the utility of fMRI and to broaden its scope of application in clinical research and clinical practice. In this review article we discuss some of the practical issues related to the calibrated-fMRI approach to the measurement of CMRO 2 . We give an overview of the necessary precautions to ensure high quality data acquisition, and explore some of the pitfalls and challenges that must be considered as it is applied and interpreted in a widening array of diseases and research questions. Copyright © 2018 Elsevier Inc. All rights reserved.
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Regional homogeneity of fMRI time series in autism spectrum disorders.
Shukla, Dinesh K; Keehn, Brandon; Müller, Ralph Axel
2010-05-26
Functional magnetic resonance imaging (fMRI) and functional connectivity MRI (fcMRI) studies of autism spectrum disorders (ASD) have suggested atypical patterns of activation and long-distance connectivity for diverse tasks and networks in ASD. We explored the regional homogeneity (ReHo) approach in ASD, which is analogous to conventional fcMRI, but focuses on local connectivity. FMRI data of 26 children with ASD and 29 typically developing (TD) children were acquired during continuous task performance (visual search). Effects of motion and task were removed and Kendall's coefficient of concordance (KCC) was computed, based on the correlation of the blood oxygen level dependent (BOLD) time series for each voxel and its six nearest neighbors. ReHo was lower in the ASD than the TD group in superior parietal and anterior prefrontal regions. Inverse effects of greater ReHo in the ASD group were detected in lateral and medial temporal regions, predominantly in the right hemisphere. Our findings suggest that ReHo is a sensitive measure for detecting cortical abnormalities in autism. However, impact of methodological factors (such as spatial resolution) on ReHo require further investigation. Published by Elsevier Ireland Ltd.
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Oberlin, Brandon G; Dzemidzic, Mario; Harezlak, Jaroslaw; Kudela, Maria A; Tran, Stella M; Soeurt, Christina M; Yoder, Karmen K; Kareken, David A
2016-09-01
Cue-evoked drug-seeking behavior likely depends on interactions between frontal activity and ventral striatal (VST) dopamine (DA) transmission. Using [(11) C]raclopride (RAC) positron emission tomography (PET), we previously demonstrated that beer flavor (absent intoxication) elicited VST DA release in beer drinkers, inferred by RAC displacement. Here, a subset of subjects from this previous RAC-PET study underwent a similar paradigm during functional magnetic resonance imaging (fMRI) to test how orbitofrontal cortex (OFC) and VST blood oxygenation level-dependent (BOLD) responses to beer flavor are related to VST DA release and motivation to drink. Male beer drinkers (n = 28, age = 24 ± 2, drinks/wk = 16 ± 10) from our previous PET study participated in a similar fMRI paradigm wherein subjects tasted their most frequently consumed brand of beer and Gatorade(®) (appetitive control). We tested for correlations between BOLD activation in fMRI and VST DA responses in PET, and drinking-related variables. Compared to Gatorade, beer flavor increased wanting and desire to drink, and induced BOLD responses in bilateral OFC and right VST. Wanting and desire to drink correlated with both right VST and medial OFC BOLD activation to beer flavor. Like the BOLD findings, beer flavor (relative to Gatorade) again induced right VST DA release in this fMRI subject subset, but there was no correlation between DA release and the magnitude of BOLD responses in frontal regions of interest. Both imaging modalities showed a right-lateralized VST response (BOLD and DA release) to a drug-paired conditioned stimulus, whereas fMRI BOLD responses in the VST and medial OFC also reflected wanting and desire to drink. The data suggest the possibility that responses to drug-paired cues may be rightward biased in the VST (at least in right-handed males) and that VST and OFC responses in this gustatory paradigm reflect stimulus wanting. Copyright © 2016 by the Research Society on
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One approach to design of speech emotion database
Uhrin, Dominik; Chmelikova, Zdenka; Tovarek, Jaromir; Partila, Pavol; Voznak, Miroslav
2016-05-01
This article describes a system for evaluating the credibility of recordings with emotional character. Sound recordings form Czech language database for training and testing systems of speech emotion recognition. These systems are designed to detect human emotions in his voice. The emotional state of man is useful in the security forces and emergency call service. Man in action (soldier, police officer and firefighter) is often exposed to stress. Information about the emotional state (his voice) will help to dispatch to adapt control commands for procedure intervention. Call agents of emergency call service must recognize the mental state of the caller to adjust the mood of the conversation. In this case, the evaluation of the psychological state is the key factor for successful intervention. A quality database of sound recordings is essential for the creation of the mentioned systems. There are quality databases such as Berlin Database of Emotional Speech or Humaine. The actors have created these databases in an audio studio. It means that the recordings contain simulated emotions, not real. Our research aims at creating a database of the Czech emotional recordings of real human speech. Collecting sound samples to the database is only one of the tasks. Another one, no less important, is to evaluate the significance of recordings from the perspective of emotional states. The design of a methodology for evaluating emotional recordings credibility is described in this article. The results describe the advantages and applicability of the developed method.
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Final Report on Atomic Database Project
International Nuclear Information System (INIS)
Yuan, J.; Gui, Z.; Moses, G.A.
2006-01-01
Atomic physics in hot dense plasmas is essential for understanding the radiative properties of plasmas either produced terrestrially such as in fusion energy research or in space such as the study of the core of the sun. Various kinds of atomic data are needed for spectrum analysis or for radiation hydrodynamics simulations. There are many atomic databases accessible publicly through the web, such as CHIANTI (an atomic database for spectroscopic diagnostics for astrophysical plasmas) from Naval Research Laboratory [1], collaborative development of TOPbase (The Opacity Project for astrophysically abundant elements) [2], NIST atomic spectra database from NIST [3], TOPS Opacities from Los Alamos National Laboratory [4], etc. Most of these databases are specific to astrophysics, which provide energy levels, oscillator strength f and photoionization cross sections for astrophysical elements ( Z=1-26). There are abundant spectrum data sources for spectral analysis of low Z elements. For opacities used for radiation transport, TOPS Opacities from LANL is the most valuable source. The database provides mixed opacities from element for H (Z=1) to Zn (Z=30) The data in TOPS Opacities is calculated by the code LEDCOP. In the Fusion Technology Institute, we also have developed several different models to calculate atomic data and opacities, such as the detailed term accounting model (DTA) and the unresolved transition array (UTA) model. We use the DTA model for low-Z materials since an enormous number of transitions need to be computed for medium or high-Z materials. For medium and high Z materials, we use the UTA model which simulates the enormous number of transitions by using a single line profile to represent a collection of transition arrays. These models have been implemented in our computing code JATBASE and RSSUTA. For plasma populations, two models are used in JATBASE, one is the local thermodynamic equilibrium (LTE) model and the second is the non-LTE model. For the
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Database Description - RPD | LSDB Archive [Life Science Database Archive metadata
Lifescience Database Archive (English)
Full Text Available ase Description General information of database Database name RPD Alternative name Rice Proteome Database...titute of Crop Science, National Agriculture and Food Research Organization Setsuko Komatsu E-mail: Database... classification Proteomics Resources Plant databases - Rice Organism Taxonomy Name: Oryza sativa Taxonomy ID: 4530 Database... description Rice Proteome Database contains information on protei...and entered in the Rice Proteome Database. The database is searchable by keyword,
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Database Description - PLACE | LSDB Archive [Life Science Database Archive metadata
Lifescience Database Archive (English)
Full Text Available abase Description General information of database Database name PLACE Alternative name A Database...Kannondai, Tsukuba, Ibaraki 305-8602, Japan National Institute of Agrobiological Sciences E-mail : Databas...e classification Plant databases Organism Taxonomy Name: Tracheophyta Taxonomy ID: 58023 Database...99, Vol.27, No.1 :297-300 External Links: Original website information Database maintenance site National In...- Need for user registration Not available About This Database Database Descripti
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Mechanistic Mathematical Modeling Tests Hypotheses of the Neurovascular Coupling in fMRI.
Directory of Open Access Journals (Sweden)
Karin Lundengård
2016-06-01
Full Text Available Functional magnetic resonance imaging (fMRI measures brain activity by detecting the blood-oxygen-level dependent (BOLD response to neural activity. The BOLD response depends on the neurovascular coupling, which connects cerebral blood flow, cerebral blood volume, and deoxyhemoglobin level to neuronal activity. The exact mechanisms behind this neurovascular coupling are not yet fully investigated. There are at least three different ways in which these mechanisms are being discussed. Firstly, mathematical models involving the so-called Balloon model describes the relation between oxygen metabolism, cerebral blood volume, and cerebral blood flow. However, the Balloon model does not describe cellular and biochemical mechanisms. Secondly, the metabolic feedback hypothesis, which is based on experimental findings on metabolism associated with brain activation, and thirdly, the neurotransmitter feed-forward hypothesis which describes intracellular pathways leading to vasoactive substance release. Both the metabolic feedback and the neurotransmitter feed-forward hypotheses have been extensively studied, but only experimentally. These two hypotheses have never been implemented as mathematical models. Here we investigate these two hypotheses by mechanistic mathematical modeling using a systems biology approach; these methods have been used in biological research for many years but never been applied to the BOLD response in fMRI. In the current work, model structures describing the metabolic feedback and the neurotransmitter feed-forward hypotheses were applied to measured BOLD responses in the visual cortex of 12 healthy volunteers. Evaluating each hypothesis separately shows that neither hypothesis alone can describe the data in a biologically plausible way. However, by adding metabolism to the neurotransmitter feed-forward model structure, we obtained a new model structure which is able to fit the estimation data and successfully predict new
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Database Description - JSNP | LSDB Archive [Life Science Database Archive metadata
Lifescience Database Archive (English)
Full Text Available base Description General information of database Database name JSNP Alternative nam...n Science and Technology Agency Creator Affiliation: Contact address E-mail : Database...sapiens Taxonomy ID: 9606 Database description A database of about 197,000 polymorphisms in Japanese populat...1):605-610 External Links: Original website information Database maintenance site Institute of Medical Scien...er registration Not available About This Database Database Description Download License Update History of This Database
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Database Description - RED | LSDB Archive [Life Science Database Archive metadata
Lifescience Database Archive (English)
Full Text Available ase Description General information of database Database name RED Alternative name Rice Expression Database...enome Research Unit Shoshi Kikuchi E-mail : Database classification Plant databases - Rice Database classifi...cation Microarray, Gene Expression Organism Taxonomy Name: Oryza sativa Taxonomy ID: 4530 Database descripti... Article title: Rice Expression Database: the gateway to rice functional genomics...nt Science (2002) Dec 7 (12):563-564 External Links: Original website information Database maintenance site
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A method for independent component graph analysis of resting-state fMRI
DEFF Research Database (Denmark)
de Paula, Demetrius Ribeiro; Ziegler, Erik; Abeyasinghe, Pubuditha M.
2017-01-01
Introduction Independent component analysis (ICA) has been extensively used for reducing task-free BOLD fMRI recordings into spatial maps and their associated time-courses. The spatially identified independent components can be considered as intrinsic connectivity networks (ICNs) of non-contiguou......Introduction Independent component analysis (ICA) has been extensively used for reducing task-free BOLD fMRI recordings into spatial maps and their associated time-courses. The spatially identified independent components can be considered as intrinsic connectivity networks (ICNs) of non......-contiguous regions. To date, the spatial patterns of the networks have been analyzed with techniques developed for volumetric data. Objective Here, we detail a graph building technique that allows these ICNs to be analyzed with graph theory. Methods First, ICA was performed at the single-subject level in 15 healthy...... parcellated regions. Third, between-node functional connectivity was established by building edge weights for each networks. Group-level graph analysis was finally performed for each network and compared to the classical network. Results Network graph comparison between the classically constructed network...
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RefDB: The Reference Database for CMS Monte Carlo Production
Lefébure, V
2003-01-01
RefDB is the CMS Monte Carlo Reference Database. It is used for recording and managing all details of physics simulation, reconstruction and analysis requests, for coordinating task assignments to world-wide distributed Regional Centers, Grid-enabled or not, and trace their progress rate. RefDB is also the central database that the workflow-planner contacts in order to get task instructions. It is automatically and asynchronously updated with book-keeping run summaries. Finally it is the end-user interface to data catalogues.
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Correlation between MEG and BOLD fMRI signals induced by visual flicker stimuli
Institute of Scientific and Technical Information of China (English)
Chu Renxin; Holroyd Tom; Duyn Jeff
2007-01-01
The goal of this work was to investigate how the MEG signal amplitude correlates with that of BOLD fMRI.To investigate the correlation between fMRI and macroscopic electrical activity, BOLD fMRI and MEG was performed on the same subjects (n =5). A visual flicker stimulus of varying temporal frequency was used to elicit neural responses in early visual areas. A strong similarity was observed in frequency tuning curves between both modalities.Although, averaged over subjects, the BOLD tuning curve was somewhat broader than MEG, both BOLD and MEG had maxima at a flicker frequency of 10 Hz. Also, we measured the first and second harmonic components as the stimuli frequency by MEG. In the low stimuli frequency (less than 6 Hz), the second harmonic has comparable amplitude with the first harmonic, which implies that neural frequency response is nonlinear and has more nonlinear components in low frequency than in high frequency.
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Database Description - ConfC | LSDB Archive [Life Science Database Archive metadata
Lifescience Database Archive (English)
Full Text Available abase Description General information of database Database name ConfC Alternative name Database...amotsu Noguchi Tel: 042-495-8736 E-mail: Database classification Structure Database...s - Protein structure Structure Databases - Small molecules Structure Databases - Nucleic acid structure Database... services - Need for user registration - About This Database Database Description Download License Update History of This Database... Site Policy | Contact Us Database Description - ConfC | LSDB Archive ...
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Directory of Open Access Journals (Sweden)
Markus Muehlhan
Full Text Available It has been repeatedly shown that functional magnetic resonance imaging (fMRI triggers distress and neuroendocrine response systems. Prior studies have revealed that sympathetic arousal increases, particularly at the beginning of the examination. Against this background it appears likely that those stress reactions during the scanning procedure may influence task performance and neural correlates. However, the question how sympathetic arousal elicited by the scanning procedure itself may act as a potential confounder of fMRI data remains unresolved today. Thirty-seven scanner naive healthy subjects performed a simple cued target detection task. Levels of salivary alpha amylase (sAA, as a biomarker for sympathetic activity, were assessed in samples obtained at several time points during the lab visit. SAA increased two times, immediately prior to scanning and at the end of the scanning procedure. Neural activation related to motor preparation and timing as well as task performance was positively correlated with the first increase. Furthermore, the first sAA increase was associated with task induced deactivation (TID in frontal and parietal regions. However, these effects were restricted to the first part of the experiment. Consequently, this bias of scanner related sympathetic activation should be considered in future fMRI investigations. It is of particular importance for pharmacological investigations studying adrenergic agents and the comparison of groups with different stress vulnerabilities like patients and controls or adolescents and adults.
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The effect of fMRI task combinations on determining the hemispheric dominance of language functions
International Nuclear Information System (INIS)
Niskanen, Eini; Koenoenen, Mervi; Villberg, Ville; Aeikiae, Marja; Nissi, Mikko; Ranta-aho, Perttu; Karjalainen, Pasi; Saeisaenen, Laura; Mervaala, Esa; Kaelviaeinen, Reetta; Vanninen, Ritva
2012-01-01
The purpose of this study is to establish the most suitable combination of functional magnetic resonance imaging (fMRI) language tasks for clinical use in determining language dominance and to define the variability in laterality index (LI) and activation power between different combinations of language tasks. Activation patterns of different fMRI analyses of five language tasks (word generation, responsive naming, letter task, sentence comprehension, and word pair) were defined for 20 healthy volunteers (16 right-handed). LIs and sums of T values were calculated for each task separately and for four combinations of tasks in predefined regions of interest. Variability in terms of activation power and lateralization was defined in each analysis. In addition, the visual assessment of lateralization of language functions based on the individual fMRI activation maps was conducted by an experienced neuroradiologist. A combination analysis of word generation, responsive naming, and sentence comprehension was the most suitable in terms of activation power, robustness to detect essential language areas, and scanning time. In general, combination analyses of the tasks provided higher overall activation levels than single tasks and reduced the number of outlier voxels disturbing the calculation of LI. A combination of auditory and visually presented tasks that activate different aspects of language functions with sufficient activation power may be a useful task battery for determining language dominance in patients. (orig.)
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The effect of fMRI task combinations on determining the hemispheric dominance of language functions
Energy Technology Data Exchange (ETDEWEB)
Niskanen, Eini [University of Eastern Finland, Department of Applied Physics, Kuopio (Finland); Kuopio University Hospital, Department of Clinical Radiology, Kuopio (Finland); Koenoenen, Mervi [Kuopio University Hospital, Department of Clinical Radiology, Kuopio (Finland); Kuopio University Hospital, Department of Clinical Neurophysiology, Kuopio (Finland); Villberg, Ville; Aeikiae, Marja [Kuopio University Hospital, Department of Neurology, Kuopio (Finland); Nissi, Mikko; Ranta-aho, Perttu; Karjalainen, Pasi [University of Eastern Finland, Department of Applied Physics, Kuopio (Finland); Saeisaenen, Laura; Mervaala, Esa [Kuopio University Hospital, Department of Clinical Neurophysiology, Kuopio (Finland); University of Eastern Finland, Institute of Clinical Medicine, Clinical Neurophysiology, Kuopio (Finland); Kaelviaeinen, Reetta [Kuopio University Hospital, Department of Neurology, Kuopio (Finland); University of Eastern Finland, Institute of Clinical Medicine, Neurology, Kuopio (Finland); Vanninen, Ritva [Kuopio University Hospital, Department of Clinical Radiology, Kuopio (Finland); University of Eastern Finland, Institute of Clinical Medicine, Clinical Radiology, Kuopio (Finland)
2012-04-15
The purpose of this study is to establish the most suitable combination of functional magnetic resonance imaging (fMRI) language tasks for clinical use in determining language dominance and to define the variability in laterality index (LI) and activation power between different combinations of language tasks. Activation patterns of different fMRI analyses of five language tasks (word generation, responsive naming, letter task, sentence comprehension, and word pair) were defined for 20 healthy volunteers (16 right-handed). LIs and sums of T values were calculated for each task separately and for four combinations of tasks in predefined regions of interest. Variability in terms of activation power and lateralization was defined in each analysis. In addition, the visual assessment of lateralization of language functions based on the individual fMRI activation maps was conducted by an experienced neuroradiologist. A combination analysis of word generation, responsive naming, and sentence comprehension was the most suitable in terms of activation power, robustness to detect essential language areas, and scanning time. In general, combination analyses of the tasks provided higher overall activation levels than single tasks and reduced the number of outlier voxels disturbing the calculation of LI. A combination of auditory and visually presented tasks that activate different aspects of language functions with sufficient activation power may be a useful task battery for determining language dominance in patients. (orig.)
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The effect of fMRI task combinations on determining the hemispheric dominance of language functions.
Niskanen, Eini; Könönen, Mervi; Villberg, Ville; Nissi, Mikko; Ranta-Aho, Perttu; Säisänen, Laura; Karjalainen, Pasi; Aikiä, Marja; Kälviäinen, Reetta; Mervaala, Esa; Vanninen, Ritva
2012-04-01
The purpose of this study is to establish the most suitable combination of functional magnetic resonance imaging (fMRI) language tasks for clinical use in determining language dominance and to define the variability in laterality index (LI) and activation power between different combinations of language tasks. Activation patterns of different fMRI analyses of five language tasks (word generation, responsive naming, letter task, sentence comprehension, and word pair) were defined for 20 healthy volunteers (16 right-handed). LIs and sums of T values were calculated for each task separately and for four combinations of tasks in predefined regions of interest. Variability in terms of activation power and lateralization was defined in each analysis. In addition, the visual assessment of lateralization of language functions based on the individual fMRI activation maps was conducted by an experienced neuroradiologist. A combination analysis of word generation, responsive naming, and sentence comprehension was the most suitable in terms of activation power, robustness to detect essential language areas, and scanning time. In general, combination analyses of the tasks provided higher overall activation levels than single tasks and reduced the number of outlier voxels disturbing the calculation of LI. A combination of auditory and visually presented tasks that activate different aspects of language functions with sufficient activation power may be a useful task battery for determining language dominance in patients.
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An Integrated Database of Unit Training Performance: Description an Lessons Learned
National Research Council Canada - National Science Library
Leibrecht, Bruce
1997-01-01
The Army Research Institute (ARI) has developed a prototype relational database for processing and archiving unit performance data from home station, training area, simulation based, and Combat Training Center training exercises...
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Database management systems understanding and applying database technology
Gorman, Michael M
1991-01-01
Database Management Systems: Understanding and Applying Database Technology focuses on the processes, methodologies, techniques, and approaches involved in database management systems (DBMSs).The book first takes a look at ANSI database standards and DBMS applications and components. Discussion focus on application components and DBMS components, implementing the dynamic relationship application, problems and benefits of dynamic relationship DBMSs, nature of a dynamic relationship application, ANSI/NDL, and DBMS standards. The manuscript then ponders on logical database, interrogation, and phy
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Wan, Yi-Ting; Chiang, Ching-Sui; Chen, Sharon Chia-Ju; Wuang, Yee-Pay
2017-07-01
This study investigated the effectiveness of the Computerized Visual Perception Training (CVPT) program on individuals with Down syndrome (DS, mean age=13.17±4.35years, age range: 6.54-20.75 years). All participants have mild intellectual disability classified by the standard IQ measures (mean=61.2, ranges from 55 to 68). Both the Test of Visual Perceptual Skill- Third Edition (TVPS-3) and functional magnetic resonance imaging (fMRI) were used to evaluate the training outcomes. Results of TVPS-3 and fMRI showed that DS group had visual perceptual deficits and abnormal neural networks related to visual organization. The results showed that DS intervention group had significant improvements on TVPS-3 after intervention. The fMRI results indicated more activation in superior and inferior parietal lobes (spatial manipulation), as well as precentral gyrus and dorsal premotor cortex (motor imagery) in DS intervention group. The CVPT program was effective in improving visual perceptual functions and enhancing associated cortical activations in DS. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Amygdala fMRI Signal as a Predictor of Reaction Time
Directory of Open Access Journals (Sweden)
Philipp Riedel
2016-10-01
Full Text Available Reaction times (RT are a valuable measure for assessing cognitive processes. However, RTs are susceptible to confounds and therefore variable. Exposure to threat, for example, speeds up or slows down responses. Distinct task types to some extent account for differential effects of threat on RTs. But also do inter-individual differences like trait anxiety. In this functional magnetic resonance imaging study, we investigated whether activation within the amygdala, a brain region closely linked to the processing of threat, may also function as a predictor of RTs, similar to trait anxiety scores. After threat conditioning by means of aversive electric shocks, 45 participants performed a choice RT task during alternating 30s blocks in the presence of the threat conditioned stimulus CS+ or of the safe control stimulus CS-. Trait anxiety was assessed with the State-Trait-Anxiety-Inventory and participants were median split into a high- and a low-anxiety subgroup. We tested three hypotheses: 1 RTs will be faster during the exposure to threat compared to the safe condition in individuals with high trait anxiety. 2 The amygdala fMRI signal will be higher in the threat condition compared to the safe condition. 3 Amygdala fMRI signal prior to a RT trial will be correlated with the corresponding RT. We found that, the high-anxious subgroup showed faster responses in the threat condition compared to the safe condition, while the low-anxious subgroup showed no significant difference in RTs in the threat condition compared to the safe condition. Though the fMRI analysis did not reveal an effect of condition on amygdala activity, we found a trial-by-trial correlation between blood-oxygen-level-dependent signal within the right amygdala prior to the CRT task and the subsequent RT. Taken together, the results of this study showed that: Exposure to threat modulates task performance. This modulation is influenced by personality trait. Additionally and most
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Vannest, Jennifer J; Karunanayaka, Prasanna R; Altaye, Mekibib; Schmithorst, Vincent J; Plante, Elena M; Eaton, Kenneth J; Rasmussen, Jerod M; Holland, Scott K
2009-04-01
To use functional MRI (fMRI) methods to visualize a network of auditory and language-processing brain regions associated with processing an aurally-presented story. We compare a passive listening (PL) story paradigm to an active-response (AR) version including online performance monitoring and a sparse acquisition technique. Twenty children (ages 11-13 years) completed PL and AR story processing tasks. The PL version presented alternating 30-second blocks of stories and tones; the AR version presented story segments, comprehension questions, and 5-second tone sequences, with fMRI acquisitions between stimuli. fMRI data was analyzed using a general linear model approach and paired t-test identifying significant group activation. Both tasks showed activation in the primary auditory cortex, superior temporal gyrus bilaterally, and left inferior frontal gyrus (IFG). The AR task demonstrated more extensive activation, including the dorsolateral prefrontal cortex and anterior/posterior cingulate cortex. Comparison of effect size in each paradigm showed a larger effect for the AR paradigm in a left inferior frontal region-of-interest (ROI). Activation patterns for story processing in children are similar in PL and AR tasks. Increases in extent and magnitude of activation in the AR task are likely associated with memory and attention resources engaged across acquisition intervals.
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Brain Network Response to Acupuncture Stimuli in Experimental Acute Low Back Pain: An fMRI Study
Directory of Open Access Journals (Sweden)
Yu Shi
2015-01-01
Full Text Available Most neuroimaging studies have demonstrated that acupuncture can significantly modulate brain activation patterns in healthy subjects, while only a few studies have examined clinical pain. In the current study, we combined an experimental acute low back pain (ALBP model and functional magnetic resonance imaging (fMRI to explore the neural mechanisms of acupuncture analgesia. All ALBP subjects first underwent two resting state fMRI scans at baseline and during a painful episode and then underwent two additional fMRI scans, once during acupuncture stimulation (ACUP and once during tactile stimulation (SHAM pseudorandomly, at the BL40 acupoint. Our results showed that, compared with the baseline, the pain state had higher regional homogeneity (ReHo values in the pain matrix, limbic system, and default mode network (DMN and lower ReHo values in frontal gyrus and temporal gyrus; compared with the OFF status, ACUP yielded broad deactivation in subjects, including nearly all of the limbic system, pain status, and DMN, and also evoked numerous activations in the attentional and somatosensory systems; compared with SHAM, we found that ACUP induced more deactivations and fewer activations in the subjects. Multiple brain networks play crucial roles in acupuncture analgesia, suggesting that ACUP exceeds a somatosensory-guided mind-body therapy for ALBP.
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Directory of Open Access Journals (Sweden)
Qian Xiao
Full Text Available UNLABELLED: Pediatric bipolar disorder (PBD is a severely debilitating illness, which is characterized by episodes of mania and depression separated by periods of remission. Previous fMRI studies investigating PBD were mainly task-related. However, little is known about the abnormalities in PBD, especially during resting state. Resting state brain activity measured by fMRI might help to explore neurobiological biomarkers of the disorder. METHODS: Regional homogeneity (ReHo was examined with resting-state fMRI (RS-fMRI on 15 patients with PBD in manic state, with 15 age-and sex-matched healthy youth subjects as controls. RESULTS: Compared with the healthy controls, the patients with PBD showed altered ReHo in the cortical and subcortical structures. The ReHo measurement of the PBD group was negatively correlated with the score of Young Mania Rating Scale (YMRS in the superior frontal gyrus. Positive correlations between the ReHo measurement and the score of YMRS were found in the hippocampus and the anterior cingulate cortex in the PBD group. CONCLUSIONS: Altered regional brain activity is present in patients with PBD during manic state. This study presents new evidence for abnormal ventral-affective and dorsal-cognitive circuits in PBD during resting state and may add fresh insights into the pathophysiological mechanisms underlying PBD.
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Spalek, Klara; Fastenrath, Matthias; Ackermann, Sandra; Auschra, Bianca; Coynel, David; Frey, Julia; Gschwind, Leo; Hartmann, Francina; van der Maarel, Nadine; Papassotiropoulos, Andreas; de Quervain, Dominique; Milnik, Annette
2015-01-21
Extensive evidence indicates that women outperform men in episodic memory tasks. Furthermore, women are known to evaluate emotional stimuli as more arousing than men. Because emotional arousal typically increases episodic memory formation, the females' memory advantage might be more pronounced for emotionally arousing information than for neutral information. Here, we report behavioral data from 3398 subjects, who performed picture rating and memory tasks, and corresponding fMRI data from up to 696 subjects. We were interested in the interaction between sex and valence category on emotional appraisal, memory performances, and fMRI activity. The behavioral results showed that females evaluate in particular negative (p pictures, as emotionally more arousing (pinteraction recall females outperformed males not only in positive (p picture recall (p pictures (pinteraction memory advantage during free recall was absent in a recognition setting. We identified activation differences in fMRI, which corresponded to the females' stronger appraisal of especially negative pictures, but no activation differences that reflected the interaction effect in the free recall memory task. In conclusion, females' valence-category-specific memory advantage is only observed in a free recall, but not a recognition setting and does not depend on females' higher emotional appraisal. Copyright © 2015 the authors 0270-6474/15/350920-16$15.00/0.
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Integration of EEG source imaging and fMRI during continuous viewing of natural movies.
Whittingstall, Kevin; Bartels, Andreas; Singh, Vanessa; Kwon, Soyoung; Logothetis, Nikos K
2010-10-01
Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are noninvasive neuroimaging tools which can be used to measure brain activity with excellent temporal and spatial resolution, respectively. By combining the neural and hemodynamic recordings from these modalities, we can gain better insight into how and where the brain processes complex stimuli, which may be especially useful in patients with different neural diseases. However, due to their vastly different spatial and temporal resolutions, the integration of EEG and fMRI recordings is not always straightforward. One fundamental obstacle has been that paradigms used for EEG experiments usually rely on event-related paradigms, while fMRI is not limited in this regard. Therefore, here we ask whether one can reliably localize stimulus-driven EEG activity using the continuously varying feature intensities occurring in natural movie stimuli presented over relatively long periods of time. Specifically, we asked whether stimulus-driven aspects in the EEG signal would be co-localized with the corresponding stimulus-driven BOLD signal during free viewing of a movie. Secondly, we wanted to integrate the EEG signal directly with the BOLD signal, by estimating the underlying impulse response function (IRF) that relates the BOLD signal to the underlying current density in the primary visual area (V1). We made sequential fMRI and 64-channel EEG recordings in seven subjects who passively watched 2-min-long segments of a James Bond movie. To analyze EEG data in this natural setting, we developed a method based on independent component analysis (ICA) to reject EEG artifacts due to blinks, subject movement, etc., in a way unbiased by human judgment. We then calculated the EEG source strength of this artifact-free data at each time point of the movie within the entire brain volume using low-resolution electromagnetic tomography (LORETA). This provided for every voxel in the brain (i.e., in 3D space) an
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Bera, Maitreyee
2017-10-16
The U.S. Geological Survey (USGS), in cooperation with the DuPage County Stormwater Management Department, maintains a database of hourly meteorological and hydrologic data for use in a near real-time streamflow simulation system. This system is used in the management and operation of reservoirs and other flood-control structures in the West Branch DuPage River watershed in DuPage County, Illinois. The majority of the precipitation data are collected from a tipping-bucket rain-gage network located in and near DuPage County. The other meteorological data (air temperature, dewpoint temperature, wind speed, and solar radiation) are collected at Argonne National Laboratory in Argonne, Ill. Potential evapotranspiration is computed from the meteorological data using the computer program LXPET (Lamoreux Potential Evapotranspiration). The hydrologic data (water-surface elevation [stage] and discharge) are collected at U.S.Geological Survey streamflow-gaging stations in and around DuPage County. These data are stored in a Watershed Data Management (WDM) database.This report describes a version of the WDM database that is quality-assured and quality-controlled annually to ensure datasets are complete and accurate. This database is named WBDR13.WDM. It contains data from January 1, 2007, through September 30, 2013. Each precipitation dataset may have time periods of inaccurate data. This report describes the methods used to estimate the data for the periods of missing, erroneous, or snowfall-affected data and thereby improve the accuracy of these data. The other meteorological datasets are described in detail in Over and others (2010), and the hydrologic datasets in the database are fully described in the online USGS annual water data reports for Illinois (U.S. Geological Survey, 2016) and, therefore, are described in less detail than the precipitation datasets in this report.
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Sparse PCA, a new method for unsupervised analyses of fMRI data
DEFF Research Database (Denmark)
Sjöstrand, Karl; Lund, Torben E.; Madsen, Kristoffer Hougaard
2006-01-01
favorable circumstances, one of more of these signals describe activation patterns, while others model noise and other nuisance factors. This work introduces a competing method for fMRI analysis known as sparse principal component analysis (SPCA). We argue that SPCA is less committed than ICA and show...... that similar results, with better suppression of noise, are obtained....
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fMRI Evidence for Dorsal Stream Processing Abnormality in Adults Born Preterm
Chaminade, Thierry; Leutcher, Russia Ha-Vinh; Millet, Veronique; Deruelle, Christine
2013-01-01
We investigated the consequences of premature birth on the functional neuroanatomy of the dorsal stream of visual processing. fMRI was recorded while sixteen healthy participants, 8 (two men) adults (19 years 6 months old, SD 10 months) born premature (mean gestational age 30 weeks), referred to as Premas, and 8 (two men) matched controls (20…
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Conflict anticipation in alcohol dependence - A model-based fMRI study of stop signal task.
Hu, Sien; Ide, Jaime S; Zhang, Sheng; Sinha, Rajita; Li, Chiang-Shan R
2015-01-01
Our previous work characterized altered cerebral activations during cognitive control in individuals with alcohol dependence (AD). A hallmark of cognitive control is the ability to anticipate changes and adjust behavior accordingly. Here, we employed a Bayesian model to describe trial-by-trial anticipation of the stop signal and modeled fMRI signals of conflict anticipation in a stop signal task. Our goal is to characterize the neural correlates of conflict anticipation and its relationship to response inhibition and alcohol consumption in AD. Twenty-four AD and 70 age and gender matched healthy control individuals (HC) participated in the study. fMRI data were pre-processed and modeled with SPM8. We modeled fMRI signals at trial onset with individual events parametrically modulated by estimated probability of the stop signal, p(Stop), and compared regional responses to conflict anticipation between AD and HC. To address the link to response inhibition, we regressed whole-brain responses to conflict anticipation against the stop signal reaction time (SSRT). Compared to HC (54/70), fewer AD (11/24) showed a significant sequential effect - a correlation between p(Stop) and RT during go trials - and the magnitude of sequential effect is diminished, suggesting a deficit in proactive control. Parametric analyses showed decreased learning rate and over-estimated prior mean of the stop signal in AD. In fMRI, both HC and AD responded to p(Stop) in bilateral inferior parietal cortex and anterior pre-supplementary motor area, although the magnitude of response increased in AD. In contrast, HC but not AD showed deactivation of the perigenual anterior cingulate cortex (pgACC). Furthermore, deactivation of the pgACC to increasing p(Stop) is positively correlated with the SSRT in HC but not AD. Recent alcohol consumption is correlated with increased activation of the thalamus and cerebellum in AD during conflict anticipation. The current results highlight altered proactive
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High-throughput ab-initio dilute solute diffusion database.
Wu, Henry; Mayeshiba, Tam; Morgan, Dane
2016-07-19
We demonstrate automated generation of diffusion databases from high-throughput density functional theory (DFT) calculations. A total of more than 230 dilute solute diffusion systems in Mg, Al, Cu, Ni, Pd, and Pt host lattices have been determined using multi-frequency diffusion models. We apply a correction method for solute diffusion in alloys using experimental and simulated values of host self-diffusivity. We find good agreement with experimental solute diffusion data, obtaining a weighted activation barrier RMS error of 0.176 eV when excluding magnetic solutes in non-magnetic alloys. The compiled database is the largest collection of consistently calculated ab-initio solute diffusion data in the world.
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Decoding Overlapping Memories in the Medial Temporal Lobes Using High-Resolution fMRI
Chadwick, Martin J.; Hassabis, Demis; Maguire, Eleanor A.
2011-01-01
The hippocampus is proposed to process overlapping episodes as discrete memory traces, although direct evidence for this in human episodic memory is scarce. Using green-screen technology we created four highly overlapping movies of everyday events. Participants were scanned using high-resolution fMRI while recalling the movies. Multivariate…
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Dual-Tasking Alleviated Sleep Deprivation Disruption in Visuomotor Tracking: An fMRI Study
Gazes, Yunglin; Rakitin, Brian C.; Steffener, Jason; Habeck, Christian; Butterfield, Brady; Basner, Robert C.; Ghez, Claude; Stern, Yaakov
2012-01-01
Effects of dual-responding on tracking performance after 49-h of sleep deprivation (SD) were evaluated behaviorally and with functional magnetic resonance imaging (fMRI). Continuous visuomotor tracking was performed simultaneously with an intermittent color-matching visual detection task in which a pair of color-matched stimuli constituted a…
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Brewer, Kimberly D; Rioux, James A; Klassen, Martyn; Bowen, Chris V; Beyea, Steven D
2012-07-01
Susceptibility field gradients (SFGs) cause problems for functional magnetic resonance imaging (fMRI) in regions like the orbital frontal lobes, leading to signal loss and image artifacts (signal displacement and "pile-up"). Pulse sequences with spiral-in k-space trajectories are often used when acquiring fMRI in SFG regions such as inferior/medial temporal cortex because it is believed that they have improved signal recovery and decreased signal displacement properties. Previously postulated theories explain differing reasons why spiral-in appears to perform better than spiral-out; however it is clear that multiple mechanisms are occurring in parallel. This study explores differences in spiral-in and spiral-out images using human and phantom empirical data, as well as simulations consistent with the phantom model. Using image simulations, the displacement of signal was characterized using point spread functions (PSFs) and target maps, the latter of which are conceptually inverse PSFs describing which spatial locations contribute signal to a particular voxel. The magnitude of both PSFs and target maps was found to be identical for spiral-out and spiral-in acquisitions, with signal in target maps being displaced from distant regions in both cases. However, differences in the phase of the signal displacement patterns that consequently lead to changes in the intervoxel phase coherence were found to be a significant mechanism explaining differences between the spiral sequences. The results demonstrate that spiral-in trajectories do preserve more total signal in SFG regions than spiral-out; however, spiral-in does not in fact exhibit decreased signal displacement. Given that this signal can be displaced by significant distances, its recovery may not be preferable for all fMRI applications. Copyright © 2012 Elsevier Inc. All rights reserved.
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Database Description - RMG | LSDB Archive [Life Science Database Archive metadata
Lifescience Database Archive (English)
Full Text Available ase Description General information of database Database name RMG Alternative name ...raki 305-8602, Japan National Institute of Agrobiological Sciences E-mail : Database... classification Nucleotide Sequence Databases Organism Taxonomy Name: Oryza sativa Japonica Group Taxonomy ID: 39947 Database...rnal: Mol Genet Genomics (2002) 268: 434–445 External Links: Original website information Database...available URL of Web services - Need for user registration Not available About This Database Database Descri
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Energy Technology Data Exchange (ETDEWEB)
Smits, Marion [Erasmus MC - University Medical Center Rotterdam, Department of Radiology, Hs 224, Rotterdam (Netherlands); Kovacs, Silvia; Peeters, Ronald R; Hecke, Paul van; Sunaert, Stefan [University Hospitals of the Catholic University Leuven, Department of Radiology, Leuven (Belgium); Ridder, Dirk de [University of Antwerp, Department of Neurosurgery, Edegem (Belgium)
2007-08-15
Tinnitus is hypothesized to be an auditory phantom phenomenon resulting from spontaneous neuronal activity somewhere along the auditory pathway. We performed fMRI of the entire auditory pathway, including the inferior colliculus (IC), the medial geniculate body (MGB) and the auditory cortex (AC), in 42 patients with tinnitus and 10 healthy volunteers to assess lateralization of fMRI activation. Subjects were scanned on a 3T MRI scanner. A T2*-weighted EPI silent gap sequence was used during the stimulation paradigm, which consisted of a blocked design of 12 epochs in which music presented binaurally through headphones, which was switched on and off for periods of 50 s. Using SPM2 software, single subject and group statistical parametric maps were calculated. Lateralization of activation was assessed qualitatively and quantitatively. Tinnitus was lateralized in 35 patients (83%, 13 right-sided and 22 left-sided). Significant signal change (P{sub corrected} < 0.05) was found bilaterally in the primary and secondary AC, the IC and the MGB. Signal change was symmetrical in patients with bilateral tinnitus. In patients with lateralized tinnitus, fMRI activation was lateralized towards the side of perceived tinnitus in the primary AC and IC in patients with right-sided tinnitus, and in the MGB in patients with left-sided tinnitus. In healthy volunteers, activation in the primary AC was left-lateralized. Our paradigm adequately visualized the auditory pathways in tinnitus patients. In lateralized tinnitus fMRI activation was also lateralized, supporting the hypothesis that tinnitus is an auditory phantom phenomenon. (orig.)
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International Nuclear Information System (INIS)
Smits, Marion; Kovacs, Silvia; Peeters, Ronald R.; Hecke, Paul van; Sunaert, Stefan; Ridder, Dirk de
2007-01-01
Tinnitus is hypothesized to be an auditory phantom phenomenon resulting from spontaneous neuronal activity somewhere along the auditory pathway. We performed fMRI of the entire auditory pathway, including the inferior colliculus (IC), the medial geniculate body (MGB) and the auditory cortex (AC), in 42 patients with tinnitus and 10 healthy volunteers to assess lateralization of fMRI activation. Subjects were scanned on a 3T MRI scanner. A T2*-weighted EPI silent gap sequence was used during the stimulation paradigm, which consisted of a blocked design of 12 epochs in which music presented binaurally through headphones, which was switched on and off for periods of 50 s. Using SPM2 software, single subject and group statistical parametric maps were calculated. Lateralization of activation was assessed qualitatively and quantitatively. Tinnitus was lateralized in 35 patients (83%, 13 right-sided and 22 left-sided). Significant signal change (P corrected < 0.05) was found bilaterally in the primary and secondary AC, the IC and the MGB. Signal change was symmetrical in patients with bilateral tinnitus. In patients with lateralized tinnitus, fMRI activation was lateralized towards the side of perceived tinnitus in the primary AC and IC in patients with right-sided tinnitus, and in the MGB in patients with left-sided tinnitus. In healthy volunteers, activation in the primary AC was left-lateralized. Our paradigm adequately visualized the auditory pathways in tinnitus patients. In lateralized tinnitus fMRI activation was also lateralized, supporting the hypothesis that tinnitus is an auditory phantom phenomenon. (orig.)
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Mokhtari, Fatemeh; Bakhtiari, Shahab K.; Hossein-Zadeh, Gholam Ali; Soltanian-Zadeh, Hamid
2012-02-01
Decoding techniques have opened new windows to explore the brain function and information encoding in brain activity. In the current study, we design a recursive support vector machine which is enriched by a subtree graph kernel. We apply the classifier to discriminate between attentional cueing task and resting state from a block design fMRI dataset. The classifier is trained using weighted fMRI graphs constructed from activated regions during the two mentioned states. The proposed method leads to classification accuracy of 1. It is also able to elicit discriminative regions and connectivities between the two states using a backward edge elimination algorithm. This algorithm shows the importance of regions including cerebellum, insula, left middle superior frontal gyrus, post cingulate cortex, and connectivities between them to enhance the correct classification rate.
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International Nuclear Information System (INIS)
Chang, M W; Gwo, T J; Deng, T M; Chang, H C
2006-01-01
A Capacitive Micromachined Ultrasonic Transducers simulation database, based on electromechanical coupling theory, has been fully developed for versatile capacitive microtransducer design and analysis. Both arithmetic and graphic configurations are used to find optimal parameters based on serial coupling simulations. The key modeling parameters identified can improve microtransducer's character and reliability effectively. This method could be used to reduce design time and fabrication cost, eliminating trial-and-error procedures. Various microtransducers, with optimized characteristics, can be developed economically using the developed database. A simulation to design an ultrasonic microtransducer is completed as an executed example. The dependent relationship between membrane geometry, vibration displacement and output response is demonstrated. The electromechanical coupling effects, mechanical impedance and frequency response are also taken into consideration for optimal microstructures. The microdevice parameters with the best output signal response are predicted, and microfabrication processing constraints and realities are also taken into consideration
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Bell, D A
1986-01-01
Relational Databases explores the major advances in relational databases and provides a balanced analysis of the state of the art in relational databases. Topics covered include capture and analysis of data placement requirements; distributed relational database systems; data dependency manipulation in database schemata; and relational database support for computer graphics and computer aided design. This book is divided into three sections and begins with an overview of the theory and practice of distributed systems, using the example of INGRES from Relational Technology as illustration. The
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Database Description - DGBY | LSDB Archive [Life Science Database Archive metadata
Lifescience Database Archive (English)
Full Text Available base Description General information of database Database name DGBY Alternative name Database...EL: +81-29-838-8066 E-mail: Database classification Microarray Data and other Gene Expression Databases Orga...nism Taxonomy Name: Saccharomyces cerevisiae Taxonomy ID: 4932 Database descripti...-called phenomics). We uploaded these data on this website which is designated DGBY(Database for Gene expres...ma J, Ando A, Takagi H. Journal: Yeast. 2008 Mar;25(3):179-90. External Links: Original website information Database
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Database Description - KOME | LSDB Archive [Life Science Database Archive metadata
Lifescience Database Archive (English)
Full Text Available base Description General information of database Database name KOME Alternative nam... Sciences Plant Genome Research Unit Shoshi Kikuchi E-mail : Database classification Plant databases - Rice ...Organism Taxonomy Name: Oryza sativa Taxonomy ID: 4530 Database description Information about approximately ...Hayashizaki Y, Kikuchi S. Journal: PLoS One. 2007 Nov 28; 2(11):e1235. External Links: Original website information Database...OS) Rice mutant panel database (Tos17) A Database of Plant Cis-acting Regulatory
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WholeCellSimDB: a hybrid relational/HDF database for whole-cell model predictions.
Karr, Jonathan R; Phillips, Nolan C; Covert, Markus W
2014-01-01
Mechanistic 'whole-cell' models are needed to develop a complete understanding of cell physiology. However, extracting biological insights from whole-cell models requires running and analyzing large numbers of simulations. We developed WholeCellSimDB, a database for organizing whole-cell simulations. WholeCellSimDB was designed to enable researchers to search simulation metadata to identify simulations for further analysis, and quickly slice and aggregate simulation results data. In addition, WholeCellSimDB enables users to share simulations with the broader research community. The database uses a hybrid relational/hierarchical data format architecture to efficiently store and retrieve both simulation setup metadata and results data. WholeCellSimDB provides a graphical Web-based interface to search, browse, plot and export simulations; a JavaScript Object Notation (JSON) Web service to retrieve data for Web-based visualizations; a command-line interface to deposit simulations; and a Python API to retrieve data for advanced analysis. Overall, we believe WholeCellSimDB will help researchers use whole-cell models to advance basic biological science and bioengineering. http://www.wholecellsimdb.org SOURCE CODE REPOSITORY: URL: http://github.com/CovertLab/WholeCellSimDB. © The Author(s) 2014. Published by Oxford University Press.
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Domijan, Dražen
2011-12-01
A computational model was developed to explain a pattern of results of fMRI activation in the intraparietal sulcus (IPS) supporting visual working memory for multiobject scenes. The model is based on the hypothesis that dendrites of excitatory neurons are major computational elements in the cortical circuit. Dendrites enable formation of a competitive queue that exhibits a gradient of activity values for nodes encoding different objects, and this pattern is stored in working memory. In the model, brain imaging data are interpreted as a consequence of blood flow arising from dendritic processing. Computer simulations showed that the model successfully simulates data showing the involvement of inferior IPS in object individuation and spatial grouping through representation of objects' locations in space, along with the involvement of superior IPS in object identification through representation of a set of objects' features. The model exhibits a capacity limit due to the limited dynamic range for nodes and the operation of lateral inhibition among them. The capacity limit is fixed in the inferior IPS regardless of the objects' complexity, due to the normalization of lateral inhibition, and variable in the superior IPS, due to the different encoding demands for simple and complex shapes. Systematic variation in the strength of self-excitation enables an understanding of the individual differences in working memory capacity. The model offers several testable predictions regarding the neural basis of visual working memory.
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Directory of Open Access Journals (Sweden)
Jungho Cha
2015-01-01
Full Text Available Resting-state functional magnetic resonance imaging (RS FMRI has been widely used to analyze functional alterations in amnestic mild cognitive impairment (aMCI and Alzheimer’s disease (AD patients. Although many clinical studies of aMCI and AD patients using RS FMRI have been undertaken, conducting a meta-analysis has not been easy because of seed selection bias by the investigators. The purpose of our study was to investigate the functional differences in aMCI and AD patients compared with healthy subjects in a meta-analysis. Thus, a multimethod approach using regional homogeneity, amplitude of low-frequency fluctuation (ALFF, fractional ALFF (fALFF, and global brain connectivity was used to investigate differences between three groups based on previously published data. According to the choice of RS FMRI approach used, the patterns of functional alteration were slightly different. Nevertheless, patients with aMCI and AD displayed consistently decreased functional characteristics with all approaches. All approaches showed that the functional characteristics in the left parahippocampal gyrus were decreased in AD patients compared with healthy subjects. Although some regions were slightly different according to the different RS FMRI approaches, patients with aMCI and AD showed a consistent pattern of decreased functional characteristics with all approaches.