An asymmetrical relationship between verbal and visual thinking: Converging evidence from behavior and fMRI.

Science.gov (United States)

Amit, Elinor; Hoeflin, Caitlyn; Hamzah, Nada; Fedorenko, Evelina

2017-05-15

Humans rely on at least two modes of thought: verbal (inner speech) and visual (imagery). Are these modes independent, or does engaging in one entail engaging in the other? To address this question, we performed a behavioral and an fMRI study. In the behavioral experiment, participants received a prompt and were asked to either silently generate a sentence or create a visual image in their mind. They were then asked to judge the vividness of the resulting representation, and of the potentially accompanying representation in the other format. In the fMRI experiment, participants had to recall sentences or images (that they were familiarized with prior to the scanning session) given prompts, or read sentences and view images, in the control, perceptual, condition. An asymmetry was observed between inner speech and visual imagery. In particular, inner speech was engaged to a greater extent during verbal than visual thought, but visual imagery was engaged to a similar extent during both modes of thought. Thus, it appears that people generate more robust verbal representations during deliberate inner speech compared to when their intent is to visualize. However, they generate visual images regardless of whether their intent is to visualize or to think verbally. One possible interpretation of these results is that visual thinking is somehow primary, given the relatively late emergence of verbal abilities during human development and in the evolution of our species. Copyright © 2017 Elsevier Inc. All rights reserved.

Convergence of human brain mapping tools: neuronavigated TMS parameters and fMRI activity in the hand motor area.

Science.gov (United States)

Sarfeld, Anna-Sophia; Diekhoff, Svenja; Wang, Ling E; Liuzzi, Gianpiero; Uludağ, Kamil; Eickhoff, Simon B; Fink, Gereon R; Grefkes, Christian

2012-05-01

Functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS) are well-established tools for investigating the human motor system in-vivo. We here studied the relationship between movement-related fMRI signal changes in the primary motor cortex (M1) and electrophysiological properties of the hand motor area assessed with neuronavigated TMS in 17 healthy subjects. The voxel showing the highest task-related BOLD response in the left hand motor area during right hand movements was identified for each individual subject. This fMRI peak voxel in M1 served as spatial target for coil positioning during neuronavigated TMS. We performed correlation analyses between TMS parameters, BOLD signal estimates and effective connectivity parameters of M1 assessed with dynamic causal modeling (DCM). The results showed a negative correlation between the movement-related BOLD signal in left M1 and resting as well as active motor threshold (MT) obtained for left M1. The DCM analysis revealed that higher excitability of left M1 was associated with a stronger coupling between left supplementary motor area (SMA) and M1. Furthermore, BOLD activity in left M1 correlated with ipsilateral silent period (ISP), i.e. the stronger the task-related BOLD response in left M1, the higher interhemispheric inhibition effects targeting right M1. DCM analyses revealed a positive correlation between the coupling of left SMA with left M1 and the duration of ISP. The data show that TMS parameters assessed for the hand area of M1 do not only reflect the intrinsic properties at the stimulation site but also interactions with remote areas in the human motor system. Copyright © 2011 Wiley-Liss, Inc.

Learning effective connectivity from fMRI using autoregressive hidden Markov model with missing data.

Science.gov (United States)

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.

Reduced vergence adaptation is associated with a prolonged output of convergence accommodation in convergence insufficiency.

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Sreenivasan, Vidhyapriya; Bobier, William R

2014-07-01

Convergence insufficiency (CI) is a developmental visual anomaly defined clinically by a reduced near point of convergence, a reduced capacity to view through base-out prisms (fusional convergence); coupled with asthenopic symptoms typically blur and diplopia. Experimental studies show reduced vergence parameters and tonic adaptation. Based upon current models of accommodation and vergence, we hypothesize that the reduced vergence adaptation in CI leads to excessive amounts of convergence accommodation (CA). Eleven CI participants (mean age=17.4±2.3 years) were recruited with reduced capacity to view through increasing magnitudes of base out (BO) prisms (mean fusional convergence at 40 cm=12±0.9Δ). Testing followed our previous experimental design for (n=11) binocularly normal adults. Binocular fixation of a difference of Gaussian (DoG) target (0.2 cpd) elicited CA responses during vergence adaptation to a 12Δ BO. Vergence and CA responses were obtained at 3 min intervals over a 15 min period and time course were quantified using exponential decay functions. Results were compared to previously published data on eleven binocular normals. Eight participants completed the study. CI's showed significantly reduced magnitude of vergence adaptation (CI: 2.9Δ vs. normals: 6.6Δ; p=0.01) and CA reduction (CI=0.21 D, Normals=0.55 D; p=0.03). However, the decay time constants for adaptation and CA responses were not significantly different. CA changes were not confounded by changes in tonic accommodation (Change in TA=0.01±0.2D; p=0.8). The reduced magnitude of vergence adaptation found in CI patients resulting in higher levels of CA may potentially explain their clinical findings of reduced positive fusional vergence (PFV) and the common symptom of blur. Copyright © 2014 Elsevier B.V. All rights reserved.

Serial changes of humor comprehension for four-frame comic Manga: an fMRI study.

Science.gov (United States)

Osaka, Mariko; Yaoi, Ken; Minamoto, Takehiro; Osaka, Naoyuki

2014-07-25

Serial changes of humor comprehension evoked by a well organized four-frame comic Manga were investigated by fMRI in each step of humor comprehension. The neural substrates underlying the amusing effects in response to funny and mixed order manga were compared. In accordance with the time course of the four frames, fMRI activations changed serially. Beginning with the second frame (development scene), activation of the temporo-parietal junction (TPJ) was observed, followed by activations in the temporal and frontal areas during viewing of the third frame (turn scene). For the fourth frame (punch line), strong increased activations were confirmed in the medial prefrontal cortex (MPFC) and cerebellum. Interestingly, distinguishable activation differences in the cerebellum between funny and non-funny conditions were also found for the fourth frame. These findings suggest that humor comprehension evokes activation that initiates in the TPJ and expands to the MPFC and cerebellum at the convergence level.

Understanding others' regret: a FMRI study.

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Nicola Canessa

Full Text Available Previous studies showed that the understanding of others' basic emotional experiences is based on a "resonant" mechanism, i.e., on the reactivation, in the observer's brain, of the cerebral areas associated with those experiences. The present study aimed to investigate whether the same neural mechanism is activated both when experiencing and attending complex, cognitively-generated, emotions. A gambling task and functional-Magnetic-Resonance-Imaging (fMRI were used to test this hypothesis using regret, the negative cognitively-based emotion resulting from an unfavorable counterfactual comparison between the outcomes of chosen and discarded options. Do the same brain structures that mediate the experience of regret become active in the observation of situations eliciting regret in another individual? Here we show that observing the regretful outcomes of someone else's choices activates the same regions that are activated during a first-person experience of regret, i.e. the ventromedial prefrontal cortex, anterior cingulate cortex and hippocampus. These results extend the possible role of a mirror-like mechanism beyond basic emotions.

Enhanced sympathetic arousal in response to FMRI scanning correlates with task induced activations and deactivations.

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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.

Hemispheric differences in processing the literal interpretation of idioms: converging evidence from behavioral and fMRI studies.

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Mashal, Nira; Faust, Miriam; Hendler, Talma; Jung-Beeman, Mark

2008-01-01

The present study examined the role of the left (LH) and right (RH) cerebral hemispheres in processing alternative meanings of idiomatic sentences. We conducted two experiments using ambiguous idioms with plausible literal interpretations as stimuli. In the first experiment we tested hemispheric differences in accessing either the literal or the idiomatic meaning of idioms for targets presented to either the left or the right visual field. In the second experiment, we used functional magnetic resonance imaging (fMRI) to define regional brain activation patterns in healthy adults processing either the idiomatic meaning of idioms or the literal meanings of either idioms or literal sentences. According to the Graded Salience Hypothesis (GSH, Giora, 2003), a selective RH involvement in the processing of nonsalient meanings, such as literal interpretations of idiomatic expressions, was expected. Results of the two experiments were consistent with the GSH predictions and show that literal interpretations of idioms are accessed faster than their idiomatic meanings in the RH. The fMRI data showed that processing the idiomatic interpretation of idioms and the literal interpretations of literal sentences involved LH regions whereas processing the literal interpretation of idioms was associated with increased activity in right brain regions including the right precuneus, right middle frontal gyrus (MFG), right posterior middle temporal gyrus (MTG), and right anterior superior temporal gyrus (STG). We suggest that these RH areas are involved in semantic ambiguity resolution and in processing nonsalient meanings of conventional idiomatic expressions.

Supplementary Motor Area Activation in Disfluency Perception : An fMRI Study of Listener Neural Responses to Spontaneously Produced Unfilled and Filled Pauses

OpenAIRE

Eklund, Robert; Ingvar, Martin

2016-01-01

Spontaneously produced Unfilled Pauses (UPs) and Filled Pauses (FPs) were played to subjects in an fMRI experiment. For both stimuli increased activity was observed in the Primary Auditory Cortex (PAC). However, FPs, but not UPs, elicited modulation in the Supplementary Motor Area (SMA), Brodmann Area 6. Our results provide neurocognitive confirmation of the alleged difference between FPs and other kinds of speech disfluency and could also provide a partial explanation for the previously repo...

Do convergent developmental mechanisms underlie convergent phenotypes?

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Wray, Gregory A.

2002-01-01

Convergence is a pervasive evolutionary process, affecting many aspects of phenotype and even genotype. Relatively little is known about convergence in developmental processes, however, nor about the degree to which convergence in development underlies convergence in anatomy. A switch in the ecology of sea urchins from feeding to nonfeeding larvae illustrates how convergence in development can be associated with convergence in anatomy. Comparisons to more distantly related taxa, however, suggest that this association may be limited to relatively close phylogenetic comparisons. Similarities in gene expression during development provide another window into the association between convergence in developmental processes and convergence in anatomy. Several well-studied transcription factors exhibit likely cases of convergent gene expression in distantly related animal phyla. Convergence in regulatory gene expression domains is probably more common than generally acknowledged, and can arise for several different reasons. Copyright 2002 S. Karger AG, Basel.

Color tuning in alert macaque V1 assessed with fMRI and single-unit recording shows a bias toward daylight colors.

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Lafer-Sousa, Rosa; Liu, Yang O; Lafer-Sousa, Luis; Wiest, Michael C; Conway, Bevil R

2012-05-01

Colors defined by the two intermediate directions in color space, "orange-cyan" and "lime-magenta," elicit the same spatiotemporal average response from the two cardinal chromatic channels in the lateral geniculate nucleus (LGN). While we found LGN functional magnetic resonance imaging (fMRI) responses to these pairs of colors were statistically indistinguishable, primary visual cortex (V1) fMRI responses were stronger to orange-cyan. Moreover, linear combinations of single-cell responses to cone-isolating stimuli of V1 cone-opponent cells also yielded stronger predicted responses to orange-cyan over lime-magenta, suggesting these neurons underlie the fMRI result. These observations are consistent with the hypothesis that V1 recombines LGN signals into "higher-order" mechanisms tuned to noncardinal color directions. In light of work showing that natural images and daylight samples are biased toward orange-cyan, our findings further suggest that V1 is adapted to daylight. V1, especially double-opponent cells, may function to extract spatial information from color boundaries correlated with scene-structure cues, such as shadows lit by ambient blue sky juxtaposed with surfaces reflecting sunshine. © 2012 Optical Society of America

Spatial and Temporal Features of Superordinate Semantic Processing Studied with fMRI and EEG.

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Michelle E Costanzo

2013-07-01

Full Text Available The relationships between the anatomical representation of semantic knowledge in the human brain and the timing of neurophysiological mechanisms involved in manipulating such information remain unclear. This is the case for superordinate semantic categorization – the extraction of general features shared by broad classes of exemplars (e.g. living vs. non-living semantic categories. We proposed that, because of the abstract nature, of this information, input from diverse input modalities (visual or auditory, lexical or non-lexical should converge and be processed in the same regions of the brain, at similar time scales during superordinate categorization - specifically in a network of heteromodal regions, and late in the course of the categorization process. In order to test this hypothesis, we utilized electroencephalography and event related potentials (EEG/ERP with functional magnetic resonance imaging (fMRI to characterize subjects’ responses as they made superordinate categorical decisions (living vs. nonliving about objects presented as visual pictures or auditory words. Our results reveal that, consistent with our hypothesis, during the course of superordinate categorization, information provided by these diverse inputs appears to converge in both time and space: fMRI showed that heteromodal areas of the parietal and temporal cortices are active during categorization of both classes of stimuli. The ERP results suggest that superordinate categorization is reflected as a late positive component (LPC with a parietal distribution and long latencies for both stimulus types. Within the areas and times in which modality independent responses were identified, some differences between living and non-living categories were observed, with a more widespread spatial extent and longer latency responses for categorization of non-living items.  

Spatial and temporal features of superordinate semantic processing studied with fMRI and EEG.

Science.gov (United States)

Costanzo, Michelle E; McArdle, Joseph J; Swett, Bruce; Nechaev, Vladimir; Kemeny, Stefan; Xu, Jiang; Braun, Allen R

2013-01-01

The relationships between the anatomical representation of semantic knowledge in the human brain and the timing of neurophysiological mechanisms involved in manipulating such information remain unclear. This is the case for superordinate semantic categorization-the extraction of general features shared by broad classes of exemplars (e.g., living vs. non-living semantic categories). We proposed that, because of the abstract nature of this information, input from diverse input modalities (visual or auditory, lexical or non-lexical) should converge and be processed in the same regions of the brain, at similar time scales during superordinate categorization-specifically in a network of heteromodal regions, and late in the course of the categorization process. In order to test this hypothesis, we utilized electroencephalography and event related potentials (EEG/ERP) with functional magnetic resonance imaging (fMRI) to characterize subjects' responses as they made superordinate categorical decisions (living vs. non-living) about objects presented as visual pictures or auditory words. Our results reveal that, consistent with our hypothesis, during the course of superordinate categorization, information provided by these diverse inputs appears to converge in both time and space: fMRI showed that heteromodal areas of the parietal and temporal cortices are active during categorization of both classes of stimuli. The ERP results suggest that superordinate categorization is reflected as a late positive component (LPC) with a parietal distribution and long latencies for both stimulus types. Within the areas and times in which modality independent responses were identified, some differences between living and non-living categories were observed, with a more widespread spatial extent and longer latency responses for categorization of non-living items.

Object recognition - Convergence of vision, audition, and touch

DEFF Research Database (Denmark)

Kassuba, Tanja

of object information across audition and touch or across all thee senses. Further, even though object recognition within different senses is to some degree redundant, the different senses differ with respect to their intrinsic efficiency in extracting types of information (Lederman & Klatzky, 2009...... magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), and repetitive transcranial magnetic stimulation (rTMS). The following research questions were addressed: 1. Where in the human brain does object recognition converge across vision, audition, and touch? 2. How is audio-haptic object......-match-to-sample task was applied in which participants had to match a target object with a previously presented sample object within and across audition and touch in both directions (auditory─haptic and haptic─auditory). As a coherence in content is an important binding cue (Laurienti et al., 2004), semantic...

Differential brain responses to cries of infants with autistic disorder and typical development: an fMRI study.

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Venuti, Paola; Caria, Andrea; Esposito, Gianluca; De Pisapia, Nicola; Bornstein, Marc H; de Falco, Simona

2012-01-01

This study used fMRI to measure brain activity during adult processing of cries of infants with autistic disorder (AD) compared to cries of typically developing (TD) infants. Using whole brain analysis, we found that cries of infants with AD compared to those of TD infants elicited enhanced activity in brain regions associated with verbal and prosodic processing, perhaps because altered acoustic patterns of AD cries render them especially difficult to interpret, and increased activity in brain regions associated with emotional processing, indicating that AD cries also elicit more negative feelings and may be perceived as more aversive and/or arousing. Perceived distress engendered by AD cries related to increased activation in brain regions associated with emotional processing. This study supports the hypothesis that cry is an early and meaningful anomaly displayed by children with AD. It could be that cries associated with AD alter parent-child interactions much earlier than the time that reliable AD diagnosis normally occurs. Copyright © 2012 Elsevier Ltd. All rights reserved.

How verbal and spatial manipulation networks contribute to calculation: An fMRI study

International Nuclear Information System (INIS)

Zago, L.; Petit, L.; Turbelin, M.R.; Anderson, F.; Vigneau, M.; Tzourio-Mazoyer, N.

2008-01-01

The manipulation of numbers required during calculation is known to rely on working memory (WM) resources. Here, we investigated the respective contributions of verbal and/or spatial WM manipulation brain networks during the addition of four numbers performed by adults, using functional magnetic resonance imaging (fMRI). Both manipulation and maintenance tasks were proposed with syllables, locations, or two-digit numbers. As compared to their maintenance, numbers manipulation (addition) elicited increased activation within a widespread cortical network including inferior temporal, parietal, and prefrontal regions. Our results demonstrate that mastery of arithmetic calculation requires the cooperation of three WM manipulation systems: an executive manipulation system conjointly recruited by the three manipulation tasks, including the anterior cingulate cortex (ACC), the orbital part of the inferior frontal gyrus, and the caudate nuclei; a left-lateralized, language-related, inferior fronto-temporal system elicited by numbers and syllables manipulation tasks required for retrieval, selection, and association of symbolic information; and a right superior and posterior fronto-parietal system elicited by numbers and locations manipulation tasks for spatial WM and attentional processes. Our results provide new information that the anterior intra-parietal sulcus (IPS) is involved in tasks requiring a magnitude processing with symbolic (numbers) and non-symbolic (locations) stimuli. Furthermore, the specificity of arithmetic processing is mediated by a left-hemispheric specialization of the anterior and posterior parts of the IPS as compared to a spatial task involving magnitude processing with non-symbolic material. (authors)

How verbal and spatial manipulation networks contribute to calculation: An fMRI study

Energy Technology Data Exchange (ETDEWEB)

Zago, L.; Petit, L.; Turbelin, M.R.; Anderson, F.; Vigneau, M.; Tzourio-Mazoyer, N. [Univ Paris 05, Univ Caen Basse Normandie, CEA, DSV, CNRS, CI NAPSUMR 6232, Paris (France)

2008-07-01

The manipulation of numbers required during calculation is known to rely on working memory (WM) resources. Here, we investigated the respective contributions of verbal and/or spatial WM manipulation brain networks during the addition of four numbers performed by adults, using functional magnetic resonance imaging (fMRI). Both manipulation and maintenance tasks were proposed with syllables, locations, or two-digit numbers. As compared to their maintenance, numbers manipulation (addition) elicited increased activation within a widespread cortical network including inferior temporal, parietal, and prefrontal regions. Our results demonstrate that mastery of arithmetic calculation requires the cooperation of three WM manipulation systems: an executive manipulation system conjointly recruited by the three manipulation tasks, including the anterior cingulate cortex (ACC), the orbital part of the inferior frontal gyrus, and the caudate nuclei; a left-lateralized, language-related, inferior fronto-temporal system elicited by numbers and syllables manipulation tasks required for retrieval, selection, and association of symbolic information; and a right superior and posterior fronto-parietal system elicited by numbers and locations manipulation tasks for spatial WM and attentional processes. Our results provide new information that the anterior intra-parietal sulcus (IPS) is involved in tasks requiring a magnitude processing with symbolic (numbers) and non-symbolic (locations) stimuli. Furthermore, the specificity of arithmetic processing is mediated by a left-hemispheric specialization of the anterior and posterior parts of the IPS as compared to a spatial task involving magnitude processing with non-symbolic material. (authors)

Left Posterior Orbitofrontal Cortex Is Associated With Odor-Induced Autobiographical Memory: An fMRI Study

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Keiko Watanabe

2018-05-01

Full Text Available Autobiographical odor memory (AM-odor accompanied by a sense of realism of a specific memory elicits strong emotions. AM-odor differs from memory triggered by other sensory modalities, possibly because olfaction involves a unique sensory process. Here, we examined the orbitofrontal cortex (OFC, using functional magnetic resonance imaging (fMRI to determine which OFC subregions are related to AM-odor. Both AM-odor and a control odor successively increased subjective ratings of comfortableness and pleasantness. Importantly, AM-odor also increased arousal levels and the vividness of memories, and was associated with a deep and slow breathing pattern. fMRI analysis indicated robust activation in the left posterior OFC (L-POFC. Connectivity between the POFC and whole brain regions was estimated using psychophysiological interaction analysis (PPI. We detected several trends in connectivity between L-POFC and bilateral precuneus, bilateral rostral dorsal anterior cingulate cortex (rdACC, and left parahippocampus, which will be useful for targeting our hypotheses for future investigations. The slow breathing observed in AM-odor was correlated with rdACC activation. Odor associated with emotionally significant autobiographical memories was accompanied by slow and deep breathing, possibly involving rdACC processing.

Left Posterior Orbitofrontal Cortex Is Associated With Odor-Induced Autobiographical Memory: An fMRI Study.

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Watanabe, Keiko; Masaoka, Yuri; Kawamura, Mitsuru; Yoshida, Masaki; Koiwa, Nobuyoshi; Yoshikawa, Akira; Kubota, Satomi; Ida, Masahiro; Ono, Kenjiro; Izumizaki, Masahiko

2018-01-01

Autobiographical odor memory (AM-odor) accompanied by a sense of realism of a specific memory elicits strong emotions. AM-odor differs from memory triggered by other sensory modalities, possibly because olfaction involves a unique sensory process. Here, we examined the orbitofrontal cortex (OFC), using functional magnetic resonance imaging (fMRI) to determine which OFC subregions are related to AM-odor. Both AM-odor and a control odor successively increased subjective ratings of comfortableness and pleasantness. Importantly, AM-odor also increased arousal levels and the vividness of memories, and was associated with a deep and slow breathing pattern. fMRI analysis indicated robust activation in the left posterior OFC (L-POFC). Connectivity between the POFC and whole brain regions was estimated using psychophysiological interaction analysis (PPI). We detected several trends in connectivity between L-POFC and bilateral precuneus, bilateral rostral dorsal anterior cingulate cortex (rdACC), and left parahippocampus, which will be useful for targeting our hypotheses for future investigations. The slow breathing observed in AM-odor was correlated with rdACC activation. Odor associated with emotionally significant autobiographical memories was accompanied by slow and deep breathing, possibly involving rdACC processing.

Spatially adaptive mixture modeling for analysis of FMRI time series.

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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

Resting state FMRI research in child psychiatric disorders

NARCIS (Netherlands)

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

A pooling-LiNGAM algorithm for effective connectivity analysis of fMRI data

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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.

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.)

Corticostriatal and Dopaminergic Response to Beer Flavor with Both fMRI and [(11) C]raclopride Positron Emission Tomography.

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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

Resting-state FMRI confounds and cleanup

Science.gov (United States)

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

Applying Convergent Immunity to Innovative Vaccines Targeting Staphylococcus aureus

Science.gov (United States)

Yeaman, Michael R.; Filler, Scott G.; Schmidt, Clint S.; Ibrahim, Ashraf S.; Edwards, John E.; Hennessey, John P.

2014-01-01

Recent perspectives forecast a new paradigm for future “third generation” vaccines based on commonalities found in diverse pathogens or convergent immune defenses to such pathogens. For Staphylococcus aureus, recurring infections and a limited success of vaccines containing S. aureus antigens imply that native antigens induce immune responses insufficient for optimal efficacy. These perspectives exemplify the need to apply novel vaccine strategies to high-priority pathogens. One such approach can be termed convergent immunity, where antigens from non-target organisms that contain epitope homologs found in the target organism are applied in vaccines. This approach aims to evoke atypical immune defenses via synergistic processes that (1) afford protective efficacy; (2) target an epitope from one organism that contributes to protective immunity against another; (3) cross-protect against multiple pathogens occupying a common anatomic or immunological niche; and/or (4) overcome immune subversion or avoidance strategies of target pathogens. Thus, convergent immunity has a potential to promote protective efficacy not usually elicited by native antigens from a target pathogen. Variations of this concept have been mainstays in the history of viral and bacterial vaccine development. A more far-reaching example is the pre-clinical evidence that specific fungal antigens can induce cross-kingdom protection against bacterial pathogens. This trans-kingdom protection has been demonstrated in pre-clinical studies of the recombinant Candida albicans agglutinin-like sequence 3 protein (rAls3) where it was shown that a vaccine containing rAls3 provides homologous protection against C. albicans, heterologous protection against several other Candida species, and convergent protection against several strains of S. aureus. Convergent immunity reflects an intriguing new approach to designing and developing vaccine antigens and is considered here in the context of vaccines to target S

Applying Convergent Immunity to Innovative Vaccines Targeting Staphylococcus aureus

Directory of Open Access Journals (Sweden)

Michael R Yeaman

2014-09-01

Full Text Available Recent perspectives forecast a new paradigm for future 3rd generation vaccines based on commonalities found in diverse pathogens or convergent immune defenses to such pathogens. For Staphylococcus aureus, recurring infections and a limited success of vaccines containing S. aureus antigens imply that native antigens induce immune responses insufficient for optimal efficacy. These perspectives exemplify the need to apply novel vaccine strategies to high priority pathogens. One such approach can be termed convergent immunity, where antigens from non-target organisms that contain epitope homologues found in the target organism are applied in vaccines. This approach aims to evoke atypical immune defenses via synergistic processes that 1 afford protective efficacy; 2 target an epitope from one organism that contributes to protective immunity against another; 3 cross-protect against multiple pathogens occupying a common anatomic or immunologic niche; and/or 4 overcome immune subversion or avoidance strategies of target pathogens. Thus, convergent immunity has a potential to promote protective efficacy not usually elicited by native antigens from a target pathogen. Variations of this concept have been mainstays in the history of viral and bacterial vaccine development. A more far-reaching example is the pre–clinical evidence that specific fungal antigens can induce cross-kingdom protection against bacterial pathogens. This trans-kingdom protection has been demonstrated in preclinical studies of the recombinant Candida albicans agglutinin-like sequence 3 protein (rAls3 where it was shown that a vaccine containing rAls3 provides homologous protection against C. albicans, heterologous protection against several other Candida species, and convergent protection against several strains of S. aureus. Convergent immunity reflects an intriguing new approach to designing and developing vaccine antigens and is considered here in the context of vaccines to target

Mapping of the brain hemodynamic responses to sensorimotor stimulation in a rodent model: A BOLD fMRI study.

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Salem Boussida

Full Text Available Blood Oxygenation Level Dependent functional MRI (BOLD fMRI during electrical paw stimulation has been widely used in studies aimed at the understanding of the somatosensory network in rats. However, despite the well-established anatomical connections between cortical and subcortical structures of the sensorimotor system, most of these functional studies have been concentrated on the cortical effects of sensory electrical stimulation. BOLD fMRI study of the integration of a sensorimotor input across the sensorimotor network requires an appropriate methodology to elicit functional activation in cortical and subcortical areas owing to the regional differences in both neuronal and vascular architectures between these brain regions. Here, using a combination of low level anesthesia, long pulse duration of the electrical stimulation along with improved spatial and temporal signal to noise ratios, we provide a functional description of the main cortical and subcortical structures of the sensorimotor rat brain. With this calibrated fMRI protocol, unilateral non-noxious sensorimotor electrical hindpaw stimulation resulted in robust positive activations in the contralateral sensorimotor cortex and bilaterally in the sensorimotor thalamus nuclei, whereas negative activations were observed bilaterally in the dorsolateral caudate-putamen. These results demonstrate that, once the experimental setup allowing necessary spatial and temporal signal to noise ratios is reached, hemodynamic changes related to neuronal activity, as preserved by the combination of a soft anesthesia with a soft muscle relaxation, can be measured within the sensorimotor network. Moreover, the observed responses suggest that increasing pulse duration of the electrical stimulus adds a proprioceptive component to the sensory input that activates sensorimotor network in the brain, and that these activation patterns are similar to those induced by digits paw's movements. These findings may

Gender differences in the processing of disgust- and fear-inducing pictures: an fMRI study.

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Schienle, Anne; Schäfer, Axel; Stark, Rudolf; Walter, Bertram; Vaitl, Dieter

2005-02-28

We examined whether males and females differ in the intensity and laterality of their hemodynamic responses towards visual disgust and fear stimuli. Forty-one female, and 51 male subjects viewed disgust-inducing, fear-inducing and neutral pictures in an fMRI block design. Self-report data indicated that the target emotions had been elicited successfully with women responding stronger than men. While viewing the fear pictures, which depicted attacks by humans or animals, men exhibited greater activation in the bilateral amygdala and the left fusiform gyrus than women. This response pattern may reflect greater attention from males to cues of aggression in their environment. Further, the lateralization of brain activation was comparable in the two genders during both aversive picture conditions.

Convergence accommodation to convergence CA/C ratio: convergence versus divergence.

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Simmons, Joshua M; Firth, Alison Y

2014-09-01

To determine whether the convergence accommodation to convergence (CA/C) ratio during divergence with base-in (BI) prisms is of a similar or different magnitude to that measured during convergence with base-out (BO) prisms. Eighteen participants with normal binocular single vision were recruited. The participants viewed a pseudo-Gaussian target, which consisted of a light emitting diode (LED) behind a diffusing screen at 40 cm. After 5 minutes of dark adaptation, the refractive status of the eye was measured without any prism using a Shin-Nippon SRW-5000 autorefractor. The participant held the selected prism (5Δ or 10Δ BO or BI, counterbalanced) in front of their right eye and obtained a single, fused image of the target while refractive measures were taken with each. A 30-second rest period was given between measurements. The mean age of the participants was 20.6±3.22 years. The mean CA/C ratios for the 5Δ BO, 10Δ BO, 5Δ BI, and 10Δ BI were 0.108 (±0.074) D/Δ, 0.110 (±0.056) D/Δ, 0.100 (±0.090) D/Δ, and 0.089 (±0.055) D/Δ, respectively. A 2-factor repeated measures ANOVA found that the CA/C ratio did not significantly change with differing levels of prism-induced convergence and divergence (p=0.649). Change in accommodation induced by manipulating vergence is similar whether convergence or divergence are induced. The CA/C ratio did not show any change with differing levels of prism-induced convergence and divergence.

Network modelling methods for FMRI.

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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.

Convergent validity between willingness to pay elicitation methods: an application to Grand Canyon whitewater boaters

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Neher, Christopher; Bair, Lucas S.; Duffield, John; Patterson, David A.; Neher, Katherine

2018-01-01

We directly compare trip willingness to pay (WTP) values between dichotomous choice contingent valuation (DCCV) and discrete choice experiment (DCE) stated preference surveys of private party Grand Canyon whitewater boaters. The consistency of DCCV and DCE estimates is debated in the literature, and this study contributes to the body of work comparing the methods. Comparisons were made of mean WTP estimates for four hypothetical Colorado River flow-level scenarios. Boaters were found to most highly value mid-range flows, with very low and very high flows eliciting lower WTP estimates across both DCE and DCCV surveys. Mean WTP precision was estimated through simulation. No statistically significant differences were detected between the two methods at three of the four hypothetical flow levels.

Multiplier convergent series and uniform convergence of mapping ...

Indian Academy of Sciences (India)

MS received 14 April 2011; revised 17 November 2012. Abstract. In this paper, we introduce the frame property of complex sequence sets and study the uniform convergence of nonlinear mapping series in β-dual of spaces consisting of multiplier convergent series. Keywords. Multiplier convergent series; mapping series. 1.

Temporal and Spatial Independent Component Analysis for fMRI Data Sets Embedded in the AnalyzeFMRI R Package

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.

Processing and regulation of negative emotions in anorexia nervosa: An fMRI study

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Maria Seidel

Full Text Available Theoretical models and recent advances in the treatment of anorexia nervosa (AN have increasingly focused on the role of alterations in the processing and regulation of emotions. To date, however, our understanding of these changes is still limited and reports of emotional dysregulation in AN have been based largely on self-report data, and there is a relative lack of objective experimental evidence or neurobiological data.The current functional magnetic resonance imaging (fMRI study investigated the hemodynamic correlates of passive viewing and voluntary downregulation of negative emotions by means of the reappraisal strategy detachment in AN patients. Detachment is regarded as adaptive regulation strategy associated with a reduction in emotion-related amygdala activity and increased recruitment of prefrontal brain regions associated with cognitive control processes. Emotion regulation efficacy was assessed via behavioral arousal ratings and fMRI activation elicited by an established experimental paradigm including negative images. Participants were instructed to either simply view emotional pictures or detach themselves from feelings triggered by the stimuli.The sample consisted of 36 predominantly adolescent female AN patients and a pairwise age-matched healthy control group. Behavioral and neuroimaging data analyses indicated a reduction of arousal and amygdala activity during the regulation condition for both patients and controls. However, compared with controls, individuals with AN showed increased activation in the amygdala as well as in the right dorsolateral prefrontal cortex (dlPFC during the passive viewing of aversive compared with neutral pictures.These results extend previous findings indicative of altered processing of salient emotional stimuli in AN, but do not point to a general deficit in the voluntary regulation of negative emotions. Increased dlPFC activation in AN during passive viewing of negative stimuli is in line with

Neural correlates of experienced moral emotion: an fMRI investigation of emotion in response to prejudice feedback.

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Fourie, Melike M; Thomas, Kevin G F; Amodio, David M; Warton, Christopher M R; Meintjes, Ernesta M

2014-01-01

Guilt, shame, and embarrassment are quintessential moral emotions with important regulatory functions for the individual and society. Moral emotions are, however, difficult to study with neuroimaging methods because their elicitation is more intricate than that of basic emotions. Here, using functional MRI (fMRI), we employed a novel social prejudice paradigm to examine specific brain regions associated with real-time moral emotion, focusing on guilt and related moral-negative emotions. The paradigm induced intense moral-negative emotion (primarily guilt) in 22 low-prejudice individuals through preprogrammed feedback indicating implicit prejudice against Black and disabled people. fMRI data indicated that this experience of moral-negative emotion was associated with increased activity in anterior paralimbic structures, including the anterior cingulate cortex (ACC) and anterior insula, in addition to areas associated with mentalizing, including the dorsomedial prefrontal cortex, posterior cingulate cortex, and precuneus. Of significance was prominent conflict-related activity in the supragenual ACC, which is consistent with theories proposing an association between acute guilt and behavioral inhibition. Finally, a significant negative association between self-reported guilt and neural activity in the pregenual ACC suggested a role of self-regulatory processes in response to moral-negative affect. These findings are consistent with the multifaceted self-regulatory functions of moral-negative emotions in social behavior.

Behavior, neuropsychology and fMRI.

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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.

Technology assessment using NBIC convergence

International Nuclear Information System (INIS)

Vaseashta, Ashok

2009-01-01

Technologies' has considerably influenced scientific and social thinking about the future, there are several active debates in progress. The first being about the future of technologies and their relations to humans as nanoscale materials and systems provide the means to probe cells and provide basis for human performance augmentation - hence contributing to the formation of political and public opinion on societal aspects of science and technology. Such debates have lead to socio-political and ethical issues that transcend academic disciplinary borders that are rooted outside of the scientific arena. Thus it necessitates, inter- and often trans-disciplinary research to contribute effectively to these formative process. Such concerns are independently addressed using studies relating to toxicology, fate, transport, and bioavailability of nanomaterials, as well as human exposures to these materials. On another front, the debate is on the future of the scientific disciplines and visions about technological developments. Such predictions often relate to human way of life, environmental and international security, and are used by scientists, engineers, managers, policymakers, media, philosophers and authors - all with different interpretations. We present balanced, yet strategic assessments and recommendations of revolutionary scientific breakthroughs in multidisciplinary environments based on the NBIC convergence approach. Technology roadmaps are cautiously formulated based on extensive research, expert elicitation, and networking approaches to project 'future scenarios' realistically and epistemologically. Such roadmaps enable development of transformative tools and methodologies that fill fundamental knowledge gaps, and change culture in academia to foster collaboration, thus providing unique solutions. It is expected that the synergy arising from converging technologies and research methodologies at the IASC will leverage emerging and potentially transformative studies. The

An fMRI study

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 ...

Advances in fMRI Real-Time Neurofeedback.

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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.

Stimulus-Elicited Connectivity Influences Resting-State Connectivity Years Later in Human Development: A Prospective Study.

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Gabard-Durnam, Laurel Joy; Gee, Dylan Grace; Goff, Bonnie; Flannery, Jessica; Telzer, Eva; Humphreys, Kathryn Leigh; Lumian, Daniel Stephen; Fareri, Dominic Stephen; Caldera, Christina; Tottenham, Nim

2016-04-27

Although the functional architecture of the brain is indexed by resting-state connectivity networks, little is currently known about the mechanisms through which these networks assemble into stable mature patterns. The current study posits and tests the long-term phasic molding hypothesis that resting-state networks are gradually shaped by recurring stimulus-elicited connectivity across development by examining how both stimulus-elicited and resting-state functional connections of the human brain emerge over development at the systems level. Using a sequential design following 4- to 18-year-olds over a 2 year period, we examined the predictive associations between stimulus-elicited and resting-state connectivity in amygdala-cortical circuitry as an exemplar case (given this network's protracted development across these ages). Age-related changes in amygdala functional connectivity converged on the same regions of medial prefrontal cortex (mPFC) and inferior frontal gyrus when elicited by emotional stimuli and when measured at rest. Consistent with the long-term phasic molding hypothesis, prospective analyses for both connections showed that the magnitude of an individual's stimulus-elicited connectivity unidirectionally predicted resting-state functional connectivity 2 years later. For the amygdala-mPFC connection, only stimulus-elicited connectivity during childhood and the transition to adolescence shaped future resting-state connectivity, consistent with a sensitive period ending with adolescence for the amygdala-mPFC circuit. Together, these findings suggest that resting-state functional architecture may arise from phasic patterns of functional connectivity elicited by environmental stimuli over the course of development on the order of years. A fundamental issue in understanding the ontogeny of brain function is how resting-state (intrinsic) functional networks emerge and relate to stimulus-elicited functional connectivity. Here, we posit and test the long

EEG-Informed fMRI: A Review of Data Analysis Methods

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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

EEG-Informed fMRI: A Review of Data Analysis Methods

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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.

Triple representation of language, working memory, social and emotion processing in the cerebellum: convergent evidence from task and seed-based resting-state fMRI analyses in a single large cohort.

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Guell, Xavier; Gabrieli, John D E; Schmahmann, Jeremy D

2018-05-15

Delineation of functional topography is critical to the evolving understanding of the cerebellum's role in a wide range of nervous system functions. We used data from the Human Connectome Project (n = 787) to analyze cerebellar fMRI task activation (motor, working memory, language, social and emotion processing) and resting-state functional connectivity calculated from cerebral cortical seeds corresponding to the peak Cohen's d of each task contrast. The combination of exceptional statistical power, activation from both motor and multiple non-motor tasks in the same participants, and convergent resting-state networks in the same participants revealed novel aspects of the functional topography of the human cerebellum. Consistent with prior studies there were two distinct representations of motor activation. Newly revealed were three distinct representations each for working memory, language, social, and emotional task processing that were largely separate for these four cognitive and affective domains. In most cases, the task-based activations and the corresponding resting-network correlations were congruent in identifying the two motor representations and the three non-motor representations that were unique to working memory, language, social cognition, and emotion. The definitive localization and characterization of distinct triple representations for cognition and emotion task processing in the cerebellum opens up new basic science questions as to why there are triple representations (what different functions are enabled by the different representations?) and new clinical questions (what are the differing consequences of lesions to the different representations?). Copyright © 2018 Elsevier Inc. All rights reserved.

Monkey cortex through fMRI glasses.

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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.

Bilateral contributions of the cerebellum to the complex motor tasks on EPI fMRI

International Nuclear Information System (INIS)

Chung, Eun Chul; Youn, Eun Kyung; Lee, Young Rae; Kim, Yoo Kyung; Park, Kee Duk

1999-01-01

To demonstrate activation signals within the cerebellar cortex and to determine the side of the cerebellar cortex eliciting activation signals in response to complex motor tasks, as seen on EPI fMRI. Seven right-handed subjects (M : F=3 : 4; mean age, 30.3 years) underwent repetitive finger apposition with the dominant right hand. Using a 1.5 T MRI scanner, EPI fMR images were obtained. MR parameters used for EPI fMRI were TR/TE/Flip angle : 0.96 msec/64msec/90 deg FOV 22cm, 128 X 128 matrix, 10 slices, 10mm thickness while those for SE T1 weighted localized images were TR/TE : 450/16, FOV 23cm, 256 X 256 matrix. The paradigm was three sets of alternate resting and moving fingers for six cycles, resulting in times of 360 seconds (10 slices X 15 EPI X 6 cycles = 900 images). Image processing involved the use of a 200mHz Dual Pentium PC with homemade software. T-testing (p < 0.005 approx.= p < 0.0005) and time series analysis were performed, and to verify the locations of activated regions, resulting images were analyzed in a color-coded overlay to reference T1-weighted spin echo coronal images. Percentage change in signal intensity (PCSI) was calculated from the processed data. All normal subjects showed significant activation signals in both the contralateral (left) primary motor cortex (PCSI = 3.12% 0.96) and ipsilateral (right) cerebellar cortex (PCSI = 3.09% ±1.14). Signal activation was detected in the contralateral supplemental motor area (2.91% ±0.82), and motor activation in the anterior upper half of the contralateral cerebellum (PCSI 2.50% ±0.69). The difference in activation signals between both sides of the cerebellar cortex was not statistically significant. All data were matched with time-series analysis. Bilateral cerebellar activation is associated with unilateral complex finger movements, as seen on fMRI. This result may support the recent neurological observation that the cerebellum may exert bilateral effects on motor performance

Convergence

Science.gov (United States)

Darcie, Thomas E.; Doverspike, Robert; Zirngibl, Martin; Korotky, Steven K.

2005-01-01

.p {padding-bottom:6px} Call for Papers: Convergence Guest Editors: Thomas E. Darcie, University of Victoria Robert Doverspike, AT&T Martin Zirngibl, Lucent Technologies Coordinating Associate Editor: Steven K. Korotky, Lucent Technologies The Journal of Optical Networking (JON) invites submissions to a special issue on Convergence. Convergence has become a popular theme in telecommunications, one that has broad implications across all segments of the industry. Continual evolution of technology and applications continues to erase lines between traditionally separate lines of business, with dramatic consequences for vendors, service providers, and consumers. Spectacular advances in all layers of optical networking-leading to abundant, dynamic, cost-effective, and reliable wide-area and local-area connections-have been essential drivers of this evolution. As services and networks continue to evolve towards some notion of convergence, the continued role of optical networks must be explored. One vision of convergence renders all information in a common packet (especially IP) format. This vision is driven by the proliferation of data services. For example, time-division multiplexed (TDM) voice becomes VoIP. Analog cable-television signals become MPEG bits streamed to digital set-top boxes. T1 or OC-N private lines migrate to Ethernet virtual private networks (VPNs). All these packets coexist peacefully within a single packet-routing methodology built on an optical transport layer that combines the flexibility and cost of data networks with telecom-grade reliability. While this vision is appealing in its simplicity and shared widely, specifics of implementation raise many challenges and differences of opinion. For example, many seek to expand the role of Ethernet in these transport networks, while massive efforts are underway to make traditional TDM networks more data friendly within an evolved but backward-compatible SDH/SONET (synchronous digital hierarchy and

Convergence

Science.gov (United States)

Darcie, Thomas E.; Doverspike, Robert; Zirngibl, Martin; Korotky, Steven K.

2005-09-01

Call for Papers: Convergence The Journal of Optical Networking (JON) invites submissions to a special issue on Convergence. Convergence has become a popular theme in telecommunications, one that has broad implications across all segments of the industry. Continual evolution of technology and applications continues to erase lines between traditionally separate lines of business, with dramatic consequences for vendors, service providers, and consumers. Spectacular advances in all layers of optical networking-leading to abundant, dynamic, cost-effective, and reliable wide-area and local-area connections-have been essential drivers of this evolution. As services and networks continue to evolve towards some notion of convergence, the continued role of optical networks must be explored. One vision of convergence renders all information in a common packet (especially IP) format. This vision is driven by the proliferation of data services. For example, time-division multiplexed (TDM) voice becomes VoIP. Analog cable-television signals become MPEG bits streamed to digital set-top boxes. T1 or OC-N private lines migrate to Ethernet virtual private networks (VPNs). All these packets coexist peacefully within a single packet-routing methodology built on an optical transport layer that combines the flexibility and cost of data networks with telecom-grade reliability. While this vision is appealing in its simplicity and shared widely, specifics of implementation raise many challenges and differences of opinion. For example, many seek to expand the role of Ethernet in these transport networks, while massive efforts are underway to make traditional TDM networks more data friendly within an evolved but backward-compatible SDH/SONET (synchronous digital hierarchy and synchronous optical network) multiplexing hierarchy. From this common underlying theme follow many specific instantiations. Examples include the convergence at the physical, logical, and operational levels of voice and

Improving fMRI reliability in presurgical mapping for brain tumours.

Science.gov (United States)

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

ANALYSIS OF CONVERGENCE WITHIN THE EUROPEAN UNION SIGMA AND BETA CONVERGENCE

Directory of Open Access Journals (Sweden)

Begu Liviu-Stelian

2010-12-01

Full Text Available Real convergence study began with the development of neoclassical models of growth and especially with the passage of econometric applications of these models. In this paper we present applications of indicators and patterns of convergence on the example of European Union member countries and some current economic impact assessments on European convergence process. This analysis is based on the estimated a- and b convergence and on Markov chains. The study deals with the economic convergence of the European countries and especially the convergence of the EU countries, including Romania. In the end of the study presents several economic scenarios for a faster and easier exit from the current crisis in Romania.

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.

Automatic fission source convergence criteria for Monte Carlo criticality calculations

International Nuclear Information System (INIS)

Shim, Hyung Jin; Kim, Chang Hyo

2005-01-01

The Monte Carlo criticality calculations for the multiplication factor and the power distribution in a nuclear system require knowledge of stationary or fundamental-mode fission source distribution (FSD) in the system. Because it is a priori unknown, so-called inactive cycle Monte Carlo (MC) runs are performed to determine it. The inactive cycle MC runs should be continued until the FSD converges to the stationary FSD. Obviously, if one stops them prematurely, the MC calculation results may have biases because the followup active cycles may be run with the non-stationary FSD. Conversely, if one performs the inactive cycle MC runs more than necessary, one is apt to waste computing time because inactive cycle MC runs are used to elicit the fundamental-mode FSD only. In the absence of suitable criteria for terminating the inactive cycle MC runs, one cannot but rely on empiricism in deciding how many inactive cycles one should conduct for a given problem. Depending on the problem, this may introduce biases into Monte Carlo estimates of the parameters one tries to calculate. The purpose of this paper is to present new fission source convergence criteria designed for the automatic termination of inactive cycle MC runs

Functional Laterality of Task-Evoked Activation in Sensorimotor Cortex of Preterm Infants: An Optimized 3 T fMRI Study Employing a Customized Neonatal Head Coil.

Science.gov (United States)

Scheef, Lukas; Nordmeyer-Massner, Jurek A; Smith-Collins, Adam Pr; Müller, Nicole; Stegmann-Woessner, Gaby; Jankowski, Jacob; Gieseke, Jürgen; Born, Mark; Seitz, Hermann; Bartmann, Peter; Schild, Hans H; Pruessmann, Klaas P; Heep, Axel; Boecker, Henning

2017-01-01

Functional magnetic resonance imaging (fMRI) in neonates has been introduced as a non-invasive method for studying sensorimotor processing in the developing brain. However, previous neonatal studies have delivered conflicting results regarding localization, lateralization, and directionality of blood oxygenation level dependent (BOLD) responses in sensorimotor cortex (SMC). Amongst the confounding factors in interpreting neonatal fMRI studies include the use of standard adult MR-coils providing insufficient signal to noise, and liberal statistical thresholds, compromising clinical interpretation at the single subject level. Here, we employed a custom-designed neonatal MR-coil adapted and optimized to the head size of a newborn in order to improve robustness, reliability and validity of neonatal sensorimotor fMRI. Thirteen preterm infants with a median gestational age of 26 weeks were scanned at term-corrected age using a prototype 8-channel neonatal head coil at 3T (Achieva, Philips, Best, NL). Sensorimotor stimulation was elicited by passive extension/flexion of the elbow at 1 Hz in a block design. Analysis of temporal signal to noise ratio (tSNR) was performed on the whole brain and the SMC, and was compared to data acquired with an 'adult' 8 channel head coil published previously. Task-evoked activation was determined by single-subject SPM8 analyses, thresholded at p lateralization of SMC activation, as found in children and adults, is already present in the newborn period.

High-field fMRI unveils orientation columns in humans.

Science.gov (United States)

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.

The Use of Cognitive Maps for Requirements Elicitation in Product Development

Directory of Open Access Journals (Sweden)

Raquel Dias

2016-04-01

Full Text Available This article approaches Engineering Requirements concepts and proposes the use of cognitive maps as support to the problem identification of the stakeholders during the requirements elicitation process. It presents a case study of the aerospace cluster of São José dos Campos, State of São Paulo. The cognitive map technique was developed to represent the views of the individuals, generating cognitive maps, which, in an aggregated way, express graphically the collective vision to support the decision-making process. Applied to Engineering Requirements, it has revealed the potential to promote the convergence of different points of view on the actual stakeholders’ needs in innovative fashion. This technique has demonstrated effectiveness when approaching the stated requirements early in the development process implemented throughout the life cycle of the system/product.

Vergence increases the gain of the human angular vestibulo-ocular reflex during peripheral hyposensitivity elicited by cold thermal irrigation.

Science.gov (United States)

Tamás, László T; Lundberg, Yunxia W; Büki, Béla

2018-01-01

When viewing a far target, the gain of the horizontal vestibulo-ocular reflex (VOR) is around 1.0, but when viewing a near target there is an increased response. It has been shown that while this convergence-mediated modulation is unaffected by canal plugging and clinically practical transmastoid galvanic stimulation, it is eliminated by a partial peripheral gentamicin lesion. The aim of this study was to determine if convergence increases the gain during peripheral hyposensitivity elicited by cold thermal irrigation. The high frequency VOR gain was measured using video head impulse testing immediately after the cold caloric stimulus in 9 healthy human subjects with the lateral semicircular canals oriented approximately earth-vertical. Before caloric irrigation, near viewing (15 cm) increased the average VOR gain by 28% (from 1 to 1.28). Cold (24°C) water irrigation of the right ear decreased the gain to 0.66 (far viewing) and 0.82 (near viewing) (22% difference). Although vergence also increased the gain for impulses to the left to the same degree before caloric stimulus, the caloric irrigation itself (applied to the right ear) did not influence the gain for contralateral impulses. In our experiments vergence increased the gain of the human angular VOR during peripheral hyposensitivity elicited by cold thermal irrigation. These results suggest that cold irrigation does not abolish the function of the nonlinear/phasic vestibular afferent pathway.

Broadband Electrophysiological Dynamics Contribute to Global Resting-State fMRI Signal.

Science.gov (United States)

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

Science and technology convergence: with emphasis for nanotechnology-inspired convergence

Energy Technology Data Exchange (ETDEWEB)

Bainbridge, William S.; Roco, Mihail C., E-mail: mroco@nsf.gov [National Science Foundation (United States)

2016-07-15

Convergence offers a new universe of discovery, innovation, and application opportunities through specific theories, principles, and methods to be implemented in research, education, production, and other societal activities. Using a holistic approach with shared goals, convergence seeks to transcend existing human limitations to achieve improved conditions for work, learning, aging, physical, and cognitive wellness. This paper outlines ten key theories that offer complementary perspectives on this complex dynamic. Principles and methods are proposed to facilitate and enhance science and technology convergence. Several convergence success stories in the first part of the 21st century—including nanotechnology and other emerging technologies—are discussed in parallel with case studies focused on the future. The formulation of relevant theories, principles, and methods aims at establishing the convergence science.

Science and technology convergence: with emphasis for nanotechnology-inspired convergence

International Nuclear Information System (INIS)

Bainbridge, William S.; Roco, Mihail C.

2016-01-01

Convergence offers a new universe of discovery, innovation, and application opportunities through specific theories, principles, and methods to be implemented in research, education, production, and other societal activities. Using a holistic approach with shared goals, convergence seeks to transcend existing human limitations to achieve improved conditions for work, learning, aging, physical, and cognitive wellness. This paper outlines ten key theories that offer complementary perspectives on this complex dynamic. Principles and methods are proposed to facilitate and enhance science and technology convergence. Several convergence success stories in the first part of the 21st century—including nanotechnology and other emerging technologies—are discussed in parallel with case studies focused on the future. The formulation of relevant theories, principles, and methods aims at establishing the convergence science.

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.)

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.)

Activation Detection in fMRI Using Jeffrey Divergence

Science.gov (United States)

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.

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.

fMRI Evidence of Acupoints Specificity in Two Adjacent Acupoints

Directory of Open Access Journals (Sweden)

Hua Liu

2013-01-01

Full Text Available Objectives. Acupoint specificity is the foundation of acupuncture treatment. The aim of this study is to investigate whether the acupoint specificity exists in two adjacent acupoints. Design and Setting. Two adjacent real acupoints, LR3 (Taichong and ST44 (Neiting, and a nearby nonacupoint were selected. Thirty-three health volunteers were divided into three groups in random order, and each group only received acupuncture at one of the three points. While they received acupuncture, fMRI scan was performed. Results. The common cerebral activated areas responding to LR3 and ST44 included the contralateral primary somatosensory area (SI and ipsilateral cerebellum. Acupuncture at LR3 specifically activated contralateral middle occipital gyrus, ipsilateral medial frontal gyrus, superior parietal lobe, middle temporal gyrus, rostral anterior cingulate cortex (rACC, lentiform nucleus, insula, and contralateral thalamus. Stimulation at ST44 selectively activated ipsilateral secondary somatosensory area (SII, contralateral middle frontal gyrus, inferior frontal gyrus, lingual gyrus, lentiform nucleus, and bilateral posterior cingulate cortex (PCC. Conclusions. Acupuncture at adjacent acupoints elicits distinct cerebral activation patterns, and those specific patterns might be involved in the mechanism of the specific therapeutic effects of different acupoints.

IT-BT convergence technology

International Nuclear Information System (INIS)

2012-12-01

This book explains IT-BT convergence technology as the future technology, which includes a prolog, easy IT-BT convergence technology that has infinite potentials for new value, policy of IT-BT convergence technology showing the potential of smart Korea, IT-BT convergence opening happy future, for the new future of IT powerful nation Korea with IT-BT convergence technology and an epilogue. This book reveals the conception, policy, performance and future of IT-BT convergence technology.

An Experimental Study of the Use of Design Thinking as a Requirements Elicitation Approach for Mobile Learning Environments

Directory of Open Access Journals (Sweden)

Carla Silva

2015-04-01

Full Text Available Mobile learning (m-learning is a research field that aims to analyze how mobile devices can contribute to learning. The development of software for mobile devices to support learning is essential for an effective implementation of m-learning or mobile learning environments (MLE. Requirements Engineering processes need to include activities that provoke creativity in the stakeholders to conceive MLEs that actually modify and improve the teaching and learning process. In this context, this paper presents a process for requirements elicitation and documentation of mobile learning environments. This process is based on the concepts of the Design Thinking process that provides a methodology to elicit customer needs, producing simple prototypes that eventually converge to innovative solutions. An experiment was conducted to evaluate if the proposed process contributes to create MLEs that present distinctive and interesting characteristics when compared to existing solutions for a specific problem.

Adaptation of a haptic robot in a 3T fMRI.

Science.gov (United States)

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

A comparison of five elicitation techniques for elicitation of attributes of low involvement products

DEFF Research Database (Denmark)

Bech-Larsen, Tino; Nielsen, Niels Asger

1999-01-01

of dimensions directed from theories of consumer buying behaviour. Although a number of differences between the techniques are identified in the study, the main findings are that the robustness of the different techniques for attribute elicitation is considerable Udgivelsesdato: JUN......The critical first step for most instruments used in analysing consumer choice and motivation is the identification of product attributes which are important to the consumer and for which there are differences among the available product alternatives. A number of techniques, ranging from...... the complex elicitation of idiosyncratic attributes or simpler picking procedures, has been developed to elicitate such attributes. The purpose of the study presented here is to com-pare attributes of a low involvement product, viz. vegetable oil, elicited by five different techniques on a number...

Brain network segregation and integration during an epoch-related working memory fMRI experiment.

Science.gov (United States)

Fransson, Peter; Schiffler, Björn C; Thompson, William Hedley

2018-05-17

The characterization of brain subnetwork segregation and integration has previously focused on changes that are detectable at the level of entire sessions or epochs of imaging data. In this study, we applied time-varying functional connectivity analysis together with temporal network theory to calculate point-by-point estimates in subnetwork segregation and integration during an epoch-based (2-back, 0-back, baseline) working memory fMRI experiment as well as during resting-state. This approach allowed us to follow task-related changes in subnetwork segregation and integration at a high temporal resolution. At a global level, the cognitively more taxing 2-back epochs elicited an overall stronger response of integration between subnetworks compared to the 0-back epochs. Moreover, the visual, sensorimotor and fronto-parietal subnetworks displayed characteristic and distinct temporal profiles of segregation and integration during the 0- and 2-back epochs. During the interspersed epochs of baseline, several subnetworks, including the visual, fronto-parietal, cingulo-opercular and dorsal attention subnetworks showed pronounced increases in segregation. Using a drift diffusion model we show that the response time for the 2-back trials are correlated with integration for the fronto-parietal subnetwork and correlated with segregation for the visual subnetwork. Our results elucidate the fast-evolving events with regard to subnetwork integration and segregation that occur in an epoch-related task fMRI experiment. Our findings suggest that minute changes in subnetwork integration are of importance for task performance. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Acoustic fMRI noise : Linear time-invariant system model

NARCIS (Netherlands)

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

Convergence in Multispecies Interactions

OpenAIRE

Bittleston, Leonora Sophia; Pierce, Naomi E.; Ellison, Aaron M.; Pringle, Anne

2016-01-01

The concepts of convergent evolution and community convergence highlight how selective pressures can shape unrelated organisms or communities in similar ways. We propose a related concept, convergent interactions, to describe the independent evolution of multispecies interactions with similar physiological or ecological functions. A focus on convergent interactions clarifies how natural selection repeatedly favors particular kinds of associations among species. Characterizing convergent inter...

Brain activation profiles during kinesthetic and visual imagery: An fMRI study.

Science.gov (United States)

Kilintari, Marina; Narayana, Shalini; Babajani-Feremi, Abbas; Rezaie, Roozbeh; Papanicolaou, Andrew C

2016-09-01

The aim of this study was to identify brain regions involved in motor imagery and differentiate two alternative strategies in its implementation: imagining a motor act using kinesthetic or visual imagery. Fourteen adults were precisely instructed and trained on how to imagine themselves or others perform a movement sequence, with the aim of promoting kinesthetic and visual imagery, respectively, in the context of an fMRI experiment using block design. We found that neither modality of motor imagery elicits activation of the primary motor cortex and that each of the two modalities involves activation of the premotor area which is also activated during action execution and action observation conditions, as well as of the supplementary motor area. Interestingly, the visual and the posterior cingulate cortices show reduced BOLD signal during both imagery conditions. Our results indicate that the networks of regions activated in kinesthetic and visual imagery of motor sequences show a substantial, while not complete overlap, and that the two forms of motor imagery lead to a differential suppression of visual areas. Copyright © 2016 Elsevier B.V. All rights reserved.

On the convergence of finite state mean-field games through Γ-convergence

KAUST Repository

Ferreira, Rita C.; Gomes, Diogo A.

2014-01-01

In this study, we consider the long-term convergence (trend toward an equilibrium) of finite state mean-field games using Γ-convergence. Our techniques are based on the observation that an important class of mean-field games can be viewed as the Euler-Lagrange equation of a suitable functional. Therefore, using a scaling argument, one can convert a long-term convergence problem into a Γ-convergence problem. Our results generalize previous results related to long-term convergence for finite state problems. © 2014 Elsevier Inc.

On the convergence of finite state mean-field games through Γ-convergence

KAUST Repository

Ferreira, Rita C.

2014-10-01

In this study, we consider the long-term convergence (trend toward an equilibrium) of finite state mean-field games using Γ-convergence. Our techniques are based on the observation that an important class of mean-field games can be viewed as the Euler-Lagrange equation of a suitable functional. Therefore, using a scaling argument, one can convert a long-term convergence problem into a Γ-convergence problem. Our results generalize previous results related to long-term convergence for finite state problems. © 2014 Elsevier Inc.

Neuroimaging studies of practice-related change: fMRI and meta-analytic evidence of a domain-general control network for learning.

Science.gov (United States)

Chein, Jason M; Schneider, Walter

2005-12-01

Functional magnetic resonance imaging and a meta-analysis of prior neuroimaging studies were used to characterize cortical changes resulting from extensive practice and to evaluate a dual-processing account of the neural mechanisms underlying human learning. Three core predictions of the dual processing theory are evaluated: 1) that practice elicits generalized reductions in regional activity by reducing the load on the cognitive control mechanisms that scaffold early learning; 2) that these control mechanisms are domain-general; and 3) that no separate processing pathway emerges as skill develops. To evaluate these predictions, a meta-analysis of prior neuroimaging studies and a within-subjects fMRI experiment contrasting unpracticed to practiced performance in a paired-associate task were conducted. The principal effect of practice was found to be a reduction in the extent and magnitude of activity in a cortical network spanning bilateral dorsal prefrontal, left ventral prefrontal, medial frontal (anterior cingulate), left insular, bilateral parietal, and occipito-temporal (fusiform) areas. These activity reductions are shown to occur in common regions across prior neuroimaging studies and for both verbal and nonverbal paired-associate learning in the present fMRI experiment. The implicated network of brain regions is interpreted as a domain-general system engaged specifically to support novice, but not practiced, performance.

Network Convergence

Indian Academy of Sciences (India)

First page Back Continue Last page Overview Graphics. Network Convergence. User is interested in application and content - not technical means of distribution. Boundaries between distribution channels fade out. Network convergence leads to seamless application and content solutions.

Requirements Elicitation Problems: A Literature Analysis

Directory of Open Access Journals (Sweden)

Bill Davey

2015-06-01

Full Text Available Requirements elicitation is the process through which analysts determine the software requirements of stakeholders. Requirements elicitation is seldom well done, and an inaccurate or incomplete understanding of user requirements has led to the downfall of many software projects. This paper proposes a classification of problem types that occur in requirements elicitation. The classification has been derived from a literature analysis. Papers reporting on techniques for improving requirements elicitation practice were examined for the problem the technique was designed to address. In each classification the most recent or prominent techniques for ameliorating the problems are presented. The classification allows the requirements engineer to be sensitive to problems as they arise and the educator to structure delivery of requirements elicitation training.

Belief Elicitation in Experiments

DEFF Research Database (Denmark)

Blanco, Mariana; Engelmann, Dirk; Koch, Alexander

Belief elicitation in economics experiments usually relies on paying subjects according to the accuracy of stated beliefs in addition to payments for other decisions. Such incentives, however, allow risk-averse subjects to hedge with their stated beliefs against adverse outcomes of other decisions......-belief elicitation treatment using a financial investment frame, where hedging arguably would be most natural....

Processing emotional words in two languages with one brain: ERP and fMRI evidence from Chinese-English bilinguals.

Science.gov (United States)

Chen, Peiyao; Lin, Jie; Chen, Bingle; Lu, Chunming; Guo, Taomei

2015-10-01

Emotional words in a bilingual's second language (L2) seem to have less emotional impact compared to emotional words in the first language (L1). The present study examined the neural mechanisms of emotional word processing in Chinese-English bilinguals' two languages by using both event-related potentials (ERPs) and functional magnetic resonance imaging (fMRI). Behavioral results show a robust positive word processing advantage in L1 such that responses to positive words were faster and more accurate compared to responses to neutral words and negative words. In L2, emotional words only received higher accuracies than neutral words. In ERPs, positive words elicited a larger early posterior negativity and a smaller late positive component than neutral words in L1, while a trend of reduced N400 component was found for positive words compared to neutral words in L2. In fMRI, reduced activation was found for L1 emotional words in both the left middle occipital gyrus and the left cerebellum whereas increased activation in the left cerebellum was found for L2 emotional words. Altogether, these results suggest that emotional word processing advantage in L1 relies on rapid and automatic attention capture while facilitated semantic retrieval might help processing emotional words in L2. Copyright © 2015 Elsevier Ltd. All rights reserved.

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)

Functional magnetic resonance imaging of divergent and convergent thinking in Big-C creativity.

Science.gov (United States)

Japardi, Kevin; Bookheimer, Susan; Knudsen, Kendra; Ghahremani, Dara G; Bilder, Robert M

2018-02-15

The cognitive and physiological processes underlying creativity remain unclear, and very few studies to date have attempted to identify the behavioral and brain characteristics that distinguish exceptional ("Big-C") from everyday ("little-c") creativity. The Big-C Project examined functional brain responses during tasks demanding divergent and convergent thinking in 35 Big-C Visual Artists (VIS), 41 Big-C Scientists (SCI), and 31 individuals in a "smart comparison group" (SCG) matched to the Big-C groups on parental educational attainment and estimated IQ. Functional MRI (fMRI) scans included two activation paradigms widely used in prior creativity research, the Alternate Uses Task (AUT) and Remote Associates Task (RAT), to assess brain function during divergent and convergent thinking, respectively. Task performance did not differ between groups. Functional MRI activation in Big-C and SCG groups differed during the divergent thinking task. No differences in activation were seen during the convergent thinking task. Big-C groups had less activation than SCG in frontal pole, right frontal operculum, left middle frontal gyrus, and bilaterally in occipital cortex. SCI displayed lower frontal and parietal activation relative to the SCG when generating alternate uses in the AUT, while VIS displayed lower frontal activation than SCI and SCG when generating typical qualities (the control condition in the AUT). VIS showed more activation in right inferior frontal gyrus and left supramarginal gyrus relative to SCI. All groups displayed considerable overlapping activation during the RAT. The results confirm substantial overlap in functional activation across groups, but suggest that exceptionally creative individuals may depend less on task-positive networks during tasks that demand divergent thinking. Published by Elsevier Ltd.

Language mapping using high gamma electrocorticography, fMRI, and TMS versus electrocortical stimulation.

Science.gov (United States)

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.

The Neural Substrates for Letter String Readings in The Normal and Reverse Directions: An fMRI Study

Science.gov (United States)

Ge, Sheng; Saito, Takashi; Wu, Jing-Long; Ogasawara, Jun-Ichi; Yamauchi, Shuichi; Matsunaga, Naofumi; Iramina, Keiji

In order to investigate the difference in cortical activations between reading letter strings in the normal direction and the reverse direction, an fMRI study was conducted. In this study, the cortical activations elicited by Japanese letter string reading and Chinese letter string reading were investigated. The subjects performed the normal direction reading task (read letter strings from left to right), and the reverse direction reading task (read letter strings from right to left). According to the experimental results, the activated brain regions during the normal and the reverse direction reading tasks were compared. It was found that visuospatial transformation was involved in the reverse direction reading task, while this function was not significant during the normal direction reading task. Furthermore, we found that there was no significant difference in cortical activation between Japanese and Chinese letter string readings.

Brain functional BOLD perturbation modelling for forward fMRI and inverse mapping

Science.gov (United States)

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

Brain functional BOLD perturbation modelling for forward fMRI and inverse mapping.

Science.gov (United States)

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.

Local Convergence and Radius of Convergence for Modified Newton Method

Directory of Open Access Journals (Sweden)

Măruşter Ştefan

2017-12-01

Full Text Available We investigate the local convergence of modified Newton method, i.e., the classical Newton method in which the derivative is periodically re-evaluated. Based on the convergence properties of Picard iteration for demicontractive mappings, we give an algorithm to estimate the local radius of convergence for considered method. Numerical experiments show that the proposed algorithm gives estimated radii which are very close to or even equal with the best ones.

Automatic EEG-assisted retrospective motion correction for fMRI (aE-REMCOR).

Science.gov (United States)

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

Eliciting Sound Memories.

Science.gov (United States)

Harris, Anna

2015-11-01

Sensory experiences are often considered triggers of memory, most famously a little French cake dipped in lime blossom tea. Sense memory can also be evoked in public history research through techniques of elicitation. In this article I reflect on different social science methods for eliciting sound memories such as the use of sonic prompts, emplaced interviewing, and sound walks. I include examples from my research on medical listening. The article considers the relevance of this work for the conduct of oral histories, arguing that such methods "break the frame," allowing room for collaborative research connections and insights into the otherwise unarticulatable.

Trophic convergence drives morphological convergence in marine tetrapods.

Science.gov (United States)

Kelley, Neil P; Motani, Ryosuke

2015-01-01

Marine tetrapod clades (e.g. seals, whales) independently adapted to marine life through the Mesozoic and Caenozoic, and provide iconic examples of convergent evolution. Apparent morphological convergence is often explained as the result of adaptation to similar ecological niches. However, quantitative tests of this hypothesis are uncommon. We use dietary data to classify the feeding ecology of extant marine tetrapods and identify patterns in skull and tooth morphology that discriminate trophic groups across clades. Mapping these patterns onto phylogeny reveals coordinated evolutionary shifts in diet and morphology in different marine tetrapod lineages. Similarities in morphology between species with similar diets-even across large phylogenetic distances-are consistent with previous hypotheses that shared functional constraints drive convergent evolution in marine tetrapods.

Feature-space-based FMRI analysis using the optimal linear transformation.

Science.gov (United States)

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.

Human amygdala activation by the sound produced during dental treatment: A fMRI study

Directory of Open Access Journals (Sweden)

Jen-Fang Yu

2015-01-01

Full Text Available During dental treatments, patients may experience negative emotions associated with the procedure. This study was conducted with the aim of using functional magnetic resonance imaging (fMRI to visualize cerebral cortical stimulation among dental patients in response to auditory stimuli produced by ultrasonic scaling and power suction equipment. Subjects (n = 7 aged 23-35 years were recruited for this study. All were right-handed and underwent clinical pure-tone audiometry testing to reveal a normal hearing threshold below 20 dB hearing level (HL. As part of the study, subjects initially underwent a dental calculus removal treatment. During the treatment, subjects were exposed to ultrasonic auditory stimuli originating from the scaling handpiece and salivary suction instruments. After dental treatment, subjects were imaged with fMRI while being exposed to recordings of the noise from the same dental instrument so that cerebral cortical stimulation in response to aversive auditory stimulation could be observed. The independent sample confirmatory t-test was used. Subjects also showed stimulation in the amygdala and prefrontal cortex, indicating that the ultrasonic auditory stimuli elicited an unpleasant response in the subjects. Patients experienced unpleasant sensations caused by contact stimuli in the treatment procedure. In addition, this study has demonstrated that aversive auditory stimuli such as sounds from the ultrasonic scaling handpiece also cause aversive emotions. This study was indicated by observed stimulation of the auditory cortex as well as the amygdala, indicating that noise from the ultrasonic scaling handpiece was perceived as an aversive auditory stimulus by the subjects. Subjects can experience unpleasant sensations caused by the sounds from the ultrasonic scaling handpiece based on their auditory stimuli.

Electrophysiological correlates of the BOLD signal for EEG-informed fMRI

Science.gov (United States)

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

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)

Convergence in Multispecies Interactions.

Science.gov (United States)

Bittleston, Leonora S; Pierce, Naomi E; Ellison, Aaron M; Pringle, Anne

2016-04-01

The concepts of convergent evolution and community convergence highlight how selective pressures can shape unrelated organisms or communities in similar ways. We propose a related concept, convergent interactions, to describe the independent evolution of multispecies interactions with similar physiological or ecological functions. A focus on convergent interactions clarifies how natural selection repeatedly favors particular kinds of associations among species. Characterizing convergent interactions in a comparative context is likely to facilitate prediction of the ecological roles of organisms (including microbes) in multispecies interactions and selective pressures acting in poorly understood or newly discovered multispecies systems. We illustrate the concept of convergent interactions with examples: vertebrates and their gut bacteria; ectomycorrhizae; insect-fungal-bacterial interactions; pitcher-plant food webs; and ants and ant-plants. Copyright © 2016 Elsevier Ltd. All rights reserved.

fMRI activation in relation to sound intensity and loudness

NARCIS (Netherlands)

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

RETROSPECTIVE DETECTION OF INTERLEAVED SLICE ACQUISITION PARAMETERS FROM FMRI DATA

Science.gov (United States)

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

IT Convergence and Security 2012

CERN Document Server

Chung, Kyung-Yong

2013-01-01

The proceedings approaches the subject matter with problems in technical convergence and convergences of security technology. This approach is new because we look at new issues that arise from techniques converging. The general scope of the proceedings content is convergence security and the latest information technology. The intended readership are societies, enterprises, and research institutes, and intended content level is mid- to highly educated personals. The most important features and benefits of the proceedings are the introduction of the most recent information technology and its related ideas, applications and problems related to technology convergence, and its case studies and finally an introduction of converging existing security techniques through convergence security. Overall, through the proceedings, authors will be able to understand the most state of the art information strategies and technologies of convergence security.

A receptor-based model for dopamine-induced fMRI signal

Science.gov (United States)

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

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.

Expert Panel Elicitation

Energy Technology Data Exchange (ETDEWEB)

Jensen, M. [Swedish Radiation Protection Authority, Stockholm (Sweden). Dept. of Waste Management and Environmental Protection; Hora, S.C. [Univ. of Hawaii, Hilo, HI (United States)

2005-09-15

Scientists are now frequently in a situation where data cannot be easily assessed, since they may have conflicting or uncertain sources. While expert judgment reflects private choices, it is possible both reduce the personal aspect as well as in crease confidence in the judgments by using formal protocols for choice and elicitation of experts. A full-scale elicitation made on seismicity following glaciation, now in its late phase and presented here in a preliminary form, illustrates the value of the technique and some essential issues in connection with the decision to launch such a project. The results show an unusual low variation between the experts.

Media Convergence: the Culture Dimensions of Thinking%Media Convergence:the Culture Dimensions of Thinking

Institute of Scientific and Technical Information of China (English)

Shen Diao; Lan Ju

2017-01-01

In the process of meida Convergence,many researchers paid excessive attention to media technology,industry and management,and ignored the culture dimensions of media convergence.Therefore,to transcend media convergence technology,industrial thinking and more to the particularity attach importance to cultural media,it is a right way to achieve media convergence.But in the context of China's culture,media convergence should value the cultural uniqueness and the imbalance of the realistic problems,to reach innovation and breakthrough.

Almost convergence of triple sequences

OpenAIRE

Ayhan Esi; M.Necdet Catalbas

2013-01-01

In this paper we introduce and study the concepts of almost convergence and almost Cauchy for triple sequences. Weshow that the set of almost convergent triple sequences of 0's and 1's is of the first category and also almost everytriple sequence of 0's and 1's is not almost convergent.Keywords: almost convergence, P-convergent, triple sequence.

Societal response to nanotechnology: converging technologies–converging societal response research?

NARCIS (Netherlands)

Ronteltap, A.; Fischer, A.R.H.; Tobi, H.

2011-01-01

Nanotechnology is an emerging technology particularly vulnerable to societal unrest, which may hinder its further development. With the increasing convergence of several technological domains in the field of nanotechnology, so too could convergence of social science methods help to anticipate

Summable series and convergence factors

CERN Document Server

Moore, Charles N

1938-01-01

Fairly early in the development of the theory of summability of divergent series, the concept of convergence factors was recognized as of fundamental importance in the subject. One of the pioneers in this field was C. N. Moore, the author of the book under review.... Moore classifies convergence factors into two types. In type I he places the factors which have only the property that they preserve convergence for a convergent series or produce convergence for a summable series. In type II he places the factors which not only maintain or produce convergence but have the additional property that

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.

Multivoxel Pattern Analysis for fMRI Data: A Review

Science.gov (United States)

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

A new paradigm for individual subject language mapping: Movie-watching fMRI

Science.gov (United States)

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

Learning Computational Models of Video Memorability from fMRI Brain Imaging.

Science.gov (United States)

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.

Intersession reliability of fMRI activation for heat pain and motor tasks.

Science.gov (United States)

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

Intersession reliability of fMRI activation for heat pain and motor tasks

Science.gov (United States)

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

fMRI in Parkinson’s Disease

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...

Elicitation of ostomy pouch preferences

DEFF Research Database (Denmark)

Bonnichsen, Ole

2011-01-01

Background: Previous studies about patients who have undergone ostomy surgery commonly address the issues of the surgery, complications, preoperative counseling, quality of life, and psychosocial changes following surgery. Only a limited number of studies deal with how technical improvements...... in stoma care would affect patients and, to the author's knowledge, the present study is the first to elicit preferences for potential improvements in ostomy pouches in the form of monetary values. Objective: This article examines and measures Swedish patients' preferences for potential improvements...... in ostomy pouch attributes. The theory, study design, elicitation procedure, and resulting preference structure of the sample is described. Methods: A discrete-choice experiment (DCE) was used to elicit preferences. Respondents were asked to choose between alternatives in choice sets, in which each...

A SYSTEMATIC LITERATURE REVIEW ABOUT SOFTWARE REQUIREMENTS ELICITATION

Directory of Open Access Journals (Sweden)

LENIS R. WONG

2017-02-01

Full Text Available Requirements Elicitation is recognized as one of the most important activity in software development process as it has direct impact on its success. Although there are many proposals for improving this task, still there are issues which have to be solved. This paper aims to identify the current status of the latest researches related to software requirements elicitation through general framework for literature review, in order to answer the following research questions: Q1 What aspects have been covered by different proposal of requirements elicitation? Q2 What activities of the requirements elicitation process have been covered? And Q3 What factors influence on requirements elicitation and how? A cross-analysis of the outcome was performed. One of the results showed that requirements elicitation process needs improvements.

Single trial classification for the categories of perceived emotional facial expressions: an event-related fMRI study

Science.gov (United States)

Song, Sutao; Huang, Yuxia; Long, Zhiying; Zhang, Jiacai; Chen, Gongxiang; Wang, Shuqing

2016-03-01

Recently, several studies have successfully applied multivariate pattern analysis methods to predict the categories of emotions. These studies are mainly focused on self-experienced emotions, such as the emotional states elicited by music or movie. In fact, most of our social interactions involve perception of emotional information from the expressions of other people, and it is an important basic skill for humans to recognize the emotional facial expressions of other people in a short time. In this study, we aimed to determine the discriminability of perceived emotional facial expressions. In a rapid event-related fMRI design, subjects were instructed to classify four categories of facial expressions (happy, disgust, angry and neutral) by pressing different buttons, and each facial expression stimulus lasted for 2s. All participants performed 5 fMRI runs. One multivariate pattern analysis method, support vector machine was trained to predict the categories of facial expressions. For feature selection, ninety masks defined from anatomical automatic labeling (AAL) atlas were firstly generated and each were treated as the input of the classifier; then, the most stable AAL areas were selected according to prediction accuracies, and comprised the final feature sets. Results showed that: for the 6 pair-wise classification conditions, the accuracy, sensitivity and specificity were all above chance prediction, among which, happy vs. neutral , angry vs. disgust achieved the lowest results. These results suggested that specific neural signatures of perceived emotional facial expressions may exist, and happy vs. neutral, angry vs. disgust might be more similar in information representation in the brain.

Intrasubject reproducibility of presurgical language lateralization and mapping using fMRI.

NARCIS (Netherlands)

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

Convergence analysis of household expenditures using the absolute β-convergence method

Directory of Open Access Journals (Sweden)

Anto Domazet

2012-01-01

Full Text Available Background: The paper examines the convergence of household expenditures, in terms of a possible usage of the standardized, rather than consumer-tailored marketing, mainly on a regional level. Objectives: The main goal of this research is to study the existence of consumption expenditure convergence in the EU-27 countries, in the period between 2000 and 2007. Methods/Approach: The analysis used the absolute β-convergence method, in order to investigate the existence of a negative correlation between the growth over time in the overall consumption expenditure in EU member- countries for each individual product and service category and the initial expenditure level. Results: According to the obtained results, in the period between 2000 and 2007, the EU-27 countries reached a high level of consumer expenditure convergence, which provides a basis for developing a regional concept of the standardized international marketing for these countries’ markets. Conclusions: The results provide an empirical contribution to claims on consumer convergence in the countries included into economic integrations. Also, the obtained results can be used to create a basis for defining and applying the regional marketing concept for companies focusing on the EU-27 countries’ market.

The continuing challenge of understanding and modeling hemodynamic variation in fMRI

OpenAIRE

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...

Cultura da Convergência

Directory of Open Access Journals (Sweden)

Rogério Christofoletti

2008-12-01

Full Text Available Three ideas would suffice for the reading of “Cultura da Convergência” (Culture of Convergence by Henry Jenkins to be of interest to journalists and researchers in the area: media convergence as a cultural process; the strengthening of an emotional economy which guides consumers of symbolic goods and media creators; the expansion of trans-media narrative forms.

Cultura da Convergência

Directory of Open Access Journals (Sweden)

Rogério Christofoletti

2011-02-01

Full Text Available Three ideas would suffice for the reading of “Cultura da Convergência” (Culture of Convergence by Henry Jenkins to be of interest to journalists and researchers in the area: media convergence as a cultural process; the strengthening of an emotional economy which guides consumers of symbolic goods and media creators; the expansion of trans-media narrative forms.

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.

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

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.

Exploring neural dysfunction in 'clinical high risk' for psychosis: a quantitative review of fMRI studies.

Science.gov (United States)

Dutt, Anirban; Tseng, Huai-Hsuan; Fonville, Leon; Drakesmith, Mark; Su, Liang; Evans, John; Zammit, Stanley; Jones, Derek; Lewis, Glyn; David, Anthony S

2015-02-01

Individuals at clinical high risk (CHR) of developing psychosis present with widespread functional abnormalities in the brain. Cognitive deficits, including working memory (WM) problems, as commonly elicited by n-back tasks, are observed in CHR individuals. However, functional MRI (fMRI) studies, comprising a heterogeneous cluster of general and social cognition paradigms, have not necessarily demonstrated consistent and conclusive results in this population. Hence, a comprehensive review of fMRI studies, spanning almost one decade, was carried out to observe for general trends with respect to brain regions and cognitive systems most likely to be dysfunctional in CHR individuals. 32 studies were included for this review, out of which 22 met the criteria for quantitative analysis using activation likelihood estimation (ALE). Task related contrast activations were firstly analysed by comparing CHR and healthy control participants in the total pooled sample, followed by a comparison of general cognitive function studies (excluding social cognition paradigms), and finally by only looking at n-back working memory task based studies. Findings from the ALE implicated four key dysfunctional and distinct neural regions in the CHR group, namely the right inferior parietal lobule (rIPL), the left medial frontal gyrus (lmFG), the left superior temporal gyrus (lSTG) and the right fronto-polar cortex (rFPC) of the superior frontal gyrus (SFG). Narrowing down to relatively few significant dysfunctional neural regions is a step forward in reducing the apparent ambiguity of overall findings, which would help to target specific neural regions and pathways of interest for future research in CHR populations. Copyright © 2014. Published by Elsevier Ltd.

The long road to convergence and back. Convergence and crossmedia journalism at Dutch Newsmedia

NARCIS (Netherlands)

Tameling, Klaske; Broersma, Marcel

2012-01-01

KLASKE TAMELING & MARCEL BROERSMA The long road to convergence and back. Convergence and crossmedia journalism at Dutch Newsmedia Since the end of the twentieth century, convergence and cross-media journalism are concepts that are widely used to guide the future of journalism world wide. This study

Position-history and spin-history artifacts in fMRI time-series

NARCIS (Netherlands)

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

Behavioral and fMRI evidence of the differing cognitive load of domain-specific assessments.

Science.gov (United States)

Howard, S J; Burianová, H; Ehrich, J; Kervin, L; Calleia, A; Barkus, E; Carmody, J; Humphry, S

2015-06-25

Standards-referenced educational reform has increased the prevalence of standardized testing; however, whether these tests accurately measure students' competencies has been questioned. This may be due to domain-specific assessments placing a differing domain-general cognitive load on test-takers. To investigate this possibility, functional magnetic resonance imaging (fMRI) was used to identify and quantify the neural correlates of performance on current, international standardized methods of spelling assessment. Out-of-scanner testing was used to further examine differences in assessment results. Results provide converging evidence that: (a) the spelling assessments differed in the cognitive load placed on test-takers; (b) performance decreased with increasing cognitive load of the assessment; and (c) brain regions associated with working memory were more highly activated during performance of assessments that were higher in cognitive load. These findings suggest that assessment design should optimize the cognitive load placed on test-takers, to ensure students' results are an accurate reflection of their true levels of competency. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Resting-State Seed-Based Analysis: An Alternative to Task-Based Language fMRI and Its Laterality Index.

Science.gov (United States)

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.

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...

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)

The influence of FMRI lie detection evidence on juror decision-making.

Science.gov (United States)

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.

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)

Using real-time fMRI brain-computer interfacing to treat eating disorders.

Science.gov (United States)

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.

Societal response to nanotechnology: converging technologies–converging societal response research?

International Nuclear Information System (INIS)

Ronteltap, Amber; Fischer, Arnout R. H.; Tobi, Hilde

2011-01-01

Nanotechnology is an emerging technology particularly vulnerable to societal unrest, which may hinder its further development. With the increasing convergence of several technological domains in the field of nanotechnology, so too could convergence of social science methods help to anticipate societal response. This paper systematically reviews the current state of convergence in societal response research by first sketching the predominant approaches to previous new technologies, followed by an analysis of current research into societal response to nanotechnology. A set of 107 papers on previous new technologies shows that rational actor models have played an important role in the study of societal response to technology, in particular in the field of information technology and the geographic region of Asia. Biotechnology and nuclear power have, in contrast, more often been investigated through risk perception and other affective determinants, particularly in Europe and the USA. A set of 42 papers on societal response to nanotechnology shows similarities to research in biotechnology, as it also builds on affective variables such as risk perception. Although there is a tendency to extend the rational models with affective variables, convergence in social science approaches to response to new technologies still has a long way to go. The challenge for researchers of societal response to technologies is to converge to some shared principles by taking up the best parts from the rational actor models dominant in information technology, whilst integrating non-rational constructs from biotechnology research. The introduction of nanotechnology gives a unique opportunity to do so.

An fMRI study of Agency

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...

Convergence of Nelson diffusions

International Nuclear Information System (INIS)

Dell'Antonio, G.; Posilicano, A.

1991-01-01

Let ψ t , ψ t n , n≥1, be solutions of Schroedinger equations with potentials form-bounded by -1/2 Δ and initial data in H 1 (R d ). Let P, P n , n≥1, be the probability measures on the path space Ω=C(R + , R d ) given by the corresponding Nelson diffusions. We show that if {ψ t n } n≥1 converges to ψ t in H 2 (R d ), uniformly in t over compact intervals, then {P n } n≥1 converges to P in total variation. Moreover, if the potentials are in the Kato class K d , we show that the above result follows from H 1 -convergence of initial data, and K d -convergence of potentials. (orig.)

A Dictionary Learning Approach for Signal Sampling in Task-Based fMRI for Reduction of Big Data

Science.gov (United States)

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

A Dictionary Learning Approach for Signal Sampling in Task-Based fMRI for Reduction of Big Data.

Science.gov (United States)

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.

CONVERGENCE AND DIVERGENCE IN EUROPEAN UNION: EVIDENCE FOR BETA CONVERGENCE AMONG NEW EU MEMBER STATES

Directory of Open Access Journals (Sweden)

Ioana Sorina Mihuț

2013-07-01

Full Text Available Abstract: Convergence may be considered a central issue of the current economic literature, and not only, concentrating upon income distribution within different economies, but also focusing on different aspects of polarity and inequality that characterize especially the emerging economies. Testing convergence within economies may serve as a useful instrument for the validation of the economic growth models. While convergence was considered a defining element of the neoclassical growth models, the majority of the new endogenous growth models argue in favour of divergence across different economies. Testing convergence among European Union is even more challenging due to the high degree of heterogeneity that characterizes these economies. The recent accessions with ten new countries in 2004 and with another two in 2007 were considered only the first step towards assuring a sustainable convergence and finally adopting a common currency-the euro. A series of empirical studies concentrated upon testing convergence among EU, using as benchmark the real convergence quantified by the level of GDP/capita as an indicator for the living standards of every economy. The most popular approach rely on Beta and Sigma convergence, the first one being and indicator of the GDP/capita dispersion between different economies, and the later one being an estimator of the reverse relationship between GDP/capita and its initial level. The main purpose of this paper is to test Beta converge among the new EU member states, in order to obtained more information about the fact whether the poor countries are trying to catch-up with the more developed one. Also Beta convergence indicator embodies useful information about conditional and un-conditional convergence, two leading hypothesis within the neoclassical and endogenous growth models. For Beta convergence hypothesis to be valid it should be taken into consideration a ”catch-up” mechanism over a longer period of time

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.

Voluntary Enhancement of Neural Signatures of Affiliative Emotion Using fMRI Neurofeedback

Science.gov (United States)

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

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....

Stable convergence and stable limit theorems

CERN Document Server

Häusler, Erich

2015-01-01

The authors present a concise but complete exposition of the mathematical theory of stable convergence and give various applications in different areas of probability theory and mathematical statistics to illustrate the usefulness of this concept. Stable convergence holds in many limit theorems of probability theory and statistics – such as the classical central limit theorem – which are usually formulated in terms of convergence in distribution. Originated by Alfred Rényi, the notion of stable convergence is stronger than the classical weak convergence of probability measures. A variety of methods is described which can be used to establish this stronger stable convergence in many limit theorems which were originally formulated only in terms of weak convergence. Naturally, these stronger limit theorems have new and stronger consequences which should not be missed by neglecting the notion of stable convergence. The presentation will be accessible to researchers and advanced students at the master's level...

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...

Regarding realities: Using photo-based projective techniques to elicit normative and alternative discourses on gender, relationships, and sexuality in Mozambique.

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Holman, Emily S; Harbour, Catherine K; Azevedo Said, Rosa Valéria; Figueroa, Maria Elena

2016-01-01

This paper argues for the methodological merit of photo-based projective techniques (PT) in formative HIV communication research. We used this technique in Mozambique to study multiple sexual partnerships (MSPs) and the roles of social and gender norms in promoting or discouraging these behaviours. Facilitators used ambiguous photographs and vignettes to ease adult men and women into discussions of sexual risk behaviour and HIV transmission. Visuals upheld a third-person perspective in discussions, enabling participants to safely project their worldviews onto the photographed characters, and indirectly share their attitudes, normative environments, personal and peer experiences, perceived risks and benefits, and theories about motivations for extramarital sex. Visually grounded storylines contained rich detail about the circumstances and interpersonal conversations that contextualise MSP behaviour and norms. The research yielded findings about conflicting social practices of public encouragement and private disapproval. Despite concerns around the verifiability of PTs, the repetition and convergence in the elicited conversations - and confirmation through subsequent campaign design and evaluation - suggest these techniques can reliably elicit information for formative public health and communication research on psychosocial and normative factors.

Giant lobelias exemplify convergent evolution

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Givnish Thomas J

2010-01-01

Full Text Available Abstract Giant lobeliads on tropical mountains in East Africa and Hawaii have highly unusual, giant-rosette growth forms that appear to be convergent on each other and on those of several independently evolved groups of Asteraceae and other families. A recent phylogenetic analysis by Antonelli, based on sequencing the widest selection of lobeliads to date, raises doubts about this paradigmatic example of convergent evolution. Here I address the kinds of evidence needed to test for convergent evolution and argue that the analysis by Antonelli fails on four points. Antonelli's analysis makes several important contributions to our understanding of lobeliad evolution and geographic spread, but his claim regarding convergence appears to be invalid. Giant lobeliads in Hawaii and Africa represent paradigmatic examples of convergent evolution.

Potential pitfalls when denoising resting state fMRI data using nuisance regression.

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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.

Modeling fMRI signals can provide insights into neural processing in the cerebral cortex.

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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.

Problematic Smartphone Use: Investigating Contemporary Experiences Using a Convergent Design

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Harkin, Lydia

2018-01-01

Internet-enabled smartphones are increasingly ubiquitous in the Western world. Research suggests a number of problems can result from mobile phone overuse, including dependence, dangerous and prohibited use. For over a decade, this has been measured by the Problematic Mobile Phone Use Questionnaire (PMPU-Q). Given the rapid developments in mobile technologies, changes of use patterns and possible problematic and addictive use, the aim of the present study was to investigate and validate an updated contemporary version of the PMPU-Q (PMPU-Q-R). A mixed methods convergent design was employed, including a psychometric survey (N = 512) alongside qualitative focus groups (N = 21), to elicit experiences and perceptions of problematic smartphone use. The results suggest the PMPU-Q-R factor structure can be updated to include smartphone dependence, dangerous driving, and antisocial smartphone use factors. Theories of problematic mobile phone use require consideration of the ubiquity and indispensability of smartphones in the present day and age, particularly regarding use whilst driving and in social interactions. PMID:29337883

Problematic Smartphone Use: Investigating Contemporary Experiences Using a Convergent Design.

Science.gov (United States)

Kuss, Daria J; Harkin, Lydia; Kanjo, Eiman; Billieux, Joel

2018-01-16

Internet-enabled smartphones are increasingly ubiquitous in the Western world. Research suggests a number of problems can result from mobile phone overuse, including dependence, dangerous and prohibited use. For over a decade, this has been measured by the Problematic Mobile Phone Use Questionnaire (PMPU-Q). Given the rapid developments in mobile technologies, changes of use patterns and possible problematic and addictive use, the aim of the present study was to investigate and validate an updated contemporary version of the PMPU-Q (PMPU-Q-R). A mixed methods convergent design was employed, including a psychometric survey ( N = 512) alongside qualitative focus groups ( N = 21), to elicit experiences and perceptions of problematic smartphone use. The results suggest the PMPU-Q-R factor structure can be updated to include smartphone dependence, dangerous driving, and antisocial smartphone use factors. Theories of problematic mobile phone use require consideration of the ubiquity and indispensability of smartphones in the present day and age, particularly regarding use whilst driving and in social interactions.

Neural substrates of embodied natural beauty and social endowed beauty: An fMRI study.

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Zhang, Wei; He, Xianyou; Lai, Siyan; Wan, Juan; Lai, Shuxian; Zhao, Xueru; Li, Darong

2017-08-02

What are the neural mechanisms underlying beauty based on objective parameters and beauty based on subjective social construction? This study scanned participants with fMRI while they performed aesthetic judgments on concrete pictographs and abstract oracle bone scripts. Behavioral results showed both pictographs and oracle bone scripts were judged to be more beautiful when they referred to beautiful objects and positive social meanings, respectively. Imaging results revealed regions associated with perceptual, cognitive, emotional and reward processing were commonly activated both in beautiful judgments of pictographs and oracle bone scripts. Moreover, stronger activations of orbitofrontal cortex (OFC) and motor-related areas were found in beautiful judgments of pictographs, whereas beautiful judgments of oracle bone scripts were associated with putamen activity, implying stronger aesthetic experience and embodied approaching for beauty were elicited by the pictographs. In contrast, only visual processing areas were activated in the judgments of ugly pictographs and negative oracle bone scripts. Results provide evidence that the sense of beauty is triggered by two processes: one based on the objective parameters of stimuli (embodied natural beauty) and the other based on the subjective social construction (social endowed beauty).

Analytic programming with FMRI data: a quick-start guide for statisticians using R.

Science.gov (United States)

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.

Convergence

DEFF Research Database (Denmark)

Madsen, Ole Brun; Nielsen, Jens Frederik Dalsgaard; Schiøler, Henrik

2002-01-01

Convergence trends between the WAN Internet area, characterized by best effort service provision, and the real time LAN domain, with requirements for guaranteed services, are identified and discussed. A bilateral evolution is identified, where typical bulk service applications from WAN, such as m......Convergence trends between the WAN Internet area, characterized by best effort service provision, and the real time LAN domain, with requirements for guaranteed services, are identified and discussed. A bilateral evolution is identified, where typical bulk service applications from WAN...... with the emergence of remote service provision, such as supervision and control of decentralized heating facilities and wind based electrical power production. The reliability issue is addressed from a structural viewpoint, where the concept of Structural QoS (SQoS) is defined to support reliability modelling...

Probing the brain with molecular fMRI.

Science.gov (United States)

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.

Signal Sampling for Efficient Sparse Representation of Resting State FMRI Data

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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

Resting-state fMRI and social cognition: An opportunity to connect.

Science.gov (United States)

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.

Cognitive and neural strategies during control of the anterior cingulate cortex by fMRI neurofeedback in patients with schizophrenia

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Julia S Cordes

2015-06-01

Full Text Available Cognitive functioning is impaired in patients with schizophrenia, leading to significant disabilities in everyday functioning. Its improvement is an important treatment target. Neurofeedback (NF seems a promising method to address the neural dysfunctions underlying those cognitive impairments. The anterior cingulate cortex (ACC, a central hub for cognitive processing, is one of the dysfunctional brain regions in schizophrenia. Here we conducted NF training based on real-time functional magnetic resonance imaging (fMRI in patients with schizophrenia to enable them to control their ACC activity. Training was performed over three days in a group of 11 patients with schizophrenia and 11 healthy controls. Social feedback was provided in accordance with the evoked activity in the selected region of interest (ROI. Neural and cognitive strategies were examined off-line. Both groups learned to control the activity of their ACC but used different neural strategies: Patients activated the dorsal and healthy controls the rostral subdivision. Patients mainly used imagination of music to elicit activity and the control group imagination of sports. However, the difference in neural control did not result from the differences in cognitive strategies but from diagnosis alone. Based on social reinforcers, schizophrenia patients can learn to regulate localized brain activity. Cognitive strategies and neural network location differ, however, from healthy controls. These data emphasize that for therapeutic interventions in schizophrenia compensatory strategies may emerge. Specific cognitive skills or specific dysfunctional networks should be addressed to train impaired skills. Social neurofeedback based on fMRI may be one method to accomplish precise learning targets.

Application of calibrated fMRI in Alzheimer's disease.

Science.gov (United States)

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.

Application of calibrated fMRI in Alzheimer's disease

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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.

Interaction vs. observation: distinctive modes of social cognition in human brain and behavior? A combined fMRI and eye-tracking study.

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Tylén, Kristian; Allen, Micah; Hunter, Bjørk K; Roepstorff, Andreas

2012-01-01

Human cognition has usually been approached on the level of individual minds and brains, but social interaction is a challenging case. Is it best thought of as a self-contained individual cognitive process aiming at an "understanding of the other," or should it rather be approached as an collective, inter-personal process where individual cognitive components interact on a moment-to-moment basis to form coupled dynamics? In a combined fMRI and eye-tracking study we directly contrasted these models of social cognition. We found that the perception of situations affording social contingent responsiveness (e.g., someone offering or showing you an object) elicited activations in regions of the right posterior temporal sulcus and yielded greater pupil dilation corresponding to a model of coupled dynamics (joint action). In contrast, the social-cognitive perception of someone "privately" manipulating an object elicited activation in medial prefrontal cortex, the right inferior frontal gyrus and right inferior parietal lobus, regions normally associated with Theory of Mind and with the mirror neuron system. Our findings support a distinction in social cognition between social observation and social interaction, and demonstrate that simple ostensive cues may shift participants' experience, behavior, and brain activity between these modes. The identification of a distinct, interactive mode has implications for research on social cognition, both in everyday life and in clinical conditions.

Interaction versus Observation: distinctive modes of social cognition in human brain and behavior? A combined fMRI and eye-tracking study.

Directory of Open Access Journals (Sweden)

Kristian eTylen

2012-12-01

Full Text Available Human cognition has usually been approached on the level of individual minds and brains, but social interaction is a challenging case. Is it best thought of as a self-contained individual cognitive process aiming at an ‘understanding of the other’, or should it rather be approached as an collective, inter-personal process where individual cognitive components interact on a moment-to-moment basis to form coupled dynamics? In a combined fMRI and eye tracking study we directly contrasted these models of social cognition. We found that the perception of situations affording social contingent responsiveness (e.g. someone offering or showing you an object elicited activations in regions of the right posterior temporal sulcus and yielded greater pupil dilation corresponding to a model of coupled dynamics (joint action. In contrast, the social-cognitive perception of someone ‘privately’ manipulating an object elicited activation in medial prefrontal cortex, the right inferior frontal gyrus and right inferior parietal lobus, regions normally associated with Theory of Mind and with the mirror neuron system. Our findings support a distinction in social cognition between social observation and social interaction, and demonstrate that simple ostensive cues may shift participants’ experience, behavior and brain activity between these modes. The identification of a distinct, interactive mode has implications for research on social cognition, both in everyday life and in clinical conditions.

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

To Resolve or Not To Resolve, that Is the Question: The Dual-Path Model of Incongruity Resolution and Absurd Verbal Humor by fMRI.

Science.gov (United States)

Dai, Ru H; Chen, Hsueh-Chih; Chan, Yu C; Wu, Ching-Lin; Li, Ping; Cho, Shu L; Hu, Jon-Fan

2017-01-01

It is well accepted that the humor comprehension processing involves incongruity detection and resolution and then induces a feeling of amusement. However, this three-stage model of humor processing does not apply to absurd humor (so-called nonsense humor). Absurd humor contains an unresolvable incongruity but can still induce a feeling of mirth. In this study, we used functional magnetic resonance imaging (fMRI) to identify the neural mechanisms of absurd humor. Specifically, we aimed to investigate the neural substrates associated with the complete resolution of incongruity resolution humor and partial resolution of absurd humor. Based on the fMRI data, we propose a dual-path model of incongruity resolution and absurd verbal humor. According to this model, the detection and resolution for the incongruity of incongruity resolution humor activate brain regions involved in the temporo-parietal lobe (TPJ) implicated in the integration of multiple information and precuneus, likely to be involved in the ability of perspective taking. The appreciation of incongruity resolution humor activates regions the posterior cingulate cortex (PCC), implicated in autobiographic or event memory retrieval, and parahippocampal gyrus (PHG), implying the funny feeling. By contrast, the partial resolution of absurd humor elicits greater activation in the fusiform gyrus which have been implicated in word processing, inferior frontal gyrus (IFG) for the process of incongruity resolution and superior temporal gyrus (STG) for the pragmatic awareness.

Test-retest reliability of an fMRI paradigm for studies of cardiovascular reactivity.

Science.gov (United States)

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.

Convergence from divergence

Science.gov (United States)

Costin, Ovidiu; Dunne, Gerald V.

2018-01-01

We show how to convert divergent series, which typically occur in many applications in physics, into rapidly convergent inverse factorial series. This can be interpreted physically as a novel resummation of perturbative series. Being convergent, these new series allow rigorous extrapolation from an asymptotic region with a large parameter, to the opposite region where the parameter is small. We illustrate the method with various physical examples, and discuss how these convergent series relate to standard methods such as Borel summation, and also how they incorporate the physical Stokes phenomenon. We comment on the relation of these results to Dyson’s physical argument for the divergence of perturbation theory. This approach also leads naturally to a wide class of relations between bosonic and fermionic partition functions, and Klein-Gordon and Dirac determinants.

Density by Moduli and Lacunary Statistical Convergence

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Vinod K. Bhardwaj

2016-01-01

Full Text Available We have introduced and studied a new concept of f-lacunary statistical convergence, where f is an unbounded modulus. It is shown that, under certain conditions on a modulus f, the concepts of lacunary strong convergence with respect to a modulus f and f-lacunary statistical convergence are equivalent on bounded sequences. We further characterize those θ for which Sθf=Sf, where Sθf and Sf denote the sets of all f-lacunary statistically convergent sequences and f-statistically convergent sequences, respectively. A general description of inclusion between two arbitrary lacunary methods of f-statistical convergence is given. Finally, we give an Sθf-analog of the Cauchy criterion for convergence and a Tauberian theorem for Sθf-convergence is also proved.

The Interview as an Approach to Elicit Requirements

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Luz Marina Iriarte

2013-07-01

Full Text Available In many software projects requirements elicitation is incomplete or inconsistent. One issue that works for this is presented has to be with the requirements engineers use a single method to do it, which can cause a deficiency in the expected results. Among the factors contributing to the success of this stage of the life cycle is an adequate selection of the elicitation technique and other approaches needed. This article describes an experimental study to elicit requirements, in which was applied a combination of methods and techniques, and discusses the advantages of doing it this way. The results obtained allow concluding that to achieve adequate elicitation is necessary to combine several techniques and methods.

Vadose zone flow convergence test suite

Energy Technology Data Exchange (ETDEWEB)

Butcher, B. T. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

2017-06-05

Performance Assessment (PA) simulations for engineered disposal systems at the Savannah River Site involve highly contrasting materials and moisture conditions at and near saturation. These conditions cause severe convergence difficulties that typically result in unacceptable convergence or long simulation times or excessive analyst effort. Adequate convergence is usually achieved in a trial-anderror manner by applying under-relaxation to the Saturation or Pressure variable, in a series of everdecreasing RELAxation values. SRNL would like a more efficient scheme implemented inside PORFLOW to achieve flow convergence in a more reliable and efficient manner. To this end, a suite of test problems that illustrate these convergence problems is provided to facilitate diagnosis and development of an improved convergence strategy. The attached files are being transmitted to you describing the test problem and proposed resolution.

Green Software Engineering Adaption In Requirement Elicitation Process

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Umma Khatuna Jannat

2015-08-01

Full Text Available A recent technology investigates the role of concern in the environment software that is green software system. Now it is widely accepted that the green software can fit all process of software development. It is also suitable for the requirement elicitation process. Now a days software companies have used requirements elicitation techniques in an enormous majority. Because this process plays more and more important roles in software development. At the present time most of the requirements elicitation process is improved by using some techniques and tools. So that the intention of this research suggests to adapt green software engineering for the intention of existing elicitation technique and recommend suitable actions for improvement. This research being involved qualitative data. I used few keywords in my searching procedure then searched IEEE ACM Springer Elsevier Google scholar Scopus and Wiley. Find out articles which published in 2010 until 2016. Finding from the literature review Identify 15 traditional requirement elicitations factors and 23 improvement techniques to convert green engineering. Lastly The paper includes a squat review of the literature a description of the grounded theory and some of the identity issues related finding of the necessity for requirements elicitation improvement techniques.

Morphological convergence in ‘river dolphin’ skulls

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Charlotte E. Page

2017-11-01

Full Text Available Convergent evolution can provide insights into the predictability of, and constraints on, the evolution of biodiversity. One striking example of convergence is seen in the ‘river dolphins’. The four dolphin genera that make up the ‘river dolphins’ (Inia geoffrensis, Pontoporia blainvillei, Platanista gangetica and Lipotes vexillifer do not represent a single monophyletic group, despite being very similar in morphology. This has led many to using the ‘river dolphins’ as an example of convergent evolution. We investigate whether the skulls of the four ‘river dolphin’ genera are convergent when compared to other toothed dolphin taxa in addition to identifying convergent cranial and mandibular features. We use geometric morphometrics to uncover shape variation in the skulls of the ‘river dolphins’ and then apply a number of phylogenetic techniques to test for convergence. We find significant convergence in the skull morphology of the ‘river dolphins’. The four genera seem to have evolved similar skull shapes, leading to a convergent morphotype characterised by elongation of skull features. The cause of this morphological convergence remains unclear. However, the features we uncover as convergent, in particular elongation of the rostrum, support hypotheses of shared feeding mode or diet and thus provide the foundation for future work into convergence within the Odontoceti.

FIACH: A biophysical model for automatic retrospective noise control in fMRI.

Science.gov (United States)

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.

Testing Convergence Versus History: Convergence Dominates Phenotypic Evolution for over 150 Million Years in Frogs.

Science.gov (United States)

Moen, Daniel S; Morlon, Hélène; Wiens, John J

2016-01-01

Striking evolutionary convergence can lead to similar sets of species in different locations, such as in cichlid fishes and Anolis lizards, and suggests that evolution can be repeatable and predictable across clades. Yet, most examples of convergence involve relatively small temporal and/or spatial scales. Some authors have speculated that at larger scales (e.g., across continents), differing evolutionary histories will prevent convergence. However, few studies have compared the contrasting roles of convergence and history, and none have done so at large scales. Here we develop a two-part approach to test the scale over which convergence can occur, comparing the relative importance of convergence and history in macroevolution using phylogenetic models of adaptive evolution. We apply this approach to data from morphology, ecology, and phylogeny from 167 species of anuran amphibians (frogs) from 10 local sites across the world, spanning ~160 myr of evolution. Mapping ecology on the phylogeny revealed that similar microhabitat specialists (e.g., aquatic, arboreal) have evolved repeatedly across clades and regions, producing many evolutionary replicates for testing for morphological convergence. By comparing morphological optima for clades and microhabitat types (our first test), we find that convergence associated with microhabitat use dominates frog morphological evolution, producing recurrent ecomorphs that together encompass all sampled species in each community in each region. However, our second test, which examines whether and how much species differ from their inferred optima, shows that convergence is incomplete: that is, phenotypes of most species are still somewhat distant from the estimated optimum for each microhabitat, seemingly because of insufficient time for more complete adaptation (an effect of history). Yet, these effects of history are related to past ecologies, and not clade membership. Overall, our study elucidates the dominant drivers of

Weak entropy inequalities and entropic convergence

Institute of Scientific and Technical Information of China (English)

2008-01-01

A criterion for algebraic convergence of the entropy is presented and an algebraic convergence result for the entropy of an exclusion process is improved. A weak entropy inequality is considered and its relationship to entropic convergence is discussed.

Convergence of mayer expansions

International Nuclear Information System (INIS)

Brydges, D.C.

1986-01-01

The tree graph bound of Battle and Federbush is extended and used to provide a simple criterion for the convergence of (iterated) Mayer expansions. As an application estimates on the radius of convergence of the Mayer expansion for the two-dimensional Yukawa gas (nonstable interaction) are obtained

Determination of hemispheric dominance with mental rotation using functional transcranial Doppler sonography and FMRI.

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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.

Extending Local Canonical Correlation Analysis to Handle General Linear Contrasts for fMRI Data

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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.

Imaging gait analysis: An fMRI dual task study.

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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.

Functional Laterality of Task-Evoked Activation in Sensorimotor Cortex of Preterm Infants: An Optimized 3 T fMRI Study Employing a Customized Neonatal Head Coil.

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Lukas Scheef

Full Text Available Functional magnetic resonance imaging (fMRI in neonates has been introduced as a non-invasive method for studying sensorimotor processing in the developing brain. However, previous neonatal studies have delivered conflicting results regarding localization, lateralization, and directionality of blood oxygenation level dependent (BOLD responses in sensorimotor cortex (SMC. Amongst the confounding factors in interpreting neonatal fMRI studies include the use of standard adult MR-coils providing insufficient signal to noise, and liberal statistical thresholds, compromising clinical interpretation at the single subject level.Here, we employed a custom-designed neonatal MR-coil adapted and optimized to the head size of a newborn in order to improve robustness, reliability and validity of neonatal sensorimotor fMRI. Thirteen preterm infants with a median gestational age of 26 weeks were scanned at term-corrected age using a prototype 8-channel neonatal head coil at 3T (Achieva, Philips, Best, NL. Sensorimotor stimulation was elicited by passive extension/flexion of the elbow at 1 Hz in a block design. Analysis of temporal signal to noise ratio (tSNR was performed on the whole brain and the SMC, and was compared to data acquired with an 'adult' 8 channel head coil published previously. Task-evoked activation was determined by single-subject SPM8 analyses, thresholded at p < 0.05, whole-brain FWE-corrected.Using a custom-designed neonatal MR-coil, we found significant positive BOLD responses in contralateral SMC after unilateral passive sensorimotor stimulation in all neonates (analyses restricted to artifact-free data sets = 8/13. Improved imaging characteristics of the neonatal MR-coil were evidenced by additional phantom and in vivo tSNR measurements: phantom studies revealed a 240% global increase in tSNR; in vivo studies revealed a 73% global and a 55% local (SMC increase in tSNR, as compared to the 'adult' MR-coil.Our findings strengthen the

Needs Elicitation for Novel Pervasive Healthcare Technology

DEFF Research Database (Denmark)

Thorpe, Julia Rosemary; Forchhammer, B. H.; Maier, Anja

2016-01-01

for pervasive healthcare technology, in which established methods for engaging users to elicit their needs can be difficult or even impossible to apply. In this paper we document our needs elicitation process in a relevant example as a method story, and present our findings and reflections on this as the key...

Diagnostic benefits of presurgical fMRI in patients with brain tumours in the primary sensorimotor cortex

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.)

Presurgical brain mapping of the language network in patients with brain tumors using resting-state fMRI: Comparison with task fMRI.

Science.gov (United States)

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.

Brain network involved in visual processing of movement stimuli used in upper limb robotic training: an fMRI study.

Science.gov (United States)

Nocchi, Federico; Gazzellini, Simone; Grisolia, Carmela; Petrarca, Maurizio; Cannatà, Vittorio; Cappa, Paolo; D'Alessio, Tommaso; Castelli, Enrico

2012-07-24

The potential of robot-mediated therapy and virtual reality in neurorehabilitation is becoming of increasing importance. However, there is limited information, using neuroimaging, on the neural networks involved in training with these technologies. This study was intended to detect the brain network involved in the visual processing of movement during robotic training. The main aim was to investigate the existence of a common cerebral network able to assimilate biological (human upper limb) and non-biological (abstract object) movements, hence testing the suitability of the visual non-biological feedback provided by the InMotion2 Robot. A visual functional Magnetic Resonance Imaging (fMRI) task was administered to 22 healthy subjects. The task required observation and retrieval of motor gestures and of the visual feedback used in robotic training. Functional activations of both biological and non-biological movements were examined to identify areas activated in both conditions, along with differential activity in upper limb vs. abstract object trials. Control of response was also tested by administering trials with congruent and incongruent reaching movements. The observation of upper limb and abstract object movements elicited similar patterns of activations according to a caudo-rostral pathway for the visual processing of movements (including specific areas of the occipital, temporal, parietal, and frontal lobes). Similarly, overlapping activations were found for the subsequent retrieval of the observed movement. Furthermore, activations of frontal cortical areas were associated with congruent trials more than with the incongruent ones. This study identified the neural pathway associated with visual processing of movement stimuli used in upper limb robot-mediated training and investigated the brain's ability to assimilate abstract object movements with human motor gestures. In both conditions, activations were elicited in cerebral areas involved in visual

Brain network involved in visual processing of movement stimuli used in upper limb robotic training: an fMRI study

Directory of Open Access Journals (Sweden)

Nocchi Federico

2012-07-01

Full Text Available Abstract Background The potential of robot-mediated therapy and virtual reality in neurorehabilitation is becoming of increasing importance. However, there is limited information, using neuroimaging, on the neural networks involved in training with these technologies. This study was intended to detect the brain network involved in the visual processing of movement during robotic training. The main aim was to investigate the existence of a common cerebral network able to assimilate biological (human upper limb and non-biological (abstract object movements, hence testing the suitability of the visual non-biological feedback provided by the InMotion2 Robot. Methods A visual functional Magnetic Resonance Imaging (fMRI task was administered to 22 healthy subjects. The task required observation and retrieval of motor gestures and of the visual feedback used in robotic training. Functional activations of both biological and non-biological movements were examined to identify areas activated in both conditions, along with differential activity in upper limb vs. abstract object trials. Control of response was also tested by administering trials with congruent and incongruent reaching movements. Results The observation of upper limb and abstract object movements elicited similar patterns of activations according to a caudo-rostral pathway for the visual processing of movements (including specific areas of the occipital, temporal, parietal, and frontal lobes. Similarly, overlapping activations were found for the subsequent retrieval of the observed movement. Furthermore, activations of frontal cortical areas were associated with congruent trials more than with the incongruent ones. Conclusions This study identified the neural pathway associated with visual processing of movement stimuli used in upper limb robot-mediated training and investigated the brain’s ability to assimilate abstract object movements with human motor gestures. In both conditions

Collective Correlations of Brodmann Areas fMRI Study with RMT-Denoising

OpenAIRE

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...

Functional Topography of Human Corpus Callosum: An fMRI Mapping Study

OpenAIRE

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...

Close relationship between fMRI signals and transient heart rate changes accompanying K-complex. Simultaneous EEG/fMRI study

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)

Beyond Brainstorming: Exploring Convergence in Teams

Science.gov (United States)

Seeber, Isabella; de Vreede, Gert-Jan; Maier, Ronald; Weber, Barbara

2017-01-01

Abstract Collaborative brainstorming is often followed by a convergence activity where teams extract the most promising ideas on a useful level of detail from the brainstorming results. Contrary to the wealth of research on electronic brainstorming, there is a dearth of research on convergence. We used experimental methods for an in-depth exploration of two facilitation-based interventions in a convergence activity: attention guidance (focusing participants on procedures to execute a convergence task) and discussion encouragement (engaging participants in conversations to combine knowledge on ideas). Our findings show that both attention guidance and discussion encouragement are correlated with higher convergence quality. We argue that attention guidance’s contribution is in its support of coordination, information processing, and goal specification. Similar, we argue that discussion encouragement’s contribution is in its stimulation of idea clarification and idea combination. Contrary to past research, our findings further show that satisfaction was higher after convergence than after brainstorming. PMID:29399005

Proposal for a Five-Step Method to Elicit Expert Judgment

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Duco Veen

2017-12-01

Full Text Available Elicitation is a commonly used tool to extract viable information from experts. The information that is held by the expert is extracted and a probabilistic representation of this knowledge is constructed. A promising avenue in psychological research is to incorporated experts’ prior knowledge in the statistical analysis. Systematic reviews on elicitation literature however suggest that it might be inappropriate to directly obtain distributional representations from experts. The literature qualifies experts’ performance on estimating elements of a distribution as unsatisfactory, thus reliably specifying the essential elements of the parameters of interest in one elicitation step seems implausible. Providing feedback within the elicitation process can enhance the quality of the elicitation and interactive software can be used to facilitate the feedback. Therefore, we propose to decompose the elicitation procedure into smaller steps with adjustable outcomes. We represent the tacit knowledge of experts as a location parameter and their uncertainty concerning this knowledge by a scale and shape parameter. Using a feedback procedure, experts can accept the representation of their beliefs or adjust their input. We propose a Five-Step Method which consists of (1 Eliciting the location parameter using the trial roulette method. (2 Provide feedback on the location parameter and ask for confirmation or adjustment. (3 Elicit the scale and shape parameter. (4 Provide feedback on the scale and shape parameter and ask for confirmation or adjustment. (5 Use the elicited and calibrated probability distribution in a statistical analysis and update it with data or to compute a prior-data conflict within a Bayesian framework. User feasibility and internal validity for the Five-Step Method are investigated using three elicitation studies.

Bayesian spatiotemporal model of fMRI data using transfer functions.

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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.

Semantic Convergence in the Bilingual Lexicon

Science.gov (United States)

Ameel, Eef; Malt, Barbara C.; Storms, Gert; Van Assche, Fons

2009-01-01

Bilinguals' lexical mappings for their two languages have been found to converge toward a common naming pattern. The present paper investigates in more detail how semantic convergence is manifested in bilingual lexical knowledge. We examined how semantic convergence affects the centers and boundaries of lexical categories for common household…

Convergence semigroup actions: generalized quotients

Directory of Open Access Journals (Sweden)

H. Boustique

2009-10-01

Full Text Available Continuous actions of a convergence semigroup are investigated in the category of convergence spaces. Invariance properties of actions as well as properties of a generalized quotient space are presented

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...

Fully automated processing of fMRI data in SPM: from MRI scanner to PACS.

Science.gov (United States)

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.

Globalization and Contemporary Fertility Convergence.

Science.gov (United States)

Hendi, Arun S

2017-09-01

The rise of the global network of nation-states has precipitated social transformations throughout the world. This article examines the role of political and economic globalization in driving fertility convergence across countries between 1965 and 2009. While past research has typically conceptualized fertility change as a country-level process, this study instead employs a theoretical and methodological framework that examines differences in fertility between pairs of countries over time. Convergence in fertility between pairs of countries is hypothesized to result from increased cross-country connectedness and cross-national transmission of fertility-related schemas. I investigate the impact of various cross-country ties, including ties through bilateral trade, intergovernmental organizations, and regional trade blocs, on fertility convergence. I find that globalization acts as a form of social interaction to produce fertility convergence. There is significant heterogeneity in the effects of different cross-country ties. In particular, trade with rich model countries, joint participation in the UN and UNESCO, and joining a free trade agreement all contribute to fertility convergence between countries. Whereas the prevailing focus in fertility research has been on factors producing fertility declines, this analysis highlights specific mechanisms-trade and connectedness through organizations-leading to greater similarity in fertility across countries. Globalization is a process that propels the spread of culturally laden goods and schemas impinging on fertility, which in turn produces fertility convergence.

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

CCSI Risk Estimation: An Application of Expert Elicitation

Energy Technology Data Exchange (ETDEWEB)

Engel, David W.; Dalton, Angela C.

2012-10-01

The Carbon Capture Simulation Initiative (CCSI) is a multi-laboratory simulation-driven effort to develop carbon capture technologies with the goal of accelerating commercialization and adoption in the near future. One of the key CCSI technical challenges is representing and quantifying the inherent uncertainty and risks associated with developing, testing, and deploying the technology in simulated and real operational settings. To address this challenge, the CCSI Element 7 team developed a holistic risk analysis and decision-making framework. The purpose of this report is to document the CCSI Element 7 structured systematic expert elicitation to identify additional risk factors. We review the significance of and established approaches to expert elicitation, describe the CCSI risk elicitation plan and implementation strategies, and conclude by discussing the next steps and highlighting the contribution of risk elicitation toward the achievement of the overarching CCSI objectives.

Convergence of Networks

DEFF Research Database (Denmark)

Prasad, Ramjee; Ruggieri, Marina

2008-01-01

The paper focuses on the revolutionary changes that could characterise the future of networks. Those changes involve many aspects in the conceivement and exploitation of networks: architecture, services, technologies and modeling. The convergence of wired and wireless technologies along...... with the integration of system componennts and the convergence of services (e.g. communications and navigation) are only some of the elements that shape the perpsected mosaic. Authors delineate this vision, highlighting the presence of the space and stratospheric components and the related services as building block...

Integrating fMRI with psychophysiological measurements in the study of decision-making

OpenAIRE

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 ...

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

OpenMC In Situ Source Convergence Detection

Energy Technology Data Exchange (ETDEWEB)

Aldrich, Garrett Allen [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Univ. of California, Davis, CA (United States); Dutta, Soumya [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); The Ohio State Univ., Columbus, OH (United States); Woodring, Jonathan Lee [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-05-07

We designed and implemented an in situ version of particle source convergence for the OpenMC particle transport simulator. OpenMC is a Monte Carlo based-particle simulator for neutron criticality calculations. For the transport simulation to be accurate, source particles must converge on a spatial distribution. Typically, convergence is obtained by iterating the simulation by a user-settable, fixed number of steps, and it is assumed that convergence is achieved. We instead implement a method to detect convergence, using the stochastic oscillator for identifying convergence of source particles based on their accumulated Shannon Entropy. Using our in situ convergence detection, we are able to detect and begin tallying results for the full simulation once the proper source distribution has been confirmed. Our method ensures that the simulation is not started too early, by a user setting too optimistic parameters, or too late, by setting too conservative a parameter.

Problematic Smartphone Use: Investigating Contemporary Experiences Using a Convergent Design

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Daria J. Kuss

2018-01-01

Full Text Available Internet-enabled smartphones are increasingly ubiquitous in the Western world. Research suggests a number of problems can result from mobile phone overuse, including dependence, dangerous and prohibited use. For over a decade, this has been measured by the Problematic Mobile Phone Use Questionnaire (PMPU-Q. Given the rapid developments in mobile technologies, changes of use patterns and possible problematic and addictive use, the aim of the present study was to investigate and validate an updated contemporary version of the PMPU-Q (PMPU-Q-R. A mixed methods convergent design was employed, including a psychometric survey (N = 512 alongside qualitative focus groups (N = 21, to elicit experiences and perceptions of problematic smartphone use. The results suggest the PMPU-Q-R factor structure can be updated to include smartphone dependence, dangerous driving, and antisocial smartphone use factors. Theories of problematic mobile phone use require consideration of the ubiquity and indispensability of smartphones in the present day and age, particularly regarding use whilst driving and in social interactions.

A SVM-based quantitative fMRI method for resting-state functional network detection.

Science.gov (United States)

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.

The Convergence in Spatial Tasks

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Vladimir P. Kulagin

2013-01-01

Full Text Available The article reveals the problem of convergence of direct and inverse problems in Earth Sciences, describes the features and application of these problems, discloses analytical features of direct and inverse problems. The convergence criteria and conditions for convergence were presented. This work is supported by the Grant of the Government of the Russian Federation for support of scientific research, implemented under the supervision of leading scientists in Russian institutions of higher education in the field "Space Research and Technologies" in 2011–2013.

Auditory processing in the brainstem and audiovisual integration in humans studied with fMRI

NARCIS (Netherlands)

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

The effect of ageing on fMRI: Correction for the confounding effects of vascular reactivity evaluated by joint fMRI and MEG in 335 adults

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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

Effects of hypoglycemia on human brain activation measured with fMRI.

Science.gov (United States)

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.

Expert elicitation and the problem of detecting undeclared activities

International Nuclear Information System (INIS)

Pilat, Joseph F.; Sylvester, Kori Budlong; Stanbro, William D.

2002-01-01

Measures applicable to the detection of undeclared activities are not well established, and their effectiveness is uncertain. To detect clandestine paths, the IAEA is still developing processes and procedures. As the Agency gains experience with new measures and with integrated safeguards, dealing with such problems may become more experience-based and perhaps more closely parallel the process with current safeguards where detection probabilities for the measures to be utilized on declared paths are well characterized. Whether or not this point will be reached for undeclared and mixed paths, the only tool that appears suitable at present for the purpose of generating a reasonable detection probability that can over time be tested against reality and, if necessary, adjusted is formal expert judgment, or expert elicitation. Formal expert elicitation is a structured process that makes use of people knowledgeable in certain areas to make assessments. To provide a 'proof of principle' of this methodology for presentation to the Agency, experts in nuclear technology, nonproliferation, safeguards and open source information, as well as in formal expert elicitation processes, engaged in three illustrative expert elicitations on assessing information analysis as a means to detect undeclared activities. These elicitations were successful. This paper will discuss the process of and issues raised by the elicitations.

Topologically convergent and divergent functional connectivity patterns in unmedicated unipolar depression and bipolar disorder.

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Wang, Y; Wang, J; Jia, Y; Zhong, S; Zhong, M; Sun, Y; Niu, M; Zhao, L; Zhao, L; Pan, J; Huang, L; Huang, R

2017-07-04

Bipolar disorder (BD), particularly BD II, is frequently misdiagnosed as unipolar depression (UD), leading to inappropriate treatment and poor clinical outcomes. Although depressive symptoms may be expressed similarly in UD and BD, the similarities and differences in the architecture of brain functional networks between the two disorders are still unknown. In this study, we hypothesized that UD and BD II patients would show convergent and divergent patterns of disrupted topological organization of the functional connectome, especially in the default mode network (DMN) and the limbic network. Brain resting-state functional magnetic resonance imaging (fMRI) data were acquired from 32 UD-unmedicated patients, 31 unmedicated BD II patients (current episode depressed) and 43 healthy subjects. Using graph theory, we systematically studied the topological organization of their whole-brain functional networks at the following three levels: whole brain, modularity and node. First, both the UD and BD II patients showed increased characteristic path length and decreased global efficiency compared with the controls. Second, both the UD and BD II patients showed disrupted intramodular connectivity within the DMN and limbic system network. Third, decreased nodal characteristics (nodal strength and nodal efficiency) were found predominantly in brain regions in the DMN, limbic network and cerebellum of both the UD and BD II patients, whereas differences between the UD and BD II patients in the nodal characteristics were also observed in the precuneus and temporal pole. Convergent deficits in the topological organization of the whole brain, DMN and limbic networks may reflect overlapping pathophysiological processes in unipolar and bipolar depression. Our discovery of divergent regional connectivity that supports emotion processing could help to identify biomarkers that will aid in differentiating these disorders.

Variational Bayesian Causal Connectivity Analysis for fMRI

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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.

Eliciting and communicating expert judgments: Methodology and application to nuclear safety

International Nuclear Information System (INIS)

Winterfeldt, D. von

1989-01-01

The most ambitious and certainly the most extensive formal expert judgment process was the elicitation of numerous events and uncertain quantities for safety issues in five nuclear power plants in the U.S. The general methodology for formal expert elicitations are described. An overview of the expert elicitation process of NUREG 1150 is provided and the elicitation of probabilities for the interfacing systems loss of coolant accident LOCA (ISL) in PWRs is given as an example of this elicitation process. Some lessons learned from this study are presented. (DG)

An fMRI study on cortical responses during active self-touch and passive touch from others

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Rochelle eAckerley

2012-08-01

Full Text Available Active, self-touch and the passive touch from an external source engage comparable afferent mechanoreceptors on the touched skin site. However, touch directed to glabrous skin compared to hairy skin will activate different types of afferent mechanoreceptors. Despite perceptual similarities between touch to different body sites, it is likely that the touch information is processed differently. In the present study, we used functional magnetic resonance imaging (fMRI to elucidate the cortical differences in the neural signal of touch representations during active, self-touch and passive touch from another, to both glabrous (palm and hairy (arm skin, where a soft brush was used as the stimulus. There were two active touch conditions, where the participant used the brush in their right hand to stroke either their left palm or arm. There were two similar passive, touch conditions where the experimenter used an identical brush to stroke the same palm and arm areas on the participant. Touch on the left palm elicited a large, significant, positive blood-oxygenation level dependence (BOLD signal in right sensorimotor areas. Less extensive activity was found for touch to the arm. Separate somatotopical palm and arm representations were found in Brodmann area 3 of the right primary somatosensory cortex (SI and in both these areas, active stroking gave significantly higher signals than passive stroking. Active, self-touch elicited a positive BOLD signal in a network of sensorimotor cortical areas in the left hemisphere, compared to the resting baseline. In contrast, during passive touch, a significant negative BOLD signal was found in the left SI. Thus, each of the four conditions had a unique cortical signature despite similarities in afferent signalling or evoked perception. It is hypothesized that attentional mechanisms play a role in the modulation of the touch signal in the right SI, accounting for the differences found between active and passive touch.

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...

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...

Autogenic training alters cerebral activation patterns in fMRI.

Science.gov (United States)

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.

Brain activity changes in cognitive networks in relapsing-remitting multiple sclerosis - insights from a longitudinal FMRI study.

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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

Brain activity changes in cognitive networks in relapsing-remitting multiple sclerosis - insights from a longitudinal FMRI study.

Science.gov (United States)

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

Neural correlates of phonetic convergence and speech imitation.

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Garnier, Maëva; Lamalle, Laurent; Sato, Marc

2013-01-01

Speakers unconsciously tend to mimic their interlocutor's speech during communicative interaction. This study aims at examining the neural correlates of phonetic convergence and deliberate imitation, in order to explore whether imitation of phonetic features, deliberate, or unconscious, might reflect a sensory-motor recalibration process. Sixteen participants listened to vowels with pitch varying around the average pitch of their own voice, and then produced the identified vowels, while their speech was recorded and their brain activity was imaged using fMRI. Three degrees and types of imitation were compared (unconscious, deliberate, and inhibited) using a go-nogo paradigm, which enabled the comparison of brain activations during the whole imitation process, its active perception step, and its production. Speakers followed the pitch of voices they were exposed to, even unconsciously, without being instructed to do so. After being informed about this phenomenon, 14 participants were able to inhibit it, at least partially. The results of whole brain and ROI analyses support the fact that both deliberate and unconscious imitations are based on similar neural mechanisms and networks, involving regions of the dorsal stream, during both perception and production steps of the imitation process. While no significant difference in brain activation was found between unconscious and deliberate imitations, the degree of imitation, however, appears to be determined by processes occurring during the perception step. Four regions of the dorsal stream: bilateral auditory cortex, bilateral supramarginal gyrus (SMG), and left Wernicke's area, indeed showed an activity that correlated significantly with the degree of imitation during the perception step.

Effect of fMRI acoustic noise on non-auditory working memory task: comparison between continuous and pulsed sound emitting EPI.

Science.gov (United States)

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.

Statistical convergence on intuitionistic fuzzy normed spaces

International Nuclear Information System (INIS)

Karakus, S.; Demirci, K.; Duman, O.

2008-01-01

Saadati and Park [Saadati R, Park JH, Chaos, Solitons and Fractals 2006;27:331-44] has recently introduced the notion of intuitionistic fuzzy normed space. In this paper, we study the concept of statistical convergence on intuitionistic fuzzy normed spaces. Then we give a useful characterization for statistically convergent sequences. Furthermore, we display an example such that our method of convergence is stronger than the usual convergence on intuitionistic fuzzy normed spaces

Time course of brain activation elicited by basic emotions.

Science.gov (United States)

Hot, Pascal; Sequeira, Henrique

2013-11-13

Whereas facial emotion recognition protocols have shown that each discrete emotion has a specific time course of brain activation, there is no electrophysiological evidence to support these findings for emotional induction by complex pictures. Our objective was to specify the differences between the time courses of brain activation elicited by feelings of happiness and, with unpleasant pictures, by feelings of disgust and sadness. We compared event-related potentials (ERPs) elicited by the watching of high-arousing pictures from the International Affective Picture System, selected to induce specific emotions. In addition to a classical arousal effect on late positive components, we found specific ERP patterns for each emotion in early temporal windows (emotion to be associated with different brain processing after 140 ms, whereas happiness and sadness differed in ERPs elicited at the frontal and central sites after 160 ms. Our findings highlight the limits of the classical averaging of ERPs elicited by different emotions inside the same valence and suggest that each emotion could elicit a specific temporal pattern of brain activation, similar to those observed with emotional face recognition.

A task-related and resting state realistic fMRI simulator for fMRI data validation

Science.gov (United States)

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.

Cultura da Convergência

Directory of Open Access Journals (Sweden)

Rogério Christofoletti

2008-12-01

Full Text Available Três idéias já seriam suficientes para que a leitura de “Culturada Convergência”, de Henry Jenkins, interessasse a jornalistas epesquisadores da área: a convergência midiática como um processo cultural; o fortalecimento de uma economia afetiva que orienta consumidores de bens simbólicos e criadores midiáticos; a expansão de formas narrativas transmidiáticas.

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....

Convergent systems vs. incremental stability

NARCIS (Netherlands)

Rüffer, B.S.; Wouw, van de N.; Mueller, M.

2013-01-01

Two similar stability notions are considered; one is the long established notion of convergent systems, the other is the younger notion of incremental stability. Both notions require that any two solutions of a system converge to each other. Yet these stability concepts are different, in the sense

Regional Convergence and Sustainable Development in China

Directory of Open Access Journals (Sweden)

Fang Yang

2016-01-01

Full Text Available Based on the convergence theory of economic growth, this paper extends this concept to the human development index and carries out an empirical analysis of regional development in China between 1997 and 2006. Our research shows that the conditional convergence has been identified. Investment in fixed assets, government expenditure on education, health and infrastructure construction have positive effects on regional convergence of social development. Population weighted analysis of human development index provides support for weak convergence amongst provinces. Analysis of dynamics of regional distribution reveals the club convergence, which indicate two different convergence states. Central China is in the shade and lags behind, giving rise to the so-called “central downfall”. To solve this problem, the “Rise of Central China” Plan is necessary to promote the connection between coastal and inland regions of China and reduce the regional development gap.

Intermittent reductions in respiratory neural activity elicit spinal TNF-α-independent, atypical PKC-dependent inactivity-induced phrenic motor facilitation.

Science.gov (United States)

Baertsch, Nathan A; Baker-Herman, Tracy L

2015-04-15

In many neural networks, mechanisms of compensatory plasticity respond to prolonged reductions in neural activity by increasing cellular excitability or synaptic strength. In the respiratory control system, a prolonged reduction in synaptic inputs to the phrenic motor pool elicits a TNF-α- and atypical PKC-dependent form of spinal plasticity known as inactivity-induced phrenic motor facilitation (iPMF). Although iPMF may be elicited by a prolonged reduction in respiratory neural activity, iPMF is more efficiently induced when reduced respiratory neural activity (neural apnea) occurs intermittently. Mechanisms giving rise to iPMF following intermittent neural apnea are unknown. The purpose of this study was to test the hypothesis that iPMF following intermittent reductions in respiratory neural activity requires spinal TNF-α and aPKC. Phrenic motor output was recorded in anesthetized and ventilated rats exposed to brief intermittent (5, ∼1.25 min), brief sustained (∼6.25 min), or prolonged sustained (30 min) neural apnea. iPMF was elicited following brief intermittent and prolonged sustained neural apnea, but not following brief sustained neural apnea. Unlike iPMF following prolonged neural apnea, spinal TNF-α was not required to initiate iPMF during intermittent neural apnea; however, aPKC was still required for its stabilization. These results suggest that different patterns of respiratory neural activity induce iPMF through distinct cellular mechanisms but ultimately converge on a similar downstream pathway. Understanding the diverse cellular mechanisms that give rise to inactivity-induced respiratory plasticity may lead to development of novel therapeutic strategies to treat devastating respiratory control disorders when endogenous compensatory mechanisms fail. Copyright © 2015 the American Physiological Society.

Who gets afraid in the MRI-scanner? Neurogenetics of state-anxiety changes during an fMRI experiment.

Science.gov (United States)

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.

On the relationship between instantaneous phase synchrony and correlation-based sliding windows for time-resolved fMRI connectivity analysis.

Science.gov (United States)

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

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.)

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.)

Convergence as conditionant for Media Regulation

Directory of Open Access Journals (Sweden)

Othon Jambeiro

2011-01-01

Full Text Available Convergence comprises a combination of interlinked and interdependent transformations, of technological, industrial, commercial, cultural and social nature, which affect communication regulation. Customers, at their time, turned also convergent, involved in an intense participative culture, which is too, from the point of view of its social and geographical range, thanks to convergence, more and more extense. Instead of passive consumers of media and information and communication services, we have now active and socially connected consumers, no more readers/spectators/listeners, but noisy activists and publishers. To understand this phenomenon is essential to discern a regulatory frame suitable for it. This paper tries to define convergence and to discuss its consequences.

Elicited vs. voluntary promises

NARCIS (Netherlands)

Ismayilov, H.; Potters, Jan

2017-01-01

We set up an experiment with pre-play communication to study the impact of promise elicitation by trustors from trustees on trust and trustworthiness. When given the opportunity a majority of trustors solicits a promise from the trustee. This drives up the promise making rate by trustees to almost

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.

Cultura da Convergência

Directory of Open Access Journals (Sweden)

Rogério Christofoletti

2008-12-01

Full Text Available Três idéias já seriam suficientes para que a leitura de “Cultura da Convergência”, de Henry Jenkins, interessasse a jornalistas e pesquisadores da área: a convergência midiática como um processo cultural; o fortalecimento de uma economia afetiva que orienta consumidores de bens simbólicos e criadores midiáticos; a expansão de formas narrativas transmidiáticas.

Convergence of barycentric coordinates to barycentric kernels

KAUST Repository

Kosinka, Jiří

2016-02-12

We investigate the close correspondence between barycentric coordinates and barycentric kernels from the point of view of the limit process when finer and finer polygons converge to a smooth convex domain. We show that any barycentric kernel is the limit of a set of barycentric coordinates and prove that the convergence rate is quadratic. Our convergence analysis extends naturally to barycentric interpolants and mappings induced by barycentric coordinates and kernels. We verify our theoretical convergence results numerically on several examples.

Convergence of barycentric coordinates to barycentric kernels

KAUST Repository

Kosinka, Jiří ; Barton, Michael

2016-01-01

We investigate the close correspondence between barycentric coordinates and barycentric kernels from the point of view of the limit process when finer and finer polygons converge to a smooth convex domain. We show that any barycentric kernel is the limit of a set of barycentric coordinates and prove that the convergence rate is quadratic. Our convergence analysis extends naturally to barycentric interpolants and mappings induced by barycentric coordinates and kernels. We verify our theoretical convergence results numerically on several examples.

Mapping cerebrovascular reactivity using concurrent fMRI and near infrared spectroscopy

Science.gov (United States)

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.

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...

Δim-lacunary statistical convergence of order α

Science.gov (United States)

Altınok, Hıfsı; Et, Mikail; Işık, Mahmut

2018-01-01

The purpose of this work is to introduce the concepts of Δim-lacunary statistical convergence of order α and lacunary strongly (Δim,p )-convergence of order α. We establish some connections between lacunary strongly (Δim,p )-convergence of order α and Δim-lacunary statistical convergence of order α. It is shown that if a sequence is lacunary strongly (Δim,p )-summable of order α then it is Δim-lacunary statistically convergent of order α.

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/.

Increasing dominance of IT in ICT convergence

DEFF Research Database (Denmark)

Henten, Anders; Tadayoni, Reza

The aim of the paper is to examine the increasing dominance of IT companies in the converging ICT industry and, on the basis of this development, to contribute to extending the theoretical understanding of market and industry convergence in the ICT area.......The aim of the paper is to examine the increasing dominance of IT companies in the converging ICT industry and, on the basis of this development, to contribute to extending the theoretical understanding of market and industry convergence in the ICT area....

Regional homogeneity changes in prelingually deafened patients: a resting-state fMRI study

Science.gov (United States)

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.

Eliciting expert opinion for economic models: an applied example.

Science.gov (United States)

Leal, José; Wordsworth, Sarah; Legood, Rosa; Blair, Edward

2007-01-01

Expert opinion is considered as a legitimate source of information for decision-analytic modeling where required data are unavailable. Our objective was to develop a practical computer-based tool for eliciting expert opinion about the shape of the uncertainty distribution around individual model parameters. We first developed a prepilot survey with departmental colleagues to test a number of alternative approaches to eliciting opinions on the shape of the uncertainty distribution around individual parameters. This information was used to develop a survey instrument for an applied clinical example. This involved eliciting opinions from experts to inform a number of parameters involving Bernoulli processes in an economic model evaluating DNA testing for families with a genetic disease, hypertrophic cardiomyopathy. The experts were cardiologists, clinical geneticists, and laboratory scientists working with cardiomyopathy patient populations and DNA testing. Our initial prepilot work suggested that the more complex elicitation techniques advocated in the literature were difficult to use in practice. In contrast, our approach achieved a reasonable response rate (50%), provided logical answers, and was generally rated as easy to use by respondents. The computer software user interface permitted graphical feedback throughout the elicitation process. The distributions obtained were incorporated into the model, enabling the use of probabilistic sensitivity analysis. There is clearly a gap in the literature between theoretical elicitation techniques and tools that can be used in applied decision-analytic models. The results of this methodological study are potentially valuable for other decision analysts deriving expert opinion.

Strategic business transformation through technology convergence

DEFF Research Database (Denmark)

Agarwal, Nivedita; Brem, Alexander

2015-01-01

-time intelligence. This paper presents the case of General Electric (GE) and studies the various transitional phases and transformation dimensions that GE is experiencing, to manage this technology convergence. The evaluation of GE's experience indicates that convergence-related business transformation is nonlinear......Technology adoption is crucial for an organisation to remain competitive in the marketplace. Traditionally, two technologies - operational technology (OT) and information technology (IT) - have operated independently from one another; however, technological advancements that businesses...... are experiencing have increased the overlap and convergence of these two areas. Industrial organisations are investing heavily in the integration and alignment of these technologies and expect to benefit in several ways from this convergence, such as through increased productivity, reduction in cost, and real...

Fixed mobile convergence handbook

CERN Document Server

Ahson, Syed A

2010-01-01

From basic concepts to future directions, this handbook provides technical information on all aspects of fixed-mobile convergence (FMC). The book examines such topics as integrated management architecture, business trends and strategic implications for service providers, personal area networks, mobile controlled handover methods, SIP-based session mobility, and supervisory and notification aggregator service. Case studies are used to illustrate technical and systematic implementation of unified and rationalized internet access by fixed-mobile network convergence. The text examines the technolo

A Globally Convergent Matrix-Free Method for Constrained Equations and Its Linear Convergence Rate

Directory of Open Access Journals (Sweden)

Min Sun

2014-01-01

Full Text Available A matrix-free method for constrained equations is proposed, which is a combination of the well-known PRP (Polak-Ribière-Polyak conjugate gradient method and the famous hyperplane projection method. The new method is not only derivative-free, but also completely matrix-free, and consequently, it can be applied to solve large-scale constrained equations. We obtain global convergence of the new method without any differentiability requirement on the constrained equations. Compared with the existing gradient methods for solving such problem, the new method possesses linear convergence rate under standard conditions, and a relax factor γ is attached in the update step to accelerate convergence. Preliminary numerical results show that it is promising in practice.

"Nanoselves": NBIC and the Culture of Convergence

Science.gov (United States)

Venkatesan, Priya

2010-01-01

The subject of this essay is NBIC convergence (nanotechnology, biotechnology, information technology and cognitive science convergence). NBIC convergence is a recurring trope that is dominated by the paradigm of integration of the sciences. It is largely influenced by the considerations of social and economic impact, and it assumes positivism in…

A Java-based fMRI processing pipeline evaluation system for assessment of univariate general linear model and multivariate canonical variate analysis-based pipelines.

Science.gov (United States)

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.

Sectoral Energy, and Labour, Productivity Convergence

International Nuclear Information System (INIS)

Mulder, P.; De Groot, H.L.F.

2007-01-01

This paper empirically investigates the development of cross-country differences in energy- and labour productivity. The analysis is performed at a detailed sectoral level for 14 OECD countries, covering the period 1970-1997. A ρ-convergence analysis reveals that the development over time of the cross-country variation in productivity performance differs across sectors as well as across different levels of aggregation. Both patterns of convergence as well as divergence are found. Cross-country variation of productivity levels is typically larger for energy than for labour. A β-convergence analysis provides support for the hypothesis that in most sectors lagging countries tend to catch up with technological leaders, in particular in terms of energy productivity. Moreover, the results show that convergence is conditional, meaning that productivity levels converge to country-specific steady states. Energy prices and wages are shown to positively affect energy- and labour-productivity growth, respectively. We also find evidence for the importance of economies of scale, whereas the investment share, openness and specialization play only a modest role in explaining cross-country variation in energy- and labour-productivity growth

Cognitive dissonance induction in everyday life: An fMRI study.

Science.gov (United States)

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.

Implicit Structured Sequence Learning: An FMRI Study of the Structural Mere-Exposure Effect

OpenAIRE

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 ...

Convergent evolution of the genomes of marine mammals

Science.gov (United States)

Foote, Andrew D.; Liu, Yue; Thomas, Gregg W.C.; Vinař, Tomáš; Alföldi, Jessica; Deng, Jixin; Dugan, Shannon; van Elk, Cornelis E.; Hunter, Margaret; Joshi, Vandita; Khan, Ziad; Kovar, Christie; Lee, Sandra L.; Lindblad-Toh, Kerstin; Mancia, Annalaura; Nielsen, Rasmus; Qin, Xiang; Qu, Jiaxin; Raney, Brian J.; Vijay, Nagarjun; Wolf, Jochen B. W.; Hahn, Matthew W.; Muzny, Donna M.; Worley, Kim C.; Gilbert, M. Thomas P.; Gibbs, Richard A.

2015-01-01

Marine mammals from different mammalian orders share several phenotypic traits adapted to the aquatic environment and therefore represent a classic example of convergent evolution. To investigate convergent evolution at the genomic level, we sequenced and performed de novo assembly of the genomes of three species of marine mammals (the killer whale, walrus and manatee) from three mammalian orders that share independently evolved phenotypic adaptations to a marine existence. Our comparative genomic analyses found that convergent amino acid substitutions were widespread throughout the genome and that a subset of these substitutions were in genes evolving under positive selection and putatively associated with a marine phenotype. However, we found higher levels of convergent amino acid substitutions in a control set of terrestrial sister taxa to the marine mammals. Our results suggest that, whereas convergent molecular evolution is relatively common, adaptive molecular convergence linked to phenotypic convergence is comparatively rare.

Convergence Insufficiency

Science.gov (United States)

... is also found to be weak. If both accommodation and convergence are weak, reading glasses, sometimes with prism added, may be a great option for these patients. It is very difficult to improve accommodation with exercises. Updated 7/2017 Eye Terms & Conditions ...

A convergent and essential interneuron pathway for Mauthner-cell-mediated escapes.

Science.gov (United States)

Lacoste, Alix M B; Schoppik, David; Robson, Drew N; Haesemeyer, Martin; Portugues, Ruben; Li, Jennifer M; Randlett, Owen; Wee, Caroline L; Engert, Florian; Schier, Alexander F

2015-06-01

The Mauthner cell (M-cell) is a command-like neuron in teleost fish whose firing in response to aversive stimuli is correlated with short-latency escapes [1-3]. M-cells have been proposed as evolutionary ancestors of startle response neurons of the mammalian reticular formation [4], and studies of this circuit have uncovered important principles in neurobiology that generalize to more complex vertebrate models [3]. The main excitatory input was thought to originate from multisensory afferents synapsing directly onto the M-cell dendrites [3]. Here, we describe an additional, convergent pathway that is essential for the M-cell-mediated startle behavior in larval zebrafish. It is composed of excitatory interneurons called spiral fiber neurons, which project to the M-cell axon hillock. By in vivo calcium imaging, we found that spiral fiber neurons are active in response to aversive stimuli capable of eliciting escapes. Like M-cell ablations, bilateral ablations of spiral fiber neurons largely eliminate short-latency escapes. Unilateral spiral fiber neuron ablations shift the directionality of escapes and indicate that spiral fiber neurons excite the M-cell in a lateralized manner. Their optogenetic activation increases the probability of short-latency escapes, supporting the notion that spiral fiber neurons help activate M-cell-mediated startle behavior. These results reveal that spiral fiber neurons are essential for the function of the M-cell in response to sensory cues and suggest that convergent excitatory inputs that differ in their input location and timing ensure reliable activation of the M-cell, a feedforward excitatory motif that may extend to other neural circuits. Copyright © 2015 Elsevier Ltd. All rights reserved.

Convergence theorems for Banach space valued integrable multifunctions

Directory of Open Access Journals (Sweden)

Nikolaos S. Papageorgiou

1987-01-01

Full Text Available In this work we generalize a result of Kato on the pointwise behavior of a weakly convergent sequence in the Lebesgue-Bochner spaces LXP(Ω (1≤p≤∞. Then we use that result to prove Fatou's type lemmata and dominated convergence theorems for the Aumann integral of Banach space valued measurable multifunctions. Analogous convergence results are also proved for the sets of integrable selectors of those multifunctions. In the process of proving those convergence theorems we make some useful observations concerning the Kuratowski-Mosco convergence of sets.

Weak convergence and uniform normalization in infinitary rewriting

DEFF Research Database (Denmark)

Simonsen, Jakob Grue

2010-01-01

the starkly surprising result that for any orthogonal system with finitely many rules, the system is weakly normalizing under weak convergence if{f} it is strongly normalizing under weak convergence if{f} it is weakly normalizing under strong convergence if{f} it is strongly normalizing under strong...... convergence. As further corollaries, we derive a number of new results for weakly convergent rewriting: Systems with finitely many rules enjoy unique normal forms, and acyclic orthogonal systems are confluent. Our results suggest that it may be possible to recover some of the positive results for strongly...

Electricity and gas : market and price convergence : fundamentals of restructuring and convergence

Energy Technology Data Exchange (ETDEWEB)

Heintz, H.; Spragins, R.

2000-07-01

One of the results of the transition from regulation to competition in the Canadian and American natural gas and electricity industries is convergence of the two industries. Convergence is occurring in the areas of corporate structuring activities (mergers and acquisitions), natural gas and electricity prices, products and services, and on a geographic basis. This study examines the restructuring and convergence from the perspective of industry stakeholders, consumers, competitors and regulators. The trend to deregulate to establish competitive markets has been driven by the assumption that lower prices and more choices will result. Deregulation has been made easier by technological developments and innovations in the area of conventional generation, distributed generation, information management and analysis, as well as mass communication channels such as the Internet. These changes have made it possible to measure and monitor energy use in real-time. Technological changes will continue to influence the energy industry. The use of different restructuring rules and regulations in jurisdictions that are implementing change may be one of the primary factors that could limit the extent of convergence. Successful competition by energy service providers in converged retail energy markets will depend on several factors, the first of which is the ability to control the customer interface through retail cycle services such as metering and billing. The second is the successful branding of corporate identities, products and services. These will ensure customer loyalty and facilitate the marketing of new products. Another factor would be the effective management of information regarding natural gas and electricity consumption patterns and the establishment of low cost operations through the use of conventional generation technologies. The final factor for successful competition is the effective use of low cost communication technologies such as the Internet. The transition

Electricity and gas : market and price convergence : fundamentals of restructuring and convergence

International Nuclear Information System (INIS)

Heintz, H.; Spragins, R.

2000-01-01

One of the results of the transition from regulation to competition in the Canadian and American natural gas and electricity industries is convergence of the two industries. Convergence is occurring in the areas of corporate structuring activities (mergers and acquisitions), natural gas and electricity prices, products and services, and on a geographic basis. This study examines the restructuring and convergence from the perspective of industry stakeholders, consumers, competitors and regulators. The trend to deregulate to establish competitive markets has been driven by the assumption that lower prices and more choices will result. Deregulation has been made easier by technological developments and innovations in the area of conventional generation, distributed generation, information management and analysis, as well as mass communication channels such as the Internet. These changes have made it possible to measure and monitor energy use in real-time. Technological changes will continue to influence the energy industry. The use of different restructuring rules and regulations in jurisdictions that are implementing change may be one of the primary factors that could limit the extent of convergence. Successful competition by energy service providers in converged retail energy markets will depend on several factors, the first of which is the ability to control the customer interface through retail cycle services such as metering and billing. The second is the successful branding of corporate identities, products and services. These will ensure customer loyalty and facilitate the marketing of new products. Another factor would be the effective management of information regarding natural gas and electricity consumption patterns and the establishment of low cost operations through the use of conventional generation technologies. The final factor for successful competition is the effective use of low cost communication technologies such as the Internet. The transition

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...

Video elicitation interviews: a qualitative research method for investigating physician-patient interactions.

Science.gov (United States)

Henry, Stephen G; Fetters, Michael D

2012-01-01

We describe the concept and method of video elicitation interviews and provide practical guidance for primary care researchers who want to use this qualitative method to investigate physician-patient interactions. During video elicitation interviews, researchers interview patients or physicians about a recent clinical interaction using a video recording of that interaction as an elicitation tool. Video elicitation is useful because it allows researchers to integrate data about the content of physician-patient interactions gained from video recordings with data about participants' associated thoughts, beliefs, and emotions gained from elicitation interviews. This method also facilitates investigation of specific events or moments during interactions. Video elicitation interviews are logistically demanding and time consuming, and they should be reserved for research questions that cannot be fully addressed using either standard interviews or video recordings in isolation. As many components of primary care fall into this category, high-quality video elicitation interviews can be an important method for understanding and improving physician-patient interactions in primary care.

Video Elicitation Interviews: A Qualitative Research Method for Investigating Physician-Patient Interactions

Science.gov (United States)

Henry, Stephen G.; Fetters, Michael D.

2012-01-01

We describe the concept and method of video elicitation interviews and provide practical guidance for primary care researchers who want to use this qualitative method to investigate physician-patient interactions. During video elicitation interviews, researchers interview patients or physicians about a recent clinical interaction using a video recording of that interaction as an elicitation tool. Video elicitation is useful because it allows researchers to integrate data about the content of physician-patient interactions gained from video recordings with data about participants’ associated thoughts, beliefs, and emotions gained from elicitation interviews. This method also facilitates investigation of specific events or moments during interactions. Video elicitation interviews are logistically demanding and time consuming, and they should be reserved for research questions that cannot be fully addressed using either standard interviews or video recordings in isolation. As many components of primary care fall into this category, high-quality video elicitation interviews can be an important method for understanding and improving physician-patient interactions in primary care. PMID:22412003

Adaptive smoothing based on Gaussian processes regression increases the sensitivity and specificity of fMRI data.

Science.gov (United States)

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.

Eliciting and communicating expert judgments: methodology and application to nuclear safety

International Nuclear Information System (INIS)

Winterfeldt, D. von; Commission of the European Communities, Ispra

1989-01-01

Expert judgment has always been used informally in the analysis of complex engineering problems. Increasingly, however, the use of expert judgment has been formalized by eliciting judgments in an explicit, documented and often quantitative way. In nuclear safety studies the need for formal elicitation of expert judgments arises because of the lack of data and experiences, the need to adapt model results to the specific circumstances of a plant, and the large uncertainties surrounding the events and quantities that characterize an accident sequence. The recognition of the need for a formal elicitation of expert judgments has led to one of the most extensive expert elicitation processes to date in the context of the NUREG 1150 study. About 30 safety issues were quantified using expert judgments about probabilities of various uncertain events and quantities, ranging from the failure of a check valve in the cooling system to the pressure built up due to hydrogen production to release fractions of various radionuclides. In total, some 1000 probability distributions were elicited from some 50 experts. This paper first motivates the use of formal expert elicitation in complex engineering studies and describes the methodology of formal expert elicitation. Subsequently, it describes the overall approach of NUREG 1150 and provides an example of the elicitation of the probability of a bypass failure in a pressurized water reactor. The paper ends by discussing some lessons learned, problems encountered and by providing some recommendations

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...

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.)

Quadratically convergent MCSCF scheme using Fock operators

International Nuclear Information System (INIS)

Das, G.

1981-01-01

A quadratically convergent formulation of the MCSCF method using Fock operators is presented. Among its advantages the present formulation is quadratically convergent unlike the earlier ones based on Fock operators. In contrast to other quadratically convergent schemes as well as the one based on generalized Brillouin's theorem, this method leads easily to a hybrid scheme where the weakly coupled orbitals (such as the core) are handled purely by Fock equations, while the rest of the orbitals are treated by a quadratically convergent approach with a truncated virtual space obtained by the use of the corresponding Fock equations

A Versatile Software Package for Inter-subject Correlation Based Analyses of fMRI

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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/.

A versatile software package for inter-subject correlation based analyses of fMRI.

Science.gov (United States)

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/

Language Lateralization in Children Aged 10 to 11 Years: A Combined fMRI and Dichotic Listening Study

Science.gov (United States)

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

Language lateralization in children aged 10 to 11 years: a combined fMRI and dichotic listening study.

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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.

The impact of fMRI on multimodal navigation in surgery of cerebral lesions: four years clinical experience

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.)

Patterns of brain activation when mothers view their own child and dog: an fMRI study.

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Luke E Stoeckel

Full Text Available Neural substrates underlying the human-pet relationship are largely unknown. We examined fMRI brain activation patterns as mothers viewed images of their own child and dog and an unfamiliar child and dog. There was a common network of brain regions involved in emotion, reward, affiliation, visual processing and social cognition when mothers viewed images of both their child and dog. Viewing images of their child resulted in brain activity in the midbrain (ventral tegmental area/substantia nigra involved in reward/affiliation, while a more posterior cortical brain activation pattern involving fusiform gyrus (visual processing of faces and social cognition characterized a mother's response to her dog. Mothers also rated images of their child and dog as eliciting similar levels of excitement (arousal and pleasantness (valence, although the difference in the own vs. unfamiliar child comparison was larger than the own vs. unfamiliar dog comparison for arousal. Valence ratings of their dog were also positively correlated with ratings of the attachment to their dog. Although there are similarities in the perceived emotional experience and brain function associated with the mother-child and mother-dog bond, there are also key differences that may reflect variance in the evolutionary course and function of these relationships.

Patterns of brain activation when mothers view their own child and dog: an fMRI study.

Science.gov (United States)

Stoeckel, Luke E; Palley, Lori S; Gollub, Randy L; Niemi, Steven M; Evins, Anne Eden

2014-01-01

Neural substrates underlying the human-pet relationship are largely unknown. We examined fMRI brain activation patterns as mothers viewed images of their own child and dog and an unfamiliar child and dog. There was a common network of brain regions involved in emotion, reward, affiliation, visual processing and social cognition when mothers viewed images of both their child and dog. Viewing images of their child resulted in brain activity in the midbrain (ventral tegmental area/substantia nigra involved in reward/affiliation), while a more posterior cortical brain activation pattern involving fusiform gyrus (visual processing of faces and social cognition) characterized a mother's response to her dog. Mothers also rated images of their child and dog as eliciting similar levels of excitement (arousal) and pleasantness (valence), although the difference in the own vs. unfamiliar child comparison was larger than the own vs. unfamiliar dog comparison for arousal. Valence ratings of their dog were also positively correlated with ratings of the attachment to their dog. Although there are similarities in the perceived emotional experience and brain function associated with the mother-child and mother-dog bond, there are also key differences that may reflect variance in the evolutionary course and function of these relationships.

a globally convergent hyperpl onvergent hyperplane

African Journals Online (AJOL)

userpc

Bayero Journal of Pure and App. ISSN 2006 – 6996 ... Globally Convergent Hyper plane-BFGS method for solving nonline. The attractive ... Numerical performance on some b rates there liability ..... convergence of a class of quasi methods on ...

Basis Expansion Approaches for Regularized Sequential Dictionary Learning Algorithms With Enforced Sparsity for fMRI Data Analysis.

Science.gov (United States)

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.

Ready...go: Amplitude of the FMRI signal encodes expectation of cue arrival time.

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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.

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.)

Implicit Structured Sequence Learning: An FMRI Study of the Structural Mere-Exposure Effect

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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.

Functional brain activation differences in stuttering identified with a rapid fMRI sequence

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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

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.)

Functional magnetic resonance imaging mapping of the motor cortex in patients with cerebral tumors

International Nuclear Information System (INIS)

Mueller, W.M.; Zerrin Yetkin, F.; Hammeke, T.A.

1997-01-01

Objective. The purpose of this study was to determine the usefulness of functional magnetic resonance imaging (FMRI) to map cerebral functions in patients with frontal or parietal tumors. Methods. Charts and images of patients with cerebral tumors or vascular malformations who underwent FMRI with an echo-planar technique were reviewed. The FMRI maps of motor (11 patients), tactile sensory (12 patients) and language tasks (4 patients) were obtained. The location of the FMRI activation and the positive responses to intraoperative cortical stimulation were compared. The reliability of the paradigms for mapping the rolandic cortex was evaluated. Results. Rolandic cortex was activated by tactile tasks in hall 12 patients and by motor tasks in 10 of 11 patients. Language tasks elicited activation in each of the four patients. Activation was obtained within edematous brain and adjacent to tumors. FMRI in three cases with intraoperative electro-cortical mapping results showed activation for a language, tactile, or motor task within the same gyrus in which stimulation elicited a related motor, sensory, or language function. In patients with >2 cm between the margin of the tumor, as revealed by magnetic resonance imaging, and the activation, no decline in motor function occurred from surgical resection. Conclusions. FMRI of tactile, motor, and language tasks is feasible in patients with cerebral tumors. FMRI shows promise as a means of determining the risk of a postoperative motor deficit from surgical resection of frontal or parietal tumors. (authors)

Test-retest reliability of evoked BOLD signals from a cognitive-emotive fMRI test battery.

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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

Feasibility of using fMRI to study mothers responding to infant cries.

Science.gov (United States)

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.

The potential for using visual elicitation in understanding preschool ...

African Journals Online (AJOL)

We explore the use of video and photo elicitation in a research study undertaken to understand the way in which preschool teachers perceive and construct their provision of children's educational experiences. We explore the value of visually elicited interviews based on video footage and photographs captured during ...

The Mackey convergence condition for spaces with webs

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Thomas E. Gilsdorf

1988-01-01

Full Text Available If each sequence converging to 0 in a locally convex space is also Mackey convergent to 0, that space is said to satisfy the Mackey convergence condition. The problem of characterizing those locally convex spaces with this property is still open. In this paper, spaces with compatible webs are used to construct both a necessary and a sufficient condition for a locally convex space to satisfy the Mackey convergence condition.

On the Fuzzy Convergence

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Abdul Hameed Q. A. Al-Tai

2011-01-01

Full Text Available The aim of this paper is to introduce and study the fuzzy neighborhood, the limit fuzzy number, the convergent fuzzy sequence, the bounded fuzzy sequence, and the Cauchy fuzzy sequence on the base which is adopted by Abdul Hameed (every real number r is replaced by a fuzzy number r¯ (either triangular fuzzy number or singleton fuzzy set (fuzzy point. And then, we will consider that some results respect effect of the upper sequence on the convergent fuzzy sequence, the bounded fuzzy sequence, and the Cauchy fuzzy sequence.

Explaining choice option attractiveness by beliefs elicited by the laddering method

DEFF Research Database (Denmark)

Grunert, Klaus G.; Bech-Larsen, Tino

2005-01-01

option. The laddering method is used to elicit beliefs of all three types for a choice between conventional and organic pork. As a benchmark, beliefs were also elicited in the traditional way advocated by Ajzen and Fishbein. Using both sets of beliefs in a subsequent survey, it was shown that the beliefs...... elicited by the laddering method increase explanatory power with regard to choice option attractiveness beyond the beliefs elicited by the Ajzen and Fishbein method, and that this additional explanatory power was due to those beliefs which relate the choice option to concepts with a higher level...

Responsibilities in the Usability Requirements Elicitation Process

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Marianella Aveledo

2008-12-01

Full Text Available Like any other software system quality attribute, usability places requirements on software components. In particular, it has been demonstrated that certain usability features have a direct impact throughout the software process. This paper details an approach that looks at how to deal with certain usability features in the early software development stages. In particular, we consider usability features as functional usability requirements using patterns that have been termed usability patterns to elicit requirements. Additionally, we clearly establish the responsibilities of all the players at the usability requirements elicitation stage.

On statistical acceleration convergence of double sequences

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Bipan Hazarika

2017-04-01

Full Text Available In this article the notion of statistical acceleration convergence of double sequences in Pringsheim's sense has been introduced. We prove the decompostion theorems for  statistical acceleration convergence of double sequences and some theorems related to that concept have been established using the four dimensional matrix transformations. We provided some examples, where the results of acceleration convergence fails to hold for the statistical cases.

Convergence of carbon dioxide emissions in different sectors in China

International Nuclear Information System (INIS)

Wang, Juan; Zhang, Kezhong

2014-01-01

In this paper, we analyze differences in per capita carbon dioxide emissions from 1996 to 2010 in six sectors across 28 provinces in China and examine the σ-convergence, stochastic convergence and β-convergence of these emissions. We also investigate the factors that impact the convergence of per capita carbon dioxide emissions in each sector. The results show that per capita carbon dioxide emissions in all sectors converged across provinces from 1996 to 2010. Factors that impact the convergence of per capita carbon dioxide emissions in each sector vary: GDP (gross domestic product) per capita, industrialization process and population density impact convergence in the Industry sector, while GDP per capita and population density impact convergence in the Transportation, Storage, Postal, and Telecommunications Services sector. Aside from GDP per capita and population density, trade openness also impacts convergence in the Wholesale, Retail, Trade, and Catering Service sector. Population density is the only factor that impacts convergence in the Residential Consumption sector. - Highlights: • Analyze differences in CO 2 emissions in six sectors among 28 provinces in China. • Examine the convergence of CO 2 emissions in six sectors. • Investigate factors impact on convergence of CO 2 emissions in each sector. • Factors impact on convergence of per capita CO 2 emissions in each sector vary

The dynamic programming high-order Dynamic Bayesian Networks learning for identifying effective connectivity in human brain from fMRI.

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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.

Nonvisual spatial navigation fMRI lateralizes mesial temporal lobe epilepsy in a patient with congenital blindness.

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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.

Short- and long-term reliability of language fMRI.

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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

Can Harry Potter still put a spell on us in a second language? An fMRI study on reading emotion-laden literature in late bilinguals.

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Hsu, Chun-Ting; Jacobs, Arthur M; Conrad, Markus

2015-02-01

In this fMRI study we contrasted emotional responses to literary reading in late bilinguals' first or second language. German participants with adequate English proficiency in their second language (L2) English read short text passages from Harry Potter books characterized by a "negative" or "positive" versus "neutral" emotional valence manipulation. Previous studies have suggested that given sufficient L2 proficiency, neural substrates involved in L1 versus L2 do not differ (Fabbro, 2001). On the other hand, the question of attenuated emotionality of L2 language processing is still an open debate (see Conrad, Recio, & Jacobs, 2011). Our results revealed a set of neural structures involved in the processing of emotion-laden literature, including emotion-related amygdala and a set of lateral prefrontal, anterior temporal, and temporo-parietal regions associated with discourse comprehension, high-level semantic integration, and Theory-of-Mind processing. Yet, consistent with post-scan emotion ratings of text passages, factorial fMRI analyses revealed stronger hemodynamic responses to "happy" than to "neutral" in bilateral amygdala and the left precentral cortex that were restricted to L1 reading. Furthermore, multivariate pattern analyses (MVPA) demonstrated better classifiability of differential patterns of brain activity elicited by passages of different emotional content in L1 than in L2 for the whole brain level. Overall, our results suggest that reading emotion-laden texts in our native language provides a stronger and more differentiated emotional experience than reading in a second language. Copyright © 2014 Elsevier Ltd. All rights reserved.

Motor imagery training: Kinesthetic imagery strategy and inferior parietal fMRI activation.

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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.

Integration of fMRI, NIROT and ERP for studies of human brain function.

Science.gov (United States)

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.

Combining fMRI and behavioral measures to examine the process of human learning.

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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.

Sensation seeking predicts brain responses in the old-new task: converging multimodal neuroimaging evidence.

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Lawson, Adam L; Liu, Xun; Joseph, Jane; Vagnini, Victoria L; Kelly, Thomas H; Jiang, Yang

2012-06-01

Novel images and message content enhance visual attention and memory for high sensation seekers, but the neural mechanisms associated with this effect are unclear. To investigate the individual differences in brain responses to new and old (studied) visual stimuli, we utilized event-related potentials (ERP) and functional Magnetic Resonance Imaging (fMRI) measures to examine brain reactivity among high and low sensation seekers during a classic old-new memory recognition task. Twenty low and 20 high sensation seekers completed separate, but parallel, ERP and fMRI sessions. For each session, participants initially studied drawings of common images, and then performed an old-new recognition task during scanning. High sensation seekers showed greater ERP responses to new objects at the frontal N2 ERP component, compared to low sensation seekers. The ERP Novelty-N2 responses were correlated with fMRI responses in the orbitofrontal gyrus. Sensation seeking status also modulated the FN400 ERP component indexing familiarity and conceptual learning, along with fMRI responses in the caudate nucleus, which correlated with FN400 activity. No group differences were found in the late ERP positive components indexing classic old-new amplitude effects. Our combined ERP and fMRI results suggest that sensation-seeking personality affects the early brain responses to visual processing, but not the later stage of memory recognition. Copyright © 2012 Elsevier B.V. All rights reserved.

Lexical-Semantic Search Under Different Covert Verbal Fluency Tasks: An fMRI Study

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Yunqing Li

2017-08-01

Full Text Available Background: Verbal fluency is a measure of cognitive flexibility and word search strategies that is widely used to characterize impaired cognitive function. Despite the wealth of research on identifying and characterizing distinct aspects of verbal fluency, the anatomic and functional substrates of retrieval-related search and post-retrieval control processes still have not been fully elucidated.Methods: Twenty-one native English-speaking, healthy, right-handed, adult volunteers (mean age = 31 years; range = 21–45 years; 9 F took part in a block-design functional Magnetic Resonance Imaging (fMRI study of free recall, covert word generation tasks when guided by phonemic (P, semantic-category (C, and context-based fill-in–the-blank sentence completion (S cues. General linear model (GLM, Independent Component Analysis (ICA, and psychophysiological interaction (PPI were used to further characterize the neural substrate of verbal fluency as a function of retrieval cue type.Results: Common localized activations across P, C, and S tasks occurred in the bilateral superior and left inferior frontal gyrus, left anterior cingulate cortex, bilateral supplementary motor area (SMA, and left insula. Differential task activations were centered in the occipital, temporal and parietal regions as well as the thalamus and cerebellum. The context-based fluency task, i.e., the S task, elicited higher differential brain activity in a lateralized frontal-temporal network typically engaged in complex language processing. P and C tasks elicited activation in limited pathways mainly within the left frontal regions. ICA and PPI results of the S task suggested that brain regions distributed across both hemispheres, extending beyond classical language areas, are recruited for lexical-semantic access and retrieval during sentence completion.Conclusion: Study results support the hypothesis of overlapping, as well as distinct, neural networks for covert word generation when

Quantifying convergence in the sciences

Directory of Open Access Journals (Sweden)

Sara Lumbreras

2016-02-01

Full Text Available Traditional epistemological models classify knowledge into separate disciplines with different objects of study and specific techniques, with some frameworks even proposing hierarchies (such as Comte’s. According to thinkers such as John Holland or Teilhard de Chardin, the advancement of science involves the convergence of disciplines. This proposed convergence can be studied in a number of ways, such as how works impact research outside a specific area (citation networks or how authors collaborate with other researchers in different fields (collaboration networks. While these studies are delivering significant new insights, they cannot easily show the convergence of different topics within a body of knowledge. This paper attempts to address this question in a quantitative manner, searching for evidence that supports the idea of convergence in the content of the sciences themselves (that is, whether the sciences are dealing with increasingly the same topics. We use Latent Dirichlet Analysis (LDA, a technique that is able to analyze texts and estimate the relative contributions of the topics that were used to generate them. We apply this tool to the corpus of the Santa Fe Institute (SFI working papers, which spans research on Complexity Science from 1989 to 2015. We then analyze the relatedness of the different research areas, the rise and demise of these sub-disciplines over time and, more broadly, the convergence of the research body as a whole. Combining the topic structure obtained from the collected publication history of the SFI community with techniques to infer hierarchy and clustering, we reconstruct a picture of a dynamic community which experiences trends, periodically recurring topics, and shifts in the closeness of scholarship over time. We find that there is support for convergence, and that the application of quantitative methods such as LDA to the study of knowledge can provide valuable insights that can help

Film excerpts shown to specifically elicit various affects lead to overlapping activation foci in a large set of symmetrical brain regions in males.

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Karama, Sherif; Armony, Jorge; Beauregard, Mario

2011-01-01

While the limbic system theory continues to be part of common scientific parlance, its validity has been questioned on multiple grounds. Nonetheless, the issue of whether or not there exists a set of brain areas preferentially dedicated to emotional processing remains central within affective neuroscience. Recently, a widespread neural reference space for emotion which includes limbic as well as other regions was characterized in a large meta-analysis. As methodologically heterogeneous studies go into such meta-analyses, showing in an individual study in which all parameters are kept constant, the involvement of overlapping areas for various emotion conditions in keeping with the neural reference space for emotion, would serve as valuable confirmatory evidence. Here, using fMRI, 20 young adult men were scanned while viewing validated neutral and effective emotion-eliciting short film excerpts shown to quickly and specifically elicit disgust, amusement, or sexual arousal. Each emotion-specific run included, in random order, multiple neutral and emotion condition blocks. A stringent conjunction analysis revealed a large overlap across emotion conditions that fit remarkably well with the neural reference space for emotion. This overlap included symmetrical bilateral activation of the medial prefrontal cortex, the anterior cingulate, the temporo-occipital junction, the basal ganglia, the brainstem, the amygdala, the hippocampus, the thalamus, the subthalamic nucleus, the posterior hypothalamus, the cerebellum, as well as the frontal operculum extending towards the anterior insula. This study clearly confirms for the visual modality, that processing emotional stimuli leads to widespread increases in activation that cluster within relatively confined areas, regardless of valence.

Film excerpts shown to specifically elicit various affects lead to overlapping activation foci in a large set of symmetrical brain regions in males.

Directory of Open Access Journals (Sweden)

Sherif Karama

Full Text Available While the limbic system theory continues to be part of common scientific parlance, its validity has been questioned on multiple grounds. Nonetheless, the issue of whether or not there exists a set of brain areas preferentially dedicated to emotional processing remains central within affective neuroscience. Recently, a widespread neural reference space for emotion which includes limbic as well as other regions was characterized in a large meta-analysis. As methodologically heterogeneous studies go into such meta-analyses, showing in an individual study in which all parameters are kept constant, the involvement of overlapping areas for various emotion conditions in keeping with the neural reference space for emotion, would serve as valuable confirmatory evidence. Here, using fMRI, 20 young adult men were scanned while viewing validated neutral and effective emotion-eliciting short film excerpts shown to quickly and specifically elicit disgust, amusement, or sexual arousal. Each emotion-specific run included, in random order, multiple neutral and emotion condition blocks. A stringent conjunction analysis revealed a large overlap across emotion conditions that fit remarkably well with the neural reference space for emotion. This overlap included symmetrical bilateral activation of the medial prefrontal cortex, the anterior cingulate, the temporo-occipital junction, the basal ganglia, the brainstem, the amygdala, the hippocampus, the thalamus, the subthalamic nucleus, the posterior hypothalamus, the cerebellum, as well as the frontal operculum extending towards the anterior insula. This study clearly confirms for the visual modality, that processing emotional stimuli leads to widespread increases in activation that cluster within relatively confined areas, regardless of valence.

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

Beyond Brainstorming: Exploring Convergence in Teams

DEFF Research Database (Denmark)

Seeber, Isabella; de Vreede, Gert-Jan; Maier, Ronald

2017-01-01

Collaborative brainstorming is often followed by a convergence activity where teams extract the most promising ideas on a useful level of detail from the brainstorming results. Contrary to the wealth of research on electronic brainstorming, there is a dearth of research on convergence. We used...

Task-related fMRI in hemiplegic cerebral palsy-A systematic review.

Science.gov (United States)

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

Convergence analysis of canonical genetic algorithms.

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Rudolph, G

1994-01-01

This paper analyzes the convergence properties of the canonical genetic algorithm (CGA) with mutation, crossover and proportional reproduction applied to static optimization problems. It is proved by means of homogeneous finite Markov chain analysis that a CGA will never converge to the global optimum regardless of the initialization, crossover, operator and objective function. But variants of CGA's that always maintain the best solution in the population, either before or after selection, are shown to converge to the global optimum due to the irreducibility property of the underlying original nonconvergent CGA. These results are discussed with respect to the schema theorem.

convergent methods for calculating thermodynamic Green functions

OpenAIRE

Bowen, S. P.; Williams, C. D.; Mancini, J. D.

1984-01-01

A convergent method of approximating thermodynamic Green functions is outlined briefly. The method constructs a sequence of approximants which converges independently of the strength of the Hamiltonian's coupling constants. Two new concepts associated with the approximants are introduced: the resolving power of the approximation, and conditional creation (annihilation) operators. These ideas are illustrated on an exactly soluble model and a numerical example. A convergent expression for the s...

Log-binomial models: exploring failed convergence.

Science.gov (United States)

Williamson, Tyler; Eliasziw, Misha; Fick, Gordon Hilton

2013-12-13

Relative risk is a summary metric that is commonly used in epidemiological investigations. Increasingly, epidemiologists are using log-binomial models to study the impact of a set of predictor variables on a single binary outcome, as they naturally offer relative risks. However, standard statistical software may report failed convergence when attempting to fit log-binomial models in certain settings. The methods that have been proposed in the literature for dealing with failed convergence use approximate solutions to avoid the issue. This research looks directly at the log-likelihood function for the simplest log-binomial model where failed convergence has been observed, a model with a single linear predictor with three levels. The possible causes of failed convergence are explored and potential solutions are presented for some cases. Among the principal causes is a failure of the fitting algorithm to converge despite the log-likelihood function having a single finite maximum. Despite these limitations, log-binomial models are a viable option for epidemiologists wishing to describe the relationship between a set of predictors and a binary outcome where relative risk is the desired summary measure. Epidemiologists are encouraged to continue to use log-binomial models and advocate for improvements to the fitting algorithms to promote the widespread use of log-binomial models.

Extinction and renewal of cue-elicited reward-seeking.

Science.gov (United States)

Bezzina, Louise; Lee, Jessica C; Lovibond, Peter F; Colagiuri, Ben

2016-12-01

Reward cues can contribute to overconsumption of food and drugs and can relapse. The failure of exposure therapies to reduce overconsumption and relapse is generally attributed to the context-specificity of extinction. However, no previous study has examined whether cue-elicited reward-seeking (as opposed to cue-reactivity) is sensitive to context renewal. We tested this possibility in 160 healthy volunteers using a Pavlovian-instrumental transfer (PIT) design involving voluntary responding for a high value natural reward (chocolate). One reward cue underwent Pavlovian extinction in the same (Group AAA) or different context (Group ABA) to all other phases. This cue was compared with a second non-extinguished reward cue and an unpaired control cue. There was a significant overall PIT effect with both reward cues eliciting reward-seeking on test relative to the unpaired cue. Pavlovian extinction substantially reduced this effect, with the extinguished reward cue eliciting less reward-seeking than the non-extinguished reward cue. Most interestingly, extinction of cue-elicited reward-seeking was sensitive to renewal, with extinction less effective for reducing PIT when conducted in a different context. These findings have important implications for extinction-based interventions for reducing maladaptive reward-seeking in practice. Copyright © 2016 Elsevier Ltd. All rights reserved.

Tactile and non-tactile sensory paradigms for fMRI and neurophysiologic studies in rodents

OpenAIRE

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...

Recovering task fMRI signals from highly under-sampled data with low-rank and temporal subspace constraints.

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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.

Blood Flow and Brain Function: Investigations of neurovascular coupling using BOLD fMRI at 7 tesla

NARCIS (Netherlands)

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

Minocycline inhibits D-amphetamine-elicited action potential bursts in a central snail neuron.

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Chen, Y-H; Lin, P-L; Wong, R-W; Wu, Y-T; Hsu, H-Y; Tsai, M-C; Lin, M-J; Hsu, Y-C; Lin, C-H

2012-10-25

Minocycline is a second-generation tetracycline that has been reported to have powerful neuroprotective properties. In our previous studies, we found that d-amphetamine (AMPH) elicited action potential bursts in an identifiable RP4 neuron of the African snail, Achatina fulica Ferussac. This study sought to determine the effects of minocycline on the AMPH-elicited action potential pattern changes in the central snail neuron, using the two-electrode voltage clamping method. Extracellular application of AMPH at 300 μM elicited action potential bursts in the RP4 neuron. Minocycline dose-dependently (300-900 μM) inhibited the action potential bursts elicited by AMPH. The inhibitory effects of minocycline on AMPH-elicited action potential bursts were restored by forskolin (50 μM), an adenylate cyclase activator, and by dibutyryl cAMP (N(6),2'-O-Dibutyryladenosine 3',5'-cyclic monophosphate; 1mM), a membrane-permeable cAMP analog. Co-administration of forskolin (50 μM) plus tetraethylammonium chloride (TEA; 5mM) or co-administration of TEA (5mM) plus dibutyryl cAMP (1mM) also elicited action potential bursts, which were prevented and inhibited by minocycline. In addition, minocycline prevented and inhibited forskolin (100 μM)-elicited action potential bursts. Notably, TEA (50mM)-elicited action potential bursts in the RP4 neuron were not affected by minocycline. Minocycline did not affect steady-state outward currents of the RP4 neuron. However, minocycline did decrease the AMPH-elicited steady-state current changes. Similarly, minocycline decreased the effects of forskolin-elicited steady-state current changes. Pretreatment with H89 (N-[2-(p-Bromocinnamylamino)ethyl]-5-isoquinolinesulfonamide dihydrochloride; 10 μM), a protein kinase A inhibitor, inhibited AMPH-elicited action potential bursts and decreased AMPH-elicited steady-state current changes. These results suggest that the cAMP-protein kinase A signaling pathway and the steady-state current are involved in

A class of convergent neural network dynamics

Science.gov (United States)

Fiedler, Bernold; Gedeon, Tomáš

1998-01-01

We consider a class of systems of differential equations in Rn which exhibits convergent dynamics. We find a Lyapunov function and show that every bounded trajectory converges to the set of equilibria. Our result generalizes the results of Cohen and Grossberg (1983) for convergent neural networks. It replaces the symmetry assumption on the matrix of weights by the assumption on the structure of the connections in the neural network. We prove the convergence result also for a large class of Lotka-Volterra systems. These are naturally defined on the closed positive orthant. We show that there are no heteroclinic cycles on the boundary of the positive orthant for the systems in this class.

Convergence of knowledge, technology and society beyond convergence of nano-bio-info-cognitive technologies

CERN Document Server

Bainbridge, William; Tonn, Bruce; Whitesides, George

2013-01-01

Convergence of knowledge and technology for the benefit of society (CKTS) is the core opportunity for progress in the 21st century, based on five principles: (1) the interdependence of all components of nature and society, (2) enhancement of creativity and innovation through evolutionary processes of convergence that combine existing principles, and divergence that generates new ones, (3) decision analysis for research and development based on system-logic deduction, (4) higher-level cross-domain languages to generate new solutions and support transfer of new knowledge, and (5) vision-inspired basic research embodied in grand challenges. Solutions are outlined for key societal challenges, including creating new industries and jobs, improving lifelong wellness and human potential, achieving personalized and integrated healthcare and education, and securing a sustainable quality of life for all. This report provides a ten-year “NBIC2” vision within a longer-term framework for converging technology and human...

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

Explaining convergence of oecd welfare states

DEFF Research Database (Denmark)

Schmitt, C.; Starke, Peter

2011-01-01

of conditional convergence helps to both better describe and explain the phenomenon. By applying error correction models, we examine conditional convergence of various types of social expenditure in 21 OECD countries between 1980 and 2005. Our empirical findings go beyond the existing literature in two respects...

Temporal comparison of functional brain imaging with diffuse optical tomography and fMRI during rat forepaw stimulation

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

Temporal comparison of functional brain imaging with diffuse optical tomography and fMRI during rat forepaw stimulation

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.

A method to elicit beliefs as most likely intervals

NARCIS (Netherlands)

Schlag, K.H.; van der Weele, J.J.

2015-01-01

We show how to elicit the beliefs of an expert in the form of a "most likely interval", a set of future outcomes that are deemed more likely than any other outcome. Our method, called the Most Likely Interval elicitation rule (MLI), asks the expert for an interval and pays according to how well the

Combined fMRI- and eye movement-based decoding of bistable plaid motion perception.

Science.gov (United States)

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.

Convergence Performance of Adaptive Algorithms of L-Filters

Directory of Open Access Journals (Sweden)

Robert Hudec

2003-01-01

Full Text Available This paper deals with convergence parameters determination of adaptive algorithms, which are used in adaptive L-filters design. Firstly the stability of adaptation process, convergence rate or adaptation time, and behaviour of convergence curve belong among basic properties of adaptive algorithms. L-filters with variety of adaptive algorithms were used to their determination. Convergence performances finding of adaptive filters is important mainly for their hardware applications, where filtration in real time or adaptation of coefficient filter with low capacity of input data are required.

Hormone effects on fMRI and cognitive measures of encoding: importance of hormone preparation.

Science.gov (United States)

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.

Machine learning algorithm accurately detects fMRI signature of vulnerability to major depression.

Science.gov (United States)

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.

Advances and Challenges in Convergent Communication Networks

DEFF Research Database (Denmark)

Toral-Cruz, Homero; Mihovska, Albena

2017-01-01

Welcome to this special issue of Wireless Personal Communications on Advances and Challenges in Convergent Communication Networks. The main purpose of this special issue is to present new progresses and challenges in convergent networks. Communication networks play an important role in our daily...... life because they allow communicating and sharing contents between heterogeneous nodes around the globe. The emergence of multiple network architectures and emerging technologies have resulted in new applications and services over a heterogeneous network. This heterogeneous network has undergone...... significant challenges in recent years, such as the evolution to a converged network with the capability to support multiple services, while maintaining a satisfactory level of QoE/QoS, security, efficiency and trust. The special issue on Advances and Challenges in Convergent Communication Networks...

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...

Neutron gain for converging guide tubes

International Nuclear Information System (INIS)

Mildner, D.F.R.

1982-01-01

The method of acceptance diagrams is used to obtain analytical expressions for the neutron gain of a one-dimensional converging guide tube. It is found that the results are more easily expressed by analyzing the acceptance diagram at the exit of the funnel. The results are compared with those for the straight guide. When both guides have the same dimensions at the guide exit, the converging guide has higher transmitted intensity but with greater divergence of the beam. This analytical method is useful to assess the performance of a converging guide, though numerical computations may be required for detailed analysis of a guide system. (orig.)

Convergence

DEFF Research Database (Denmark)

Prasad, Ramjee

2009-01-01

This paper presents the main conclusions which can be drawn from the discussions on Future Communication Systems and lessons on Unpredictable Future of Wireless Communication Systems. Future systems beyond the third generation are already under discussions in international bodies, such as ITU, WW...... and R&D programmes worldwide. The incoming era is characterized by the convergence of networks and access technology and the divergence of applications. Future mobile communication systems should bring something more than only faster data or wireless internet access....

Convergence in energy consumption per capita among ASEAN countries

International Nuclear Information System (INIS)

Mishra, Vinod; Smyth, Russell

2014-01-01

We test for convergence in energy consumption per capita among ASEAN countries over the period 1971 to 2011 using the panel KPSS stationarity test and panel Lagrange multiplier (LM) unit root test. The results for the panel stationarity and unit root tests with structural breaks find support for energy convergence in ASEAN. - Highlights: • We test for convergence in energy consumption per capita among the ASEAN nations. • Univariate conventional unit root tests provide mixed evidence of convergence. • Panel unit root tests with structural breaks support convergence hypothesis

Multiple fMRI system-level baseline connectivity is disrupted in patients with consciousness alterations.

Science.gov (United States)

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

fMRI responses to pictures of mutilation and contamination.

Science.gov (United States)

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.

Brain Activity Associated with Emoticons: An fMRI Study

Science.gov (United States)

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.

A technique to consider mismatches between fMRI and EEG/MEG sources for fMRI-constrained EEG/MEG source imaging: a preliminary simulation study

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

Convergence testing for MCNP5 Monte Carlo eigenvalue calculations

International Nuclear Information System (INIS)

Brown, F.; Nease, B.; Cheatham, J.

2007-01-01

Determining convergence of Monte Carlo criticality problems is complicated by the statistical noise inherent in the random, walks of the neutrons in each generation. The latest version of MCNP5 incorporates an important new tool for assessing convergence: the Shannon entropy of the fission source distribution, H src . Shannon entropy is a well-known concept from information theory and provides a single number for each iteration to help characterize convergence trends for the fission source distribution. MCNP5 computes H src for each iteration, and these values may be plotted to examine convergence trends. Convergence testing should include both k eff and H src , since the fission distribution will converge more slowly than k eff , especially when the dominance ratio is close to 1.0. (authors)

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.

Specificity of aesthetic experience for artworks: an fMRI study

Directory of Open Access Journals (Sweden)

Cinzia eDi Dio

2011-11-01

Full Text Available In a previous study aimed at investigating the neural correlates of aesthetic experience in the beholder we found that observation of canonical sculptures, relative to sculptures whose proportions had been modified, produced the activation of a specific brain network. This network included various cortical areas and, most interestingly, the right anterior insula. We interpreted this latter activation as the neural signature underpinning emotion-related responses during aesthetic experience. In the present fMRI study, we investigated whether aesthetic experience for Classical sculptures has a quality of its own, distinct from that underpinning observation of real human bodies. Sculpture images and pictures of young athletes, matched to sculptures for body postures and proportions, were used as stimuli. Participants were students naïve to art criticism. Results showed a similar activation pattern for the two stimulus-categories. Direct comparisons between stimulus-categories highlighted, however, some relevant differences. Observation of sculptures, relative to real human body images, determined a greater activation of some visual areas, including fusiform gyrus, plus the right anterior insula. The opposite contrast showed a stronger activation of the superior temporal sulcus. Moreover, canonical proportion in sculpture, but not in human body images, produced a stronger activation of the right anterior insula with respect to proportion-modified images. These data show that, during observation of sculpture images, attention is more attracted by specific visual aspects of the stimulus, whereas observation of real human body images activates areas encoding biological movement. Most interestingly, sculptures elicited activations in right anterior insula, which we suggested to be crucial in hallmarking emotional responses during aesthetic experience. This pattern was poorly expressed during observation of human bodies, suggesting poverty of true

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.

Implicit structured sequence learning: an fMRI study of the structural mere-exposure effect.

Science.gov (United States)

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.

Using fMRI to Investigate Memory in Young Children Born Small for Gestational Age.

Science.gov (United States)

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.

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.

Digital Convergence and Content Regulation

Directory of Open Access Journals (Sweden)

Michael John Starks

2014-12-01

Full Text Available Broadcasting, Press and Internet journalism systems of distribution are converging: the same infrastructure can deliver all three historically separate services. Reception devices mirror this: the Connected TV, the tablet and the smart phone overlap in their functionality. Service overlaps are evident too, with broadcasters providing online and on-demand services and newspapers developing electronic versions. Does this mean that media regulation policies must converge too?My argument is that they should, though only where historically different communications are now fulfilling a similar function, e.g. broadcaster online services and electronic versions of newspapers. Convergence requires a degree of harmonisation and, to this end, I advocate a review of UK broadcasting's 'due impartiality' requirement and of the UK's application of the public service concept. I also argue for independent self-regulation (rather than state-based regulation of non-public-service broadcasting journalism.

Rates of convergence of Brezier net over triangles

International Nuclear Information System (INIS)

Feng Yuyu.

1986-12-01

It is well known (Farin, 1979) that the sequence of Bezier nets f-circumflex n (x) associated with Bernstein-Bezier surface over a triangle converges to the surface uniformly as n goes to infinity. In this paper the precise rates of convergence are given. The pointwise convergence result and saturation theorem are presented. (author). 7 refs

Evolution and convergence in telecommunications

Energy Technology Data Exchange (ETDEWEB)

Radicella, S; Grilli, D [Abdus Salam ICTP, Trieste (Italy)

2002-12-15

These lectures throw a spotlight on different aspects of the evolution of telecommunications networks, namely on the various facets of service and network convergence. The last years progress in data and telecommunications technologies, such as P-based networks, and the enormous potential of mobile communication systems and users' demands for comprehensive and network-independent have led to a convergence of data and telecommunications infrastructures in many aspects. In order to help the reader to an easier understanding of the phenomenon convergence, in the first two parts of this volume the evolution of the basic technologies is described one by one. This is done briefly and is focused on the principle topics, just to build a basis for the third part devoted to problems of convergence in telecommunications. These notes are addressed to those readers, who in a quick overview want to be informed on the future service and network landscape. The notes are equally suited for professionals with the desire to extend their horizon as well as for students looking for an introduction into telecommunications under more general aspects. The authors clearly understand the difficulties in writing a book devoted to the evolution in telecommunications. Today, telecom landscape varies at very high speed. Every few months new network technologies, new products and new services are developed. Attempts to present them in time can be accessible only for magazine publications or contributions to conferences. Therefore, in a number of areas, such as Voice over IP and new switching technologies not much more than the starting point of new paradigms is described. However, the content is up-to-date to a degree, that the phenomenon convergence can be fully understood. Partially, these notes are based on a number of lecture courses that were delivered during recent ICTP winter schools devoted to multimedia and digital communications.

Evolution and convergence in telecommunications

International Nuclear Information System (INIS)

Radicella, S.; Grilli, D.

2002-01-01

These lectures throw a spotlight on different aspects of the evolution of telecommunications networks, namely on the various facets of service and network convergence. The last years progress in data and telecommunications technologies, such as P-based networks, and the enormous potential of mobile communication systems and users' demands for comprehensive and network-independent have led to a convergence of data and telecommunications infrastructures in many aspects. In order to help the reader to an easier understanding of the phenomenon convergence, in the first two parts of this volume the evolution of the basic technologies is described one by one. This is done briefly and is focused on the principle topics, just to build a basis for the third part devoted to problems of convergence in telecommunications. These notes are addressed to those readers, who in a quick overview want to be informed on the future service and network landscape. The notes are equally suited for professionals with the desire to extend their horizon as well as for students looking for an introduction into telecommunications under more general aspects. The authors clearly understand the difficulties in writing a book devoted to the evolution in telecommunications. Today, telecom landscape varies at very high speed. Every few months new network technologies, new products and new services are developed. Attempts to present them in time can be accessible only for magazine publications or contributions to conferences. Therefore, in a number of areas, such as Voice over IP and new switching technologies not much more than the starting point of new paradigms is described. However, the content is up-to-date to a degree, that the phenomenon convergence can be fully understood. Partially, these notes are based on a number of lecture courses that were delivered during recent ICTP winter schools devoted to multimedia and digital communications

Specialisation and Convergence in European Regions

Directory of Open Access Journals (Sweden)

Enrico Marelli

2007-09-01

Full Text Available The purpose of this paper was to analyze specialization and convergence of European countries and regions, within the framework of integration in the EU. This is important not only for long-term real convergence processes, but also for a proper functioning of the monetary union (in the line of research on the OCA's criteria, asymmetry of shocks and synchronization of business cycles. The position of new member states is particularly delicate, also considering the forthcoming adoption of the euro by some of them. As indicated by the EU Treaty, economic growth should be balanced with economic and social cohesion that includes a careful consideration of regional disparities. Our empirical investigation focuses on the regions of EU25, further broken up into other relevant groupings (EU15, EMU, and the new members' EU10 group, over the period from 1980 (or 1990 for EU10 to 2005. This paper considers a rather fine regional disaggregation (NUTS-2 level, counting 250 regions. The analysis of different indices of specialisation point to a prevalent increase of homogeneity of sector structures across European regions, although in some cases (especially in the industrial sector and in some services specialisation has increased. For convergence, a sigma convergence's analysis confirms a reduction of disparities, both at a country and regional level. However, a trade-off between fast national growth and internal distribution has emerged in the early stages of development, as in the case of new members. Moreover, beta convergence has also been established - regarding per capita income, employment and productivity - for almost all territorial aggregates (excluding the new members since 1999. The addition of structural variables, following a beta-conditional approach, indicates a positive role for services and a negative impact of agriculture. Finally, some preliminary results have been obtained by the innovative inclusion of specialisation indices within

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.

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.

Comparison of semantic and episodic memory BOLD fMRI activation in predicting cognitive decline in older adults.

Science.gov (United States)

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.

Fractal aspects and convergence of Newton`s method

Energy Technology Data Exchange (ETDEWEB)

Drexler, M. [Oxford Univ. Computing Lab. (United Kingdom)

1996-12-31

Newton`s Method is a widely established iterative algorithm for solving non-linear systems. Its appeal lies in its great simplicity, easy generalization to multiple dimensions and a quadratic local convergence rate. Despite these features, little is known about its global behavior. In this paper, we will explain a seemingly random global convergence pattern using fractal concepts and show that the behavior of the residual is entirely explicable. We will also establish quantitative results for the convergence rates. Knowing the mechanism of fractal generation, we present a stabilization to the orthodox Newton method that remedies the fractal behavior and improves convergence.

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.)

Application of expert elicitation techniques in human reliability, assessment

International Nuclear Information System (INIS)

Sanyasi Rao, V.V.S.; Saraf, R.K.; Ghosh, A.K.; Kushwaha, H.S.

2006-01-01

Expert elicitation techniques are being used, in the area of technological forecasting, in estimating data needed for analysis when it is either difficult to arrive at the data by experimental means or when it is quite involved to plan and conduct the experiment. In this study, expert elicitation techniques are applied to the evaluation of the frequencies of the various accident sequences that can result from the initiating event (IE) 'High Pressure Process Water (HPPW) system failure' in typical Indian Pressurised Heavy Water Reactor (IPHWR) of the older generation. The Operating Procedure under Emergency Conditions (OPEC) for this IE involves human actions according to a pre-defined procedure. The Human Error Probabilities for all these human actions are obtained using expert elicitation techniques. These techniques aim at eliciting the opinion of the experts in the area of interest with regard to the issue in question. The uncertainty is analysed by employing the measure of dissonance and the most probable range of human error probabilities are arrived at by maximizing this measure. These values are combined using the same procedures mentioned above to yield a distribution representing the uncertainty associated with the predictions. (author)

Do community and autonomy moral violations elicit different emotions?

Science.gov (United States)

Kollareth, Dolichan; Kikutani, Mariko; Shirai, Mariko; Russell, James A

2018-06-11

According to one important set of theories, different domains of immorality are linked to different discrete emotions-panculturally. Violations against the community elicit contempt, whereas violations against an individual elicit anger. To test this theory, American, Indian and Japanese participants (N = 480) indicated contempt and anger reactions (with verbal rating and face selection) to both the types of immorality. To remedy method problems in previous research, community and autonomy violations were created for the same story-frame, by varying the target to be either the community or an individual. Community and autonomy violations did not differ significantly in the emotion elicited: overall, both types of violations elicited more anger than contempt (and more negative emotion of any kind than positive emotion). By verbal rating, Americans and Indians reported more anger than contempt for both types of violation, whereas Japanese reported more contempt than anger for both types. By face selection, the three cultural groups selected anger more than contempt for both types of violation. The results speak against defining distinct domains of morality by their association with distinct emotions. © 2018 International Union of Psychological Science.

Revisiting convergence: A research note.

Science.gov (United States)

Clark, Rob

2015-09-01

A number of recent studies show that income inequality is declining between countries. In this research note, I question the significance of this trend by examining the role of initial conditions in producing convergence. An important (but neglected) property of inequality dynamics is the tendency for extreme distributions to become more moderate. When income disparities are large, the subsequent trend is biased toward convergence. Conversely, when initial conditions approach parity, divergence becomes the more likely long-term outcome. I apply this principle to trends in GDP PC across 127 countries during the 1980-2010 period. Using counterfactual analysis, I manipulate the initial level of inequality in GDP PC while holding constant each country's observed growth rate during the sample period. I find that the growth dynamics of GDP PC produce either convergence or divergence based simply on the initial distribution of income. The point of transition occurs at a moderate level of inequality, whether using population weights (Gini=.365) or not (Gini=.377). I conclude that the recent convergence observed in GDP PC is primarily a function of large income gaps between countries and would not have materialized at more moderate levels of initial inequality. By contrast, an examination of the pre-1950 period reveals divergent growth patterns that are not sensitive to initial conditions. Copyright © 2015 Elsevier Inc. All rights reserved.

Elicitation threshold of cobalt chloride

DEFF Research Database (Denmark)

Fischer, Louise A; Johansen, Jeanne D; Voelund, Aage

2016-01-01

: On the basis of five included studies, the ED10 values of aqueous cobalt chloride ranged between 0.0663 and 1.95 µg cobalt/cm(2), corresponding to 30.8-259 ppm. CONCLUSIONS: Our analysis provides an overview of the doses of cobalt that are required to elicit allergic cobalt contactdermatitis in sensitized...

Film clips and narrative text as subjective emotion elicitation techniques.

Science.gov (United States)

Zupan, Barbra; Babbage, Duncan R

2017-01-01

Film clips and narrative text are useful techniques in eliciting emotion in a laboratory setting but have not been examined side-by-side using the same methodology. This study examined the self-identification of emotions elicited by film clip and narrative text stimuli to confirm that selected stimuli appropriately target the intended emotions. Seventy participants viewed 30 film clips, and 40 additional participants read 30 narrative texts. Participants identified the emotion experienced (happy, sad, angry, fearful, neutral-six stimuli each). Eighty-five percent of participants self-identified the target emotion for at least two stimuli for all emotion categories of film clips, except angry (only one) and for all categories of narrative text, except fearful (only one). The most effective angry text was correctly identified 74% of the time. Film clips were more effective in eliciting all target emotions in participants for eliciting the correct emotion (angry), intensity rating (happy, sad), or both (fearful).

SCGICAR: Spatial concatenation based group ICA with reference for fMRI data analysis.

Science.gov (United States)

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.

Is the environmental performance of industrialized countries converging? A 'SURE' approach to testing for convergence

International Nuclear Information System (INIS)

Camarero, Mariam; Picazo-Tadeo, Andres J.; Tamarit, Cecilio

2008-01-01

In this paper, we test for convergence in the environmental performance of a sample of OECD countries, with data ranging from 1971 to 2002. First, we use Data Envelopment Analysis (DEA) to compute two environmental performance indicators (EPIs) in the production theory framework. Second, we propose the use of a sequential multivariate approach to test for convergence in environmental performance. These tests allow us to reconcile the time series literature with the cross-sectional dimension, which is basic when testing for convergence in regional blocs. The SURE technique is used, which allows for the existence of correlations across the series without imposing a common speed of mean reversion. The empirical results show that the group of countries as a whole, as well as the majority of countries considered on an individual basis (results for some countries vary between EPIs), are catching-up with Switzerland (the benchmark country). (author)

Determination of hemisphere dominance for language: comparison of frontal and temporal fMRI activation with intracarotid amytal testing

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.)

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.

Post-convergence automatic differentiation of iterative schemes

International Nuclear Information System (INIS)

Azmy, Y.Y.

1997-01-01

A new approach for performing automatic differentiation (AD) of computer codes that embody an iterative procedure, based on differentiating a single additional iteration upon achieving convergence, is described and implemented. This post-convergence automatic differentiation (PAD) technique results in better accuracy of the computed derivatives, as it eliminates part of the derivatives convergence error, and a large reduction in execution time, especially when many iterations are required to achieve convergence. In addition, it provides a way to compute derivatives of the converged solution without having to repeat the entire iterative process every time new parameters are considered. These advantages are demonstrated and the PAD technique is validated via a set of three linear and nonlinear codes used to solve neutron transport and fluid flow problems. The PAD technique reduces the execution time over direct AD by a factor of up to 30 and improves the accuracy of the derivatives by up to two orders of magnitude. The PAD technique's biggest disadvantage lies in the necessity to compute the iterative map's Jacobian, which for large problems can be prohibitive. Methods are discussed to alleviate this difficulty

FMRI activity during associative encoding is correlated with cardiorespiratory fitness and source memory performance in older adults

Science.gov (United States)

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

Well-Tempered Metadynamics Converges Asymptotically

Science.gov (United States)

Dama, James F.; Parrinello, Michele; Voth, Gregory A.

2014-06-01

Metadynamics is a versatile and capable enhanced sampling method for the computational study of soft matter materials and biomolecular systems. However, over a decade of application and several attempts to give this adaptive umbrella sampling method a firm theoretical grounding prove that a rigorous convergence analysis is elusive. This Letter describes such an analysis, demonstrating that well-tempered metadynamics converges to the final state it was designed to reach and, therefore, that the simple formulas currently used to interpret the final converged state of tempered metadynamics are correct and exact. The results do not rely on any assumption that the collective variable dynamics are effectively Brownian or any idealizations of the hill deposition function; instead, they suggest new, more permissive criteria for the method to be well behaved. The results apply to tempered metadynamics with or without adaptive Gaussians or boundary corrections and whether the bias is stored approximately on a grid or exactly.

Semi-convergence properties of Kaczmarz’s method

DEFF Research Database (Denmark)

Elfving, Tommy; Hansen, Per Christian; Nikazad, Touraj

2014-01-01

Kaczmarz’s method—sometimes referred to as the algebraic reconstruction technique—is an iterative method that is widely used in tomographic imaging due to its favorable semi-convergence properties. Specifically, when applied to a problem with noisy data, during the early iterations it converges......-convergence of Kaczmarz’s method as well as its projected counterpart (and their block versions). To do this we study how the data errors propagate into the iteration vectors and we derive upper bounds for this noise propagation. Our bounds are compared with numerical results obtained from tomographic imaging....

DRIVERS OF LONG-TERM CONVERGENCE. FOCUS ON ROMANIA

Directory of Open Access Journals (Sweden)

MANUELA UNGURU

2014-11-01

Full Text Available With initial low levels of income per capita, a declining population and relatively modest economic growth rates, there are little prospects of diminishing the gap between Romania and the EU countries. Nevertheless, in the long term, convergence is expected. The question then arises, “What are the drivers and their likely potential to boost economic growth and the catching-up process?”. This paper presents shortly the theoretical background of economic convergence and then focuses on the assessment of possible paths of Romania’s convergence towards the EU. Based on the existing long-term macroeconomic projections and the assessment of the possible future developments of the drivers of economic growth, we have built three scenarios of economic convergence, highlighting the possible timespan of convergence. We have employed growth accounting methods to decompose output growth rate into production factors’ contributions (capital and labour and total factor productivity.

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.

Identification of Voxels Confounded by Venous Signals Using Resting-State fMRI Functional Connectivity Graph Clustering

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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.

Correlated Disruption of Resting-State fMRI, LFP, and Spike Connectivity between Area 3b and S2 following Spinal Cord Injury in Monkeys.

Science.gov (United States)

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

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...

Plant volatile eliciting FACs in lepidopteran caterpillars, fruit flies and crickets: a convergent evolution or phylogenetic inheritance?

Directory of Open Access Journals (Sweden)

Naoko eYoshinaga

2014-04-01

Full Text Available Fatty acid amino acid conjugates (FACs, first identified in lepidopteran caterpillar spit as elicitors of plant volatile emission, also have been reported as major components in gut tracts of Drosophila melanogaster and cricket Teleogryllus taiwanemma. The profile of FAC analogs in these two insects was similar to that of tobacco hornworm Manduca sexta, showing glutamic acid conjugates predominantly over glutamine conjugates. The physiological function of FACs is presumably to enhance nitrogen assimilation in Spodoptera litura larvae, but in other insects it is totally unknown. Whether these insects share a common synthetic mechanism of FACs is also unclear. In this study, the biosynthesis of FACs was examined in vitro in five lepidopteran species (M. sexta, Cephonodes hylas, silkworm, S. litura, and Mythimna separata, fruit fly larvae and T. taiwanemma. The fresh midgut tissues of all of the tested insects showed the ability to synthesize glutamine conjugates in vitro when incubated with glutamine and sodium linolenate. Such direct conjugation was also observed for glutamic acid conjugates in all the insects but the product amount was very small and did not reflect the in vivo FAC patterns in each species. In fruit fly larvae, the predominance of glutamic acid conjugates could be explained by a shortage of substrate glutamine in midgut tissues, and in M. sexta, a rapid hydrolysis of glutamine conjugates has been reported. In crickets, we found an additional unique biosynthetic pathway for glutamic acid conjugates. T. taiwanemma converted glutamine conjugates to glutamic acid conjugates by deaminating the side chain of the glutamine moiety. Considering these findings together with previous results, a possibility that FACs in these insects are results of convergent evolution can not be ruled out, but it is more likely that the ancestral insects had the glutamine conjugates and crickets and other insects developed glutamic acid conjugates in a

Frequency response functions for nonlinear convergent systems

NARCIS (Netherlands)

Pavlov, A.V.; Wouw, van de N.; Nijmeijer, H.

2007-01-01

Convergent systems constitute a practically important class of nonlinear systems that extends the class of asymptotically stable linear time-invariant systems. In this note, we extend frequency response functions defined for linear systems to nonlinear convergent systems. Such nonlinear frequency

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

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....

Converged Registries Solution (CRS)

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Department of Veterans Affairs — The Converged Registries platform is a hardware and software architecture designed to host individual patient registries and eliminate duplicative development effort...

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...

On convergence of nuclear and correlation operators in Hilbert space

International Nuclear Information System (INIS)

Kubrusly, C.S.

1985-01-01

The convergence of sequences of nuclear operators on a separable Hilbert space is studied. Emphasis is given to trace-norm convergence, which is a basic property in stochastic systems theory. Obviously trace-norm convergence implies uniform convergence. The central theme of the paper focus the opposite way, by investigating when convergence in a weaker topology turns out to imply convergence in a stronger topology. The analysis carried out here is exhaustive in the following sense. All possible implications within a selected set of asymptotic properties for sequences of nuclear operators are established. The special case of correlation operators is also considered in detail. (Author) [pt

Competency measurements: testing convergent validity for two measures.

Science.gov (United States)

Cowin, Leanne S; Hengstberger-Sims, Cecily; Eagar, Sandy C; Gregory, Linda; Andrew, Sharon; Rolley, John

2008-11-01

This paper is a report of a study to investigate whether the Australian National Competency Standards for Registered Nurses demonstrate correlations with the Finnish Nurse Competency Scale. Competency assessment has become popular as a key regulatory requirement and performance indicator. The term competency, however, does not have a globally accepted definition and this has the potential to create controversy, ambiguity and confusion. Variations in meaning and definitions adopted in workplaces and educational settings will affect the interpretation of research findings and have implications for the nursing profession. A non-experimental cross-sectional survey design was used with a convenience sample of 116 new graduate nurses in 2005. The second version of the Australian National Competency Standards and the Nurse Competency Scale was used to elicit responses to self-assessed competency in the transitional year (first year as a Registered Nurse). Correlational analysis of self-assessed levels of competence revealed a relationship between the Australian National Competency Standards (ANCI) and the Nurse Competency Scale (NCS). The correlational relation between ANCI domains and NCS factors suggests that these scales are indeed used to measure related dimensions. A statistically significant relationship (r = 0.75) was found between the two competency measures. Although the finding of convergent validity is insufficient to establish construct validity for competency as used in both measures in this study, it is an important step towards this goal. Future studies on relationships between competencies must take into account the validity and reliability of the tools.

Segment-Specific Adhesion as a Driver of Convergent Extension

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Vroomans, Renske M. A.; Hogeweg, Paulien; ten Tusscher, Kirsten H. W. J.

2015-01-01

Convergent extension, the simultaneous extension and narrowing of tissues, is a crucial event in the formation of the main body axis during embryonic development. It involves processes on multiple scales: the sub-cellular, cellular and tissue level, which interact via explicit or intrinsic feedback mechanisms. Computational modelling studies play an important role in unravelling the multiscale feedbacks underlying convergent extension. Convergent extension usually operates in tissue which has been patterned or is currently being patterned into distinct domains of gene expression. How such tissue patterns are maintained during the large scale tissue movements of convergent extension has thus far not been investigated. Intriguingly, experimental data indicate that in certain cases these tissue patterns may drive convergent extension rather than requiring safeguarding against convergent extension. Here we use a 2D Cellular Potts Model (CPM) of a tissue prepatterned into segments, to show that convergent extension tends to disrupt this pre-existing segmental pattern. However, when cells preferentially adhere to cells of the same segment type, segment integrity is maintained without any reduction in tissue extension. Strikingly, we demonstrate that this segment-specific adhesion is by itself sufficient to drive convergent extension. Convergent extension is enhanced when we endow our in silico cells with persistence of motion, which in vivo would naturally follow from cytoskeletal dynamics. Finally, we extend our model to confirm the generality of our results. We demonstrate a similar effect of differential adhesion on convergent extension in tissues that can only extend in a single direction (as often occurs due to the inertia of the head region of the embryo), and in tissues prepatterned into a sequence of domains resulting in two opposing adhesive gradients, rather than alternating segments. PMID:25706823

Improvement of Requirement Elicitation Process through Cognitive Psychology

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Sana Fatima

2017-06-01

Full Text Available Proper requirement elicitation is necessary for client satisfaction along with the overall project success, but requirement engineers face problems in understanding user requirements and the users of the required system fail to make requirement engineering team understand what they actually want. It is then responsibility of requirement engineers to extract proper requirements. This paper discusses how to use cognitive psychology and learning style models (LSM to understand the psychology of clients. Moreover, it also discusses usage of proper elicitation technique according to one’s learning style and gather the right requirements.

Comparison of fMRI paradigms assessing visuospatial processing: Robustness and reproducibility.

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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

Phase-synchronization-based parcellation of resting state fMRI signals reveals topographically organized clusters in early visual cortex

NARCIS (Netherlands)

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

TRAC-Monterey FY16 Work Program Development and Report of Research Elicitation

Science.gov (United States)

2016-01-01

any changes to priorities or additional projects that require immediate research. Work Program; Research Elicitation Unclassified UU UU UU UU 35 MAJ...conduct analysis for the Army. 1 Marks, Chris, Nesbitt, Peter. TRAC FY14 Research Requirements Elicitation . Technical Report TRAC-M-TM-13-059. 700 Dyer... Requirements Elicitation Interviews Interview Guide: 1. Describe a research requirement in the areas of topics, techniques, and methodologies. 2

Multilingualism and fMRI: Longitudinal Study of Second Language Acquisition

Science.gov (United States)

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

Support vector machine learning-based fMRI data group analysis.

Science.gov (United States)

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.

Multilingualism and fMRI: Longitudinal Study of Second Language Acquisition

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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.

Functional brain segmentation using inter-subject correlation in fMRI.

Science.gov (United States)

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.

Multilingualism and fMRI: Longitudinal Study of Second Language Acquisition.

Science.gov (United States)

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.

Language Convergence Infrastructure

NARCIS (Netherlands)

V. Zaytsev (Vadim); J.M. Fernandes; R. Lämmel (Ralf); J.M.W. Visser (Joost); J. Saraiva

2011-01-01

htmlabstractThe process of grammar convergence involves grammar extraction and transformation for structural equivalence and contains a range of technical challenges. These need to be addressed in order for the method to deliver useful results. The paper describes a DSL and the infrastructure behind

Convergent Filter Bases

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Coghetto Roland

2015-09-01

Full Text Available We are inspired by the work of Henri Cartan [16], Bourbaki [10] (TG. I Filtres and Claude Wagschal [34]. We define the base of filter, image filter, convergent filter bases, limit filter and the filter base of tails (fr: filtre des sections.

Convergence Science in a Nano World

Science.gov (United States)

Cady, Nathaniel

2013-01-01

Convergence is a new paradigm that brings together critical advances in the life sciences, physical sciences and engineering. Going beyond traditional “interdisciplinary” studies, “convergence” describes the culmination of truly integrated research and development, yielding revolutionary advances in both scientific research and new technologies. At its core, nanotechnology embodies these elements of convergence science by bringing together multiple disciplines with the goal of creating innovative and groundbreaking technologies. In the biological and biomedical sciences, nanotechnology research has resulted in dramatic improvements in sensors, diagnostics, imaging, and even therapeutics. In particular, there is a current push to examine the interface between the biological world and micro/nano-scale systems. For example, my laboratory is developing novel strategies for spatial patterning of biomolecules, electrical and optical biosensing, nanomaterial delivery systems, cellular patterning techniques, and the study of cellular interactions with nano-structured surfaces. In this seminar, I will give examples of how convergent research is being applied to three major areas of biological research &endash; cancer diagnostics, microbiology, and DNA-based biosensing. These topics will be presented as case studies, showing the benefits (and challenges) of multi-disciplinary, convergent research and development.

FMRI connectivity analysis of acupuncture effects on an amygdala-associated brain network

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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.

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

Mapping of cognitive functions in chronic intractable epilepsy: Role of fMRI

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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.

Multi-sectorial convergence in greenhouse gas emissions.

Science.gov (United States)

Oliveira, Guilherme de; Bourscheidt, Deise Maria

2017-07-01

This paper uses the World Input-Output Database (WIOD) to test the hypothesis of per capita convergence in greenhouse gas (GHG) emissions for a multi-sectorial panel of countries. The empirical strategy applies conventional estimators of random and fixed effects and Arellano and Bond's (1991) GMM to the main pollutants related to the greenhouse effect. For reasonable empirical specifications, the model revealed robust evidence of per capita convergence in CH 4 emissions in the agriculture, food, and services sectors. The evidence of convergence in CO 2 emissions was moderate in the following sectors: agriculture, food, non-durable goods manufacturing, and services. In all cases, the time for convergence was less than 15 years. Regarding emissions by energy use, the largest source of global warming, there was only moderate evidence in the extractive industry sector-all other pollutants presented little or no evidence. Copyright © 2017 Elsevier Ltd. All rights reserved.

Testing the Conditional Convergence Hypothesis for Pakistan

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Sajjad Ahmad Jan (Corresponding Author

2011-09-01

Full Text Available This study investigates for the existence or non-existence of conditional convergence across the provinces of Pakistan. The annual output data from 1973 to 2000 is pooled for the four Pakistani provinces. The cross-sectional specific effects, the time specific effects, the manufacturing output, and the structural variable for aggregate supply or production shocks are used to control the different steady state levels of per capita incomes of thedifferent provinces. The equation for conditional convergence is estimated through generalized least squares (GLS method, after controlling for the different steady states of the provinces. The result shows that the provinces of Pakistan converge to their own respective steady states with a convergence speed of 11% per annum. At the same time manufacturing output is also statistically significant and positively affects the economic growth in the provinces. However the structural variable is not statistically significant.

Single-trial EEG-informed fMRI analysis of emotional decision problems in hot executive function.

Science.gov (United States)

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.

Report on converging insert moulding with µ-IM

DEFF Research Database (Denmark)

Islam, Aminul

moulding with µ-IM  Task 5.2.1 and COTECH demonstrator: guide line for 5PRC production based on the concept of Task 5.2.1 Information and results provided by this deliverable will be directly used for one of the COTECH demonstrators production which will call for convergent insert moulding with µ......Task 5.2.1 deals with the technical feasibility of converging the state-of-the-art µ IM process with insert moulding to offer a wide range of multi-material µ components. The main objective of this deliverable is to summarize state-of-the-art information and to make the guideline needed...... for the convergence. In particular the following aspects are summed up in the deliverable:  Need for converging insert moulding with µ-IM  Objectives and expected outcome from task 5.2.1  State-of-the-art micro insert moulding and different scenario of micro insert moulding  Challenges ahead of converging insert...

A Study on Diffusion Pattern of Technology Convergence: Patent Analysis for Korea

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Jae Young Choi

2015-08-01

Full Text Available Technology convergence indicates that technologies of different application areas are converted into a new and common unity of technology. Its range spans from inter-field, whereby technologies are converged between heterogeneous fields in homogeneous sector, to a wider inter-sector, whereby technologies belong to heterogeneous technology sector are converged. This paper determined the definition of technology convergence from previous literature and classified patents into technology category depending on patent information. Furthermore, we empirically measure technology convergence degree based on co-classification analysis and estimate its diffusion trend at the entire technology domain level by using overall 1,476,967 of patents filed to the KIPO (Korean Intellectual Property Office from 1998 to 2010. As a result, potential size and growth rate of technology convergence are varied by both technology and type of technology convergence, i.e., inter-field and inter-sector technology convergence. Diffusion pattern of inter-sector technology convergence appears as the more various form than that of inter-field technology convergence. In a relationship between potential size and growth rate of technology convergence, growth rate of technology convergence is in inverse proportion to potential size of technology convergence in general. That is, the faster the growth rate of technology convergence, the smaller the potential size of technology convergence. In addition, this paper found that technology convergence of the instrument and chemistry sector is actively progressing in both inter-field and inter-sector convergence, while the technologies related to Information and Communication Technology (ICT in electrical engineering sector have relatively mature progress of technology convergence, especially in inter-sector technology convergence.

Disparity and convergence: Chinese provincial government health expenditures.

Science.gov (United States)

Pan, Jay; Wang, Peng; Qin, Xuezheng; Zhang, Shufang

2013-01-01

The huge regional disparity in government health expenditures (GHE) is a major policy concern in China. This paper addresses whether provincial GHE converges in China from 1997 to 2009 using the economic convergence framework based on neoclassical economic growth theory. Our empirical investigation provides compelling evidence of long-term convergence in provincial GHE within China, but not in short-term. Policy implications of these empirical results are discussed.

Disparity and convergence: Chinese provincial government health expenditures.

Directory of Open Access Journals (Sweden)

Jay Pan

Full Text Available The huge regional disparity in government health expenditures (GHE is a major policy concern in China. This paper addresses whether provincial GHE converges in China from 1997 to 2009 using the economic convergence framework based on neoclassical economic growth theory. Our empirical investigation provides compelling evidence of long-term convergence in provincial GHE within China, but not in short-term. Policy implications of these empirical results are discussed.

Convergence of Transition Probability Matrix in CLVMarkov Models

Science.gov (United States)

Permana, D.; Pasaribu, U. S.; Indratno, S. W.; Suprayogi, S.

2018-04-01

A transition probability matrix is an arrangement of transition probability from one states to another in a Markov chain model (MCM). One of interesting study on the MCM is its behavior for a long time in the future. The behavior is derived from one property of transition probabilty matrix for n steps. This term is called the convergence of the n-step transition matrix for n move to infinity. Mathematically, the convergence of the transition probability matrix is finding the limit of the transition matrix which is powered by n where n moves to infinity. The convergence form of the transition probability matrix is very interesting as it will bring the matrix to its stationary form. This form is useful for predicting the probability of transitions between states in the future. The method usually used to find the convergence of transition probability matrix is through the process of limiting the distribution. In this paper, the convergence of the transition probability matrix is searched using a simple concept of linear algebra that is by diagonalizing the matrix.This method has a higher level of complexity because it has to perform the process of diagonalization in its matrix. But this way has the advantage of obtaining a common form of power n of the transition probability matrix. This form is useful to see transition matrix before stationary. For example cases are taken from CLV model using MCM called Model of CLV-Markov. There are several models taken by its transition probability matrix to find its convergence form. The result is that the convergence of the matrix of transition probability through diagonalization has similarity with convergence with commonly used distribution of probability limiting method.

Pattern visual evoked potentials elicited by organic electroluminescence screen.

Science.gov (United States)

Matsumoto, Celso Soiti; Shinoda, Kei; Matsumoto, Harue; Funada, Hideaki; Sasaki, Kakeru; Minoda, Haruka; Iwata, Takeshi; Mizota, Atsushi

2014-01-01

To determine whether organic electroluminescence (OLED) screens can be used as visual stimulators to elicit pattern-reversal visual evoked potentials (p-VEPs). Checkerboard patterns were generated on a conventional cathode-ray tube (S710, Compaq Computer Co., USA) screen and on an OLED (17 inches, 320 × 230 mm, PVM-1741, Sony, Tokyo, Japan) screen. The time course of the luminance changes of each monitor was measured with a photodiode. The p-VEPs elicited by these two screens were recorded from 15 eyes of 9 healthy volunteers (22.0 ± 0.8 years). The OLED screen had a constant time delay from the onset of the trigger signal to the start of the luminescence change. The delay during the reversal phase from black to white for the pattern was 1.0 msec on the cathode-ray tube (CRT) screen and 0.5 msec on the OLED screen. No significant differences in the amplitudes of P100 and the implicit times of N75 and P100 were observed in the p-VEPs elicited by the CRT and the OLED screens. The OLED screen can be used as a visual stimulator to elicit p-VEPs; however the time delay and the specific properties in the luminance change must be taken into account.

The convergence of lattice solutions of linearised Regge calculus

International Nuclear Information System (INIS)

Barrett, J.W.; Williams, R.M.

1988-01-01

Sequences of configurations of linearised Regge calculus converging to plane wave solutions are constructed to illustrate an earlier result on convergence. It is shown that, for these examples, the convergence criterion filters out the solutions which do not satisfy Einstein's equations from those which do. (author)

Sensitivity and specificity considerations for fMRI encoding, decoding, and mapping of auditory cortex at ultra-high field.

Science.gov (United States)

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

Fourier convergence analysis applied to neutron diffusion Eigenvalue problem

International Nuclear Information System (INIS)

Lee, Hyun Chul; Noh, Jae Man; Joo, Hyung Kook

2004-01-01

Fourier error analysis has been a standard technique for the stability and convergence analysis of linear and nonlinear iterative methods. Though the methods can be applied to Eigenvalue problems too, all the Fourier convergence analyses have been performed only for fixed source problems and a Fourier convergence analysis for Eigenvalue problem has never been reported. Lee et al proposed new 2-D/1-D coupling methods and they showed that the new ones are unconditionally stable while one of the two existing ones is unstable at a small mesh size and that the new ones are better than the existing ones in terms of the convergence rate. In this paper the convergence of method A in reference 4 for the diffusion Eigenvalue problem was analyzed by the Fourier analysis. The Fourier convergence analysis presented in this paper is the first one applied to a neutronics eigenvalue problem to the best of our knowledge

Convergence of Corporate and Information Security

OpenAIRE

Syed; Rahman, M.; Donahue, Shannon E.

2010-01-01

As physical and information security boundaries have become increasingly blurry many organizations are experiencing challenges with how to effectively and efficiently manage security within the corporate. There is no current standard or best practice offered by the security community regarding convergence; however many organizations such as the Alliance for Enterprise Security Risk Management (AESRM) offer some excellent suggestions for integrating a converged security program. This paper rep...

Convergence Science in a Nano World

OpenAIRE

Cady, Nathaniel

2013-01-01

Convergence is a new paradigm that brings together critical advances in the life sciences, physical sciences and engineering. Going beyond traditional “interdisciplinary” studies, “convergence” describes the culmination of truly integrated research and development, yielding revolutionary advances in both scientific research and new technologies. At its core, nanotechnology embodies these elements of convergence science by bringing together multiple disciplines with the goal of creating innova...

[fMRI study of the dominant hemisphere for language in patients with brain tumor].

Science.gov (United States)

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.

The IASB and FASB Convergence Process: Current Developments

Directory of Open Access Journals (Sweden)

Saher Aqel

2012-04-01

Full Text Available The importance of harmonization of accounting atandards is now widely accepted all over the world. The increased international movement of investments has strongly forces the harmonization of the various national accounting standards in a uniform financial reporting system accepted worldwide. Recently the Securities and Exchange Commission has agreed to remove the requirement international firms reporting under International Financial Reporting Standards (IFRS and listed in the U.S to provide reconciliation to U.S. Generally Accepted Accounting Principles (GAAP. This recent move of the Securities and Exchange Commission indicate that U.S. financial reporting is likely to converge with IFRS in the near future. The International Accounting Standards Board (IASB and the Financial Accounting Standards Board (FASB are currently working together so as to converge their existing accounting standards into a common set of international accounting standards. The objective of this paper is to discuss the FASB and IASB convergence process by addressing current developments regarding significant topics that were deemed critical to this convergence. The convergence of GAAP and IFRS seems inevitable. Mixed opinions have been voiced about this convergence process. Many have begun to consider obstacles that is possible to lay ahead as well as the possible costs and benefits of such a move to the IFRS .

Identifying patients with Alzheimer's disease using resting-state fMRI and graph theory.

Science.gov (United States)

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.

Modelling Convergence of Finite Element Analysis of Cantilever Beam

African Journals Online (AJOL)

Convergence studies are carried out by investigating the convergence of numerical results as the number of elements is increased. If convergence is not obtained, the engineer using the finite element method has absolutely no indication whether the results are indicative of a meaningful approximation to the correct solution ...

An fMRI study of concreteness effects in spoken word recognition.

Science.gov (United States)

Roxbury, Tracy; McMahon, Katie; Copland, David A

2014-09-30

Evidence for the brain mechanisms recruited when processing concrete versus abstract concepts has been largely derived from studies employing visual stimuli. The tasks and baseline contrasts used have also involved varying degrees of lexical processing. This study investigated the neural basis of the concreteness effect during spoken word recognition and employed a lexical decision task with a novel pseudoword condition. The participants were seventeen healthy young adults (9 females). The stimuli consisted of (a) concrete, high imageability nouns, (b) abstract, low imageability nouns and (c) opaque legal pseudowords presented in a pseudorandomised, event-related design. Activation for the concrete, abstract and pseudoword conditions was analysed using anatomical regions of interest derived from previous findings of concrete and abstract word processing. Behaviourally, lexical decision reaction times for the concrete condition were significantly faster than both abstract and pseudoword conditions and the abstract condition was significantly faster than the pseudoword condition (p word recognition. Significant activity was also elicited by concrete words relative to pseudowords in the left fusiform and left anterior middle temporal gyrus. These findings confirm the involvement of a widely distributed network of brain regions that are activated in response to the spoken recognition of concrete but not abstract words. Our findings are consistent with the proposal that distinct brain regions are engaged as convergence zones and enable the binding of supramodal input.

Real Economic Convergence in Western Europe from 1995 to 2013

Directory of Open Access Journals (Sweden)

Dzenita Siljak

2016-05-01

Full Text Available The aim of the paper is to analyze the economic convergence of real per capita GDP in the Western European countries with two types of measurement methodology. The first is sigma convergence, based on the coefficient of variation of real per capita GDP. The second is beta convergence, absolute/unconditional and conditional, including economic and socio-political variables, based on the neoclassical growth theory. The hypothesis of the paper is that there has been real economic convergence in Western Europe in at least one analyzed sub-period. The relationships between selected macroeconomic variables and the rate of economic growth are econometrically tested. Both sigma and beta convergence are estimated for the period 1995-2013 and four sub-periods: 1995-2003, 2004-2013, pre-crisis sub-period 2004-2008 and the crisis sub-period 2009-2013. The empirical findings support the hypothesis of economic convergence, i.e. that the poorer countries tend to grow faster than the rich ones in per capita terms, for some periods. However, the countries had a tendency to diverge, confiriming the negative effects of the crisis on per capita GDP growth. Sigma convergence is consistent with beta convergence. According to the results, the half-life of real convergence may take from 12 to 1078 years. Significant dissimilarities between the growth patterns among individual countries show the considerable heterogeneity of growth, i.e. the convergence clubs.

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.

Monetary policy rules for convergence to the Euro

OpenAIRE

Orlowski, Lucjan T.

2008-01-01

This paper aims to devise a monetary policy instrument rule that is suitable for open economies undergoing monetary convergence to a common currency area. The open-economy convergence-consistent Taylor rule is forward-looking, consistent with monetary framework based on inflation targeting, containing input variables that are relative to the corresponding variables in the common currency area. The policy rule is tested empirically for three inflation targeting countries converging to the euro...

Convergence criteria for systems of nonlinear elliptic partial differential equations

International Nuclear Information System (INIS)

Sharma, R.K.

1986-01-01

This thesis deals with convergence criteria for a special system of nonlinear elliptic partial differential equations. A fixed-point algorithm is used, which iteratively solves one linearized elliptic partial differential equation at a time. Conditions are established that help foresee the convergence of the algorithm. Under reasonable hypotheses it is proved that the algorithm converges for such nonlinear elliptic systems. Extensive experimental results are reported and they show the algorithm converges in a wide variety of cases and the convergence is well correlated with the theoretical conditions introduced in this thesis

Possibilities for global governance of converging technologies

Science.gov (United States)

Roco, Mihail C.

2008-01-01

The convergence of nanotechnology, modern biology, the digital revolution and cognitive sciences will bring about tremendous improvements in transformative tools, generate new products and services, enable opportunities to meet and enhance human potential and social achievements, and in time reshape societal relationships. This paper focuses on the progress made in governance of such converging, emerging technologies and suggests possibilities for a global approach. Specifically, this paper suggests creating a multidisciplinary forum or a consultative coordinating group with members from various countries to address globally governance of converging, emerging technologies. The proposed framework for governance of converging technologies calls for four key functions: supporting the transformative impact of the new technologies; advancing responsible development that includes health, safety and ethical concerns; encouraging national and global partnerships; and establishing commitments to long-term planning and investments centered on human development. Principles of good governance guiding these functions include participation of all those who are forging or affected by the new technologies, transparency of governance strategies, responsibility of each participating stakeholder, and effective strategic planning. Introduction and management of converging technologies must be done with respect for immediate concerns, such as privacy, access to medical advancements, and potential human health effects. At the same time, introduction and management should also be done with respect for longer-term concerns, such as preserving human integrity, dignity and welfare. The suggested governance functions apply to four levels of governance: (a) adapting existing regulations and organizations; (b) establishing new programs, regulations and organizations specifically to handle converging technologies; (c) building capacity for addressing these issues into national policies and

Possibilities for global governance of converging technologies

International Nuclear Information System (INIS)

Roco, Mihail C.

2008-01-01

The convergence of nanotechnology, modern biology, the digital revolution and cognitive sciences will bring about tremendous improvements in transformative tools, generate new products and services, enable opportunities to meet and enhance human potential and social achievements, and in time reshape societal relationships. This paper focuses on the progress made in governance of such converging, emerging technologies and suggests possibilities for a global approach. Specifically, this paper suggests creating a multidisciplinary forum or a consultative coordinating group with members from various countries to address globally governance of converging, emerging technologies. The proposed framework for governance of converging technologies calls for four key functions: supporting the transformative impact of the new technologies; advancing responsible development that includes health, safety and ethical concerns; encouraging national and global partnerships; and establishing commitments to long-term planning and investments centered on human development. Principles of good governance guiding these functions include participation of all those who are forging or affected by the new technologies, transparency of governance strategies, responsibility of each participating stakeholder, and effective strategic planning. Introduction and management of converging technologies must be done with respect for immediate concerns, such as privacy, access to medical advancements, and potential human health effects. At the same time, introduction and management should also be done with respect for longer-term concerns, such as preserving human integrity, dignity and welfare. The suggested governance functions apply to four levels of governance: (a) adapting existing regulations and organizations; (b) establishing new programs, regulations and organizations specifically to handle converging technologies; (c) building capacity for addressing these issues into national policies and

Possibilities for global governance of converging technologies

Energy Technology Data Exchange (ETDEWEB)

Roco, Mihail C. [National Science Foundation (NSF) (United States)], E-mail: mroco@nsf.gov

2008-01-15

The convergence of nanotechnology, modern biology, the digital revolution and cognitive sciences will bring about tremendous improvements in transformative tools, generate new products and services, enable opportunities to meet and enhance human potential and social achievements, and in time reshape societal relationships. This paper focuses on the progress made in governance of such converging, emerging technologies and suggests possibilities for a global approach. Specifically, this paper suggests creating a multidisciplinary forum or a consultative coordinating group with members from various countries to address globally governance of converging, emerging technologies. The proposed framework for governance of converging technologies calls for four key functions: supporting the transformative impact of the new technologies; advancing responsible development that includes health, safety and ethical concerns; encouraging national and global partnerships; and establishing commitments to long-term planning and investments centered on human development. Principles of good governance guiding these functions include participation of all those who are forging or affected by the new technologies, transparency of governance strategies, responsibility of each participating stakeholder, and effective strategic planning. Introduction and management of converging technologies must be done with respect for immediate concerns, such as privacy, access to medical advancements, and potential human health effects. At the same time, introduction and management should also be done with respect for longer-term concerns, such as preserving human integrity, dignity and welfare. The suggested governance functions apply to four levels of governance: (a) adapting existing regulations and organizations; (b) establishing new programs, regulations and organizations specifically to handle converging technologies; (c) building capacity for addressing these issues into national policies and

Statistical convergence of double sequences in intuitionistic fuzzy normed spaces

International Nuclear Information System (INIS)

Mursaleen, M.; Mohiuddine, S.A.

2009-01-01

Recently, the concept of intuitionistic fuzzy normed spaces was introduced by Saadati and Park [Saadati R, Park JH. Chaos, Solitons and Fractals 2006;27:331-44]. Karakus et al. [Karakus S, Demirci K, Duman O. Chaos, Solitons and Fractals 2008;35:763-69] have quite recently studied the notion of statistical convergence for single sequences in intuitionistic fuzzy normed spaces. In this paper, we study the concept of statistically convergent and statistically Cauchy double sequences in intuitionistic fuzzy normed spaces. Furthermore, we construct an example of a double sequence to show that in IFNS statistical convergence does not imply convergence and our method of convergence even for double sequences is stronger than the usual convergence in intuitionistic fuzzy normed space.

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.

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.

Text experiments of disk chopper with supermirror converging system

International Nuclear Information System (INIS)

Aizawa, K.; Soyama, K.; Matsubayashi, M.; Suzuki, J.; Watanabe, N.

2001-01-01

We measured transportation property of neutron pulsed by disk chopper with three kinds of setting of supermirror guide at JRR-3M, JAERI. We confirmed a gain of supermirror converging system to narrow straight supermirror system. The gain is approximately same as the ratio of entrance width of converging guide to width of narrow straight guide. On the other hand, we did not get a gain of supermirror converging system to wide straight supermirror system which has a same width to entrance width of converging guide and we will plan more precisely experiment. (author)

Institutional and Socio-Economic Convergence in the European Union

Directory of Open Access Journals (Sweden)

Jordi López-Tamayo

2014-12-01

Full Text Available The objective of this paper is to analyze convergence in institutional, social, and macroeconomic conditions between EU member states. Our analysis covers the period 1995-2013 and considers the potential impact of the Great Recession. With this aim, we use a composite indicator that combines information from 51 hard and soft indicators, and we estimate convergence equations for the composite indicator and its seven dimensions considering different country groups. The obtained results show evidence of conditional convergence among EU member states but limited evidence of unconditional convergence over the considered period.

Entropy-optimal weight constraint elicitation with additive multi-attribute utility models

NARCIS (Netherlands)

Valkenhoef , van Gert; Tervonen, Tommi

2016-01-01

We consider the elicitation of incomplete preference information for the additive utility model in terms of linear constraints on the weights. Eliciting incomplete preferences using holistic pair-wise judgments is convenient for the decision maker, but selecting the best pair-wise comparison is

Eliciting Subjective Probabilities with Binary Lotteries

DEFF Research Database (Denmark)

Harrison, Glenn W.; Martínez-Correa, Jimmy; Swarthout, J. Todd

objective probabilities. Drawing a sample from the same subject population, we find evidence that the binary lottery procedure induces linear utility in a subjective probability elicitation task using the Quadratic Scoring Rule. We also show that the binary lottery procedure can induce direct revelation...

Memory Deficits in Schizophrenia: A Selective Review of Functional Magnetic Resonance Imaging (fMRI Studies

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.

Sample Size for Measuring Grammaticality in Preschool Children from Picture-Elicited Language Samples

Science.gov (United States)

Eisenberg, Sarita L.; Guo, Ling-Yu

2015-01-01

Purpose: The purpose of this study was to investigate whether a shorter language sample elicited with fewer pictures (i.e., 7) would yield a percent grammatical utterances (PGU) score similar to that computed from a longer language sample elicited with 15 pictures for 3-year-old children. Method: Language samples were elicited by asking forty…

Convergence of the Distorted Wave Born series

International Nuclear Information System (INIS)

MacMillan, D.S.

1981-01-01

The aim of this thesis is to begin to understand the idea of reaction mechanisms in nonrelativistic scattering systems. If we have a complete reaction theory of a particular scattering system, then we claim that the theory itself must contain information about important reaction mechanisms in the system. This information can be used to decide what reaction mechanisms should be included in an approximate calculation. To investigate this claim, we studied several solvable models. The primary concept employed in studying our models is the convergence of the multistep series generated by iterating the corresponding scattering integral equation. We known that the eigenvalues of the kernel of the Lippmann-Schwinger equation for potential scattering determine the rate of convergence of the Born series. The Born series will converge only if these eigenvalues all life within the unit circle. We extend these results to a study of the distorted wave Born series for inelastic scattering. The convergence criterion tells us when approximations are valid. We learn how the convergence of the distorted wave series depends upon energy, coupling constants, angular momentum, and angular momentum transfer. In one of our models, we look at several possible distorting potentials to see which one gives the best convergence. We have also applied our results to several actual DWBA or coupled channel calculations in the literature. In addition to the study of models of two-body scattering systems, we have considered the case of rearrangement scattering. We have discussed the formulation of (N greater than or equal to 3)-body distorted wave equations in which the interior dynamics have been redistributed by introducing compact N-body distortion potentials

Preoperative functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS)

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...

Geometric convergence of some two-point Pade approximations

International Nuclear Information System (INIS)

Nemeth, G.

1983-01-01

The geometric convergences of some two-point Pade approximations are investigated on the real positive axis and on certain infinite sets of the complex plane. Some theorems concerning the geometric convergence of Pade approximations are proved, and bounds on geometric convergence rates are given. The results may be interesting considering the applications both in numerical computations and in approximation theory. As a specific case, the numerical calculations connected with the plasma dispersion function may be performed. (D.Gy.)

Growth Convergence and Spending Efficiency among Filipino Households

OpenAIRE

Erniel B. Barrios

2007-01-01

A growth model is used in the context of Sala-i-Martin’s definition of conditional convergence to assess the household income dynamics in segmented groups at the provincial level in the Philippines. There is a direct relationship between spending efficiency and income growth convergence across income groups. The lower income convergence rate among low income households can be attributed to their relatively less efficient access to the factors of production. The study provides tools in identif...

Collective Correlations of Brodmann Areas fMRI Study with RMT-Denoising

Science.gov (United States)

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.

The power of using functional fMRI on small rodents to study brain pharmacology and disease

OpenAIRE

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...

A step-by-step tutorial on using the cognitive architecture ACT-R in combination with fMRI data

NARCIS (Netherlands)

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

Eliciting Information on Sensitive Matters Without Inviting ...

Indian Academy of Sciences (India)

Eliciting Information on Sensitive Matters. Without Inviting Respondents' ... methods based on Randomized Response tech- niques. ... while collecting data on some sensitive issues are well ..... Suppose there is an association of professionals.

On the convergence of multigroup discrete-ordinates approximations

International Nuclear Information System (INIS)

Victory, H.D. Jr.; Allen, E.J.; Ganguly, K.

1987-01-01

Our analysis is divided into two distinct parts which we label for convenience as Part A and Part B. In Part A, we demonstrate that the multigroup discrete-ordinates approximations are well-defined and converge to the exact transport solution in any subcritical setting. For the most part, we focus on transport in two-dimensional Cartesian geometry. A Nystroem technique is used to extend the discrete ordinates multigroup approximates to all values of the angular and energy variables. Such an extension enables us to employ collectively compact operator theory to deduce stability and convergence of the approximates. In Part B, we perform a thorough convergence analysis for the multigroup discrete-ordinates method for an anisotropically-scattering subcritical medium in slab geometry. The diamond-difference and step-characteristic spatial approximation methods are each studied. The multigroup neutron fluxes are shown to converge in a Banach space setting under realistic smoothness conditions on the solution. This is the first thorough convergence analysis for the fully-discretized multigroup neutron transport equations

Pain-mediated affect regulation is reduced after dialectical behavior therapy in borderline personality disorder: a longitudinal fMRI study.

Science.gov (United States)

Niedtfeld, Inga; Schmitt, Ruth; Winter, Dorina; Bohus, Martin; Schmahl, Christian; Herpertz, Sabine C

2017-05-01

Borderline Personality Disorder (BPD) is characterized by affective instability, but self-injurious behavior appears to have an emotion-regulating effect. We investigated whether pain-mediated affect regulation can be altered at the neural level by residential Dialectical Behavior Therapy (DBT), providing adaptive emotion regulation techniques. Likewise, we investigated whether pain thresholds or the appraisal of pain change after psychotherapy. We investigated 28 patients with BPD undergoing DBT (self-referral), 15 patients with treatment as usual and 23 healthy control subjects at two time points 12 weeks apart. We conducted an fMRI experiment eliciting negative emotions with picture stimuli and induced heat pain to investigate the role of pain in emotion regulation. Additionally, we assessed heat and cold pain thresholds.At first measurement, patients with BPD showed amygdala deactivation in response to painful stimulation, as well as altered connectivity between left amygdala and dorsal anterior cingulate cortex. These effects were reduced after DBT, as compared with patients with treatment as usual. Pain thresholds did not differ between the patient groups. We replicated the role of pain as a means of affect regulation in BPD, indicated by increased amygdala coupling. For the first time, we could demonstrate that pain-mediated affect regulation can be changed by DBT. © The Author (2017). Published by Oxford University Press.

The Convergence Years

Science.gov (United States)

Kolodzy, Janet; Grant, August E.; DeMars, Tony R.; Wilkinson, Jeffrey S.

2014-01-01

The emergence of the Internet, social media, and digital technologies in the twenty-first century accelerated an evolution in journalism and communication that fit under the broad term of convergence. That evolution changed the relationship between news producers and consumers. It broke down the geographical boundaries in defining our communities,…

Autobiographical Memory in Semantic Dementia: A Longitudinal fMRI Study

Science.gov (United States)

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…

Item Memory, Context Memory and the Hippocampus: fMRI Evidence

Science.gov (United States)

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…

Pattern Visual Evoked Potentials Elicited by Organic Electroluminescence Screen

Directory of Open Access Journals (Sweden)

Celso Soiti Matsumoto

2014-01-01

Full Text Available Purpose. To determine whether organic electroluminescence (OLED screens can be used as visual stimulators to elicit pattern-reversal visual evoked potentials (p-VEPs. Method. Checkerboard patterns were generated on a conventional cathode-ray tube (S710, Compaq Computer Co., USA screen and on an OLED (17 inches, 320 × 230 mm, PVM-1741, Sony, Tokyo, Japan screen. The time course of the luminance changes of each monitor was measured with a photodiode. The p-VEPs elicited by these two screens were recorded from 15 eyes of 9 healthy volunteers (22.0 ± 0.8 years. Results. The OLED screen had a constant time delay from the onset of the trigger signal to the start of the luminescence change. The delay during the reversal phase from black to white for the pattern was 1.0 msec on the cathode-ray tube (CRT screen and 0.5 msec on the OLED screen. No significant differences in the amplitudes of P100 and the implicit times of N75 and P100 were observed in the p-VEPs elicited by the CRT and the OLED screens. Conclusion. The OLED screen can be used as a visual stimulator to elicit p-VEPs; however the time delay and the specific properties in the luminance change must be taken into account.

Neural convergence for language comprehension and grammatical class production in highly proficient bilinguals is independent of age of acquisition.

Science.gov (United States)

Consonni, Monica; Cafiero, Riccardo; Marin, Dario; Tettamanti, Marco; Iadanza, Antonella; Fabbro, Franco; Perani, Daniela

2013-05-01

In bilinguals, native (L1) and second (L2) languages are processed by the same neural resources that can be modulated by age of second language acquisition (AOA), proficiency level, and daily language exposure and usage. AOA seems to particularly affect grammar processing, where a complete neural convergence has been shown only in bilinguals with parallel language acquisition from birth. Despite the fact that proficiency-related neuroanatomical differences have been well documented in language comprehension (LC) and production, few reports have addressed the influence of language exposure. A still unanswered question pertains to the role of AOA, when proficiency is comparably high across languages, with respect to its modulator effects both on LC and production. Here, we evaluated with fMRI during sentence comprehension and verb and noun production tasks, two groups of highly proficient bilinguals only differing in AOA. One group learned Italian and Friulian in parallel from birth, whereas the second group learned Italian between 3 and 6 years. All participants were highly exposed to both languages, but more to Italian than Friulian. The results indicate a complete overlap of neural activations for the comprehension of both languages, not only in bilinguals from birth, but also in late bilinguals. A slightly extra activation in the left thalamus for the less-exposed language confirms that exposure may affect language processing. Noteworthy, we report for the first time that, when proficiency and exposure are kept high, noun and verb production recruit the same neural networks for L1 and L2, independently of AOA. These results support the neural convergence hypothesis. Copyright © 2012 Elsevier Ltd. All rights reserved.

Cerebral somatic pain modulation during autogenic training in fMRI.

Science.gov (United States)

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.

A 3 T event-related functional magnetic resonance imaging (fMRI) study of primary and secondary gustatory cortex localization using natural tastants

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.)

A 3 T event-related functional magnetic resonance imaging (fMRI) study of primary and secondary gustatory cortex localization using natural tastants

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.)

Disentangling reward anticipation with simultaneous pupillometry / fMRI.

Science.gov (United States)

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.

Linear Discriminant Analysis achieves high classification accuracy for the BOLD fMRI response to naturalistic movie stimuli.

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

Towards automated composition of convergent services: A survey

OpenAIRE

Ordónez, Armando; Alcazar, Vidal; Rendon, Oscar Mauricio Caicedo; Falcarin, Paolo; Corrales, Juan C.; Granville, Lisandro Zambenedetti

2015-01-01

A convergent service is defined as a service that exploits the convergence of\\ud communication networks and at the same time takes advantage of features of\\ud the Web. Nowadays, building up a convergent service is not trivial, because\\ud although there are significant approaches that aim to automate the service\\ud composition at different levels in the Web and Telecom domains, selecting\\ud the most appropriate approach for specific case studies is complex due to\\ud the big amount of involved ...

Convergence Analysis for the Multiplicative Schwarz Preconditioned Inexact Newton Algorithm

KAUST Repository

Liu, Lulu

2016-10-26

The multiplicative Schwarz preconditioned inexact Newton (MSPIN) algorithm, based on decomposition by field type rather than by subdomain, was recently introduced to improve the convergence of systems with unbalanced nonlinearities. This paper provides a convergence analysis of the MSPIN algorithm. Under reasonable assumptions, it is shown that MSPIN is locally convergent, and desired superlinear or even quadratic convergence can be obtained when the forcing terms are picked suitably.

Convergence Analysis for the Multiplicative Schwarz Preconditioned Inexact Newton Algorithm

KAUST Repository

Liu, Lulu; Keyes, David E.

2016-01-01

The multiplicative Schwarz preconditioned inexact Newton (MSPIN) algorithm, based on decomposition by field type rather than by subdomain, was recently introduced to improve the convergence of systems with unbalanced nonlinearities. This paper provides a convergence analysis of the MSPIN algorithm. Under reasonable assumptions, it is shown that MSPIN is locally convergent, and desired superlinear or even quadratic convergence can be obtained when the forcing terms are picked suitably.

Convergent engineering techniques for management of nuclear processes

International Nuclear Information System (INIS)

Carabulea, A.; Popa, I.

1995-01-01

The paper briefly presents the concept of convergent arhemo-systematical engineering, its advantages in comparison with classical methods of research, design, manufacture. The convergent engineering application supposes the usage of the advanced methods, techniques and equipment corresponding to the domain and specific for the corresponding branch of computer science. Starting from the convergent engineering principles and concept, the paper proposes two models applicable for new products and also for improving and optimizing the existing ones. The models are based on two levels of feedback corresponding to two levels of control and they assume the utilization of expert and robot-expert systems. The economical efficiency of the application of the convergent engineering method is evaluated for the case of a nuclear power plant by calculation the main technical and economical indicators. (Author) 2 Figs., 5 Refs

PABRE-Proj: applying patterns in requirements elicitation

OpenAIRE

Palomares Bonache, Cristina; Quer Bosor, Maria Carme; Franch Gutiérrez, Javier

2013-01-01

Software requirement patterns have been proposed as a type of artifact for fostering requirements reuse. In this paper, we present PABRE-Proj, a tool aimed at supporting requirements elicitation and specification. Peer Reviewed

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.

Test-retest and between-site reliability in a multicenter fMRI study.

Science.gov (United States)

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.

Effect of scanner acoustic background noise on strict resting-state fMRI.

Science.gov (United States)

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.

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.

The Convergent Learning Space

DEFF Research Database (Denmark)

Kjeldsen, Lars Peter; Kjærgaard, Hanne Wacher

networks are still more prominently expected by students. Against this backdrop, an action research project has worked with the definition and testing of the hypothesized constituents of the Convergent Learning Space and how it challenges our traditional conceptions of learning spaces. The article...... describes this pilot study involving teachers in conscious, documented reflection on methods, approaches, and procedures conducive to learning processes in this new learning space. As a perspective, the article briefly outlines an intervention study aimed at investigating how students benefit from......The concept of the Convergent Learning Space has been hypothesized and explored in an ongoing action research project carried out at undergraduate level in select bachelor programs at a Danish University College, where classrooms are technology rich and students bring their own devices. The changes...

Convergent evolution as natural experiment: the tape of life reconsidered.

Science.gov (United States)

Powell, Russell; Mariscal, Carlos

2015-12-06

Stephen Jay Gould argued that replaying the 'tape of life' would result in radically different evolutionary outcomes. Recently, biologists and philosophers of science have paid increasing attention to the theoretical importance of convergent evolution-the independent origination of similar biological forms and functions-which many interpret as evidence against Gould's thesis. In this paper, we examine the evidentiary relevance of convergent evolution for the radical contingency debate. We show that under the right conditions, episodes of convergent evolution can constitute valid natural experiments that support inferences regarding the deep counterfactual stability of macroevolutionary outcomes. However, we argue that proponents of convergence have problematically lumped causally heterogeneous phenomena into a single evidentiary basket, in effect treating all convergent events as if they are of equivalent theoretical import. As a result, the 'critique from convergent evolution' fails to engage with key claims of the radical contingency thesis. To remedy this, we develop ways to break down the heterogeneous set of convergent events based on the nature of the generalizations they support. Adopting this more nuanced approach to convergent evolution allows us to differentiate iterated evolutionary outcomes that are probably common among alternative evolutionary histories and subject to law-like generalizations, from those that do little to undermine and may even support, the Gouldian view of life.

Reliability enhancement of Navier-Stokes codes through convergence acceleration

Science.gov (United States)

Merkle, Charles L.; Dulikravich, George S.

1995-01-01

Methods for enhancing the reliability of Navier-Stokes computer codes through improving convergence characteristics are presented. The improving of these characteristics decreases the likelihood of code unreliability and user interventions in a design environment. The problem referred to as a 'stiffness' in the governing equations for propulsion-related flowfields is investigated, particularly in regard to common sources of equation stiffness that lead to convergence degradation of CFD algorithms. Von Neumann stability theory is employed as a tool to study the convergence difficulties involved. Based on the stability results, improved algorithms are devised to ensure efficient convergence in different situations. A number of test cases are considered to confirm a correlation between stability theory and numerical convergence. The examples of turbulent and reacting flow are presented, and a generalized form of the preconditioning matrix is derived to handle these problems, i.e., the problems involving additional differential equations for describing the transport of turbulent kinetic energy, dissipation rate and chemical species. Algorithms for unsteady computations are considered. The extension of the preconditioning techniques and algorithms derived for Navier-Stokes computations to three-dimensional flow problems is discussed. New methods to accelerate the convergence of iterative schemes for the numerical integration of systems of partial differential equtions are developed, with a special emphasis on the acceleration of convergence on highly clustered grids.

Combining task-evoked and spontaneous activity to improve pre-operative brain mapping with fMRI

Science.gov (United States)

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

Brain Correlates of Aesthetic Expertise: A Parametric fMRI Study

Science.gov (United States)

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…

Eliciting User Requirements Using Appreciative Inquiry

Science.gov (United States)

Gonzales, Carol Kernitzki

2010-01-01

Many software development projects fail because they do not meet the needs of users, are over-budget, and abandoned. To address this problem, the user requirements elicitation process was modified based on principles of Appreciative Inquiry. Appreciative Inquiry, commonly used in organizational development, aims to build organizations, processes,…

Ideal Convergence of k-Positive Linear Operators

Directory of Open Access Journals (Sweden)

Akif Gadjiev

2012-01-01

Full Text Available We study some ideal convergence results of k-positive linear operators defined on an appropriate subspace of the space of all analytic functions on a bounded simply connected domain in the complex plane. We also show that our approximation results with respect to ideal convergence are more general than the classical ones.

A wavelet method for modeling and despiking motion artifacts from resting-state fMRI time series

Science.gov (United States)

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

State-of-the-Art Prescriptive Criteria Weight Elicitation

Directory of Open Access Journals (Sweden)

Mona Riabacke

2012-01-01

Full Text Available Comparatively few of the vast amounts of decision analytical methods suggested have been widely spread in actual practice. Some approaches have nevertheless been more successful in this respect than others. Quantitative decision making has moved from the study of decision theory founded on a single criterion towards decision support for more realistic decision-making situations with multiple, often conflicting, criteria. Furthermore, the identified gap between normative and descriptive theories seems to suggest a shift to more prescriptive approaches. However, when decision analysis applications are used to aid prescriptive decision-making processes, additional demands are put on these applications to adapt to the users and the context. In particular, the issue of weight elicitation is crucial. There are several techniques for deriving criteria weights from preference statements. This is a cognitively demanding task, subject to different biases, and the elicited values can be heavily dependent on the method of assessment. There have been a number of methods suggested for assessing criteria weights, but these methods have properties which impact their applicability in practice. This paper provides a survey of state-of-the-art weight elicitation methods in a prescriptive setting.

Emotional Picture and Word Processing: An fMRI Study on Effects of Stimulus Complexity

Science.gov (United States)

Schlochtermeier, Lorna H.; Kuchinke, Lars; Pehrs, Corinna; Urton, Karolina; Kappelhoff, Hermann; Jacobs, Arthur M.

2013-01-01

Neuroscientific investigations regarding aspects of emotional experiences usually focus on one stimulus modality (e.g., pictorial or verbal). Similarities and differences in the processing between the different modalities have rarely been studied directly. The comparison of verbal and pictorial emotional stimuli often reveals a processing advantage of emotional pictures in terms of larger or more pronounced emotion effects evoked by pictorial stimuli. In this study, we examined whether this picture advantage refers to general processing differences or whether it might partly be attributed to differences in visual complexity between pictures and words. We first developed a new stimulus database comprising valence and arousal ratings for more than 200 concrete objects representable in different modalities including different levels of complexity: words, phrases, pictograms, and photographs. Using fMRI we then studied the neural correlates of the processing of these emotional stimuli in a valence judgment task, in which the stimulus material was controlled for differences in emotional arousal. No superiority for the pictorial stimuli was found in terms of emotional information processing with differences between modalities being revealed mainly in perceptual processing regions. While visual complexity might partly account for previously found differences in emotional stimulus processing, the main existing processing differences are probably due to enhanced processing in modality specific perceptual regions. We would suggest that both pictures and words elicit emotional responses with no general superiority for either stimulus modality, while emotional responses to pictures are modulated by perceptual stimulus features, such as picture complexity. PMID:23409009

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.

PyMVPA: A python toolbox for multivariate pattern analysis of fMRI data.

Science.gov (United States)

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.

Reducing task-based fMRI scanning time using simultaneous multislice echo planar imaging

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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.)

Modality Specific Cerebro-Cerebellar Activations in Verbal Working Memory: An fMRI Study

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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

Conjunction analysis and propositional logic in fMRI data analysis using Bayesian statistics.

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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.

Resting-state fMRI activity predicts unsupervised learning and memory in an immersive virtual reality environment.

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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.

Real time fMRI: a tool for the routine presurgical localisation of the motor cortex

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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.)

Increasing fMRI sampling rate improves Granger causality estimates.

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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.

Convergent close-coupling calculations of electron-hydrogen scattering

International Nuclear Information System (INIS)

Bray, Igor; Stelbovics, A.T.

1992-04-01

The convergence of the close-coupling formalism is studied by expanding the target states in an orthogonal L 2 Laguerre basis. The theory is without approximation and convergence is established by simply increasing the basis size. The convergent elastic, 2s, and 2p differential cross sections, spin asymmetries, and angular correlation parameters for the 2p excitation at 35, 54.4, and 100 eV are calculated. Integrated and total cross sections as well as T-matrix elements for the first five partial waves are also given. 30 refs., 3 tabs., 9 figs

Gene Acquisition Convergence between Entomopoxviruses and Baculoviruses

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Julien Thézé

2015-04-01

Full Text Available Organisms from diverse phylogenetic origins can thrive within the same ecological niches. They might be induced to evolve convergent adaptations in response to a similar landscape of selective pressures. Their genomes should bear the signature of this process. The study of unrelated virus lineages infecting the same host panels guarantees a clear identification of phyletically independent convergent adaptation. Here, we investigate the evolutionary history of genes in the accessory genome shared by unrelated insect large dsDNA viruses: the entomopoxviruses (EPVs, Poxviridae and the baculoviruses (BVs. EPVs and BVs have overlapping ecological niches and have independently evolved similar infection processes. They are, in theory, subjected to the same selective pressures from their host’s immune responses. Their accessory genomes might, therefore, bear analogous genomic signatures of convergent adaption and could point out key genomic mechanisms of adaptation hitherto undetected in viruses. We uncovered 32 homologous, yet independent acquisitions of genes originating from insect hosts, different eukaryotes, bacteria and viruses. We showed different evolutionary levels of gene acquisition convergence in these viruses, underlining a continuous evolutionary process. We found both recent and ancient gene acquisitions possibly involved to the adaptation to both specific and distantly related hosts. Multidirectional and multipartite gene exchange networks appear to constantly drive exogenous gene assimilations, bringing key adaptive innovations and shaping the life histories of large DNA viruses. This evolutionary process might lead to genome level adaptive convergence.

Noise can speed convergence in Markov chains.

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Franzke, Brandon; Kosko, Bart

2011-10-01

A new theorem shows that noise can speed convergence to equilibrium in discrete finite-state Markov chains. The noise applies to the state density and helps the Markov chain explore improbable regions of the state space. The theorem ensures that a stochastic-resonance noise benefit exists for states that obey a vector-norm inequality. Such noise leads to faster convergence because the noise reduces the norm components. A corollary shows that a noise benefit still occurs if the system states obey an alternate norm inequality. This leads to a noise-benefit algorithm that requires knowledge of the steady state. An alternative blind algorithm uses only past state information to achieve a weaker noise benefit. Simulations illustrate the predicted noise benefits in three well-known Markov models. The first model is a two-parameter Ehrenfest diffusion model that shows how noise benefits can occur in the class of birth-death processes. The second model is a Wright-Fisher model of genotype drift in population genetics. The third model is a chemical reaction network of zeolite crystallization. A fourth simulation shows a convergence rate increase of 64% for states that satisfy the theorem and an increase of 53% for states that satisfy the corollary. A final simulation shows that even suboptimal noise can speed convergence if the noise applies over successive time cycles. Noise benefits tend to be sharpest in Markov models that do not converge quickly and that do not have strong absorbing states.

Investigating Inhibitory Control in Children with Epilepsy: An fMRI Study

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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

Effects of penicillin on procaine-elicited bursts of potential in central neuron of snail, Achatina fulica.