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Sample records for brain resting state

  1. Resting state brain activity and functional brain mapping

    Institute of Scientific and Technical Information of China (English)

    Zhao Xiaohu; Wang Peijun; Tang Xiaowei

    2007-01-01

    Functional brain imaging studies commonly use either resting or passive task states as their control conditions, and typically identify the activation brain region associated with a specific task by subtracting the resting from the active task conditions. Numerous studies now suggest, however, that the resting state may not reflect true mental "rest" conditions. The mental activity that occurs during"rest" might therefore greatly influence the functional neuroimaging observations that are collected through the usual subtracting analysis strategies. Exploring the ongoing mental processes that occur during resting conditions is thus of particular importance for deciphering functional brain mapping results and obtaining a more comprehensive understanding of human brain functions. In this review article, we will mainly focus on the discussion of the current research background of functional brain mapping at resting state and the physiological significance of the available neuroimaging data.

  2. Addiction Related Alteration in Resting-state Brain Connectivity

    OpenAIRE

    Ma, Ning; Liu, Ying; Li, Nan; Wang, Chang-Xin; Zhang, Hao; Jiang, Xiao-Feng; Xu, Hu-Sheng; Fu, Xian-ming; Hu, Xiaoping; Zhang, Da-Ren

    2009-01-01

    It is widely accepted that addictive drug use is related to abnormal functional organization in the user’s brain. The present study aimed to identify this type of abnormality within the brain networks implicated in addiction by resting-state functional connectivity measured with functional magnetic resonance imaging (fMRI). With fMRI data acquired during resting state from 14 chronic heroin users (12 of whom were being treated with methadone) and 13 non-addicted controls, we investigated the ...

  3. Hierarchical Functional Modularity in the Resting-State Human Brain

    NARCIS (Netherlands)

    Ferrarini, Luca; Veer, Ilya M.; Baerends, Evelinda; van Tol, Marie-Jose; Renken, Remco J.; van der Wee, Nic J. A.; Veltman, Dirk. J.; Aleman, Andre; Zitman, Frans G.; Penninx, Brenda W. J. H.; van Buchem, Mark A.; Reiber, Johan H. C.; Rombouts, Serge A. R. B.; Milles, Julien

    2009-01-01

    Functional magnetic resonance imaging (fMRI) studies have shown that anatomically distinct brain regions are functionally connected during the resting state. Basic topological properties in the brain functional connectivity (BFC) map have highlighted the BFC's small-world topology. Modularity, a mor

  4. Resting state brain networks and their implications in neurodegenerative disease

    Science.gov (United States)

    Sohn, William S.; Yoo, Kwangsun; Kim, Jinho; Jeong, Yong

    2012-10-01

    Neurons are the basic units of the brain, and form network by connecting via synapses. So far, there have been limited ways to measure the brain networks. Recently, various imaging modalities are widely used for this purpose. In this paper, brain network mapping using resting state fMRI will be introduced with several applications including neurodegenerative disease such as Alzheimer's disease, frontotemporal lobar degeneration and Parkinson's disease. The resting functional connectivity using intrinsic functional connectivity in mouse is useful since we can take advantage of perturbation or stimulation of certain nodes of the network. The study of brain connectivity will open a new era in understanding of brain and diseases thus will be an essential foundation for future research.

  5. Energy landscapes of resting-state brain networks

    Directory of Open Access Journals (Sweden)

    Takamitsu eWatanabe

    2014-02-01

    Full Text Available During rest, the human brain performs essential functions such as memory maintenance, which are associated with resting-state brain networks (RSNs including the default-mode network (DMN and frontoparietal network (FPN. Previous studies based on spiking-neuron network models and their reduced models, as well as those based on imaging data, suggest that resting-state network activity can be captured as attractor dynamics, i.e., dynamics of the brain state toward an attractive state and transitions between different attractors. Here, we analyze the energy landscapes of the RSNs by applying the maximum entropy model, or equivalently the Ising spin model, to human RSN data. We use the previously estimated parameter values to define the energy landscape, and the disconnectivity graph method to estimate the number of local energy minima (equivalent to attractors in attractor dynamics, the basin size, and hierarchical relationships among the different local minima. In both of the DMN and FPN, low-energy local minima tended to have large basins. A majority of the network states belonged to a basin of one of a few local minima. Therefore, a small number of local minima constituted the backbone of each RSN. In the DMN, the energy landscape consisted of two groups of low-energy local minima that are separated by a relatively high energy barrier. Within each group, the activity patterns of the local minima were similar, and different minima were connected by relatively low energy barriers. In the FPN, all dominant energy were separated by relatively low energy barriers such that they formed a single coarse-grained global minimum. Our results indicate that multistable attractor dynamics may underlie the DMN, but not the FPN, and assist memory maintenance with different memory states.

  6. Measuring Asymmetric Interactions in Resting State Brain Networks.

    Science.gov (United States)

    Joshi, Anand A; Salloum, Ronald; Bhushan, Chitresh; Leahy, Richard M

    2015-01-01

    Directed graph representations of brain networks are increasingly being used to indicate the direction and level of influence among brain regions. Most of the existing techniques for directed graph representations are based on time series analysis and the concept of causality, and use time lag information in the brain signals. These time lag-based techniques can be inadequate for functional magnetic resonance imaging (fMRI) signal analysis due to the limited time resolution of fMRI as well as the low frequency hemodynamic response. The aim of this paper is to present a novel measure of necessity that uses asymmetry in the joint distribution of brain activations to infer the direction and level of interaction among brain regions. We present a mathematical formula for computing necessity and extend this measure to partial necessity, which can potentially distinguish between direct and indirect interactions. These measures do not depend on time lag for directed modeling of brain interactions and therefore are more suitable for fMRI signal analysis. The necessity measures were used to analyze resting state fMRI data to determine the presence of hierarchy and asymmetry of brain interactions during resting state. We performed ROI-wise analysis using the proposed necessity measures to study the default mode network. The empirical joint distribution of the fMRI signals was determined using kernel density estimation, and was used for computation of the necessity and partial necessity measures. The significance of these measures was determined using a one-sided Wilcoxon rank-sum test. Our results are consistent with the hypothesis that the posterior cingulate cortex plays a central role in the default mode network. PMID:26221690

  7. DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging.

    Science.gov (United States)

    Yan, Chao-Gan; Wang, Xin-Di; Zuo, Xi-Nian; Zang, Yu-Feng

    2016-07-01

    Brain imaging efforts are being increasingly devoted to decode the functioning of the human brain. Among neuroimaging techniques, resting-state fMRI (R-fMRI) is currently expanding exponentially. Beyond the general neuroimaging analysis packages (e.g., SPM, AFNI and FSL), REST and DPARSF were developed to meet the increasing need of user-friendly toolboxes for R-fMRI data processing. To address recently identified methodological challenges of R-fMRI, we introduce the newly developed toolbox, DPABI, which was evolved from REST and DPARSF. DPABI incorporates recent research advances on head motion control and measurement standardization, thus allowing users to evaluate results using stringent control strategies. DPABI also emphasizes test-retest reliability and quality control of data processing. Furthermore, DPABI provides a user-friendly pipeline analysis toolkit for rat/monkey R-fMRI data analysis to reflect the rapid advances in animal imaging. In addition, DPABI includes preprocessing modules for task-based fMRI, voxel-based morphometry analysis, statistical analysis and results viewing. DPABI is designed to make data analysis require fewer manual operations, be less time-consuming, have a lower skill requirement, a smaller risk of inadvertent mistakes, and be more comparable across studies. We anticipate this open-source toolbox will assist novices and expert users alike and continue to support advancing R-fMRI methodology and its application to clinical translational studies.

  8. Resting State Brain Entropy Alterations in Relapsing Remitting Multiple Sclerosis.

    Science.gov (United States)

    Zhou, Fuqing; Zhuang, Ying; Gong, Honghan; Zhan, Jie; Grossman, Murray; Wang, Ze

    2016-01-01

    Brain entropy (BEN) mapping provides a novel approach to characterize brain temporal dynamics, a key feature of human brain. Using resting state functional magnetic resonance imaging (rsfMRI), reliable and spatially distributed BEN patterns have been identified in normal brain, suggesting a potential use in clinical populations since temporal brain dynamics and entropy may be altered in disease conditions. The purpose of this study was to characterize BEN in multiple sclerosis (MS), a neurodegenerative disease that affects millions of people. Since currently there is no cure for MS, developing treatment or medication that can slow down its progression represents a high research priority, for which validating a brain marker sensitive to disease and the related functional impairments is essential. Because MS can start long time before any measurable symptoms and structural deficits, assessing the dynamic brain activity and correspondingly BEN may provide a critical way to study MS and its progression. Because BEN is new to MS, we aimed to assess BEN alterations in the relapsing-remitting MS (RRMS) patients using a patient versus control design, to examine the correlation of BEN to clinical measurements, and to check the correlation of BEN to structural brain measures which have been more often used in MS studies. As compared to controls, RRMS patients showed increased BEN in motor areas, executive control area, spatial coordinating area, and memory system. Increased BEN was related to greater disease severity as measured by the expanded disability status scale (EDSS) and greater tissue damage as indicated by the mean diffusivity. Patients also showed decreased BEN in other places, which was associated with less disability or fatigue, indicating a disease-related BEN re-distribution. Our results suggest BEN as a novel and useful tool for characterizing RRMS. PMID:26727514

  9. Resting State Brain Entropy Alterations in Relapsing Remitting Multiple Sclerosis.

    Directory of Open Access Journals (Sweden)

    Fuqing Zhou

    Full Text Available Brain entropy (BEN mapping provides a novel approach to characterize brain temporal dynamics, a key feature of human brain. Using resting state functional magnetic resonance imaging (rsfMRI, reliable and spatially distributed BEN patterns have been identified in normal brain, suggesting a potential use in clinical populations since temporal brain dynamics and entropy may be altered in disease conditions. The purpose of this study was to characterize BEN in multiple sclerosis (MS, a neurodegenerative disease that affects millions of people. Since currently there is no cure for MS, developing treatment or medication that can slow down its progression represents a high research priority, for which validating a brain marker sensitive to disease and the related functional impairments is essential. Because MS can start long time before any measurable symptoms and structural deficits, assessing the dynamic brain activity and correspondingly BEN may provide a critical way to study MS and its progression. Because BEN is new to MS, we aimed to assess BEN alterations in the relapsing-remitting MS (RRMS patients using a patient versus control design, to examine the correlation of BEN to clinical measurements, and to check the correlation of BEN to structural brain measures which have been more often used in MS studies. As compared to controls, RRMS patients showed increased BEN in motor areas, executive control area, spatial coordinating area, and memory system. Increased BEN was related to greater disease severity as measured by the expanded disability status scale (EDSS and greater tissue damage as indicated by the mean diffusivity. Patients also showed decreased BEN in other places, which was associated with less disability or fatigue, indicating a disease-related BEN re-distribution. Our results suggest BEN as a novel and useful tool for characterizing RRMS.

  10. Plasticity of resting state brain networks in recovery from stress

    Directory of Open Access Journals (Sweden)

    Jose Miguel Soares

    2013-12-01

    Full Text Available Chronic stress has been widely reported to have deleterious impact in multiple biological systems. Specifically, structural and functional remodelling of several brain regions following prolonged stress exposure have been described; importantly, some of these changes are eventually reversible. Recently, we showed the impact of stress on resting state networks (RSNs, but nothing is known about the plasticity of RSNs after recovery from stress. Herein, we examined the plasticity of RSNs, both at functional and structural levels, by comparing the same individuals before and after recovery from the exposure to chronic stress; results were also contrasted with a control group. Here we show that the stressed individuals after recovery displayed a decreased resting functional connectivity in the default mode network (DMN, ventral attention network (VAN and sensorimotor network (SMN when compared to themselves immediately after stress; however, this functional plastic recovery was only partial as when compared with the control group, as there were still areas of increased connectivity in dorsal attention network (DAN, SMN and primary visual network (VN in participants recovered from stress. Data also shows that participants after recovery from stress displayed increased deactivations in DMN, SMN and auditory network (AN, to levels similar to those of controls, showing a normalization of the deactivation pattern in RSNs after recovery from stress. In contrast, structural changes (volumetry of the brain areas involving these networks are absent after the recovery period. These results reveal plastic phenomena in specific RSNs and a functional remodeling of the activation-deactivation pattern following recovery from chronic-stress, which is not accompanied by significant structural plasticity.

  11. Frequency dependent topological patterns of resting-state brain networks.

    Directory of Open Access Journals (Sweden)

    Long Qian

    Full Text Available The topological organization underlying brain networks has been extensively investigated using resting-state fMRI, focusing on the low frequency band from 0.01 to 0.1 Hz. However, the frequency specificities regarding the corresponding brain networks remain largely unclear. In the current study, a data-driven method named complementary ensemble empirical mode decomposition (CEEMD was introduced to separate the time series of each voxel into several intrinsic oscillation rhythms with distinct frequency bands. Our data indicated that the whole brain BOLD signals could be automatically divided into five specific frequency bands. After applying the CEEMD method, the topological patterns of these five temporally correlated networks were analyzed. The results showed that global topological properties, including the network weighted degree, network efficiency, mean characteristic path length and clustering coefficient, were observed to be most prominent in the ultra-low frequency bands from 0 to 0.015 Hz. Moreover, the saliency of small-world architecture demonstrated frequency-density dependency. Compared to the empirical mode decomposition method (EMD, CEEMD could effectively eliminate the mode-mixing effects. Additionally, the robustness of CEEMD was validated by the similar results derived from a split-half analysis and a conventional frequency division method using the rectangular window band-pass filter. Our findings suggest that CEEMD is a more effective method for extracting the intrinsic oscillation rhythms embedded in the BOLD signals than EMD. The application of CEEMD in fMRI data analysis will provide in-depth insight in investigations of frequency specific topological patterns of the dynamic brain networks.

  12. The influence of low-grade glioma on resting state oscillatory brain activity: a magnetoencephalography study

    NARCIS (Netherlands)

    Bosma, I.; Stam, C.; Douw, L.; Bartolomei, F.; Heimans, J.; Dijk, van B.; Postma, T.; Klein, M.; Reijneveld, J.

    2008-01-01

    Purpose: In the present MEG-study, power spectral analysis of oscillatory brain activity was used to compare resting state brain activity in both low-grade glioma (LGG) patients and healthy controls. We hypothesized that LGG patients show local as well as diffuse slowing of resting state brain activ

  13. The influence of low-grade glioma on resting state oscillatory brain activity : a magnetoencephalography study

    NARCIS (Netherlands)

    Bosma, I; Stam, C J; Douw, L; Bartolomei, F; Heimans, J J; van Dijk, B W; Postma, T J; Klein, M; Reijneveld, J C

    2008-01-01

    PURPOSE: In the present MEG-study, power spectral analysis of oscillatory brain activity was used to compare resting state brain activity in both low-grade glioma (LGG) patients and healthy controls. We hypothesized that LGG patients show local as well as diffuse slowing of resting state brain activ

  14. Progress in clinical research and application of resting state functional brain imaging

    International Nuclear Information System (INIS)

    Resting state functional brain imaging experimental design is free of stimulus task and offers various parametric maps through different data-driven post processing methods with endogenous BOLD signal changes as the source of imaging. Mechanism of resting state brain activities could be extensively studied with improved patient compliance and clinical application compared with task related functional brain imaging. Also resting state functional brain imaging can be used as a method of data acquisition, with implicit neuronal activity as a kind of experimental design, to reveal characteristic brain activities of epileptic patient. Even resting state functional brain imaging data processing method can be used to analyze task related functional MRI data, opening new horizons of task related functional MRI study. (authors)

  15. Resting State Brain Connectivity After Surgical and Behavioral Weight Loss

    Science.gov (United States)

    Lepping, Rebecca J.; Bruce, Amanda S.; Francisco, Alex; Yeh, Hung-Wen; Martin, Laura E.; Powell, Joshua N.; Hancock, Laura; Patrician, Trisha M.; Breslin, Florence J.; Selim, Niazy; Donnelly, Joseph E.; Brooks, William M.; Savage, Cary R.; Simmons, W. Kyle; Bruce, Jared M.

    2015-01-01

    OBJECTIVE We previously reported changes in food-cue neural reactivity associated with behavioral and surgical weight loss interventions. Resting functional connectivity represents tonic neural activity that may contribute to weight loss success. Here we explore whether intervention type is associated with differences in functional connectivity after weight loss. METHODS Fifteen obese participants were recruited prior to adjustable gastric banding surgery. Thirteen demographically matched obese participants were selected from a separate behavioral diet intervention. Resting state fMRI was collected three months after surgery/behavioral intervention. ANOVA was used to examine post-weight loss differences between the two groups in connectivity to seed regions previously identified as showing differential cue-reactivity after weight loss. RESULTS Following weight loss, behavioral dieters exhibited increased connectivity between left precuneus/superior parietal lobule (SPL) and bilateral insula pre- to post-meal and bariatric patients exhibited decreased connectivity between these regions pre- to post-meal (pcorrected<.05). CONCLUSIONS Behavioral dieters showed increased connectivity pre- to post-meal between a region associated with processing of self-referent information (precuneus/SPL) and a region associated with interoception (insula) whereas bariatric patients showed decreased connectivity between these regions. This may reflect increased attention to hunger signals following surgical procedures, and increased attention to satiety signals following behavioral diet interventions. PMID:26053145

  16. Stability of whole brain and regional network topology within and between resting and cognitive states.

    Directory of Open Access Journals (Sweden)

    Justyna K Rzucidlo

    Full Text Available BACKGROUND: Graph-theory based analyses of resting state functional Magnetic Resonance Imaging (fMRI data have been used to map the network organization of the brain. While numerous analyses of resting state brain organization exist, many questions remain unexplored. The present study examines the stability of findings based on this approach over repeated resting state and working memory state sessions within the same individuals. This allows assessment of stability of network topology within the same state for both rest and working memory, and between rest and working memory as well. METHODOLOGY/PRINCIPAL FINDINGS: fMRI scans were performed on five participants while at rest and while performing the 2-back working memory task five times each, with task state alternating while they were in the scanner. Voxel-based whole brain network analyses were performed on the resulting data along with analyses of functional connectivity in regions associated with resting state and working memory. Network topology was fairly stable across repeated sessions of the same task, but varied significantly between rest and working memory. In the whole brain analysis, local efficiency, Eloc, differed significantly between rest and working memory. Analyses of network statistics for the precuneus and dorsolateral prefrontal cortex revealed significant differences in degree as a function of task state for both regions and in local efficiency for the precuneus. Conversely, no significant differences were observed across repeated sessions of the same state. CONCLUSIONS/SIGNIFICANCE: These findings suggest that network topology is fairly stable within individuals across time for the same state, but also fluid between states. Whole brain voxel-based network analyses may prove to be a valuable tool for exploring how functional connectivity changes in response to task demands.

  17. Resting state brain dynamics and its transients: a combined TMS-EEG study.

    Science.gov (United States)

    Bonnard, Mireille; Chen, Sophie; Gaychet, Jérôme; Carrere, Marcel; Woodman, Marmaduke; Giusiano, Bernard; Jirsa, Viktor

    2016-01-01

    The brain at rest exhibits a spatio-temporally rich dynamics which adheres to systematic behaviours that persist in task paradigms but appear altered in disease. Despite this hypothesis, many rest state paradigms do not act directly upon the rest state and therefore cannot confirm hypotheses about its mechanisms. To address this challenge, we combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG) to study brain's relaxation toward rest following a transient perturbation. Specifically, TMS targeted either the medial prefrontal cortex (MPFC), i.e. part of the Default Mode Network (DMN) or the superior parietal lobule (SPL), involved in the Dorsal Attention Network. TMS was triggered by a given brain state, namely an increase in occipital alpha rhythm power. Following the initial TMS-Evoked Potential, TMS at MPFC enhances the induced occipital alpha rhythm, called Event Related Synchronisation, with a longer transient lifetime than TMS at SPL, and a higher amplitude. Our findings show a strong coupling between MPFC and the occipital alpha power. Although the rest state is organized around a core of resting state networks, the DMN functionally takes a special role among these resting state networks. PMID:27488504

  18. Resting state brain dynamics and its transients: a combined TMS-EEG study.

    Science.gov (United States)

    Bonnard, Mireille; Chen, Sophie; Gaychet, Jérôme; Carrere, Marcel; Woodman, Marmaduke; Giusiano, Bernard; Jirsa, Viktor

    2016-08-04

    The brain at rest exhibits a spatio-temporally rich dynamics which adheres to systematic behaviours that persist in task paradigms but appear altered in disease. Despite this hypothesis, many rest state paradigms do not act directly upon the rest state and therefore cannot confirm hypotheses about its mechanisms. To address this challenge, we combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG) to study brain's relaxation toward rest following a transient perturbation. Specifically, TMS targeted either the medial prefrontal cortex (MPFC), i.e. part of the Default Mode Network (DMN) or the superior parietal lobule (SPL), involved in the Dorsal Attention Network. TMS was triggered by a given brain state, namely an increase in occipital alpha rhythm power. Following the initial TMS-Evoked Potential, TMS at MPFC enhances the induced occipital alpha rhythm, called Event Related Synchronisation, with a longer transient lifetime than TMS at SPL, and a higher amplitude. Our findings show a strong coupling between MPFC and the occipital alpha power. Although the rest state is organized around a core of resting state networks, the DMN functionally takes a special role among these resting state networks.

  19. The Effect of Aging on Resting-State Brain Function: An fMRI Study

    Directory of Open Access Journals (Sweden)

    A. H. Batouli

    2009-11-01

    Full Text Available Background/Objective: Healthy aging may be accompanied by some types of cognitive impairment; moreover, normal aging may cause natural atrophy in the healthy human brain. The hypothesis of the healthy aging brain is the structural changes together with the functional impairment happening. The brain struggles to over-compensate for those functional age-related impairments to continue as a healthy brain in its functions. Our goal in this study was to evaluate the effects of aging on the resting-state activation network of the brain using the multi-session probabilistic independent component analysis algorithm (PICA. "nPatients and Methods: We compared the resting-state brain activities between two groups of healthy aged and young subjects, so we examined 30 right-handed subjects and finally 12 healthy aging and 11 controls were enrolled in the study. "nResults: Our results showed that during the resting-state, older brains benefit from larger areas of activation, while in young competent brains, higher activation occurs in terms of greater intensity. These results were obtained in prefrontal areas as regions with regard to memory function as well as the posterior cingulate cortex (PCC as parts of the default mode network. Meanwhile, we reached the same results after normalization of activation size with total brain volume. "nConclusion: The difference in activation patterns between the two groups shows the brain's endeavor to compensate the functional impairment.

  20. Is functional integration of resting state brain networks an unspecific biomarker for working memory performance?

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    Alavash, Mohsen; Doebler, Philipp; Holling, Heinz; Thiel, Christiane M; Gießing, Carsten

    2015-03-01

    Is there one optimal topology of functional brain networks at rest from which our cognitive performance would profit? Previous studies suggest that functional integration of resting state brain networks is an important biomarker for cognitive performance. However, it is still unknown whether higher network integration is an unspecific predictor for good cognitive performance or, alternatively, whether specific network organization during rest predicts only specific cognitive abilities. Here, we investigated the relationship between network integration at rest and cognitive performance using two tasks that measured different aspects of working memory; one task assessed visual-spatial and the other numerical working memory. Network clustering, modularity and efficiency were computed to capture network integration on different levels of network organization, and to statistically compare their correlations with the performance in each working memory test. The results revealed that each working memory aspect profits from a different resting state topology, and the tests showed significantly different correlations with each of the measures of network integration. While higher global network integration and modularity predicted significantly better performance in visual-spatial working memory, both measures showed no significant correlation with numerical working memory performance. In contrast, numerical working memory was superior in subjects with highly clustered brain networks, predominantly in the intraparietal sulcus, a core brain region of the working memory network. Our findings suggest that a specific balance between local and global functional integration of resting state brain networks facilitates special aspects of cognitive performance. In the context of working memory, while visual-spatial performance is facilitated by globally integrated functional resting state brain networks, numerical working memory profits from increased capacities for local processing

  1. Resting state brain dynamics and its transients: a combined TMS-EEG study

    Science.gov (United States)

    Bonnard, Mireille; Chen, Sophie; Gaychet, Jérôme; Carrere, Marcel; Woodman, Marmaduke; Giusiano, Bernard; Jirsa, Viktor

    2016-01-01

    The brain at rest exhibits a spatio-temporally rich dynamics which adheres to systematic behaviours that persist in task paradigms but appear altered in disease. Despite this hypothesis, many rest state paradigms do not act directly upon the rest state and therefore cannot confirm hypotheses about its mechanisms. To address this challenge, we combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG) to study brain’s relaxation toward rest following a transient perturbation. Specifically, TMS targeted either the medial prefrontal cortex (MPFC), i.e. part of the Default Mode Network (DMN) or the superior parietal lobule (SPL), involved in the Dorsal Attention Network. TMS was triggered by a given brain state, namely an increase in occipital alpha rhythm power. Following the initial TMS-Evoked Potential, TMS at MPFC enhances the induced occipital alpha rhythm, called Event Related Synchronisation, with a longer transient lifetime than TMS at SPL, and a higher amplitude. Our findings show a strong coupling between MPFC and the occipital alpha power. Although the rest state is organized around a core of resting state networks, the DMN functionally takes a special role among these resting state networks. PMID:27488504

  2. Resting-state fMRI: A window into human brain plasticity

    OpenAIRE

    Guerra-Carrillo, B; Mackey, AP; Bunge, SA

    2014-01-01

    © The Author(s) 2014. Although brain plasticity is greatest in the first few years of life, the brain continues to be shaped by experience throughout adulthood. Advances in fMRI have enabled us to examine the plasticity of large-scale networks using blood oxygen level-dependent (BOLD) correlations measured at rest. Resting-state functional connectivity analysis makes it possible to measure task-independent changes in brain function and therefore could provide unique insights into experience-d...

  3. An abnormal resting-state functional brain network indicates progression towards Alzheimer’s disease*****

    Institute of Scientific and Technical Information of China (English)

    Jie Xiang; Hao Guo; Rui Cao; Hong Liang; Junjie Chen

    2013-01-01

    Brain structure and cognitive function change in the temporal lobe, hippocampus, and prefrontal cortex of patients with mild cognitive impairment and Alzheimer’s disease, and brain network-connection strength, network efficiency, and nodal attributes are abnormal. However, existing research has only analyzed the differences between these patients and normal controls. In this study, we constructed brain networks using resting-state functional MRI data that was extracted from four populations mal controls, patients with early mild cognitive impairment, patients with late mild cognitive impairment, and patients with Alzheimer’s disease) using the Alzheimer’s Disease Neuroimaging Initiative data set. The aim was to analyze the characteristics of resting-state functional neural networks, and to observe mild cognitive impairment at different stages before the transformation to Alzheimer’s disease. Results showed that as cognitive deficits increased across the four groups, the shortest path in the rest-ing-state functional network gradual y increased, while clustering coefficients gradual y decreased. This evidence indicates that dementia is associated with a decline of brain network efficiency. In tion, the changes in functional networks revealed the progressive deterioration of network function across brain regions from healthy elderly adults to those with mild cognitive impairment and Alzhei-mer’s disease. The alterations of node attributes in brain regions may reflect the cognitive functions in brain regions, and we speculate that early impairments in memory, hearing, and language function can eventual y lead to diffuse brain injury and other cognitive impairments.

  4. [Functional connectivity analysis of the brain network using resting-state FMRI].

    Science.gov (United States)

    Hayashi, Toshihiro

    2011-12-01

    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. PMID:22147450

  5. Functional connectivity analysis of the brain network using resting-state fMRI

    International Nuclear Information System (INIS)

    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)

  6. Disrutpted resting-state functional architecture of the brain after 45-day simulated microgravity

    Directory of Open Access Journals (Sweden)

    Yuan eZhou

    2014-06-01

    Full Text Available Long-term spaceflight induces both physiological and psychological changes in astronauts. To understand the neural mechanisms underlying these physiological and psychological changes, it is critical to investigate the effects of microgravity on the functional architecture of the brain. In this study, we used resting-state functional MRI (rs-fMRI to study whether the functional architecture of the brain is altered after 45 days of -6° head-down tilt (HDT bed rest, which is a reliable model for the simulation of microgravity. Sixteen healthy male volunteers underwent rs-fMRI scans before and after 45 days of -6° HDT bed rest. Specifically, we used a commonly employed graph-based measure of network organization, i.e., degree centrality (DC, to perform a full-brain exploration of the regions that were influenced by simulated microgravity. We subsequently examined the functional connectivities of these regions using a seed-based resting-state functional connectivity (RSFC analysis. We found decreased DC in two regions, the left anterior insula (aINS and the anterior part of the middle cingulate cortex (MCC; also called the dorsal anterior cingulate cortex in many studies, in the male volunteers after 45 days of -6° HDT bed rest. Furthermore, seed-based RSFC analyses revealed that a functional network anchored in the aINS and MCC was particularly influenced by simulated microgravity. These results provide evidence that simulated microgravity alters the resting-state functional architecture of the brains of males and suggest that the processing of salience information, which is primarily subserved by the aINS–MCC functional network, is particularly influenced by spaceflight. The current findings provide a new perspective for understanding the relationships between microgravity, cognitive function, autonomic neural function and central neural activity.

  7. Probing Intrinsic Resting-State Networks in the Infant Rat Brain

    Science.gov (United States)

    Bajic, Dusica; Craig, Michael M.; Borsook, David; Becerra, Lino

    2016-01-01

    Resting-state functional magnetic resonance imaging (rs-fMRI) measures spontaneous fluctuations in blood oxygenation level-dependent (BOLD) signal in the absence of external stimuli. It has become a powerful tool for mapping large-scale brain networks in humans and animal models. Several rs-fMRI studies have been conducted in anesthetized and awake adult rats, reporting consistent patterns of brain activity at the systems level. However, the evolution to adult patterns of resting-state activity has not yet been evaluated and quantified in the developing rat brain. In this study, we hypothesized that large-scale intrinsic networks would be easily detectable but not fully established as specific patterns of activity in lightly anesthetized 2-week-old rats (N = 11). Independent component analysis (ICA) identified 8 networks in 2-week-old-rats. These included Default mode, Sensory (Exteroceptive), Salience (Interoceptive), Basal Ganglia-Thalamic-Hippocampal, Basal Ganglia, Autonomic, Cerebellar, as well as Thalamic-Brainstem networks. Many of these networks consisted of more than one component, possibly indicative of immature, underdeveloped networks at this early time point. Except for the Autonomic network, infant rat networks showed reduced connectivity with subcortical structures in comparison to previously published adult networks. Reported slow fluctuations in the BOLD signal that correspond to functionally relevant resting-state networks in 2-week-old rats can serve as an important tool for future studies of brain development in the settings of different pharmacological applications or disease. PMID:27803653

  8. Test-retest reliability of graph metrics of resting state MRI functional brain networks: A review.

    Science.gov (United States)

    Andellini, Martina; Cannatà, Vittorio; Gazzellini, Simone; Bernardi, Bruno; Napolitano, Antonio

    2015-09-30

    The employment of graph theory to analyze spontaneous fluctuations in resting state BOLD fMRI data has become a dominant theme in brain imaging studies and neuroscience. Analysis of resting state functional brain networks based on graph theory has proven to be a powerful tool to quantitatively characterize functional architecture of the brain and it has provided a new platform to explore the overall structure of local and global functional connectivity in the brain. Due to its increased use and possible expansion to clinical use, it is essential that the reliability of such a technique is very strongly assessed. In this review, we explore the outcome of recent studies in network reliability which apply graph theory to analyze connectome resting state networks. Therefore, we investigate which preprocessing steps may affect reproducibility the most. In order to investigate network reliability, we compared the test-retest (TRT) reliability of functional data of published neuroimaging studies with different preprocessing steps. In particular we tested influence of global signal regression, correlation metric choice, binary versus weighted link definition, frequency band selection and length of time-series. Statistical analysis shows that only frequency band selection and length of time-series seem to affect TRT reliability. Our results highlight the importance of the choice of the preprocessing steps to achieve more reproducible measurements. PMID:26072249

  9. Resting-State and Task-Based Functional Brain Connectivity in Developmental Dyslexia.

    Science.gov (United States)

    Schurz, Matthias; Wimmer, Heinz; Richlan, Fabio; Ludersdorfer, Philipp; Klackl, Johannes; Kronbichler, Martin

    2015-10-01

    Reading requires the interaction between multiple cognitive processes situated in distant brain areas. This makes the study of functional brain connectivity highly relevant for understanding developmental dyslexia. We used seed-voxel correlation mapping to analyse connectivity in a left-hemispheric network for task-based and resting-state fMRI data. Our main finding was reduced connectivity in dyslexic readers between left posterior temporal areas (fusiform, inferior temporal, middle temporal, superior temporal) and the left inferior frontal gyrus. Reduced connectivity in these networks was consistently present for 2 reading-related tasks and for the resting state, showing a permanent disruption which is also present in the absence of explicit task demands and potential group differences in performance. Furthermore, we found that connectivity between multiple reading-related areas and areas of the default mode network, in particular the precuneus, was stronger in dyslexic compared with nonimpaired readers.

  10. Mapping Thalamocortical Networks in Rat Brain using Resting-State Functional Connectivity

    OpenAIRE

    Liang, Zhifeng; Li, Tao; King, Jean; Zhang, Nanyin

    2013-01-01

    Thalamocortical connectivity plays a vital role in brain function. The anatomy and function of thalamocortical networks have been extensively studied in animals by numerous invasive techniques. Non-invasively mapping thalamocortical networks in humans has also been demonstrated by utilizing resting-state functional magnetic resonance imaging (rsfMRI). However, success in simultaneously imaging multiple thalamocortical networks in animals is rather limited. This is largely due to the profound ...

  11. Brain activation and inhibition after acupuncture at Taichong and Taixi: resting-state functional magnetic resonance imaging

    OpenAIRE

    Shao-qun Zhang; Yan-jie Wang; Ji-ping Zhang; Jun-qi Chen; Chun-xiao Wu; Zhi-peng Li; Jia-rong Chen; Huai-liang Ouyang; Yong Huang; Chun-zhi Tang

    2015-01-01

    Acupuncture can induce changes in the brain. However, the majority of studies to date have focused on a single acupoint at a time. In the present study, we observed activity changes in the brains of healthy volunteers before and after acupuncture at Taichong (LR3) and Taixi (KI3) using resting-state functional magnetic resonance imaging. Fifteen healthy volunteers underwent resting-state functional magnetic resonance imaging of the brain 15 minutes before acupuncture, then received acupunctur...

  12. EEG Resting-State Brain Topological Reorganization as a Function of Age

    Directory of Open Access Journals (Sweden)

    Manuela Petti

    2016-01-01

    Full Text Available Resting state connectivity has been increasingly studied to investigate the effects of aging on the brain. A reduced organization in the communication between brain areas was demonstrated by combining a variety of different imaging technologies (fMRI, EEG, and MEG and graph theory. In this paper, we propose a methodology to get new insights into resting state connectivity and its variations with age, by combining advanced techniques of effective connectivity estimation, graph theoretical approach, and classification by SVM method. We analyzed high density EEG signals recorded at rest from 71 healthy subjects (age: 20–63 years. Weighted and directed connectivity was computed by means of Partial Directed Coherence based on a General Linear Kalman filter approach. To keep the information collected by the estimator, weighted and directed graph indices were extracted from the resulting networks. A relation between brain network properties and age of the subject was found, indicating a tendency of the network to randomly organize increasing with age. This result is also confirmed dividing the whole population into two subgroups according to the age (young and middle-aged adults: significant differences exist in terms of network organization measures. Classification of the subjects by means of such indices returns an accuracy greater than 80%.

  13. Testing a dual-systems model of adolescent brain development using resting-state connectivity analyses.

    Science.gov (United States)

    van Duijvenvoorde, A C K; Achterberg, M; Braams, B R; Peters, S; Crone, E A

    2016-01-01

    The current study aimed to test a dual-systems model of adolescent brain development by studying changes in intrinsic functional connectivity within and across networks typically associated with cognitive-control and affective-motivational processes. To this end, resting-state and task-related fMRI data were collected of 269 participants (ages 8-25). Resting-state analyses focused on seeds derived from task-related neural activation in the same participants: the dorsal lateral prefrontal cortex (dlPFC) from a cognitive rule-learning paradigm and the nucleus accumbens (NAcc) from a reward-paradigm. Whole-brain seed-based resting-state analyses showed an age-related increase in dlPFC connectivity with the caudate and thalamus, and an age-related decrease in connectivity with the (pre)motor cortex. nAcc connectivity showed a strengthening of connectivity with the dorsal anterior cingulate cortex (ACC) and subcortical structures such as the hippocampus, and a specific age-related decrease in connectivity with the ventral medial PFC (vmPFC). Behavioral measures from both functional paradigms correlated with resting-state connectivity strength with their respective seed. That is, age-related change in learning performance was mediated by connectivity between the dlPFC and thalamus, and age-related change in winning pleasure was mediated by connectivity between the nAcc and vmPFC. These patterns indicate (i) strengthening of connectivity between regions that support control and learning, (ii) more independent functioning of regions that support motor and control networks, and (iii) more independent functioning of regions that support motivation and valuation networks with age. These results are interpreted vis-à-vis a dual-systems model of adolescent brain development. PMID:25969399

  14. Testing a dual-systems model of adolescent brain development using resting-state connectivity analyses.

    Science.gov (United States)

    van Duijvenvoorde, A C K; Achterberg, M; Braams, B R; Peters, S; Crone, E A

    2016-01-01

    The current study aimed to test a dual-systems model of adolescent brain development by studying changes in intrinsic functional connectivity within and across networks typically associated with cognitive-control and affective-motivational processes. To this end, resting-state and task-related fMRI data were collected of 269 participants (ages 8-25). Resting-state analyses focused on seeds derived from task-related neural activation in the same participants: the dorsal lateral prefrontal cortex (dlPFC) from a cognitive rule-learning paradigm and the nucleus accumbens (NAcc) from a reward-paradigm. Whole-brain seed-based resting-state analyses showed an age-related increase in dlPFC connectivity with the caudate and thalamus, and an age-related decrease in connectivity with the (pre)motor cortex. nAcc connectivity showed a strengthening of connectivity with the dorsal anterior cingulate cortex (ACC) and subcortical structures such as the hippocampus, and a specific age-related decrease in connectivity with the ventral medial PFC (vmPFC). Behavioral measures from both functional paradigms correlated with resting-state connectivity strength with their respective seed. That is, age-related change in learning performance was mediated by connectivity between the dlPFC and thalamus, and age-related change in winning pleasure was mediated by connectivity between the nAcc and vmPFC. These patterns indicate (i) strengthening of connectivity between regions that support control and learning, (ii) more independent functioning of regions that support motor and control networks, and (iii) more independent functioning of regions that support motivation and valuation networks with age. These results are interpreted vis-à-vis a dual-systems model of adolescent brain development.

  15. Brain regions involved in dispositional mindfulness during resting state and their relation with well-being.

    Science.gov (United States)

    Kong, Feng; Wang, Xu; Song, Yiying; Liu, Jia

    2016-08-01

    Mindfulness can be viewed as an important dispositional characteristic that reflects the tendency to be mindful in daily life, which is beneficial for improving individuals' both hedonic and eudaimonic well-being. However, no study to date has examined the brain regions involved in individual differences in dispositional mindfulness during the resting state and its relation with hedonic and eudaimonic well-being. To investigate this issue, the present study employed resting-state functional magnetic resonance imaging (rs-fMRI) to evaluate the regional homogeneity (ReHo) that measures the local synchronization of spontaneous brain activity in a large sample. We found that dispositional mindfulness was positively associated with the ReHo in the left orbitofrontal cortex (OFC), left parahippocampal gyrus (PHG), and right insula implicated in emotion processing, body awareness, and self-referential processing, and negatively associated with the ReHo in right inferior frontal gyrus (IFG) implicated in response inhibition and attentional control. Furthermore, we found different neural associations with hedonic (i.e., positive and negative affect) and eudaimonic well-being (i.e., the meaningful and purposeful life). Specifically, the ReHo in the IFG predicted eudaimonic well-being whereas the OFC predicted positive affect, both of which were mediated by dispositional mindfulness. Taken together, our study provides the first evidence for linking individual differences in dispositional mindfulness to spontaneous brain activity and demonstrates that dispositional mindfulness engages multiple brain mechanisms that differentially influence hedonic and eudaimonic well-being. PMID:26360907

  16. Resting-state, functional MRI on regional homogeneity changes of brain in the heavy smokers

    International Nuclear Information System (INIS)

    Objective: To explore the mechanism of self-awareness in the heavy smokers (HS) by using regional homogeneity (ReHo) combined with resting-state functional MRI (fMRI). Methods: Thirty HS and 31 healthy non-smokers (NS) matched for age and sex underwent a 3.0 T resting-state fMRI. The data were post-processed by SPM 5 and then the ReHo values were calculated by REST software. The ReHo values between the two groups were compared by two-sample t-test. The brain map with significant difference of ReHo value was obtained. Results: Compared with that in NS group, the regions with decreased ReHo value included the bilateral precuneus, superior frontal gyrus,medial prefrontal cortex, right angular gyrus, inferior frontal gyrus, inferior occipital gyrus, cerebellum, and left middle frontal gyrus in HS group. The regions of increased ReHo value included the bilateral insula, parahippocampal gyrus, white matter of parietal lobe, pons, left inferior parietal lobule, lingual gyrus, thalamus, inferior orbital gyrus, white matter of temporal-frontal lobe, and cerebellum. The difference was more obvious in the left hemisphere. Conclusions: In HS, abnormal ReHo on a resting state which reflects network of smoking addiction. This method may be helpful in understanding the mechanism of self-awareness in HS. (authors)

  17. Dynamic Multiscale Modes of Resting State Brain Activity Detected by Entropy Field Decomposition.

    Science.gov (United States)

    Frank, Lawrence R; Galinsky, Vitaly L

    2016-09-01

    The ability of functional magnetic resonance imaging (FMRI) to noninvasively measure fluctuations in brain activity in the absence of an applied stimulus offers the possibility of discerning functional networks in the resting state of the brain. However, the reconstruction of brain networks from these signal fluctuations poses a significant challenge because they are generally nonlinear and nongaussian and can overlap in both their spatial and temporal extent. Moreover, because there is no explicit input stimulus, there is no signal model with which to compare the brain responses. A variety of techniques have been devised to address this problem, but the predominant approaches are based on the presupposition of statistical properties of complex brain signal parameters, which are unprovable but facilitate the analysis. In this article, we address this problem with a new method, entropy field decomposition, for estimating structure within spatiotemporal data. This method is based on a general information field-theoretic formulation of Bayesian probability theory incorporating prior coupling information that allows the enumeration of the most probable parameter configurations without the need for unjustified statistical assumptions. This approach facilitates the construction of brain activation modes directly from the spatial-temporal correlation structure of the data. These modes and their associated spatial-temporal correlation structure can then be used to generate space-time activity probability trajectories, called functional connectivity pathways, which provide a characterization of functional brain networks. PMID:27391678

  18. Distinct disruptions of resting-state functional brain networks in familial and sporadic schizophrenia.

    Science.gov (United States)

    Zhu, Jiajia; Zhuo, Chuanjun; Liu, Feng; Qin, Wen; Xu, Lixue; Yu, Chunshui

    2016-01-01

    Clinical and brain structural differences have been reported between patients with familial and sporadic schizophrenia; however, little is known about the brain functional differences between the two subtypes of schizophrenia. Twenty-six patients with familial schizophrenia (PFS), 26 patients with sporadic schizophrenia (PSS) and 26 healthy controls (HC) underwent a resting-state functional magnetic resonance imaging. The whole-brain functional network was constructed and analyzed using graph theoretical approaches. Topological properties (including global, nodal and edge measures) were compared among the three groups. We found that PFS, PSS and HC exhibited common small-world architecture of the functional brain networks. However, at a global level, only PFS showed significantly lower normalized clustering coefficient, small-worldness, and local efficiency, indicating a randomization shift of their brain networks. At a regional level, PFS and PSS disrupted different neural circuits, consisting of abnormal nodes (increased or decreased nodal centrality) and edges (decreased functional connectivity strength), which were widely distributed throughout the entire brain. Furthermore, some of these altered network measures were significantly correlated with severity of psychotic symptoms. These results suggest that familial and sporadic schizophrenia had segregated disruptions in the topological organization of the intrinsic functional brain network, which may be due to different etiological contributions. PMID:27032817

  19. Reduced brain resting-state network specificity in infants compared with adults

    Directory of Open Access Journals (Sweden)

    Wylie KP

    2014-07-01

    Full Text Available Korey P Wylie,1,* Donald C Rojas,1,* Randal G Ross,1 Sharon K Hunter,1 Keeran Maharajh,1 Marc-Andre Cornier,2 Jason R Tregellas1,3 1Department of Psychiatry, 2Division of Endocrinology, Metabolism and Diabetes, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; 3Denver Veterans Affairs Medical Center, Denver, CO, USA *These authors contributed equally to this work Purpose: Infant resting-state networks do not exhibit the same connectivity patterns as those of young children and adults. Current theories of brain development emphasize developmental progression in regional and network specialization. We compared infant and adult functional connectivity, predicting that infants would exhibit less regional specificity and greater internetwork communication compared with adults.Patients and methods: Functional magnetic resonance imaging at rest was acquired in 12 healthy, term infants and 17 adults. Resting-state networks were extracted, using independent components analysis, and the resulting components were then compared between the adult and infant groups.Results: Adults exhibited stronger connectivity in the posterior cingulate cortex node of the default mode network, but infants had higher connectivity in medial prefrontal cortex/anterior cingulate cortex than adults. Adult connectivity was typically higher than infant connectivity within structures previously associated with the various networks, whereas infant connectivity was frequently higher outside of these structures. Internetwork communication was significantly higher in infants than in adults.Conclusion: We interpret these findings as consistent with evidence suggesting that resting-state network development is associated with increasing spatial specificity, possibly reflecting the corresponding functional specialization of regions and their interconnections through experience. Keywords: functional connectivity magnetic resonance imaging

  20. Progesterone mediates brain functional connectivity changes during the menstrual cycle - A pilot resting state MRI study

    Directory of Open Access Journals (Sweden)

    Katrin eArelin

    2015-02-01

    Full Text Available The growing interest in intrinsic brain organization has sparked various innovative approaches to generating comprehensive connectivity-based maps of the human brain. Prior reports point to a sexual dimorphism of the structural and functional human connectome. However, it is uncertain whether subtle changes in sex hormones, as occur during the monthly menstrual cycle, substantially impact the functional architecture of the female brain. Here, we performed eigenvector centrality (EC mapping in 32 longitudinal resting state fMRI scans of a single healthy subject without oral contraceptive use, across four menstrual cycles, and assessed estrogen and progesterone levels. To investigate associations between cycle-dependent hormones and brain connectivity, we performed correlation analyses between the EC maps and the respective hormone levels. On the whole brain level, we found a significant positive correlation between progesterone and EC in the bilateral DLPFC and bilateral sensorimotor cortex. In a secondary region-of-interest analysis, we detected a progesterone-modulated increase in functional connectivity of both bilateral DLPFC and bilateral sensorimotor cortex with the hippocampus. Our results suggest that the menstrual cycle substantially impacts intrinsic functional connectivity, particularly in brain areas associated with contextual memory-regulation, such as the hippocampus. These findings are the first to link the subtle hormonal fluctuations that occur during the menstrual cycle, to significant changes in regional functional connectivity in the hippocampus in a longitudinal design, given the limitation of data acquisition in a single subject. Our study demonstrates the feasibility of such a longitudinal rs-fMRI design and illustrates a means of creating a personalized map of the human brain by integrating potential mediators of brain states, such as menstrual cycle phase.

  1. Robust brain parcellation using sparse representation on resting-state fMRI.

    Science.gov (United States)

    Zhang, Yu; Caspers, Svenja; Fan, Lingzhong; Fan, Yong; Song, Ming; Liu, Cirong; Mo, Yin; Roski, Christian; Eickhoff, Simon; Amunts, Katrin; Jiang, Tianzi

    2015-11-01

    Resting-state fMRI (rs-fMRI) has been widely used to segregate the brain into individual modules based on the presence of distinct connectivity patterns. Many parcellation methods have been proposed for brain parcellation using rs-fMRI, but their results have been somewhat inconsistent, potentially due to various types of noise. In this study, we provide a robust parcellation method for rs-fMRI-based brain parcellation, which constructs a sparse similarity graph based on the sparse representation coefficients of each seed voxel and then uses spectral clustering to identify distinct modules. Both the local time-varying BOLD signals and whole-brain connectivity patterns may be used as features and yield similar parcellation results. The robustness of our method was tested on both simulated and real rs-fMRI datasets. In particular, on simulated rs-fMRI data, sparse representation achieved good performance across different noise levels, including high accuracy of parcellation and high robustness to noise. On real rs-fMRI data, stable parcellation of the medial frontal cortex (MFC) and parietal operculum (OP) were achieved on three different datasets, with high reproducibility within each dataset and high consistency across these results. Besides, the parcellation of MFC was little influenced by the degrees of spatial smoothing. Furthermore, the consistent parcellation of OP was also well corresponding to cytoarchitectonic subdivisions and known somatotopic organizations. Our results demonstrate a new promising approach to robust brain parcellation using resting-state fMRI by sparse representation.

  2. Whole brain resting-state analysis reveals decreased functional connectivity in major depression

    Directory of Open Access Journals (Sweden)

    Ilya M. Veer

    2010-09-01

    Full Text Available Recently, both increases and decreases in resting-state functional connectivity have been found in major depression. However, these studies only assessed functional connectivity within a specific network or between a few regions of interest, while comorbidity and use of medication was not always controlled for. Therefore, the aim of the current study was to investigate whole-brain functional connectivity, unbiased by a priori definition of regions or networks of interest, in medication-free depressive patients without comorbidity. We analyzed resting-state fMRI data of 19 medication-free patients with a recent diagnosis of major depression (within six months before inclusion and no comorbidity, and 19 age- and gender-matched controls. Independent component analysis was employed on the concatenated data sets of all participants. Thirteen functionally relevant networks were identified, describing the entire study sample. Next, individual representations of the networks were created using a dual regression method. Statistical inference was subsequently done on these spatial maps using voxelwise permutation tests. Abnormal functional connectivity was found within three resting-state networks in depression: 1 decreased bilateral amygdala and left anterior insula connectivity in an affective network, 2 reduced connectivity of the left frontal pole in a network associated with attention and working memory, and 3 decreased bilateral lingual gyrus connectivity within ventromedial visual regions. None of these effects were associated with symptom severity or grey matter density. We found abnormal resting-state functional connectivity not previously associated with major depression, which might relate to abnormal affect regulation and mild cognitive deficits, both associated with the symptomatology of the disorder.

  3. Resting-State Brain Functional Connectivity Is Altered in Type 2 Diabetes

    OpenAIRE

    Musen, Gail; Jacobson, Alan M.; Bolo, Nicolas R.; Simonson, Donald C.; Martha E. Shenton; McCartney, Richard L.; Flores, Veronica L.; Hoogenboom, Wouter S.

    2012-01-01

    Type 2 diabetes mellitus (T2DM) is a risk factor for Alzheimer disease (AD). Populations at risk for AD show altered brain activity in the default mode network (DMN) before cognitive dysfunction. We evaluated this brain pattern in T2DM patients. We compared T2DM patients (n = 10, age = 56 ± 2.2 years, fasting plasma glucose [FPG] = 8.4 ± 1.3 mmol/L, HbA1c = 7.5 ± 0.54%) with nondiabetic age-matched control subjects (n = 11, age = 54 ± 1.8 years, FPG = 4.8 ± 0.2 mmol/L) using resting-state fun...

  4. Distinct resting-state brain activity in patients with functional constipation.

    Science.gov (United States)

    Zhu, Qiang; Cai, Weiwei; Zheng, Jianyong; Li, Guanya; Meng, Qianqian; Liu, Qiaoyun; Zhao, Jizheng; von Deneen, Karen M; Wang, Yuanyuan; Cui, Guangbin; Duan, Shijun; Han, Yu; Wang, Huaning; Tian, Jie; Zhang, Yi; Nie, Yongzhan

    2016-10-01

    Functional constipation (FC) is a common functional gastrointestinal disorder (FGID) with a higher prevalence in clinical practice. The primary brain regions involved in emotional arousal regulation, somatic, sensory and motor control processing have been identified with neuroimaging in FGID. It remains unclear how these factors interact to influence the baseline brain activity of patients with FC. In the current study, we combined resting-state fMRI (RS-fMRI) with Granger causality analysis (GCA) to investigate the causal interactions of the brain areas in 14 patients with FC and in 26 healthy controls (HC). Our data showed significant differences in baseline brain activities in a number of major brain regions implicated in emotional process modulation (i.e. dorsal anterior cingulate cortex-dACC, anterior insula-aINS, orbitofrontal cortex-OFC, hippocampus-HIPP), somatic and sensory processing, and motor control (i.e., supplementary motor area-SMA, precentral gyrus-PreCen) (Ppropel limbic regions at the aINS and HIPP to induce abnormal emotional processing regulating visceral responses; and weaker effective connectivity from the SMA and PreCen, which are regions involved with somatic, sensory and motor control, propel the aINS and HIPP, suggesting abnormalities of sensory and behavioral responses. Such information of basal level functional abnormalities expands our current understanding of neural mechanisms underlying functional constipation.

  5. Alterations in regional homogeneity of resting-state brain activity in internet gaming addicts

    Directory of Open Access Journals (Sweden)

    Dong Guangheng

    2012-08-01

    Full Text Available Abstract Backgrounds Internet gaming addiction (IGA, as a subtype of internet addiction disorder, is rapidly becoming a prevalent mental health concern around the world. The neurobiological underpinnings of IGA should be studied to unravel the potential heterogeneity of IGA. This study investigated the brain functions in IGA patients with resting-state fMRI. Methods Fifteen IGA subjects and fourteen healthy controls participated in this study. Regional homogeneity (ReHo measures were used to detect the abnormal functional integrations. Results Comparing to the healthy controls, IGA subjects show enhanced ReHo in brainstem, inferior parietal lobule, left posterior cerebellum, and left middle frontal gyrus. All of these regions are thought related with sensory-motor coordination. In addition, IGA subjects show decreased ReHo in temporal, occipital and parietal brain regions. These regions are thought responsible for visual and auditory functions. Conclusions Our results suggest that long-time online game playing enhanced the brain synchronization in sensory-motor coordination related brain regions and decreased the excitability in visual and auditory related brain regions.

  6. Love-related changes in the brain: A resting-state functional magnetic resonance imaging study

    Directory of Open Access Journals (Sweden)

    Hongwen eSong

    2015-02-01

    Full Text Available Romantic love is a motivational state associated with a desire to enter or maintain a close relationship with a specific other person. Studies with functional magnetic resonance imaging (fMRI have found activation increases in brain regions involved in processing of reward, emotion, motivation when romantic lovers view photographs of their partners. However, not much is known on whether romantic love affects the brain’s functional architecture during rest. In the present study, resting state functional magnetic resonance imaging (rsfMRI data was collected to compare the regional homogeneity (ReHo and functional connectivity (FC across a lover group (LG, N=34, currently intensely in love, ended-love group (ELG, N=34, romantic relationship ended recently, and single group (SG, N=32, never fallen in love.The results showed that:1 ReHo of the left dorsal anterior cingulate cortex (dACC was significantly increased in the LG (in comparison to the ELG and the SG; 2 ReHo of the left dACC was positively correlated with length of time in love in the LG, and negatively correlated with the lovelorn duration since breakup in the ELG; 3 functional connectivity (FC within the reward, motivation, and emotion network (dACC, insula, caudate, amygdala and nucleus accumbens and the social cognition network (temporo-parietal junction (TPJ, posterior cingulate cortex (PCC, medial prefrontal cortex (MPFC, inferior parietal, precuneus and temporal lobe was significantly increased in the LG (in comparison to the ELG and SG; 4 in most regions within both networks FC was positively correlated with the love duration in the LG but negatively correlated with the lovelorn duration in the ELG. This study provides first empirical evidence of love-related alterations of brain functional architecture. The results shed light on the underlying neural mechanisms of romantic love, and demonstrate the possibility of applying a resting state approach for investigating romantic love.

  7. Acute effects of modafinil on brain resting state networks in young healthy subjects.

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    Roberto Esposito

    Full Text Available BACKGROUND: There is growing debate on the use of drugs that promote cognitive enhancement. Amphetamine-like drugs have been employed as cognitive enhancers, but they show important side effects and induce addiction. In this study, we investigated the use of modafinil which appears to have less side effects compared to other amphetamine-like drugs. We analyzed effects on cognitive performances and brain resting state network activity of 26 healthy young subjects. METHODOLOGY: A single dose (100 mg of modafinil was administered in a double-blind and placebo-controlled study. Both groups were tested for neuropsychological performances with the Raven's Advanced Progressive Matrices II set (APM before and three hours after administration of drug or placebo. Resting state functional magnetic resonance (rs-FMRI was also used, before and after three hours, to investigate changes in the activity of resting state brain networks. Diffusion Tensor Imaging (DTI was employed to evaluate differences in structural connectivity between the two groups. Protocol ID: Modrest_2011; NCT01684306; http://clinicaltrials.gov/ct2/show/NCT01684306. PRINCIPAL FINDINGS: Results indicate that a single dose of modafinil improves cognitive performance as assessed by APM. Rs-fMRI showed that the drug produces a statistically significant increased activation of Frontal Parietal Control (FPC; p<0.04 and Dorsal Attention (DAN; p<0.04 networks. No modifications in structural connectivity were observed. CONCLUSIONS AND SIGNIFICANCE: Overall, our findings support the notion that modafinil has cognitive enhancing properties and provide functional connectivity data to support these effects. TRIAL REGISTRATION: ClinicalTrials.gov NCT01684306 http://clinicaltrials.gov/ct2/show/NCT01684306.

  8. Extraversion and Neuroticism relate to topological properties of resting-state brain networks

    Directory of Open Access Journals (Sweden)

    Qing eGao

    2013-06-01

    Full Text Available With the advent and development of modern neuroimaging techniques, there is an increasing interest in linking extraversion and neuroticism to anatomical and functional brain markers. Here we aimed to test the theoretically derived biological personality model as proposed by Eysenck using graph theoretical analyses. Specifically, the association between the topological organization of whole-brain functional networks and extraversion/neuroticism was explored. To construct functional brain networks, functional connectivity among 90 brain regions was measured by temporal correlation using resting-state functional magnetic resonance imaging (fMRI data of 71 healthy subjects. Graph theoretical analysis revealed a positive association of extraversion scores and normalized clustering coefficient values. These results suggested a more clustered configuration in brain networks of individuals high in extraversion, which could imply a higher arousal threshold and higher levels of arousal tolerance in the cortex of extraverts. On a local network level, we observed that a specific nodal measure, i.e. betweenness centrality (BC, was positively associated with neuroticism scores in the right precentral gyrus, right caudate nucleus, right olfactory cortex and bilateral amygdala. For individuals high in neuroticism, these results suggested a more frequent participation of these specific regions in information transition within the brain network and, in turn, may partly explain greater regional activation levels and lower arousal thresholds in these regions. In contrast, extraversion scores were positively correlated with BC in the right insula, while negatively correlated with BC in the bilateral middle temporal gyrus, indicating that the relationship between extraversion and regional arousal is not as simple as proposed by Eysenck.

  9. Altered causal connectivity of resting state brain networks in amnesic MCI.

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    Peipeng Liang

    Full Text Available Most neuroimaging studies of resting state networks in amnesic mild cognitive impairment (aMCI have concentrated on functional connectivity (FC based on instantaneous correlation in a single network. The purpose of the current study was to investigate effective connectivity in aMCI patients based on Granger causality of four important networks at resting state derived from functional magnetic resonance imaging data--default mode network (DMN, hippocampal cortical memory network (HCMN, dorsal attention network (DAN and fronto-parietal control network (FPCN. Structural and functional MRI data were collected from 16 aMCI patients and 16 age, gender-matched healthy controls. Correlation-purged Granger causality analysis was used, taking gray matter atrophy as covariates, to compare the group difference between aMCI patients and healthy controls. We found that the causal connectivity between networks in aMCI patients was significantly altered with both increases and decreases in the aMCI group as compared to healthy controls. Some alterations were significantly correlated with the disease severity as measured by mini-mental state examination (MMSE, and California verbal learning test (CVLT scores. When the whole-brain signal averaged over the entire brain was used as a nuisance co-variate, the within-group maps were significantly altered while the between-group difference maps did not. These results suggest that the alterations in causal influences may be one of the possible underlying substrates of cognitive impairments in aMCI. The present study extends and complements previous FC studies and demonstrates the coexistence of causal disconnection and compensation in aMCI patients, and thus might provide insights into biological mechanism of the disease.

  10. Deep brain stimulation modulates synchrony within spatially and spectrally distinct resting state networks in Parkinson's disease.

    Science.gov (United States)

    Oswal, Ashwini; Beudel, Martijn; Zrinzo, Ludvic; Limousin, Patricia; Hariz, Marwan; Foltynie, Tom; Litvak, Vladimir; Brown, Peter

    2016-05-01

    Chronic dopamine depletion in Parkinson's disease leads to progressive motor and cognitive impairment, which is associated with the emergence of characteristic patterns of synchronous oscillatory activity within cortico-basal-ganglia circuits. Deep brain stimulation of the subthalamic nucleus is an effective treatment for Parkinson's disease, but its influence on synchronous activity in cortico-basal-ganglia loops remains to be fully characterized. Here, we demonstrate that deep brain stimulation selectively suppresses certain spatially and spectrally segregated resting state subthalamic nucleus-cortical networks. To this end we used a validated and novel approach for performing simultaneous recordings of the subthalamic nucleus and cortex using magnetoencephalography (during concurrent subthalamic nucleus deep brain stimulation). Our results highlight that clinically effective subthalamic nucleus deep brain stimulation suppresses synchrony locally within the subthalamic nucleus in the low beta oscillatory range and furthermore that the degree of this suppression correlates with clinical motor improvement. Moreover, deep brain stimulation relatively selectively suppressed synchronization of activity between the subthalamic nucleus and mesial premotor regions, including the supplementary motor areas. These mesial premotor regions were predominantly coupled to the subthalamic nucleus in the high beta frequency range, but the degree of deep brain stimulation-associated suppression in their coupling to the subthalamic nucleus was not found to correlate with motor improvement. Beta band coupling between the subthalamic nucleus and lateral motor areas was not influenced by deep brain stimulation. Motor cortical coupling with subthalamic nucleus predominantly involved driving of the subthalamic nucleus, with those drives in the higher beta frequency band having much shorter net delays to subthalamic nucleus than those in the lower beta band. These observations raise the

  11. Moral competence and brain connectivity: A resting-state fMRI study.

    Science.gov (United States)

    Jung, Wi Hoon; Prehn, Kristin; Fang, Zhuo; Korczykowski, Marc; Kable, Joseph W; Rao, Hengyi; Robertson, Diana C

    2016-11-01

    Moral competence (MC) refers to the ability to apply certain moral orientations in a consistent and differentiated manner when judging moral issues. People greatly differ in terms of MC, however, little is known about how these differences are implemented in the brain. To investigate this question, we used functional magnetic resonance imaging and examined resting-state functional connectivity (RSFC) in n=31 individuals with MC scores in the highest 15% of the population and n=33 individuals with MC scores in the lowest 15%, selected from a large sample of 730 Master of Business Administration (MBA) students. Compared to individuals with lower MC, individuals with higher MC showed greater amygdala-ventromedial prefrontal connectivity, which may reflect better ability to cope with emotional conflicts elicited by moral dilemmas. Moreover, individuals with higher MC showed less inter-network connectivity between the amygdalar and fronto-parietal networks, suggesting a more independent operation of these networks. Our findings provide novel insights into how individual differences in moral judgment are associated with RSFC in brain circuits related to emotion processing and cognitive control.

  12. Modular reorganization of brain resting state networks and its independent validation in Alzheimer's disease patients.

    Science.gov (United States)

    Chen, Guangyu; Zhang, Hong-Ying; Xie, Chunming; Chen, Gang; Zhang, Zhi-Jun; Teng, Gao-Jun; Li, Shi-Jiang

    2013-01-01

    Previous studies have demonstrated disruption in structural and functional connectivity occurring in the Alzheimer's Disease (AD). However, it is not known how these disruptions alter brain network reorganization. With the modular analysis method of graph theory, and datasets acquired by the resting-state functional connectivity MRI (R-fMRI) method, we investigated and compared the brain organization patterns between the AD group and the cognitively normal control (CN) group. Our main finding is that the largest homotopic module (defined as the insula module) in the CN group was broken down to the pieces in the AD group. Specifically, it was discovered that the eight pairs of the bilateral regions (the opercular part of inferior frontal gyrus, area triangularis, insula, putamen, globus pallidus, transverse temporal gyri, superior temporal gyrus, and superior temporal pole) of the insula module had lost symmetric functional connection properties, and the corresponding gray matter concentration (GMC) was significant lower in AD group. We further quantified the functional connectivity changes with an index (index A) and structural changes with the GMC index in the insula module to demonstrate their great potential as AD biomarkers. We further validated these results with six additional independent datasets (271 subjects in six groups). Our results demonstrated specific underlying structural and functional reorganization from young to old, and for diseased subjects. Further, it is suggested that by combining the structural GMC analysis and functional modular analysis in the insula module, a new biomarker can be developed at the single-subject level.

  13. Thirty minute transcutaneous electric acupoint stimulation modulates resting state brain activities: a perfusion and BOLD fMRI study.

    Science.gov (United States)

    Jiang, Yin; Hao, Ying; Zhang, Yue; Liu, Jing; Wang, Xiaoying; Han, Jisheng; Fang, Jing; Zhang, Jue; Cui, Cailian

    2012-05-31

    Increasing neuroimaging studies have focused on the sustained after effects of acupuncture, especially for the changes of brain activities in rest. However, short-period stimuli have mostly been chosen in these works. The present study aimed to investigate how the resting state brain activities in healthy subjects were modulated by relatively long-period (30 min) acupuncture, a widely used modality in clinical practice. Transcutaneous electric acupoint stimulation (TEAS) or intermittent minimal TEAS (MTEAS) were given for 30 min to 40 subjects. Functional MRI (fMRI) data were collected including the pre-stimulation resting state and the post-stimulation resting state, using dual-echo arterial spin labeling (ASL) techniques, representing both cerebral blood flow (CBF) signals and blood oxygen-dependent level (BOLD) signals simultaneously. Following 30 min TEAS, but not MTEAS, the mean global CBF decreased, and a significant decrease of regional CBF was observed in SI, insula, STG, MOG and IFG. Functional connectivity analysis showed more secure and spatially extended connectivity of both the DMN and SMN after 30 min TEAS. Our results implied that modulation of the regional brain activities and network connectivity induced by thirty minute TEAS may associate with the acupuncture-related therapeutic effects. Furthermore, the resting state regional CBF quantified by ASL perfusion fMRI may serve as a potential biomarker in future acupuncture studies. PMID:22541167

  14. Altered baseline brain activity in children with bipolar disorder during mania state: a resting-state study

    Directory of Open Access Journals (Sweden)

    Lu D

    2014-02-01

    Full Text Available Dali Lu,1 Qing Jiao,2 Yuan Zhong,3,4 Weijia Gao,1 Qian Xiao,1 Xiaoqun Liu,1 Xiaoling Lin,5 Wentao Cheng,6 Lanzhu Luo,6 Chuanjian Xu,3 Guangming Lu,2 Linyan Su1 1Mental Health Institute of the Second Xiangya Hospital, Key Laboratory of Psychiatry and Mental Health of Hunan Province, Central South University, Changsha, People's Republic of China; 2Department of Radiology, Taishan Medical University, Taian, People's Republic of China; 3Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, People's Republic of China; 4School of Psychology, Nanjing Normal University, Nanjing, People's Republic of China; 5School of Nursing of Central South University, Changsha, People's Republic of China; 6Department of Pediatric and Geriatric Psychiatry, Fuzhou Neuropsychiatric Hospital, Fuzhou, People's Republic of China Background: Previous functional magnetic resonance imaging (fMRI studies have shown abnormal functional connectivity in regions involved in emotion processing and regulation in pediatric bipolar disorder (PBD. Recent studies indicate, however, that task-dependent neural changes only represent a small fraction of the brain's total activity. How the brain allocates the majority of its resources at resting state is still unknown. We used the amplitude of low-frequency fluctuation (ALFF method of fMRI to explore the spontaneous neuronal activity in resting state in PBD patients. Methods: Eighteen PBD patients during the mania phase and 18 sex-, age- and education-matched healthy subjects were enrolled in this study and all patients underwent fMRI scanning. The ALFF method was used to compare the resting-state spontaneous neuronal activity between groups. Correlation analysis was performed between the ALFF values and Young Mania Rating Scale scores. Results: Compared with healthy controls, PBD patients presented increased ALFF in bilateral caudate and left pallidum as well as decreased ALFF in left precuneus

  15. Frequency specificity of regional homogeneity in the resting-state human brain.

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    Xiaopeng Song

    Full Text Available Resting state-fMRI studies have found that the inter-areal correlations in cortical networks concentrate within ultra-low frequencies (0.01-0.04 Hz while long-distance connections within subcortical networks distribute over a wider frequency range (0.01-0.14 Hz. However, the frequency characteristics of regional homogeneity (ReHo in different areas are still unclear. To examine the ReHo properties in different frequency bands, a data-driven method, Empirical Mode Decomposition (EMD, was adopted to decompose the time series of each voxel into several components with distinct frequency bands. ReHo values in each of the components were then calculated. Our results showed that ReHo in cortical areas were higher and more frequency-dependent than those in the subcortical regions. BOLD oscillations of 0.02-0.04 Hz mainly contributed to the cortical ReHo, whereas the ReHo in limbic areas involved a wider frequency range and were dominated by higher-frequency BOLD oscillations (>0.08 Hz. The frequency characteristics of ReHo are distinct between different parts of the striatum, with the frequency band of 0.04-0.1 Hz contributing the most to ReHo in caudate nucleus, and oscillations lower than 0.02 Hz contributing more to ReHo in putamen. The distinct frequency-specific ReHo properties of different brain areas may arise from the assorted cytoarchitecture or synaptic types in these areas. Our work may advance the understanding of the neural-physiological basis of local BOLD activities and the functional specificity of different brain regions.

  16. Brain activation and inhibition after acupuncture at Taichong and Taixi: resting-state functional magnetic resonance imaging

    Directory of Open Access Journals (Sweden)

    Shao-qun Zhang

    2015-01-01

    Full Text Available Acupuncture can induce changes in the brain. However, the majority of studies to date have focused on a single acupoint at a time. In the present study, we observed activity changes in the brains of healthy volunteers before and after acupuncture at Taichong (LR3 and Taixi (KI3 using resting-state functional magnetic resonance imaging. Fifteen healthy volunteers underwent resting-state functional magnetic resonance imaging of the brain 15 minutes before acupuncture, then received acupuncture at Taichong and Taixi using the nail-pressing needle insertion method, after which the needle was retained in place for 30 minutes. Fifteen minutes after withdrawal of the needle, the volunteers underwent a further session of resting-state functional magnetic resonance imaging, which revealed that the amplitude of low-frequency fluctuation, a measure of spontaneous neuronal activity, increased mainly in the cerebral occipital lobe and middle occipital gyrus (Brodmann area 18/19, inferior occipital gyrus (Brodmann area 18 and cuneus (Brodmann area 18, but decreased mainly in the gyrus rectus of the frontal lobe (Brodmann area 11, inferior frontal gyrus (Brodmann area 44 and the center of the posterior lobe of the cerebellum. The present findings indicate that acupuncture at Taichong and Taixi specifically promote blood flow and activation in the brain areas related to vision, emotion and cognition, and inhibit brain areas related to emotion, attention, phonological and semantic processing, and memory.

  17. Brain activation and inhibition after acupuncture at Taichong and Taixi: resting-state functional magnetic resonance imaging.

    Science.gov (United States)

    Zhang, Shao-Qun; Wang, Yan-Jie; Zhang, Ji-Ping; Chen, Jun-Qi; Wu, Chun-Xiao; Li, Zhi-Peng; Chen, Jia-Rong; Ouyang, Huai-Liang; Huang, Yong; Tang, Chun-Zhi

    2015-02-01

    Acupuncture can induce changes in the brain. However, the majority of studies to date have focused on a single acupoint at a time. In the present study, we observed activity changes in the brains of healthy volunteers before and after acupuncture at Taichong (LR3) and Taixi (KI3) using resting-state functional magnetic resonance imaging. Fifteen healthy volunteers underwent resting-state functional magnetic resonance imaging of the brain 15 minutes before acupuncture, then received acupuncture at Taichong and Taixi using the nail-pressing needle insertion method, after which the needle was retained in place for 30 minutes. Fifteen minutes after withdrawal of the needle, the volunteers underwent a further session of resting-state functional magnetic resonance imaging, which revealed that the amplitude of low-frequency fluctuation, a measure of spontaneous neuronal activity, increased mainly in the cerebral occipital lobe and middle occipital gyrus (Brodmann area 18/19), inferior occipital gyrus (Brodmann area 18) and cuneus (Brodmann area 18), but decreased mainly in the gyrus rectus of the frontal lobe (Brodmann area 11), inferior frontal gyrus (Brodmann area 44) and the center of the posterior lobe of the cerebellum. The present findings indicate that acupuncture at Taichong and Taixi specifically promote blood flow and activation in the brain areas related to vision, emotion and cognition, and inhibit brain areas related to emotion, attention, phonological and semantic processing, and memory. PMID:25883630

  18. Brain activation and inhibition after acupuncture at Taichong andTaixi:resting-state functional magnetic resonance imaging

    Institute of Scientific and Technical Information of China (English)

    Shao-qun Zhang; Chun-zhi Tang; Yan-jie Wang; Ji-ping Zhang; Jun-qi Chen; Chun-xiao Wu; Zhi-peng Li; Jia-rong Chen; Huai-liang Ouyang; Yong Huang

    2015-01-01

    Acupuncture can induce changes in the brain. However, the majority of studies to date have focused on a single acupoint at a time. In the present study, we observed activity changes in the brains of healthy volunteers before and after acupuncture atTaichong (LR3) andTaixi (KI3) using resting-state functional magnetic resonance imaging. Fifteen healthy volunteers underwent resting-state functional magnetic resonance imaging of the brain 15 minutes before acupuncture, then received acupuncture atTaichong andTaixi using the nail-pressing needle insertion method, after which the needle was retained in place for 30 minutes. Fifteen minutes after withdrawal of the needle, the volunteers underwent a further session of resting-state functional magnetic res-onance imaging, which revealed that the amplitude of low-frequency lfuctuation, a measure of spontaneous neuronal activity, increased mainly in the cerebral occipital lobe and middle occipital gyrus (Brodmann area 18/19), inferior occipital gyrus (Brodmann area 18) and cuneus (Brodmann area 18), but decreased mainly in the gyrus rectus of the frontal lobe (Brodmann area 11), inferi-or frontal gyrus (Brodmann area 44) and the center of the posterior lobe of the cerebellum. The present ifndings indicate that acupuncture atTaichong andTaixi speciifcally promote blood lfow and activation in the brain areas related to vision, emotion and cognition, and inhibit brain areas related to emotion, attention, phonological and semantic processing, and memory.

  19. Abnormal baseline brain activity in patients with neuromyelitis optica: A resting-state fMRI study

    International Nuclear Information System (INIS)

    Purpose: Recent immunopathologic and MRI findings suggest that tissue damage in neuromyelitis optica (NMO) is not limited to spinal cord and optic nerve, but also in brain. Baseline brain activity can reveal the brain functional changes to the tissue damages and give clues to the pathophysiology of NMO, however, it has never been explored by resting-state functional MRI (fMRI). We used regional amplitude of low frequency fluctuation (ALFF) as an index in resting-state fMRI to investigate how baseline brain activity changes in patients with NMO. Methods: Resting-state fMRIs collected from seventeen NMO patients and seventeen age- and sex-matched normal controls were compared to investigate the ALFF difference between the two groups. The relationships between ALFF in regions with significant group differences and the EDSS (Expanded Disability Status Scale), disease duration were further explored. Results: Our results showed that NMO patients had significantly decreased ALFF in precuneus, posterior cingulate cortex (PCC) and lingual gyrus; and increased ALFF in middle frontal gyrus, caudate nucleus and thalamus, compared to normal controls. Moderate negative correlations were found between the EDSS and ALFF in the left middle frontal gyrus (r = -0.436, p = 0.040) and the left caudate (r = -0.542, p = 0.012). Conclusion: The abnormal baseline brain activity shown by resting-state fMRI in NMO is relevant to cognition, visual and motor systems. It implicates a complex baseline brain status of both functional impairments and adaptations caused by tissue damages in these systems, which gives clues to the pathophysiology of NMO.

  20. Abnormal baseline brain activity in patients with neuromyelitis optica: A resting-state fMRI study

    Energy Technology Data Exchange (ETDEWEB)

    Liu Yaou [Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China); Liang Peipeng [Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China); International WIC institute, Beijing University of Technology, Beijing 100024 (China); Duan Yunyun; Jia Xiuqin; Wang Fei; Yu Chunshui; Qin Wen [Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China); Dong Huiqing; Ye Jing [Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China); Li Kuncheng, E-mail: likuncheng1955@yahoo.com.cn [Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China)

    2011-11-15

    Purpose: Recent immunopathologic and MRI findings suggest that tissue damage in neuromyelitis optica (NMO) is not limited to spinal cord and optic nerve, but also in brain. Baseline brain activity can reveal the brain functional changes to the tissue damages and give clues to the pathophysiology of NMO, however, it has never been explored by resting-state functional MRI (fMRI). We used regional amplitude of low frequency fluctuation (ALFF) as an index in resting-state fMRI to investigate how baseline brain activity changes in patients with NMO. Methods: Resting-state fMRIs collected from seventeen NMO patients and seventeen age- and sex-matched normal controls were compared to investigate the ALFF difference between the two groups. The relationships between ALFF in regions with significant group differences and the EDSS (Expanded Disability Status Scale), disease duration were further explored. Results: Our results showed that NMO patients had significantly decreased ALFF in precuneus, posterior cingulate cortex (PCC) and lingual gyrus; and increased ALFF in middle frontal gyrus, caudate nucleus and thalamus, compared to normal controls. Moderate negative correlations were found between the EDSS and ALFF in the left middle frontal gyrus (r = -0.436, p = 0.040) and the left caudate (r = -0.542, p = 0.012). Conclusion: The abnormal baseline brain activity shown by resting-state fMRI in NMO is relevant to cognition, visual and motor systems. It implicates a complex baseline brain status of both functional impairments and adaptations caused by tissue damages in these systems, which gives clues to the pathophysiology of NMO.

  1. Disrupted small-world brain networks in moderate Alzheimer's disease: a resting-state FMRI study.

    Directory of Open Access Journals (Sweden)

    Xiaohu Zhao

    Full Text Available The small-world organization has been hypothesized to reflect a balance between local processing and global integration in the human brain. Previous multimodal imaging studies have consistently demonstrated that the topological architecture of the brain network is disrupted in Alzheimer's disease (AD. However, these studies have reported inconsistent results regarding the topological properties of brain alterations in AD. One potential explanation for these inconsistent results lies with the diverse homogeneity and distinct progressive stages of the AD involved in these studies, which are thought to be critical factors that might affect the results. We investigated the topological properties of brain functional networks derived from resting functional magnetic resonance imaging (fMRI of carefully selected moderate AD patients and normal controls (NCs. Our results showed that the topological properties were found to be disrupted in AD patients, which showing increased local efficiency but decreased global efficiency. We found that the altered brain regions are mainly located in the default mode network, the temporal lobe and certain subcortical regions that are closely associated with the neuropathological changes in AD. Of note, our exploratory study revealed that the ApoE genotype modulates brain network properties, especially in AD patients.

  2. Transient brain activity disentangles fMRI resting-state dynamics in terms of spatially and temporally overlapping networks.

    Science.gov (United States)

    Karahanoğlu, Fikret Işik; Van De Ville, Dimitri

    2015-07-16

    Dynamics of resting-state functional magnetic resonance imaging (fMRI) provide a new window onto the organizational principles of brain function. Using state-of-the-art signal processing techniques, we extract innovation-driven co-activation patterns (iCAPs) from resting-state fMRI. The iCAPs' maps are spatially overlapping and their sustained-activity signals temporally overlapping. Decomposing resting-state fMRI using iCAPs reveals the rich spatiotemporal structure of functional components that dynamically assemble known resting-state networks. The temporal overlap between iCAPs is substantial; typically, three to four iCAPs occur simultaneously in combinations that are consistent with their behaviour profiles. In contrast to conventional connectivity analysis, which suggests a negative correlation between fluctuations in the default-mode network (DMN) and task-positive networks, we instead find evidence for two DMN-related iCAPs consisting the posterior cingulate cortex that differentially interact with the attention network. These findings demonstrate how the fMRI resting state can be functionally decomposed into spatially and temporally overlapping building blocks using iCAPs.

  3. Directionality of large-scale resting-state brain networks during eyes open and eyes closed conditions

    Directory of Open Access Journals (Sweden)

    Delong eZhang

    2015-02-01

    Full Text Available The present study examined directional connections in the brain among resting-state networks (RSNs when the participant had their eyes open (EO or had their eyes closed (EC. The resting-state fMRI data were collected from 20 healthy participants (11 males, 20.17 ± 2.74 years under the EO and EC states. Independent component analysis (ICA was applied to identify the separated RSNs (i.e., the primary/high-level visual, primary sensory-motor, ventral motor, salience/dorsal attention, and anterior/posterior default-mode networks, and the Gaussian Bayesian network (BN learning approach was then used to explore the conditional dependencies among these RSNs. The network-to-network directional connections related to EO and EC were depicted, and a support vector machine (SVM was further employed to identify the directional connection patterns that could effectively discriminate between the two states. The results indicated that the connections among RSNs are directionally connected within a BN during the EO and EC states. The directional connections from the salient attention network to the anterior/posterior default-mode networks and the high-level to primary-level visual network were the obvious characteristics of both the EO and EC resting-state BNs. Of the directional connections in BN, the attention (salient and dorsal-related directional connections were observed to be discriminative between the EO and EC states. In particular, we noted that the properties of the salient and dorsal attention networks were in opposite directions. Overall, the present study described the directional connections of RSNs using a BN learning approach during the EO and EC states, and the results suggested that the attention system (the salient and the dorsal attention network might have important roles in resting-state brain networks and the neural substrate underpinning of switching between the EO and EC states.

  4. MRI Study on the Functional and Spatial Consistency of Resting State-Related Independent Components of the Brain Network

    Energy Technology Data Exchange (ETDEWEB)

    Jeong, Bum Seok [Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of); Choi, Jee Wook [Daejeon St. Mary' s Hospital, The Catholic University of Korea College of Medicine, Daejeon (Korea, Republic of); Kim, Ji Woong [College of Medical Science, Konyang University, Daejeon(Korea, Republic of)

    2012-06-15

    Resting-state networks (RSNs), including the default mode network (DMN), have been considered as markers of brain status such as consciousness, developmental change, and treatment effects. The consistency of functional connectivity among RSNs has not been fully explored, especially among resting-state-related independent components (RSICs). This resting-state fMRI study addressed the consistency of functional connectivity among RSICs as well as their spatial consistency between 'at day 1' and 'after 4 weeks' in 13 healthy volunteers. We found that most RSICs, especially the DMN, are reproducible across time, whereas some RSICs were variable in either their spatial characteristics or their functional connectivity. Relatively low spatial consistency was found in the basal ganglia, a parietal region of left frontoparietal network, and the supplementary motor area. The functional connectivity between two independent components, the bilateral angular/supramarginal gyri/intraparietal lobule and bilateral middle temporal/occipital gyri, was decreased across time regardless of the correlation analysis method employed, (Pearson's or partial correlation). RSICs showing variable consistency are different between spatial characteristics and functional connectivity. To understand the brain as a dynamic network, we recommend further investigation of both changes in the activation of specific regions and the modulation of functional connectivity in the brain network.

  5. Clustering of resting state networks.

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    Megan H Lee

    Full Text Available BACKGROUND: The goal of the study was to demonstrate a hierarchical structure of resting state activity in the healthy brain using a data-driven clustering algorithm. METHODOLOGY/PRINCIPAL FINDINGS: The fuzzy-c-means clustering algorithm was applied to resting state fMRI data in cortical and subcortical gray matter from two groups acquired separately, one of 17 healthy individuals and the second of 21 healthy individuals. Different numbers of clusters and different starting conditions were used. A cluster dispersion measure determined the optimal numbers of clusters. An inner product metric provided a measure of similarity between different clusters. The two cluster result found the task-negative and task-positive systems. The cluster dispersion measure was minimized with seven and eleven clusters. Each of the clusters in the seven and eleven cluster result was associated with either the task-negative or task-positive system. Applying the algorithm to find seven clusters recovered previously described resting state networks, including the default mode network, frontoparietal control network, ventral and dorsal attention networks, somatomotor, visual, and language networks. The language and ventral attention networks had significant subcortical involvement. This parcellation was consistently found in a large majority of algorithm runs under different conditions and was robust to different methods of initialization. CONCLUSIONS/SIGNIFICANCE: The clustering of resting state activity using different optimal numbers of clusters identified resting state networks comparable to previously obtained results. This work reinforces the observation that resting state networks are hierarchically organized.

  6. Resting state networks and memory consolidation

    OpenAIRE

    Albert, Neil B.; Robertson, Edwin M; Mehta, Puja; Miall, R. Chris

    2009-01-01

    Despite their name, resting state networks (RSNs) provide a clear indication that the human brain may be hard-working. Unlike the cardiac and respiratory systems, which greatly reduce their rate of function during periods of inactivity, the human brain may have additional responsibilities during rest. One particularly intriguing function performed by the resting brain is the consolidation of recent learned information, which is known to take place over a period of several hours after learning...

  7. Resting-state EEG oscillatory dynamics in fragile X syndrome: abnormal functional connectivity and brain network organization.

    Directory of Open Access Journals (Sweden)

    Melle J W van der Molen

    Full Text Available Disruptions in functional connectivity and dysfunctional brain networks are considered to be a neurological hallmark of neurodevelopmental disorders. Despite the vast literature on functional brain connectivity in typical brain development, surprisingly few attempts have been made to characterize brain network integrity in neurodevelopmental disorders. Here we used resting-state EEG to characterize functional brain connectivity and brain network organization in eight males with fragile X syndrome (FXS and 12 healthy male controls. Functional connectivity was calculated based on the phase lag index (PLI, a non-linear synchronization index that is less sensitive to the effects of volume conduction. Brain network organization was assessed with graph theoretical analysis. A decrease in global functional connectivity was observed in FXS males for upper alpha and beta frequency bands. For theta oscillations, we found increased connectivity in long-range (fronto-posterior and short-range (frontal-frontal and posterior-posterior clusters. Graph theoretical analysis yielded evidence of increased path length in the theta band, suggesting that information transfer between brain regions is particularly impaired for theta oscillations in FXS. These findings are discussed in terms of aberrant maturation of neuronal oscillatory dynamics, resulting in an imbalance in excitatory and inhibitory neuronal circuit activity.

  8. Baseline brain activity changes in patients with clinically isolated syndrome revealed by resting-state functional MRI

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Yaou; Duan, Yunyun; Liang, Peipeng; Jia, Xiuqin; Yu, Chunshui [Dept. of Radiology, Xuanwu Hospital, Capital Medical Univ., Beijing (China); Ye, Jing [Dept. of Neurology, Xuanwu Hospital, Capital Medical Univ., Beijing (China); Butzkueven, Helmut [Dept. of Medicine, Univ. of Melbourne, Melbourne (Australia); Dong, Huiqing [Dept. of Neurology, Xuanwu Hospital, Capital Medical Univ., Beijing (China); Li, Kuncheng [Dept. of Radiology, Xuanwu Hospital, Capital Medical Univ., Beijing (China); Beijing Key Laboratory of MRI and Brain Informatics, Beijing (China)], E-mail: likuncheng1955@yahoo.com.cn

    2012-11-15

    Background A clinically isolated syndrome (CIS) is the first manifestation of multiple sclerosis (MS). Previous task-related functional MRI studies demonstrate functional reorganization in patients with CIS. Purpose To assess baseline brain activity changes in patients with CIS by using the technique of regional amplitude of low frequency fluctuation (ALFF) as an index in resting-state fMRI. Material and Methods Resting-state fMRIs data acquired from 37 patients with CIS and 37 age- and sex-matched normal controls were compared to investigate ALFF differences. The relationships between ALFF in regions with significant group differences and the EDSS (Expanded Disability Status Scale), disease duration, and T2 lesion volume (T2LV) were further explored. Results Patients with CIS had significantly decreased ALFF in the right anterior cingulate cortex, right caudate, right lingual gyrus, and right cuneus (P < 0.05 corrected for multiple comparisons using Monte Carlo simulation) compared to normal controls, while no significantly increased ALFF were observed in CIS. No significant correlation was found between the EDSS, disease duration, T2LV, and ALFF in regions with significant group differences. Conclusion In patients with CIS, resting-state fMRI demonstrates decreased activity in several brain regions. These results are in contrast to patients with established MS, in whom ALFF demonstrates several regions of increased activity. It is possible that this shift from decreased activity in CIS to increased activity in MS could reflect the dynamics of cortical reorganization.

  9. Altered topological properties of functional network connectivity in schizophrenia during resting state: a small-world brain network study.

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    Qingbao Yu

    Full Text Available Aberrant topological properties of small-world human brain networks in patients with schizophrenia (SZ have been documented in previous neuroimaging studies. Aberrant functional network connectivity (FNC, temporal relationships among independent component time courses has also been found in SZ by a previous resting state functional magnetic resonance imaging (fMRI study. However, no study has yet determined if topological properties of FNC are also altered in SZ. In this study, small-world network metrics of FNC during the resting state were examined in both healthy controls (HCs and SZ subjects. FMRI data were obtained from 19 HCs and 19 SZ. Brain images were decomposed into independent components (ICs by group independent component analysis (ICA. FNC maps were constructed via a partial correlation analysis of ICA time courses. A set of undirected graphs were built by thresholding the FNC maps and the small-world network metrics of these maps were evaluated. Our results demonstrated significantly altered topological properties of FNC in SZ relative to controls. In addition, topological measures of many ICs involving frontal, parietal, occipital and cerebellar areas were altered in SZ relative to controls. Specifically, topological measures of whole network and specific components in SZ were correlated with scores on the negative symptom scale of the Positive and Negative Symptom Scale (PANSS. These findings suggest that aberrant architecture of small-world brain topology in SZ consists of ICA temporally coherent brain networks.

  10. Effects of methylphenidate on resting-state brain activity in normal adults: an fMRI study

    Institute of Scientific and Technical Information of China (English)

    Yihong Zhu; Bin Gao; Jianming Hua; Weibo Liu; Yichao Deng; Lijie Zhang; Biao Jiang

    2013-01-01

    Methylphenidate (MPH) is one of the most commonly used stimulants for the treatment of attention deficit hyperactivity disorder (ADHD).Although several studies have evaluated the effects of MPH on human brain activation during specific cognitive tasks using functional magnetic resonance imaging (fMRI),few studies have focused on spontaneous brain activity.In the current study,we investigated the effect of MPH on the intra-regional synchronization of spontaneous brain activity during the resting state in 18normal adult males.A handedness questionnaire and the Wechsler Adult Intelligence Scale were applied before medication,and a resting-state fMRI scan was obtained 1 h after medication (20 mg MPH or placebo,order counterbalanced between participants).We demonstrated that:(1) there were no significant differences in the performance of behavioral tasks between the MPH and placebo groups; (2) the left middle and superior temporal gyri had stronger MPH-related regional homogeneity (ReHo); and (3) the left lingual gyrus had weaker MPH-related ReHo.Our findings showed that the ReHo in some brain areas changes with MPH compared to placebo in normal adults,even though there are no behavioral differences.This method can be applied to patients with mental illness who may be treated with MPH,and be used to compare the difference between patients taking MPH and normal participants,to help reveal the mechanism of how MPH works.

  11. Altered baseline brain activity with 72 h of simulated microgravity--initial evidence from resting-state fMRI.

    Science.gov (United States)

    Liao, Yang; Zhang, Jinsong; Huang, Zhiping; Xi, Yibin; Zhang, Qianru; Zhu, Tianli; Liu, Xufeng

    2012-01-01

    To provide the basis and reference to further insights into the neural activity of the human brain in a microgravity environment, we discuss the amplitude changes of low-frequency brain activity fluctuations using a simulated microgravity model. Twelve male participants between 24 and 31 years old received resting-state fMRI scans in both a normal condition and after 72 hours in a -6° head down tilt (HDT). A paired sample t-test was used to test the amplitude differences of low-frequency brain activity fluctuations between these two conditions. With 72 hours in a -6° HDT, the participants showed a decreased amplitude of low-frequency fluctuations in the left thalamus compared with the normal condition (a combined threshold of Pmicrogravity environment. PMID:23285086

  12. Self-regulation of circumscribed brain activity modulates spatially selective and frequency specific connectivity of distributed resting state networks

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    Mathias eVukelić

    2015-07-01

    Full Text Available The mechanisms of learning involved in brain self-regulation have still to be unveiled to exploit the full potential of this methodology for therapeutic interventions. This skill of volitionally changing brain activity presumably resembles motor skill learning which in turn is accompanied by plastic changes modulating resting state networks. Along these lines, we hypothesized that brain regulation and neurofeedback would similarly modify intrinsic networks at rest while presenting a distinct spatio-temporal pattern. High-resolution EEG preceded and followed a single neurofeedback training intervention of modulating circumscribed sensorimotor low β -activity by motor imagery in eleven healthy participants. They were kept in the deliberative phase of skill acquisition with high demands for learning self-regulation through stepwise increases of task difficulty. By applying the corrected imaginary part of the coherency function, we observed increased functional connectivity of both the primary motor and the primary somatosensory cortex with their respective contralateral homologous cortices in the low β-frequency band which was self-regulated during feedback. At the same time, the primary motor cortex - but none of the surrounding cortical areas - showed connectivity to contralateral supplementary motor and dorsal premotor areas in the high β-band. Simultaneously, the neurofeedback target displayed a specific increase of functional connectivity with an ipsilateral fronto-parietal network in the α-band while presenting a de-coupling with contralateral primary and secondary sensorimotor areas in the very same frequency band.Brain self-regulating modifies resting state connections spatially selective to the neurofeedback target of the dominant hemisphere. These are anatomically distinct with regard to the cortico-cortical connectivity pattern and are functionally specific with regard to the time domain of coherent activity consistent with a Hebbian

  13. Altered spontaneous brain activity in patients with acute spinal cord injury revealed by resting-state functional MRI.

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    Ling Zhu

    Full Text Available Previous neuroimaging studies have provided evidence of structural and functional reorganization of brain in patients with chronic spinal cord injury (SCI. However, it remains unknown whether the spontaneous brain activity changes in acute SCI. In this study, we investigated intrinsic brain activity in acute SCI patients using a regional homogeneity (ReHo analysis based on resting-state functional magnetic resonance imaging.A total of 15 patients with acute SCI and 16 healthy controls participated in the study. The ReHo value was used to evaluate spontaneous brain activity, and voxel-wise comparisons of ReHo were performed to identify brain regions with altered spontaneous brain activity between groups. We also assessed the associations between ReHo and the clinical scores in brain regions showing changed spontaneous brain activity.Compared with the controls, the acute SCI patients showed decreased ReHo in the bilateral primary motor cortex/primary somatosensory cortex, bilateral supplementary motor area/dorsal lateral prefrontal cortex, right inferior frontal gyrus, bilateral dorsal anterior cingulate cortex and bilateral caudate; and increased ReHo in bilateral precuneus, the left inferior parietal lobe, the left brainstem/hippocampus, the left cingulate motor area, bilateral insula, bilateral thalamus and bilateral cerebellum. The average ReHo values of the left thalamus and right insula were negatively correlated with the international standards for the neurological classification of spinal cord injury motor scores.Our findings indicate that acute distant neuronal damage has an immediate impact on spontaneous brain activity. In acute SCI patients, the ReHo was prominently altered in brain regions involved in motor execution and cognitive control, default mode network, and which are associated with sensorimotor compensatory reorganization. Abnormal ReHo values in the left thalamus and right insula could serve as potential biomarkers for

  14. Altered baseline brain activity with 72 h of simulated microgravity--initial evidence from resting-state fMRI.

    Directory of Open Access Journals (Sweden)

    Yang Liao

    Full Text Available To provide the basis and reference to further insights into the neural activity of the human brain in a microgravity environment, we discuss the amplitude changes of low-frequency brain activity fluctuations using a simulated microgravity model. Twelve male participants between 24 and 31 years old received resting-state fMRI scans in both a normal condition and after 72 hours in a -6° head down tilt (HDT. A paired sample t-test was used to test the amplitude differences of low-frequency brain activity fluctuations between these two conditions. With 72 hours in a -6° HDT, the participants showed a decreased amplitude of low-frequency fluctuations in the left thalamus compared with the normal condition (a combined threshold of P<0.005 and a minimum cluster size of 351 mm(3 (13 voxels, which corresponded with the corrected threshold of P<0.05 determined by AlphaSim. Our findings indicate that a gravity change-induced redistribution of body fluid may disrupt the function of the left thalamus in the resting state, which may contribute to reduced motor control abilities and multiple executive functions in astronauts in a microgravity environment.

  15. Correlation between the Effects of Acupuncture at Taichong (LR3) and Functional Brain Areas: A Resting-State Functional Magnetic Resonance Imaging Study Using True versus Sham Acupuncture

    OpenAIRE

    Chunxiao Wu; Shanshan Qu; Jiping Zhang; Junqi Chen; Shaoqun Zhang; Zhipeng Li; Jiarong Chen; Huailiang Ouyang; Yong Huang; Chunzhi Tang

    2014-01-01

    Functional magnetic resonance imaging (fMRI) has been shown to detect the specificity of acupuncture points, as proved by numerous studies. In this study, resting-state fMRI was used to observe brain areas activated by acupuncture at the Taichong (LR3) acupoint. A total of 15 healthy subjects received brain resting-state fMRI before acupuncture and after sham and true acupuncture, respectively, at LR3. Image data processing was performed using Data Processing Assistant for Resting-State fMRI ...

  16. Watching the fetal brain at 'rest'.

    Science.gov (United States)

    Schöpf, V; Kasprian, G; Brugger, P C; Prayer, D

    2012-02-01

    Functional magnetic resonance imaging (fMRI) has allowed insights into the spatiotemporal distribution of human brain networks. According to the neurophysiological property of the fetal brain to generate spontaneous activity, we aimed to determine the feasibility of investigating the maturation of intrinsic networks, beginning at gestational week 20 in healthy human fetuses by combining resting-state fMRI and an analytical approach, independent component analysis (ICA). In this study, functional images of 16 fetuses with morphologically normal brain development, from 20 to 36 gestational weeks of age, were acquired on a 1.5T unit (Philips Medical Systems, Best, The Netherlands) using single-shot, gradient-recalled echo-planar imaging. After preprocessing (motion correction, brain extraction), images were analyzed using single-subject ICA. We visualized a bilateral occipital network and medial and lateral prefrontal activity pattern that involved the future Brodmann areas 9-11. Furthermore, there was one either predominantly right (3/7 cases) or left (4/7 cases) hemispheric lateralized network that involved the superior temporal cortical regions (Brodmann areas 22 and 39). Frequency oscillations were in the range of 0.01-0.06Hz for all networks. This study shows that resting-state networks (RSNs) are shaped and are detectable in utero. Further investigations of resting-state measurements in the fetus may therefore allow developmental brain activity monitoring and may provide insights into early brain function. PMID:22044604

  17. Recursive cluster elimination based support vector machine for disease state prediction using resting state functional and effective brain connectivity.

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    Gopikrishna Deshpande

    Full Text Available BACKGROUND: Brain state classification has been accomplished using features such as voxel intensities, derived from functional magnetic resonance imaging (fMRI data, as inputs to efficient classifiers such as support vector machines (SVM and is based on the spatial localization model of brain function. With the advent of the connectionist model of brain function, features from brain networks may provide increased discriminatory power for brain state classification. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we introduce a novel framework where in both functional connectivity (FC based on instantaneous temporal correlation and effective connectivity (EC based on causal influence in brain networks are used as features in an SVM classifier. In order to derive those features, we adopt a novel approach recently introduced by us called correlation-purged Granger causality (CPGC in order to obtain both FC and EC from fMRI data simultaneously without the instantaneous correlation contaminating Granger causality. In addition, statistical learning is accelerated and performance accuracy is enhanced by combining recursive cluster elimination (RCE algorithm with the SVM classifier. We demonstrate the efficacy of the CPGC-based RCE-SVM approach using a specific instance of brain state classification exemplified by disease state prediction. Accordingly, we show that this approach is capable of predicting with 90.3% accuracy whether any given human subject was prenatally exposed to cocaine or not, even when no significant behavioral differences were found between exposed and healthy subjects. CONCLUSIONS/SIGNIFICANCE: The framework adopted in this work is quite general in nature with prenatal cocaine exposure being only an illustrative example of the power of this approach. In any brain state classification approach using neuroimaging data, including the directional connectivity information may prove to be a performance enhancer. When brain state

  18. Alzheimer’s Biomarkers are Correlated with Brain Connectivity in Older Adults Differentially during Resting and Task States

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    Yang eJiang

    2016-02-01

    Full Text Available ß-amyloid (Aß plaques and tau-related neurodegeneration are pathologic hallmarks of Alzheimer’s disease (AD. The utility of AD biomarkers, including those measured in cerebrospinal fluid (CSF, in predicting future AD risk and cognitive decline is still being refined. Here we explored potential relationships between functional connectivity patterns within the default-mode network (DMN, age, CSF biomarkers (Aß42 and pTau181 and cognitive status in older adults. Multiple measures of functional connectivity were explored including a novel time series based measure (Total Interdependence; TI. In our sample of 27 cognitively normal older adults, no significant associations were found between levels of Aß42 or pTau181 and cognitive scores or regional brain volumes. However, we observed several novel relationships between these biomarkers and measures of functional connectivity in DMN during both resting-state and a short-term memory task. First, increased connectivity between bilateral anterior middle temporal gyri was associated with higher levels of CSF Aβ42 and Aβ42/pTau181 ratio (reflecting lower AD risk during both rest and task. Second, increased bilateral parietal connectivity during the short-term memory task, but not during rest, was associated with higher levels of CSF pTau181 (reflecting higher AD risk. Third, increased connectivity between left middle temporal and left parietal cortices during the active task was associated with decreased global cognitive status but not CSF biomarkers. Lastly, we found that our new TI method was more sensitive to the CSF Aβ42-connectivity relationship whereas the traditional cross-correlation method was more sensitive to levels of CSF pTau181 and cognitive status. With further refinement, resting-state connectivity and task-driven connectivity measures hold promise as non-invasive neuroimaging markers of Aβ and pTau burden in cognitively normal older adults.

  19. Altered Functional Connectivity within and between Brain Modules in Absence Epilepsy: A Resting-State Functional Magnetic Resonance Imaging Study

    Directory of Open Access Journals (Sweden)

    Cui-Ping Xu

    2013-01-01

    Full Text Available Functional connectivity has been correlated with a patient’s level of consciousness and has been found to be altered in several neuropsychiatric disorders. Absence epilepsy patients, who experience a loss of consciousness, are assumed to suffer from alterations in thalamocortical networks; however, previous studies have not explored the changes at a functional module level. We used resting-state functional magnetic resonance imaging to examine the alteration in functional connectivity that occurs in absence epilepsy patients. By parcellating the brain into 90 brain regions/nodes, we uncovered an altered functional connectivity within and between functional modules. Some brain regions had a greater number of altered connections and therefore behaved as key nodes in the changed network pattern; these regions included the superior frontal gyrus, the amygdala, and the putamen. In particular, the superior frontal gyrus demonstrated both an increased value of connections with other nodes of the frontal default mode network and a decreased value of connections with the limbic system. This divergence is positively correlated with epilepsy duration. These findings provide a new perspective and shed light on how functional connectivity and the balance of within/between module connections may contribute to both the state of consciousness and the development of absence epilepsy.

  20. Decreased Regional Homogeneity in Patients With Acute Mild Traumatic Brain Injury: A Resting-State fMRI Study.

    Science.gov (United States)

    Zhan, Jie; Gao, Lei; Zhou, Fuqing; Kuang, Hongmei; Zhao, Jing; Wang, Siyong; He, Laichang; Zeng, Xianjun; Gong, Honghan

    2015-10-01

    Mild traumatic brain injury (mTBI) is characterized by structural disconnection and large-scale neural network dysfunction in the resting state. However, little is known concerning the intrinsic changes in local spontaneous brain activity in patients with mTBI. The aim of the current study was to assess regional synchronization in acute mTBI patients. Fifteen acute mTBI patients and 15 sex-, age-, and education-matched healthy controls (HCs) were studied. We used the regional homogeneity (ReHo) method to map local connectivity across the whole brain and performed a two-sample t-test between the two groups. Compared with HCs, patients with acute mTBI showed significantly decreased ReHo in the left insula, left precentral/postcentral gyrus, and left supramarginal gyrus (p Mental State Examination (MMSE) scores across all acute mTBI patients (p < 0.05, uncorrected). The ReHo method may provide an objective biomarker for evaluating the functional abnormity of mTBI in the acute setting. PMID:26348589

  1. A multi-methodological MR resting state network analysis to assess the changes in brain physiology of children with ADHD.

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    Benito de Celis Alonso

    Full Text Available The purpose of this work was to highlight the neurological differences between the MR resting state networks of a group of children with ADHD (pre-treatment and an age-matched healthy group. Results were obtained using different image analysis techniques. A sample of n = 46 children with ages between 6 and 12 years were included in this study (23 per cohort. Resting state image analysis was performed using ReHo, ALFF and ICA techniques. ReHo and ICA represent connectivity analyses calculated with different mathematical approaches. ALFF represents an indirect measurement of brain activity. The ReHo and ICA analyses suggested differences between the two groups, while the ALFF analysis did not. The ReHo and ALFF analyses presented differences with respect to the results previously reported in the literature. ICA analysis showed that the same resting state networks that appear in healthy volunteers of adult age were obtained for both groups. In contrast, these networks were not identical when comparing the healthy and ADHD groups. These differences affected areas for all the networks except the Right Memory Function network. All techniques employed in this study were used to monitor different cerebral regions which participate in the phenomenological characterization of ADHD patients when compared to healthy controls. Results from our three analyses indicated that the cerebellum and mid-frontal lobe bilaterally for ReHo, the executive function regions in ICA, and the precuneus, cuneus and the clacarine fissure for ALFF, were the "hubs" in which the main inter-group differences were found. These results do not just help to explain the physiology underlying the disorder but open the door to future uses of these methodologies to monitor and evaluate patients with ADHD.

  2. A single session of exercise increases connectivity in sensorimotor-related brain networks: a resting-state fMRI study in young healthy adults

    OpenAIRE

    Rajab, Ahmad S.; Crane, David E.; Middleton, Laura E; Robertson, Andrew D.; Hampson, Michelle; Bradley J MacIntosh

    2014-01-01

    Habitual long term physical activity is known to have beneficial cognitive, structural, and neuro-protective brain effects, but to date there is limited knowledge on whether a single session of exercise can alter the brain’s functional connectivity, as assessed by resting-state functional magnetic resonance imaging (rs-fMRI). The primary objective of this study was to characterize potential session effects in resting-state networks (RSNs). We examined the acute effects of exercise on the func...

  3. Frequency-dependent brain regional homogeneity alterations in patients with mild cognitive impairment during working memory state relative to resting state

    Directory of Open Access Journals (Sweden)

    Pengyun eWang

    2016-03-01

    Full Text Available Several studies have reported working memory deficits in patients with mild cognitive impairment (MCI. However, previous studies investigating the neural mechanisms of MCI have primarily focused on brain activity alterations during working memory tasks. No study to date has compared brain network alterations in the working memory state between MCI patients and normal control subjects. Therefore, using the index of regional homogeneity (ReHo, we explored brain network impairments in MCI patients during a working memory task relative to the resting state, and identified frequency-dependent effects in separate frequency bands.Our results indicate that, in MCI patients, ReHo is altered in the posterior cingulate cortex in the slow-3 band (0.073–0.198 Hz, and in the bottom of the right occipital lobe and part of the right cerebellum, the right thalamus, a diffusing region in the bilateral prefrontal cortex, the left and right parietal-occipital regions, and the right angular gyrus in the slow-5 band (0.01–0.027 Hz. Furthermore, in normal controls, the value of ReHo in clusters belonging to the default mode network decreased, while the value of ReHo in clusters belonging to the attentional network increased during the task state. However, this pattern was reversed in MCI patients, and was associated with decreased working memory performance. In addition, we identified altered functional connectivity of the abovementioned regions with other parts of the brain in MCI patients.This is the first study to compare frequency-dependent alterations of ReHo in MCI patients between resting and working memory states. The results provide a new perspective regarding the neural mechanisms of working memory deficits in MCI patients, and extend our knowledge of altered brain patterns in resting and task-evoked states.

  4. Disrupted brain network topology in pediatric posttraumatic stress disorder: A resting-state fMRI study.

    Science.gov (United States)

    Suo, Xueling; Lei, Du; Li, Kaiming; Chen, Fuqin; Li, Fei; Li, Lei; Huang, Xiaoqi; Lui, Su; Li, Lingjiang; Kemp, Graham J; Gong, Qiyong

    2015-09-01

    Children exposed to natural disasters are vulnerable to the development of posttraumatic stress disorder (PTSD). Recent studies of other neuropsychiatric disorders have used graph-based theoretical analysis to investigate the topological properties of the functional brain connectome. However, little is known about this connectome in pediatric PTSD. Twenty-eight pediatric PTSD patients and 26 trauma-exposed non-PTSD patients were recruited from 4,200 screened subjects after the 2008 Sichuan earthquake to undergo a resting-state functional magnetic resonance imaging scan. Functional connectivity between 90 brain regions from the automated anatomical labeling atlas was established using partial correlation coefficients, and the whole-brain functional connectome was constructed by applying a threshold to the resultant 90 * 90 partial correlation matrix. Graph theory analysis was then used to examine the group-specific topological properties of the two functional connectomes. Both the PTSD and non-PTSD control groups exhibited "small-world" brain network topology. However, the functional connectome of the PTSD group showed a significant increase in the clustering coefficient and a normalized characteristic path length and local efficiency, suggesting a shift toward regular networks. Furthermore, the PTSD connectomes showed both enhanced nodal centralities, mainly in the default mode- and salience-related regions, and reduced nodal centralities, mainly in the central-executive network regions. The clustering coefficient and nodal efficiency of the left superior frontal gyrus were positively correlated with the Clinician-Administered PTSD Scale. These disrupted topological properties of the functional connectome help to clarify the pathogenesis of pediatric PTSD and could be potential biomarkers of brain abnormalities. PMID:26096541

  5. Towards ultrahigh resting-state functional connectivity in the mouse brain using photoacoustic microscopy

    Science.gov (United States)

    Hariri, Ali; Bely, Nicholas; Chen, Chen; Nasiriavanaki, Mohammadreza

    2016-03-01

    The increasing use of mouse models for human brain disease studies, coupled with the fact that existing high-resolution functional imaging modalities cannot be easily applied to mice, presents an emerging need for a new functional imaging modality. Utilizing both mechanical and optical scanning in the photoacoustic microscopy, we can image spontaneous cerebral hemodynamic fluctuations and their associated functional connections in the mouse brain. The images is going to be acquired noninvasively with a fast frame rate, a large field of view, and a high spatial resolution. We developed an optical resolution photoacoustic microscopy (OR-PAM) with diode laser. Laser light was raster scanned due to XY-stage movement. Images from ultra-high OR-PAM can then be used to study brain disorders such as stroke, Alzheimer's, schizophrenia, multiple sclerosis, autism, and epilepsy.

  6. A human brain atlas derived via n-cut parcellation of resting-state and task-based fMRI data.

    Science.gov (United States)

    James, George Andrew; Hazaroglu, Onder; Bush, Keith A

    2016-02-01

    The growth of functional MRI has led to development of human brain atlases derived by parcellating resting-state connectivity patterns into functionally independent regions of interest (ROIs). All functional atlases to date have been derived from resting-state fMRI data. But given that functional connectivity between regions varies with task, we hypothesized that an atlas incorporating both resting-state and task-based fMRI data would produce an atlas with finer characterization of task-relevant regions than an atlas derived from resting-state alone. To test this hypothesis, we derived parcellation atlases from twenty-nine healthy adult participants enrolled in the Cognitive Connectome project, an initiative to improve functional MRI's translation into clinical decision-making by mapping normative variance in brain-behavior relationships. Participants underwent resting-state and task-based fMRI spanning nine cognitive domains: motor, visuospatial, attention, language, memory, affective processing, decision-making, working memory, and executive function. Spatially constrained n-cut parcellation derived brain atlases using (1) all participants' functional data (Task) or (2) a single resting-state scan (Rest). An atlas was also derived from random parcellation for comparison purposes (Random). Two methods were compared: (1) a parcellation applied to the group's mean edge weights (mean), and (2) a two-stage approach with parcellation of individual edge weights followed by parcellation of mean binarized edges (two-stage). The resulting Task and Rest atlases had significantly greater similarity with each other (mean Jaccard indices JI=0.72-0.85) than with the Random atlases (JI=0.59-0.63; all patlas similarity was greatest for the two-stage method (JI=0.85), which has been shown as more robust than the mean method; these atlases also better reproduced voxelwise seed maps of the left dorsolateral prefrontal cortex during rest and performing the n-back working memory task

  7. Altered baseline brain activities before food intake in obese men: a resting state fMRI study.

    Science.gov (United States)

    Zhang, Bin; Tian, Derun; Yu, Chunshui; Zhang, Jing; Tian, Xiao; von Deneen, Karen M; Zang, Yufeng; Walter, Martin; Liu, Yijun

    2015-01-01

    Obesity as a chronic disease has become a global epidemic. However, why obese individuals eat more still remains unclear. Recent functional neuroimaging studies have found abnormal brain activations in obese people. In the present study, we used resting state functional MRI to observe spontaneous blood-oxygen-level dependent (BOLD) signal fluctuations during both hunger and satiety states in 20 lean and 20 obese men. Using a regional homogeneity (ReHo) analysis method, we measured temporal homogeneity of the regional BOLD signals. We found that, before food intake, obese men had significantly increased synchronicity of activity in the left putamen relative to lean men. Decreased synchronicity of activity was found in the orbitofrontal cortex (OFC) and medial prefrontal cortex(MPFC) in the obese subjects. And, the ratings of hunger of the obese subjects were higher than those of the lean subjects before food intake. After food intake, we did not find the significant differences between the obese men and the lean men. In all participations, synchronicity of activity increased from the fasted to the satiated state in the OFC. The results indicated that OFC plays an important role in feeding behavior, and OFC signaling may be disordered in obesity. Obese men show less inhibitory control during fasting state. This study has provided strong evidence supporting the hypothesis that there is a hypo-functioning reward circuitry in obese individuals, in which the frontal cortex may fail to inhibit the striatum, and consequently lead to overeating and obesity. PMID:25459293

  8. Affect and the brain's functional organization: a resting-state connectivity approach.

    Directory of Open Access Journals (Sweden)

    Christiane S Rohr

    Full Text Available The question of how affective processing is organized in the brain is still a matter of controversial discussions. Based on previous initial evidence, several suggestions have been put forward regarding the involved brain areas: (a right-lateralized dominance in emotional processing, (b hemispheric dominance according to positive or negative valence, (c one network for all emotional processing and (d region-specific discrete emotion matching. We examined these hypotheses by investigating intrinsic functional connectivity patterns that covary with results of the Positive and Negative Affective Schedule (PANAS from 65 participants. This approach has the advantage of being able to test connectivity rather than activation, and not requiring a potentially confounding task. Voxelwise functional connectivity from 200 regions-of-interest covering the whole brain was assessed. Positive and negative affect covaried with functional connectivity involving a shared set of regions, including the medial prefrontal cortex, the anterior cingulate, the visual cortex and the cerebellum. In addition, each affective domain had unique connectivity patterns, and the lateralization index showed a right hemispheric dominance for negative affect. Therefore, our results suggest a predominantly right-hemispheric network with affect-specific elements as the underlying organization of emotional processes.

  9. Modular Reorganization of Brain Resting State Networks and Its Independent Validation in Alzheimer’s Disease Patients

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    Guangyu eChen

    2013-08-01

    Full Text Available Previous studies have demonstrated disruption in structural and functional connectivity occurring in the Alzheimer’s Disease (AD. However, it is not known how these disruptions alter brain network reorganization. With the modular analysis method of graph theory, and datasets acquired by the resting-state functional connectivity MRI (R-fMRI method, we investigated and compared the brain organization patterns between the AD group and the cognitively normal control (CN group. Our main finding is that the largest homotopic module (defined as the insula module in the CN group was broken down to the pieces in the AD group. Specifically, it was discovered that the eight pairs of the bilateral regions (the opercular part of inferior frontal gyrus, area triangularis, insula, putamen, globus pallidus, transverse temporal gyri, superior temporal gyrus, and superior temporal pole of the insula module had lost symmetric functional connection properties, and the corresponding gray matter concentration (GMC was significant lower in AD group. We further quantified the functional connectivity changes with an index (index A and structural changes with the GMC index in the insula module to demonstrate their great potential as AD biomarkers. We further validated these results with six additional independent datasets (271 subjects in six groups. Our results demonstrated specific underlying structural and functional reorganization from young to old, and for diseased subjects. Further, it is suggested that by combining the structural GMC analysis and functional modular analysis in the insula module, a new biomarker can be developed at the single-subject level.

  10. Correlation between the Effects of Acupuncture at Taichong (LR3) and Functional Brain Areas: A Resting-State Functional Magnetic Resonance Imaging Study Using True versus Sham Acupuncture.

    Science.gov (United States)

    Wu, Chunxiao; Qu, Shanshan; Zhang, Jiping; Chen, Junqi; Zhang, Shaoqun; Li, Zhipeng; Chen, Jiarong; Ouyang, Huailiang; Huang, Yong; Tang, Chunzhi

    2014-01-01

    Functional magnetic resonance imaging (fMRI) has been shown to detect the specificity of acupuncture points, as proved by numerous studies. In this study, resting-state fMRI was used to observe brain areas activated by acupuncture at the Taichong (LR3) acupoint. A total of 15 healthy subjects received brain resting-state fMRI before acupuncture and after sham and true acupuncture, respectively, at LR3. Image data processing was performed using Data Processing Assistant for Resting-State fMRI and REST software. The combination of amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) was used to analyze the changes in brain function during sham and true acupuncture. Acupuncture at LR3 can specifically activate or deactivate brain areas related to vision, movement, sensation, emotion, and analgesia. The specific alterations in the anterior cingulate gyrus, thalamus, and cerebellar posterior lobe have a crucial effect and provide a valuable reference. Sham acupuncture has a certain effect on psychological processes and does not affect brain areas related to function. PMID:24963329

  11. Relationship between episodic memory and resting-state brain functional connectivity network in patients with Alzheimer’s disease and mild cognition impairment

    Institute of Scientific and Technical Information of China (English)

    吴钦娟

    2013-01-01

    Objective To explore the relationship between the scores of episodic memory (EM) encoding and retrieving and the resting-state changes of brain functional connectivity (FC) network of Alzheimer’s disease (AD) and mild cognition impairment (MCI) patients.Methods All

  12. Exploring the brains of Baduk (Go) experts: gray matter morphometry, resting-state functional connectivity, and graph theoretical analysis

    OpenAIRE

    Wi Hoon eJung; Sung Nyun eKim; Tae Young eLee; Joon Hwan eJang; Chi-Hoon eChoi; Do-Hyung eKang; Jun Soo eKwon

    2013-01-01

    One major characteristic of experts is intuitive judgment, which is an automatic process whereby patterns stored in memory through long-term training are recognized. Indeed, long-term training may influence brain structure and function. A recent study revealed that chess experts at rest showed differences in structure and functional connectivity (FC) in the head of caudate, which is associated with rapid best next-move generation. However, less is known about the structure and function of the...

  13. The Whole-Brain "Global" Signal from Resting State fMRI as a Potential Biomarker of Quantitative State Changes in Glucose Metabolism.

    Science.gov (United States)

    Thompson, Garth J; Riedl, Valentin; Grimmer, Timo; Drzezga, Alexander; Herman, Peter; Hyder, Fahmeed

    2016-07-01

    The evolution of functional magnetic resonance imaging to resting state (R-fMRI) allows measurement of changes in brain networks attributed to state changes, such as in neuropsychiatric diseases versus healthy controls. Since these networks are observed by comparing normalized R-fMRI signals, it is difficult to determine the metabolic basis of such group differences. To investigate the metabolic basis of R-fMRI network differences within a normal range, eyes open versus eyes closed in healthy human subjects was used. R-fMRI was recorded simultaneously with fluoro-deoxyglucose positron emission tomography (FDG-PET). Higher baseline FDG was observed in the eyes open state. Variance-based metrics calculated from R-fMRI did not match the baseline shift in FDG. Functional connectivity density (FCD)-based metrics showed a shift similar to the baseline shift of FDG, however, this was lost if R-fMRI "nuisance signals" were regressed before FCD calculation. Average correlation with the mean R-fMRI signal across the whole brain, generally regarded as a "nuisance signal," also showed a shift similar to the baseline of FDG. Thus, despite lacking a baseline itself, changes in whole-brain correlation may reflect changes in baseline brain metabolism. Conversely, variance-based metrics may remain similar between states due to inherent region-to-region differences overwhelming the differences between normal physiological states. As most previous studies have excluded the spatial means of R-fMRI metrics from their analysis, this work presents the first evidence of a potential R-fMRI biomarker for baseline shifts in quantifiable metabolism between brain states. PMID:27029438

  14. A single session of exercise increases connectivity in sensorimotor-related brain networks: A resting-state fMRI study in young healthy adults

    OpenAIRE

    Ahmad Saeed Rajab; Crane, David E.; Middleton, Laura E; Andrew eRobertson; Michelle eHampson; Bradley J MacIntosh

    2014-01-01

    Habitual long term physical activity is known to have beneficial cognitive, structural and neuro-protective brain effects, but to date there is limited knowledge on whether a single session of exercise can alter the brain’s functional connectivity, as assessed by resting-state fMRI (rs-fMRI). The primary objective of this study was to characterize potential session effects in resting state networks (RSNs). We examined the acute effects of exercise on the functional connectivity of young healt...

  15. The Amsterdam Resting-State Questionnaire reveals multiple phenotypes of resting-state cognition

    Directory of Open Access Journals (Sweden)

    B. Alexander eDiaz

    2013-08-01

    Full Text Available Resting-state neuroimaging is a dominant paradigm for studying brain function in health and disease. It is attractive for clinical research because of its simplicity for patients, straightforward standardization, and sensitivity to brain disorders. Importantly, non-sensory experiences like mind wandering may arise from ongoing brain activity. However, little is known about the link between ongoing brain activity and cognition, as phenotypes of resting-state cognition—and tools to quantify them—have been lacking. To facilitate rapid and structured measurements of resting-state cognition we developed a 50-item self-report survey, the Amsterdam Resting-State Questionnaire (ARSQ. Based on ARSQ data from 813 participants assessed after five minutes eyes-closed rest in their home, we identified seven dimensions of resting-state cognition using factor analysis: Discontinuity of Mind, Theory of Mind, Self, Planning, Sleepiness, Comfort, and Somatic Awareness. Further, we showed that the structure of cognition was similar during resting-state fMRI and EEG, and that the test-retest correlations were remarkably high for all dimensions. To explore whether inter-individual variation of resting-state cognition is related to health status, we correlated ARSQ-derived factor scores with psychometric scales measuring depression, anxiety, and sleep quality. Mental health correlated positively with Comfort and negatively with Discontinuity of Mind. Finally, we show that sleepiness may partially explain a resting-state EEG profile previously associated with Alzheimer’s disease. These findings indicate that the ARSQ readily provides information about cognitive phenotypes and that it is a promising tool for research on the neural correlates of resting-state cognition in health and disease.

  16. Selective Activation of Resting-State Networks following Focal Stimulation in a Connectome-Based Network Model of the Human Brain

    Science.gov (United States)

    2016-01-01

    Abstract When the brain is stimulated, for example, by sensory inputs or goal-oriented tasks, the brain initially responds with activities in specific areas. The subsequent pattern formation of functional networks is constrained by the structural connectivity (SC) of the brain. The extent to which information is processed over short- or long-range SC is unclear. Whole-brain models based on long-range axonal connections, for example, can partly describe measured functional connectivity dynamics at rest. Here, we study the effect of SC on the network response to stimulation. We use a human whole-brain network model comprising long- and short-range connections. We systematically activate each cortical or thalamic area, and investigate the network response as a function of its short- and long-range SC. We show that when the brain is operating at the edge of criticality, stimulation causes a cascade of network recruitments, collapsing onto a smaller space that is partly constrained by SC. We found both short- and long-range SC essential to reproduce experimental results. In particular, the stimulation of specific areas results in the activation of one or more resting-state networks. We suggest that the stimulus-induced brain activity, which may indicate information and cognitive processing, follows specific routes imposed by structural networks explaining the emergence of functional networks. We provide a lookup table linking stimulation targets and functional network activations, which potentially can be useful in diagnostics and treatments with brain stimulation. PMID:27752540

  17. Exploring the brains of Baduk (Go) experts: gray matter morphometry, resting-state functional connectivity, and graph theoretical analysis.

    Science.gov (United States)

    Jung, Wi Hoon; Kim, Sung Nyun; Lee, Tae Young; Jang, Joon Hwan; Choi, Chi-Hoon; Kang, Do-Hyung; Kwon, Jun Soo

    2013-01-01

    One major characteristic of experts is intuitive judgment, which is an automatic process whereby patterns stored in memory through long-term training are recognized. Indeed, long-term training may influence brain structure and function. A recent study revealed that chess experts at rest showed differences in structure and functional connectivity (FC) in the head of caudate, which is associated with rapid best next-move generation. However, less is known about the structure and function of the brains of Baduk experts (BEs) compared with those of experts in other strategy games. Therefore, we performed voxel-based morphometry (VBM) and FC analyses in BEs to investigate structural brain differences and to clarify the influence of these differences on functional interactions. We also conducted graph theoretical analysis (GTA) to explore the topological organization of whole-brain functional networks. Compared to novices, BEs exhibited decreased and increased gray matter volume (GMV) in the amygdala and nucleus accumbens (NA), respectively. We also found increased FC between the amygdala and medial orbitofrontal cortex (mOFC) and decreased FC between the NA and medial prefrontal cortex (mPFC). Further GTA revealed differences in measures of the integration of the network and in the regional nodal characteristics of various brain regions activated during Baduk. This study provides evidence for structural and functional differences as well as altered topological organization of the whole-brain functional networks in BEs. Our findings also offer novel suggestions about the cognitive mechanisms behind Baduk expertise, which involves intuitive decision-making mediated by somatic marker circuitry and visuospatial processing. PMID:24106471

  18. Exploring the brains of Baduk (Go experts: gray matter morphometry, resting-state functional connectivity, and graph theoretical analysis

    Directory of Open Access Journals (Sweden)

    Wi Hoon eJung

    2013-10-01

    Full Text Available One major characteristic of experts is intuitive judgment, which is an automatic process whereby patterns stored in memory through long-term training are recognized. Indeed, long-term training may influence brain structure and function. A recent study revealed that chess experts at rest showed differences in structure and functional connectivity (FC in the head of caudate, which is associated with rapid best next-move generation. However, less is known about the structure and function of the brains of Baduk experts compared with those of experts in other strategy games. Therefore, we performed voxel-based morphometry and FC analyses in Baduk experts to investigate structural brain differences and to clarify the influence of these differences on functional interactions. We also conducted graph theoretical analysis to explore the topological organization of whole-brain functional networks. Compared to novices, Baduk experts exhibited decreased and increased gray matter volume in the amygdala and nucleus accumbens, respectively. We also found increased FC between the amygdala and medial orbitofrontal cortex and decreased FC between the nucleus accumbens and medial prefrontal cortex. Further graph theoretical analysis revealed differences in measures of the integration of the network and in the regional nodal characteristics of various brain regions activated during Baduk. This study provides evidence for structural and functional differences as well as altered topological organization of the whole-brain functional networks in Baduk experts. Our findings also offer novel suggestions about the cognitive mechanisms behind Baduk expertise, which involves intuitive decision-making mediated by somatic marker circuitry and visuospatial processing.

  19. Is Traumatic Brain Injury Associated with Reduced Inter-Hemispheric Functional Connectivity? A Study of Large-Scale Resting State Networks following Traumatic Brain Injury.

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    Rigon, Arianna; Duff, Melissa C; McAuley, Edward; Kramer, Arthur F; Voss, Michelle W

    2016-06-01

    Traumatic brain injury (TBI) often has long-term debilitating sequelae in cognitive and behavioral domains. Understanding how TBI impacts functional integrity of brain networks that underlie these domains is key to guiding future approaches to TBI rehabilitation. In the current study, we investigated the differences in inter-hemispheric functional connectivity (FC) of resting state networks (RSNs) between chronic mild-to-severe TBI patients and normal comparisons (NC), focusing on two externally oriented networks (i.e., the fronto-parietal network [FPN] and the executive control network [ECN]), one internally oriented network (i.e., the default mode network [DMN]), and one somato-motor network (SMN). Seed voxel correlation analysis revealed that TBI patients displayed significantly less FC between lateralized seeds and both homologous and non-homologous regions in the opposite hemisphere for externally oriented networks but not for DMN or SMN; conversely, TBI patients showed increased FC within regions of the DMN, especially precuneus and parahippocampal gyrus. Region of interest correlation analyses confirmed the presence of significantly higher inter-hemispheric FC in NC for the FPN (p  0.05) or SMN (p > 0.05). Further analysis revealed that performance on a neuropsychological test measuring organizational skills and visuo-spatial abilities administered to the TBI group, the Rey-Osterrieth Complex Figure Test, positively correlated with FC between the right FPN and homologous regions. Our findings suggest that distinct RSNs display specific patterns of aberrant FC following TBI; this represents a step forward in the search for biomarkers useful for early diagnosis and treatment of TBI-related cognitive impairment. PMID:25719433

  20. Novel modeling of task versus rest brain state predictability using a dynamic time warping spectrum: comparisons and contrasts with other standard measures of brain dynamics

    Directory of Open Access Journals (Sweden)

    Martin eDinov

    2016-05-01

    Full Text Available Dynamic time warping, or DTW, is a powerful and domain-general sequence alignment method for computing a similarity measure. Such dynamic programming-based techniques like DTW are now the backbone and driver of most bioinformatics methods and discoveries. In neuroscience it has had far less use, though this has begun to change. We wanted to explore new ways of applying DTW, not simply as a measure with which to cluster or compare similarity between features but in a conceptually different way. We have used DTW to provide a more interpretable spectral description of the data, compared to standard approaches such as the Fourier and related transforms. The DTW approach and standard discrete Fourier transform (DFT are assessed against benchmark measures of neural dynamics. These include EEG microstates, EEG avalanches and the sum squared error (SSE from a multilayer perceptron (MLP prediction of the EEG timeseries, and simultaneously acquired FMRI BOLD signal. We explored the relationships between these variables of interest in an EEG-FMRI dataset acquired during a standard cognitive task, which allowed us to explore how DTW differentially performs in different task settings. We found that despite strong correlations between DTW and DFT-spectra, DTW was a better predictor for almost every measure of brain dynamics. Using these DTW measures, we show that predictability is almost always higher in task than in rest states, which is consistent to other theoretical and empirical findings, providing additional evidence for the utility of the DTW approach.

  1. Novel Modeling of Task vs. Rest Brain State Predictability Using a Dynamic Time Warping Spectrum: Comparisons and Contrasts with Other Standard Measures of Brain Dynamics

    Science.gov (United States)

    Dinov, Martin; Lorenz, Romy; Scott, Gregory; Sharp, David J.; Fagerholm, Erik D.; Leech, Robert

    2016-01-01

    Dynamic time warping, or DTW, is a powerful and domain-general sequence alignment method for computing a similarity measure. Such dynamic programming-based techniques like DTW are now the backbone and driver of most bioinformatics methods and discoveries. In neuroscience it has had far less use, though this has begun to change. We wanted to explore new ways of applying DTW, not simply as a measure with which to cluster or compare similarity between features but in a conceptually different way. We have used DTW to provide a more interpretable spectral description of the data, compared to standard approaches such as the Fourier and related transforms. The DTW approach and standard discrete Fourier transform (DFT) are assessed against benchmark measures of neural dynamics. These include EEG microstates, EEG avalanches, and the sum squared error (SSE) from a multilayer perceptron (MLP) prediction of the EEG time series, and simultaneously acquired FMRI BOLD signal. We explored the relationships between these variables of interest in an EEG-FMRI dataset acquired during a standard cognitive task, which allowed us to explore how DTW differentially performs in different task settings. We found that despite strong correlations between DTW and DFT-spectra, DTW was a better predictor for almost every measure of brain dynamics. Using these DTW measures, we show that predictability is almost always higher in task than in rest states, which is consistent to other theoretical and empirical findings, providing additional evidence for the utility of the DTW approach. PMID:27242502

  2. 静息态人脑功能网络的小世界特性%Small-World Properties of Resting State Human Brain Functional Networks

    Institute of Scientific and Technical Information of China (English)

    黄文涛; 冯又层

    2011-01-01

    研究了静息态下健康人脑的功能连接模式有助于理解人脑在正常或疾病状态下的功能活动规律.利用小波变换从健康志愿者静息态的功能磁共振成像中提取时间序列,计算90个脑区的相关性,设定阈值建立脑功能网络的无向简单图,然后计算特征路径长度和聚类系数,并对度分布进行拟合.结果显示:脑功能网络具有规则网络的大聚集系数又具有随机网络的小特征路径长度,度的拟合显示具有指数截断幂律分布,即脑功能网络具有小世界特性.%It is important to study the resting state functional pattern of healthy human brain because it will aid us to understand the law of functional activities of human brain in normal or disease states.Using wavelet transformation,time series of 90 brain regions were extracted from functional magnetic resonance imagines of resting state healthy volunteers.Functional correlations between brain regions were calculated,and the threshold was set to establish the simple undirected graph,then characteristic path length and clustering coefficient were computed,finally the degree distribution was fitted.The results demonstrated that the brain functional networks had both big clustering coefficients like regular networks and small characteristic path lengths similar as random networks,degree distribution met exponentially truncated power-law distribution.Taken together,the human brain functional networks have small world properties.

  3. White matter damage and brain network alterations in concussed patients: a review of recent diffusion tensor imaging and resting-state functional connectivity data.

    Science.gov (United States)

    Chong, Catherine D; Schwedt, Todd J

    2015-05-01

    Over 2 million people are diagnosed with concussion each year in the USA, resulting in substantial individual and societal burdens. Although 'routine' clinical neuroimaging is useful for the diagnosis of more severe forms of traumatic brain injury, it is insensitive for detecting pathology associated with concussion. Diffusion tensor imaging (DTI) and blood-oxygenation-level-dependent (BOLD) resting-state functional connectivity magnetic resonance imaging (rs-fMRI) are techniques that allow for investigation of brain structural and functional connectivity patterns. DTI and rs-fMRI may be more sensitive than routine neuroimaging for detecting brain sequelae of concussion. This review summarizes recent DTI and rs-fMRI findings of altered structural and functional connectivity patterns in concussed patients.

  4. THEORY OF MIND AND THE WHOLE BRAIN FUNCTIONAL CONNECTIVITY: BEHAVIORAL AND NEURAL EVIDENCES WITH THE AMSTERDAM RESTING STATE QUESTIONNAIRE

    Directory of Open Access Journals (Sweden)

    ANTONELLA eMARCHETTI

    2015-12-01

    Full Text Available A topic of common interest to psychologists and philosophers is the spontaneous flow of thoughts when the individual is awake but not involved in cognitive demands. This argument, classically referred to as the stream of consciousness of James, is now known in the psychological literature as Mind-Wandering. Although of great interest, this construct has been scarcely investigated so far. Diaz and colleagues (2013 created the Amsterdam Resting State Questionnaire (ARSQ, composed of 27 items, distributed in seven factors: discontinuity of mind, theory of mind (ToM, self, planning, sleepiness, comfort and somatic awareness. The present study aims at: testing psychometric properties of the ARSQ in a sample of 670 Italian subjects; exploring the neural correlates of a subsample of participants (N=28 divided into two groups on the basis of the scores obtained in the ToM factor. Results show a satisfactory reliability of the original factional structure in the Italian sample. In the subjects with a high mean in the ToM factor compared to low mean subjects, functional MRI revealed: a network (48 nodes with higher functional connectivity (FC with a dominance of the left hemisphere; an increased within-lobe FC in frontal and insular lobes. In both neural and behavioral terms, our results support the idea that the mind, which does not rest even when explicitly asked to do so, has various and interesting mentalistic-like contents.

  5. Spatially distributed effects of mental exhaustion on resting-state FMRI networks

    NARCIS (Netherlands)

    Esposito, Fabrizio; Otto, Tobias; Zijlstra, Fred R H; Goebel, R.

    2014-01-01

    Brain activity during rest is spatially coherent over functional connectivity networks called resting-state networks. In resting-state functional magnetic resonance imaging, independent component analysis yields spatially distributed network representations reflecting distinct mental processes, such

  6. Do resting brain dynamics predict oddball evoked-potential?

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    Lee Tien-Wen

    2011-11-01

    Full Text Available Abstract Background The oddball paradigm is widely applied to the investigation of cognitive function in neuroscience and in neuropsychiatry. Whether cortical oscillation in the resting state can predict the elicited oddball event-related potential (ERP is still not clear. This study explored the relationship between resting electroencephalography (EEG and oddball ERPs. The regional powers of 18 electrodes across delta, theta, alpha and beta frequencies were correlated with the amplitude and latency of N1, P2, N2 and P3 components of oddball ERPs. A multivariate analysis based on partial least squares (PLS was applied to further examine the spatial pattern revealed by multiple correlations. Results Higher synchronization in the resting state, especially at the alpha spectrum, is associated with higher neural responsiveness and faster neural propagation, as indicated by the higher amplitude change of N1/N2 and shorter latency of P2. None of the resting quantitative EEG indices predict P3 latency and amplitude. The PLS analysis confirms that the resting cortical dynamics which explains N1/N2 amplitude and P2 latency does not show regional specificity, indicating a global property of the brain. Conclusions This study differs from previous approaches by relating dynamics in the resting state to neural responsiveness in the activation state. Our analyses suggest that the neural characteristics carried by resting brain dynamics modulate the earlier/automatic stage of target detection.

  7. Predicting workload profiles of brain-robot interface and electromygraphic neurofeedback with cortical resting-state networks: personal trait or task-specific challenge?

    Science.gov (United States)

    Fels, Meike; Bauer, Robert; Gharabaghi, Alireza

    2015-08-01

    Objective. Novel rehabilitation strategies apply robot-assisted exercises and neurofeedback tasks to facilitate intensive motor training. We aimed to disentangle task-specific and subject-related contributions to the perceived workload of these interventions and the related cortical activation patterns. Approach. We assessed the perceived workload with the NASA Task Load Index in twenty-one subjects who were exposed to two different feedback tasks in a cross-over design: (i) brain-robot interface (BRI) with haptic/proprioceptive feedback of sensorimotor oscillations related to motor imagery, and (ii) control of neuromuscular activity with feedback of the electromyography (EMG) of the same hand. We also used electroencephalography to examine the cortical activation patterns beforehand in resting state and during the training session of each task. Main results. The workload profile of BRI feedback differed from EMG feedback and was particularly characterized by the experience of frustration. The frustration level was highly correlated across tasks, suggesting subject-related relevance of this workload component. Those subjects who were specifically challenged by the respective tasks could be detected by an interhemispheric alpha-band network in resting state before the training and by their sensorimotor theta-band activation pattern during the exercise. Significance. Neurophysiological profiles in resting state and during the exercise may provide task-independent workload markers for monitoring and matching participants’ ability and task difficulty of neurofeedback interventions.

  8. Differential effects of L-tryptophan and L-leucine administration on brain resting state functional networks and plasma hormone levels

    Science.gov (United States)

    Zanchi, Davide; Meyer-Gerspach, Anne Christin; Suenderhauf, Claudia; Janach, Katharina; le Roux, Carel W.; Haller, Sven; Drewe, Jürgen; Beglinger, Christoph; Wölnerhanssen, Bettina K.; Borgwardt, Stefan

    2016-01-01

    Depending on their protein content, single meals can rapidly influence the uptake of amino acids into the brain and thereby modify brain functions. The current study investigates the effects of two different amino acids on the human gut-brain system, using a multimodal approach, integrating physiological and neuroimaging data. In a randomized, placebo-controlled trial, L-tryptophan, L-leucine, glucose and water were administered directly into the gut of 20 healthy subjects. Functional MRI (fMRI) in a resting state paradigm (RS), combined with the assessment of insulin and glucose blood concentration, was performed before and after treatment. Independent component analysis with dual regression technique was applied to RS-fMRI data. Results were corrected for multiple comparisons. In comparison to glucose and water, L-tryptophan consistently modifies the connectivity of the cingulate cortex in the default mode network, of the insula in the saliency network and of the sensory cortex in the somatosensory network. L-leucine has lesser effects on these functional networks. L-tryptophan and L-leucine also modified plasma insulin concentration. Finally, significant correlations were found between brain modifications after L-tryptophan administration and insulin plasma levels. This study shows that acute L-tryptophan and L-leucine intake directly influence the brain networks underpinning the food-reward system and appetite regulation. PMID:27760995

  9. Abnormal intrinsic brain activity in amnestic mild cognitive impairment revealed by amplitude of low-frequency fluctuation: a resting-state functional magnetic resonance imaging study

    Institute of Scientific and Technical Information of China (English)

    XI Qian; ZHAO Xiao-hu; WANG Pei-jun; GUO Qi-hao; HE Yong

    2013-01-01

    Background Previous studies have shown that brain functional activity in the resting state is impaired in Alzheimer's disease (AD) patients.However,alterations in intrinsic brain activity patterns in mild cognitive impairment (MCI) patients are poorly understood.This study aimed to explore the differences in regional intrinsic activities throughout the whole brain between aMCI patients and controls.Methods In the present study,resting-state functional magnetic resonance imaging (fMRI) was performed on 18 amnestic MCI (aMCI) patients,18 mild AD patients and 20 healthy elderly subjects.And amplitude of low-frequency fluctuation (ALFF) method was used.Results Compared with healthy elderly subjects,aMCI patients showed decreased ALFF in the right hippocampus and parahippocampal cortex,left lateral temporal cortex,and right ventral medial prefrontal cortex (vMPFC) and increased ALFF in the left temporal-parietal junction (TPJ) and inferior parietal Iobule (IPL).Mild AD patients showed decreased ALFF in the left TPJ,posterior IPL (plPL),and dorsolateral prefrontal cortex compared with aMCI patients.Mild AD patients also had decreased ALFF in the right posterior cingulate cortex,right vMPFC and bilateral dorsal MPFC (dMPFC) compared with healthy elderly subjects.Conclusions Decreased intrinsic activities in brain regions closely related to episodic memory were found in aMCI and AD patients.Increased TPJ and IPL activity may indicate compensatory mechanisms for loss of memory function in aMCI patients.These findings suggest that the fMRI based on ALFF analysis may provide a useful tool in the study of aMCI patients.

  10. Changes in resting-state brain function of pilots after hypoxic exposure based on methods for fALFF and ReHo analysis

    Directory of Open Access Journals (Sweden)

    Jie LIU

    2015-07-01

    Full Text Available Objective The objective of this study was to evaluate the basic changes in brain activity of pilots after hypoxic exposure with the use of resting-state functional magnetic resonance imaging (rs-fMRI and regional homogeneity (ReHo method. Methods Thirty healthy male pilots were successively subjected to normal and hypoxic exposure (with an oxygen concentration of 14.5%. Both the fALFF and ReHo methods were adopted to analyze the resting-state functional MRI data before and after hypoxic exposure of the subjects, the areas of the brain with fALFF and ReHo changes after hypoxic exposure were observed. Results  After hypoxic exposure, the pulse was 64.0±10.6 beats/min, and the oxygen saturation was 92.4%±3.9% in these 30 pilots, and it was lower than those before exposure (71.4±10.9 beats/min, 96.3%±1.3%, P<0.05. Compared with the condition before hypoxic exposure, the fALFF value was decreased in superior temporal gyri on both sides and the right superior frontal gyrus, and increase in the left precuneus, while the value of ReHo was decreased in the right superior frontal gyrus (P<0.05. No brain area with an increase in ReHo value was found. Conclusions Hypoxic exposure could significantly affect the brain functions of pilots, which may contribute to change in their cognitive ability. DOI: 10.11855/j.issn.0577-7402.2015.06.18

  11. Recovery of resting brain connectivity ensuing mild traumatic brain injury

    Directory of Open Access Journals (Sweden)

    Rose Dawn Bharath

    2015-09-01

    Full Text Available Brains reveal amplified plasticity as they recover from an injury. We aimed to define time dependent plasticity changes in patients recovering from mild traumatic brain injury (mTBI. 25 subjects with mild head injury were longitudinally evaluated within 36 hours, 3 and 6 months using resting state functional connectivity (RSFC. Region of interest (ROI based connectivity differences over time within the patient group and in comparison with a healthy control group were analyzed at p<0.005. We found 33 distinct ROI pairs that revealed significant changes in their connectivity strength with time. Within three months, the majority of the ROI pairs had decreased connectivity in mTBI population, which increased and became comparable to healthy controls at 6 months. Initial imaging within 36 hours of injury revealed hyper connectivity predominantly involving the salience network and default mode network, which reduced at 3 months when lingual, inferior frontal and fronto-parietal networks revealed hyper connectivity. At six months all the evaluated networks revealed hyper connectivity and became comparable to the healthy controls. Our findings in a fairly homogenous group of patients with mTBI evaluated during the 6 month window of recovery defines time varying brain connectivity changes as the brain recovers from an injury. A majority of these changes were seen in the frontal and parietal lobes between 3-6 months after injury. Hyper connectivity of several networks supported normal recovery in the first six months and it remains to be seen in future studies whether this can predict an early and efficient recovery of brain function.

  12. Change in brain network topology as a function of treatment response in schizophrenia: a longitudinal resting-state fMRI study using graph theory.

    Science.gov (United States)

    Hadley, Jennifer Ann; Kraguljac, Nina Vanessa; White, David Matthew; Ver Hoef, Lawrence; Tabora, Janell; Lahti, Adrienne Carol

    2016-01-01

    A number of neuroimaging studies have provided evidence in support of the hypothesis that faulty interactions between spatially disparate brain regions underlie the pathophysiology of schizophrenia, but it remains unclear to what degree antipsychotic medications affect these. We hypothesized that the balance between functional integration and segregation of brain networks is impaired in unmedicated patients with schizophrenia, but that it can be partially restored by antipsychotic medications. We included 32 unmedicated patients with schizophrenia (SZ) and 32 matched healthy controls (HC) in this study. We obtained resting-state scans while unmedicated, and again after 6 weeks of treatment with risperidone to assess functional integration and functional segregation of brain networks using graph theoretical measures. Compared with HC, unmedicated SZ showed reduced global efficiency and increased clustering coefficients. This pattern of aberrant functional network integration and segregation was modulated with antipsychotic medications, but only in those who responded to treatment. Our work lends support to the concept of schizophrenia as a dysconnectivity syndrome, and suggests that faulty brain network topology in schizophrenia is modulated by antipsychotic medication as a function of treatment response. PMID:27336056

  13. Three Large-Scale Functional Brain Networks from Resting-State Functional MRI in Subjects with Different Levels of Cognitive Impairment.

    Science.gov (United States)

    Joo, Soo Hyun; Lim, Hyun Kook; Lee, Chang Uk

    2016-01-01

    Normal aging and to a greater degree degenerative brain diseases such as Alzheimer's disease (AD), cause changes in the brain's structure and function. Degenerative changes in brain structure and decline in its function are associated with declines in cognitive ability. Early detection of AD is a key priority in dementia services and research. However, depending on the disease progression, neurodegenerative manifestations, such as cerebral atrophy, are detected late in course of AD. Functional changes in the brain may be an indirect indicator of trans-synaptic activity and they usually appear prior to structural changes in AD. Resting-state functional magnetic resonance imaging (RS-fMRI) has recently been highlighted as a new technique for interrogating intrinsic functional connectivity networks. Among the majority of RS-fMRI studies, the default mode network (DMN), salience network (SN), and central executive network (CEN) gained particular focus because alterations to their functional connectivity were observed in subjects who had AD, who had mild cognitive impairment (MCI), or who were at high risk for AD. Herein, we present a review of the current research on changes in functional connectivity, as measured by RS-fMRI. We focus on the DMN, SN, and CEN to describe RS-fMRI results from three groups: normal healthy aging, MCI and AD. PMID:26766941

  14. A single session of exercise increases connectivity in sensorimotor-related brain networks: a resting-state fMRI study in young healthy adults.

    Science.gov (United States)

    Rajab, Ahmad S; Crane, David E; Middleton, Laura E; Robertson, Andrew D; Hampson, Michelle; MacIntosh, Bradley J

    2014-01-01

    Habitual long term physical activity is known to have beneficial cognitive, structural, and neuro-protective brain effects, but to date there is limited knowledge on whether a single session of exercise can alter the brain's functional connectivity, as assessed by resting-state functional magnetic resonance imaging (rs-fMRI). The primary objective of this study was to characterize potential session effects in resting-state networks (RSNs). We examined the acute effects of exercise on the functional connectivity of young healthy adults (N = 15) by collecting rs-fMRI before and after 20 min of moderate intensity aerobic exercise and compared this with a no-exercise control group (N = 15). Data were analyzed using independent component analysis, denoising and dual regression procedures. Regions of interest-based group session effect statistics were calculated in RSNs of interest using voxel-wise permutation testing and Cohen's D effect size. Group analysis in the exercising group data set revealed a session effect in sub-regions of three sensorimotor related areas: the pre and/or postcentral gyri, secondary somatosensory area and thalamus, characterized by increased co-activation after exercise (corrected p effect of session in these three RSNs (pexercise dataset produced no significant results, thereby providing support for the exercise findings and establishing the inherent test-retest reliability of the analysis pipeline on the RSNs of interest. This study establishes the feasibility of rs-fMRI to localize brain regions that are associated with acute exercise, as well as an analysis consideration to improve sensitivity to a session effect. PMID:25177284

  15. Resting-state brain and the FTO obesity risk allele: default mode, sensorimotor and salience network connectivity underlying different somatosensory integration and reward processing between genotypes.

    Directory of Open Access Journals (Sweden)

    Gaia eOlivo

    2016-02-01

    Full Text Available Single-nucleotide polymorphisms (SNPs of the fat mass and obesity associated (FTO gene are linked to obesity, but how these SNPs influence resting-state neural activation is unknown. Few brain-imaging studies have investigated the influence of obesity-related SNPs on neural activity, and no study has investigated resting-state connectivity patterns. We tested connectivity within three, main resting-state networks: default mode (DMN, sensorimotor (SMN, and salience network (SN in thirty male participants, grouped based on genotype for the rs9939609 FTO SNP, as well as punishment and reward sensitivity measured by the Behavioral Inhibition (BIS and Behavioral Activation System (BAS questionnaires. Because obesity is associated with anomalies in both systems, we calculated a BIS/BAS ratio (BBr accounting for features of both scores. A prominence of BIS over BAS (higher BBr resulted in increased connectivity in frontal and paralimbic regions. These alterations were more evident in the obesity-associated AA genotype, where a high BBr was also associated with increased SN connectivity in dopaminergic circuitries, and in a subnetwork involved in somatosensory integration regarding food. Participants with AA genotype and high BBr, compared to corresponding participants in the TT genotype, also showed greater DMN connectivity in regions involved in the processing of food cues, and in the SMN for regions involved in visceral perception and reward-based learning. These findings suggest that neural connectivity patterns influence the sensitivity toward punishment and reward more closely in the AA carriers, predisposing them to developing obesity. Our work explains a complex interaction between genetics, neural patterns, and behavioral measures in determining the risk for obesity and may help develop individually-tailored strategies for obesity prevention.

  16. Resting-State Brain and the FTO Obesity Risk Allele: Default Mode, Sensorimotor, and Salience Network Connectivity Underlying Different Somatosensory Integration and Reward Processing between Genotypes.

    Science.gov (United States)

    Olivo, Gaia; Wiemerslage, Lyle; Nilsson, Emil K; Solstrand Dahlberg, Linda; Larsen, Anna L; Olaya Búcaro, Marcela; Gustafsson, Veronica P; Titova, Olga E; Bandstein, Marcus; Larsson, Elna-Marie; Benedict, Christian; Brooks, Samantha J; Schiöth, Helgi B

    2016-01-01

    Single-nucleotide polymorphisms (SNPs) of the fat mass and obesity associated (FTO) gene are linked to obesity, but how these SNPs influence resting-state neural activation is unknown. Few brain-imaging studies have investigated the influence of obesity-related SNPs on neural activity, and no study has investigated resting-state connectivity patterns. We tested connectivity within three, main resting-state networks: default mode (DMN), sensorimotor (SMN), and salience network (SN) in 30 male participants, grouped based on genotype for the rs9939609 FTO SNP, as well as punishment and reward sensitivity measured by the Behavioral Inhibition (BIS) and Behavioral Activation System (BAS) questionnaires. Because obesity is associated with anomalies in both systems, we calculated a BIS/BAS ratio (BBr) accounting for features of both scores. A prominence of BIS over BAS (higher BBr) resulted in increased connectivity in frontal and paralimbic regions. These alterations were more evident in the obesity-associated AA genotype, where a high BBr was also associated with increased SN connectivity in dopaminergic circuitries, and in a subnetwork involved in somatosensory integration regarding food. Participants with AA genotype and high BBr, compared to corresponding participants in the TT genotype, also showed greater DMN connectivity in regions involved in the processing of food cues, and in the SMN for regions involved in visceral perception and reward-based learning. These findings suggest that neural connectivity patterns influence the sensitivity toward punishment and reward more closely in the AA carriers, predisposing them to developing obesity. Our work explains a complex interaction between genetics, neural patterns, and behavioral measures in determining the risk for obesity and may help develop individually-tailored strategies for obesity prevention. PMID:26924971

  17. Large-scale brain networks in board game experts: insights from a domain-related task and task-free resting state.

    Directory of Open Access Journals (Sweden)

    Xujun Duan

    Full Text Available Cognitive performance relies on the coordination of large-scale networks of brain regions that are not only temporally correlated during different tasks, but also networks that show highly correlated spontaneous activity during a task-free state. Both task-related and task-free network activity has been associated with individual differences in cognitive performance. Therefore, we aimed to examine the influence of cognitive expertise on four networks associated with cognitive task performance: the default mode network (DMN and three other cognitive networks (central-executive network, dorsal attention network, and salience network. During fMRI scanning, fifteen grandmaster and master level Chinese chess players (GM/M and fifteen novice players carried out a Chinese chess task and a task-free resting state. Modulations of network activity during task were assessed, as well as resting-state functional connectivity of those networks. Relative to novices, GM/Ms showed a broader task-induced deactivation of DMN in the chess problem-solving task, and intrinsic functional connectivity of DMN was increased with a connectivity pattern associated with the caudate nucleus in GM/Ms. The three other cognitive networks did not exhibit any difference in task-evoked activation or intrinsic functional connectivity between the two groups. These findings demonstrate the effect of long-term learning and practice in cognitive expertise on large-scale brain networks, suggesting the important role of DMN deactivation in expert performance and enhanced functional integration of spontaneous activity within widely distributed DMN-caudate circuitry, which might better support high-level cognitive control of behavior.

  18. Large-Scale Brain Networks in Board Game Experts: Insights from a Domain-Related Task and Task-Free Resting State

    Science.gov (United States)

    Duan, Xujun; Liao, Wei; Liang, Dongmei; Qiu, Lihua; Gao, Qing; Liu, Chengyi; Gong, Qiyong; Chen, Huafu

    2012-01-01

    Cognitive performance relies on the coordination of large-scale networks of brain regions that are not only temporally correlated during different tasks, but also networks that show highly correlated spontaneous activity during a task-free state. Both task-related and task-free network activity has been associated with individual differences in cognitive performance. Therefore, we aimed to examine the influence of cognitive expertise on four networks associated with cognitive task performance: the default mode network (DMN) and three other cognitive networks (central-executive network, dorsal attention network, and salience network). During fMRI scanning, fifteen grandmaster and master level Chinese chess players (GM/M) and fifteen novice players carried out a Chinese chess task and a task-free resting state. Modulations of network activity during task were assessed, as well as resting-state functional connectivity of those networks. Relative to novices, GM/Ms showed a broader task-induced deactivation of DMN in the chess problem-solving task, and intrinsic functional connectivity of DMN was increased with a connectivity pattern associated with the caudate nucleus in GM/Ms. The three other cognitive networks did not exhibit any difference in task-evoked activation or intrinsic functional connectivity between the two groups. These findings demonstrate the effect of long-term learning and practice in cognitive expertise on large-scale brain networks, suggesting the important role of DMN deactivation in expert performance and enhanced functional integration of spontaneous activity within widely distributed DMN-caudate circuitry, which might better support high-level cognitive control of behavior. PMID:22427852

  19. Differences in brain functional connectivity at resting-state in neonates born to healthy obese or normal-weight mothers

    Science.gov (United States)

    Recent studies have shown associations between maternal obesity at pre- or early pregnancy and long-term neurodevelopment in children, suggesting in utero effects of maternal obesity on offspring brain development. In this study, we examined whether brain functional connectivity to the prefrontal lo...

  20. Effects of different correlation metrics and preprocessing factors on small-world brain functional networks: a resting-state functional MRI study.

    Directory of Open Access Journals (Sweden)

    Xia Liang

    Full Text Available Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation, global signal presence (regressed or not and frequency band selection [slow-5 (0.01-0.027 Hz versus slow-4 (0.027-0.073 Hz] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT analyses for further guidance on how to choose the "best" network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR. The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027-0.073 Hz band exhibited greater reliability than those in the 0.01-0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics

  1. Disrupted Brain Functional Network in Internet Addiction Disorder: A Resting-State Functional Magnetic Resonance Imaging Study

    OpenAIRE

    Wee, Chong-Yaw; Zhao, Zhimin; Yap, Pew-Thian; Wu, Guorong; Shi, Feng; Price, True; Du, Yasong; Xu, Jianrong; Zhou, Yan; Shen, Dinggang

    2014-01-01

    Internet addiction disorder (IAD) is increasingly recognized as a mental health disorder, particularly among adolescents. The pathogenesis associated with IAD, however, remains unclear. In this study, we aim to explore the encephalic functional characteristics of IAD adolescents at rest using functional magnetic resonance imaging data. We adopted a graph-theoretic approach to investigate possible disruptions of functional connectivity in terms of network properties including small-worldness, ...

  2. A single session of exercise increases connectivity in sensorimotor-related brain networks: A resting-state fMRI study in young healthy adults

    Directory of Open Access Journals (Sweden)

    Ahmad Saeed Rajab

    2014-08-01

    Full Text Available Habitual long term physical activity is known to have beneficial cognitive, structural and neuro-protective brain effects, but to date there is limited knowledge on whether a single session of exercise can alter the brain’s functional connectivity, as assessed by resting-state fMRI (rs-fMRI. The primary objective of this study was to characterize potential session effects in resting state networks (RSNs. We examined the acute effects of exercise on the functional connectivity of young healthy adults (N=15 by collecting rs-fMRI before and after 20 minutes of moderate intensity aerobic exercise and compared this with a no-exercise control group (N=15. Data were analysed using independent component analysis, denoising and dual regression procedures. ROI-based group session effect statistics were calculated in RSNs of interest using voxel-wise permutation testing and Cohen’s D effect size. Group analysis in the exercising group data set revealed a session effect in sub-regions of three sensorimotor related areas: the pre and/or postcentral gyri, secondary somatosensory area and thalamus, characterized by increased co-activation after exercise (corrected p<0.05. Cohen’s D analysis also showed a significant effect of session in these three RSNs (p<0.05, corroborating the voxel-wise findings. Analyses of the no-exercise dataset produced no significant results, thereby providing support for the exercise findings and establishing the inherent test-retest reliability of the analysis pipeline on the RSNs of interest. This study establishes the feasibility of rs-fMRI to localize brain regions that are associated with acute exercise, as well as an analysis consideration to improve sensitivity to a session effect.

  3. Aberrant Brain Regional Homogeneity and Functional Connectivity in Middle-Aged T2DM Patients: A Resting-State Functional MRI Study

    Science.gov (United States)

    Liu, Daihong; Duan, Shanshan; Zhang, Jiuquan; Zhou, Chaoyang; Liang, Minglong; Yin, Xuntao; Wei, Ping; Wang, Jian

    2016-01-01

    Type 2 diabetes mellitus (T2DM) has been associated with cognitive impairment. However, its neurological mechanism remains elusive. Combining regional homogeneity (ReHo) and functional connectivity (FC) analyses, the present study aimed to investigate brain functional alterations in middle-aged T2DM patients, which could provide complementary information for the neural substrates underlying T2DM-associated brain dysfunction. Twenty-five T2DM patients and 25 healthy controls were involved in neuropsychological testing and structural and resting-state functional magnetic resonance imaging (rs-fMRI) data acquisition. ReHo analysis was conducted to determine the peak coordinates of brain regions with abnormal local brain activity synchronization. Then, the identified brain regions were considered as seeds, and FC between these brain regions and global voxels was computed. Finally, the potential correlations between the imaging indices and neuropsychological data were also explored. Compared with healthy controls, T2DM patients exhibited higher ReHo values in the anterior cingulate gyrus (ACG) and lower ReHo in the right fusiform gyrus (FFG), right precentral gyrus (PreCG) and right medial orbit of the superior frontal gyrus (SFG). Considering these areas as seed regions, T2DM patients displayed aberrant FC, mainly in the frontal and parietal lobes. The pattern of FC alterations in T2DM patients was characterized by decreased connectivity and positive to negative or negative to positive converted connectivity. Digital Span Test (DST) forward scores revealed significant correlations with the ReHo values of the right PreCG (ρ = 0.527, p = 0.014) and FC between the right FFG and middle temporal gyrus (MTG; ρ = −0.437, p = 0.048). Our findings suggest that T2DM patients suffer from cognitive dysfunction related to spatially local and remote brain activity synchronization impairment. The patterns of ReHo and FC alterations shed light on the mechanisms underlying T2DM

  4. Age-related Multiscale Changes in Brain Signal Variability in Pre-task versus Post-task Resting-state EEG.

    Science.gov (United States)

    Wang, Hongye; McIntosh, Anthony R; Kovacevic, Natasa; Karachalios, Maria; Protzner, Andrea B

    2016-07-01

    Recent empirical work suggests that, during healthy aging, the variability of network dynamics changes during task performance. Such variability appears to reflect the spontaneous formation and dissolution of different functional networks. We sought to extend these observations into resting-state dynamics. We recorded EEG in young, middle-aged, and older adults during a "rest-task-rest" design and investigated if aging modifies the interaction between resting-state activity and external stimulus-induced activity. Using multiscale entropy as our measure of variability, we found that, with increasing age, resting-state dynamics shifts from distributed to more local neural processing, especially at posterior sources. In the young group, resting-state dynamics also changed from pre- to post-task, where fine-scale entropy increased in task-positive regions and coarse-scale entropy increased in the posterior cingulate, a key region associated with the default mode network. Lastly, pre- and post-task resting-state dynamics were linked to performance on the intervening task for all age groups, but this relationship became weaker with increasing age. Our results suggest that age-related changes in resting-state dynamics occur across different spatial and temporal scales and have consequences for information processing capacity. PMID:26942319

  5. Spontaneous brain activity in chronic smokers revealed by fractional amplitude of low frequency fluctuation analysis: a resting state functional magnetic resonance imaging study

    Institute of Scientific and Technical Information of China (English)

    Chu Shuilian; Xiao Dan; Wang Shuangkun; Peng Peng; Xie Teng; He Yong; Wang Chen

    2014-01-01

    Background Nicotine is primarily rsponsible for the highly addictive properties of cigarettes.Similar to other substances,nicotine dependence is related to many important brain regions,particular in mesolimbic reward circuit.This study was to further reveal the alteration of brain function activity during resting state in chronic smokers by fractional amplitude of low frequency fluctuation (fALFF) based on functional magnetic resonance imaging (fMRI),in order to provide the evidence of neurobiological mechanism of smoking.Methods This case control study involved twenty healthy smokers and nineteen healthy nonsmokers recruited by advertisement.Sociodemographic,smoking related characteristics and fMRI images were collected and the data analyzed.Results Compared with nonsmokers,smokers showed fALFF increased significantly in the left middle occipital gyrus,left limbic lobe and left cerebellum posterior lobe but decreases in the right middle frontal gyrus,right superior temporal gyrus,right extra nuclear,left postcentral gyrus and left cerebellum anterior lobe (cluster size >100 voxels).Compared with light smokers (pack years ≤20),heavy smokers (pack years >20) showed fALFF increased significantly in the right superior temporal gyrus,right precentral gyrus,and right occipital lobe/cuneus but decreased in the right/left limbic lobe/cingulate gyrus,right/left frontal lobe/sub gyral,right/left cerebellum posterior lobe (cluster size >50 voxels).Compared with nonsevere nicotine dependent smokers (Fagerstr(o)m test for nicotine dependence,score ≤6),severe nicotine dependent smokers (score >6) showed fALFF increased significantly in the right/left middle frontal gyrus,right superior frontal gyrus and left inferior parietal lobule but decreased in the left limbic lobe/cingulate gyrus (duster size >25 voxels).Conclusions In smokers during rest,the activity of addiction related regions were increased and the activity of smoking feeling,memory,related regions were

  6. Identifying diagnostically-relevant resting state brain functional connectivity in the ventral posterior complex via genetic data mining in autism spectrum disorder.

    Science.gov (United States)

    Baldwin, Philip R; Curtis, Kaylah N; Patriquin, Michelle A; Wolf, Varina; Viswanath, Humsini; Shaw, Chad; Sakai, Yasunari; Salas, Ramiro

    2016-05-01

    Exome sequencing and copy number variation analyses continue to provide novel insight to the biological bases of autism spectrum disorder (ASD). The growing speed at which massive genetic data are produced causes serious lags in analysis and interpretation of the data. Thus, there is a need to develop systematic genetic data mining processes that facilitate efficient analysis of large datasets. We report a new genetic data mining system, ProcessGeneLists and integrated a list of ASD-related genes with currently available resources in gene expression and functional connectivity of the human brain. Our data-mining program successfully identified three primary regions of interest (ROIs) in the mouse brain: inferior colliculus, ventral posterior complex of the thalamus (VPC), and parafascicular nucleus (PFn). To understand its pathogenic relevance in ASD, we examined the resting state functional connectivity (RSFC) of the homologous ROIs in human brain with other brain regions that were previously implicated in the neuro-psychiatric features of ASD. Among them, the RSFC of the VPC with the medial frontal gyrus (MFG) was significantly more anticorrelated, whereas the RSFC of the PN with the globus pallidus was significantly increased in children with ASD compared with healthy children. Moreover, greater values of RSFC between VPC and MFG were correlated with severity index and repetitive behaviors in children with ASD. No significant RSFC differences were detected in adults with ASD. Together, these data demonstrate the utility of our data-mining program through identifying the aberrant connectivity of thalamo-cortical circuits in children with ASD. Autism Res 2016, 9: 553-562. © 2015 International Society for Autism Research, Wiley Periodicals, Inc. PMID:26451751

  7. Identifying diagnostically-relevant resting state brain functional connectivity in the ventral posterior complex via genetic data mining in autism spectrum disorder.

    Science.gov (United States)

    Baldwin, Philip R; Curtis, Kaylah N; Patriquin, Michelle A; Wolf, Varina; Viswanath, Humsini; Shaw, Chad; Sakai, Yasunari; Salas, Ramiro

    2016-05-01

    Exome sequencing and copy number variation analyses continue to provide novel insight to the biological bases of autism spectrum disorder (ASD). The growing speed at which massive genetic data are produced causes serious lags in analysis and interpretation of the data. Thus, there is a need to develop systematic genetic data mining processes that facilitate efficient analysis of large datasets. We report a new genetic data mining system, ProcessGeneLists and integrated a list of ASD-related genes with currently available resources in gene expression and functional connectivity of the human brain. Our data-mining program successfully identified three primary regions of interest (ROIs) in the mouse brain: inferior colliculus, ventral posterior complex of the thalamus (VPC), and parafascicular nucleus (PFn). To understand its pathogenic relevance in ASD, we examined the resting state functional connectivity (RSFC) of the homologous ROIs in human brain with other brain regions that were previously implicated in the neuro-psychiatric features of ASD. Among them, the RSFC of the VPC with the medial frontal gyrus (MFG) was significantly more anticorrelated, whereas the RSFC of the PN with the globus pallidus was significantly increased in children with ASD compared with healthy children. Moreover, greater values of RSFC between VPC and MFG were correlated with severity index and repetitive behaviors in children with ASD. No significant RSFC differences were detected in adults with ASD. Together, these data demonstrate the utility of our data-mining program through identifying the aberrant connectivity of thalamo-cortical circuits in children with ASD. Autism Res 2016, 9: 553-562. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

  8. Serum BDNF correlates with connectivity in the (pre)motor hub in the aging human brain--a resting-state fMRI pilot study.

    Science.gov (United States)

    Mueller, Karsten; Arelin, Katrin; Möller, Harald E; Sacher, Julia; Kratzsch, Jürgen; Luck, Tobias; Riedel-Heller, Steffi; Villringer, Arno; Schroeter, Matthias L

    2016-02-01

    Brain-derived neurotrophic factor (BDNF) has been discussed to be involved in plasticity processes in the human brain, in particular during aging. Recently, aging and its (neurodegenerative) diseases have increasingly been conceptualized as disconnection syndromes. Here, connectivity changes in neural networks (the connectome) are suggested to be the most relevant and characteristic features for such processes or diseases. To further elucidate the impact of aging on neural networks, we investigated the interaction between plasticity processes, brain connectivity, and healthy aging by measuring levels of serum BDNF and resting-state fMRI data in 25 young (mean age 24.8 ± 2.7 (SD) years) and 23 old healthy participants (mean age, 68.6 ± 4.1 years). To identify neural hubs most essentially related to serum BDNF, we applied graph theory approaches, namely the new data-driven and parameter-free approach eigenvector centrality (EC) mapping. The analysis revealed a positive correlation between serum BDNF and EC in the premotor and motor cortex in older participants in contrast to young volunteers, where we did not detect any association. This positive relationship between serum BDNF and EC appears to be specific for older adults. Our results might indicate that the amount of physical activity and learning capacities, leading to higher BDNF levels, increases brain connectivity in (pre)motor areas in healthy aging in agreement with rodent animal studies. Pilot results have to be replicated in a larger sample including behavioral data to disentangle the cause for the relationship between BDNF levels and connectivity. PMID:26827656

  9. Identification of Resting State Networks Involved in Executive Function.

    Science.gov (United States)

    Connolly, Joanna; McNulty, Jonathan P; Boran, Lorraine; Roche, Richard A P; Delany, David; Bokde, Arun L W

    2016-06-01

    The structural networks in the human brain are consistent across subjects, and this is reflected also in that functional networks across subjects are relatively consistent. These findings are not only present during performance of a goal oriented task but there are also consistent functional networks during resting state. It suggests that goal oriented activation patterns may be a function of component networks identified using resting state. The current study examines the relationship between resting state networks measured and patterns of neural activation elicited during a Stroop task. The association between the Stroop-activated networks and the resting state networks was quantified using spatial linear regression. In addition, we investigated if the degree of spatial association of resting state networks with the Stroop task may predict performance on the Stroop task. The results of this investigation demonstrated that the Stroop activated network can be decomposed into a number of resting state networks, which were primarily associated with attention, executive function, visual perception, and the default mode network. The close spatial correspondence between the functional organization of the resting brain and task-evoked patterns supports the relevance of resting state networks in cognitive function. PMID:26935902

  10. Resting state FMRI research in child psychiatric disorders

    NARCIS (Netherlands)

    Oldehinkel, M.; Francx, W.; Beckmann, C.F.; Buitelaar, J.K.; Mennes, M.

    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

  11. Functional connectomics from resting-state fMRI

    NARCIS (Netherlands)

    Smith, S.M.; Vidaurre, D.; Beckmann, C.F.; Jenkinson, M.; Nichols, T.E.; Robinson, E.C.; Woolrich, M.W.; Barch, D.M.

    2013-01-01

    Spontaneous fluctuations in activity in different parts of the brain can be used to study functional brain networks. We review the use of resting-state functional MRI (rfMRI) for the purpose of mapping the macroscopic functional connectome. After describing MRI acquisition and image-processing metho

  12. Altered intrinsic regional spontaneous brain activity in patients with optic neuritis: a resting-state functional magnetic resonance imaging study

    OpenAIRE

    Shao Y; Cai FQ; Zhong YL; Huang X; Zhang Y; Hu PH; Pei CG; Zhou FQ; Zeng XJ

    2015-01-01

    Yi Shao,1,* Feng-Qin Cai,2,* Yu-Lin Zhong,1 Xin Huang,1,3 Ying Zhang,1 Pei-Hong Hu,1 Chong-Gang Pei,1 Fu-Qing Zhou,2 Xian-Jun Zeng2 1Department of Ophthalmology, 2Department of Radiology, First Affiliated Hospital of Nanchang University, Nanchang, 3Department of Ophthalmology, First People’s Hospital of Jiujiang, Jiujiang, People’s Republic of China *These authors contributed equally to this work Objective: To investigate the underlying regional homogeneity (ReHo) in brain...

  13. Disrupted brain functional network in internet addiction disorder: a resting-state functional magnetic resonance imaging study.

    Directory of Open Access Journals (Sweden)

    Chong-Yaw Wee

    Full Text Available Internet addiction disorder (IAD is increasingly recognized as a mental health disorder, particularly among adolescents. The pathogenesis associated with IAD, however, remains unclear. In this study, we aim to explore the encephalic functional characteristics of IAD adolescents at rest using functional magnetic resonance imaging data. We adopted a graph-theoretic approach to investigate possible disruptions of functional connectivity in terms of network properties including small-worldness, efficiency, and nodal centrality on 17 adolescents with IAD and 16 socio-demographically matched healthy controls. False discovery rate-corrected parametric tests were performed to evaluate the statistical significance of group-level network topological differences. In addition, a correlation analysis was performed to assess the relationships between functional connectivity and clinical measures in the IAD group. Our results demonstrate that there is significant disruption in the functional connectome of IAD patients, particularly between regions located in the frontal, occipital, and parietal lobes. The affected connections are long-range and inter-hemispheric connections. Although significant alterations are observed for regional nodal metrics, there is no difference in global network topology between IAD and healthy groups. In addition, correlation analysis demonstrates that the observed regional abnormalities are correlated with the IAD severity and behavioral clinical assessments. Our findings, which are relatively consistent between anatomically and functionally defined atlases, suggest that IAD causes disruptions of functional connectivity and, importantly, that such disruptions might link to behavioral impairments.

  14. Classification of schizophrenia and bipolar patients using static and dynamic resting-state fMRI brain connectivity.

    Science.gov (United States)

    Rashid, Barnaly; Arbabshirani, Mohammad R; Damaraju, Eswar; Cetin, Mustafa S; Miller, Robyn; Pearlson, Godfrey D; Calhoun, Vince D

    2016-07-01

    Recently, functional network connectivity (FNC, defined as the temporal correlation among spatially distant brain networks) has been used to examine the functional organization of brain networks in various psychiatric illnesses. Dynamic FNC is a recent extension of the conventional FNC analysis that takes into account FNC changes over short periods of time. While such dynamic FNC measures may be more informative about various aspects of connectivity, there has been no detailed head-to-head comparison of the ability of static and dynamic FNC to perform classification in complex mental illnesses. This paper proposes a framework for automatic classification of schizophrenia, bipolar and healthy subjects based on their static and dynamic FNC features. Also, we compare cross-validated classification performance between static and dynamic FNC. Results show that the dynamic FNC significantly outperforms the static FNC in terms of predictive accuracy, indicating that features from dynamic FNC have distinct advantages over static FNC for classification purposes. Moreover, combining static and dynamic FNC features does not significantly improve the classification performance over the dynamic FNC features alone, suggesting that static FNC does not add any significant information when combined with dynamic FNC for classification purposes. A three-way classification methodology based on static and dynamic FNC features discriminates individual subjects into appropriate diagnostic groups with high accuracy. Our proposed classification framework is potentially applicable to additional mental disorders.

  15. Expression of microRNA-34a in Alzheimer's disease brain targets genes linked to synaptic plasticity, energy metabolism, and resting state network activity.

    Science.gov (United States)

    Sarkar, S; Jun, S; Rellick, S; Quintana, D D; Cavendish, J Z; Simpkins, J W

    2016-09-01

    Polygenetic risk factors and reduced expression of many genes in late-onset Alzheimer's disease (AD) impedes identification of a target(s) for disease-modifying therapies. We identified a single microRNA, miR-34a that is over expressed in specific brain regions of AD patients as well as in the 3xTg-AD mouse model. Specifically, increased miR-34a expression in the temporal cortex region compared to age matched healthy control correlates with severity of AD pathology. miR-34a over expression in patient's tissue and forced expression in primary neuronal culture correlates with concurrent repression of its target genes involved in synaptic plasticity, oxidative phosphorylation and glycolysis. The repression of oxidative phosphorylation and glycolysis related proteins correlates with reduced ATP production and glycolytic capacity, respectively. We also found that miR-34a overexpressed neurons secrete miR-34a containing exosomes that are taken up by neighboring neurons. Furthermore, miR-34a targets dozens of genes whose expressions are known to be correlated with synchronous activity in resting state functional networks. Our analysis of human genomic sequences from the tentative promoter of miR-34a gene shows the presence of NFκB, STAT1, c-Fos, CREB and p53 response elements. Together, our results raise the possibilities that pathophysiology-induced activation of specific transcription factor may lead to increased expression of miR-34a gene and miR-34a mediated concurrent repression of its target genes in neural networks may result in dysfunction of synaptic plasticity, energy metabolism, and resting state network activity. Thus, our results provide insights into polygenetic AD mechanisms and disclose miR-34a as a potential therapeutic target for AD. PMID:27235866

  16. Alteration of default mode network in high school football athletes due to repetitive subconcussive mild traumatic brain injury: a resting-state functional magnetic resonance imaging study.

    Science.gov (United States)

    Abbas, Kausar; Shenk, Trey E; Poole, Victoria N; Breedlove, Evan L; Leverenz, Larry J; Nauman, Eric A; Talavage, Thomas M; Robinson, Meghan E

    2015-03-01

    Long-term neurological damage as a result of head trauma while playing sports is a major concern for football athletes today. Repetitive concussions have been linked to many neurological disorders. Recently, it has been reported that repetitive subconcussive events can be a significant source of accrued damage. Since football athletes can experience hundreds of subconcussive hits during a single season, it is of utmost importance to understand their effect on brain health in the short and long term. In this study, resting-state functional magnetic resonance imaging (rs-fMRI) was used to study changes in the default mode network (DMN) after repetitive subconcussive mild traumatic brain injury. Twenty-two high school American football athletes, clinically asymptomatic, were scanned using the rs-fMRI for a single season. Baseline scans were acquired before the start of the season, and follow-up scans were obtained during and after the season to track the potential changes in the DMN as a result of experienced trauma. Ten noncollision-sport athletes were scanned over two sessions as controls. Overall, football athletes had significantly different functional connectivity measures than controls for most of the year. The presence of this deviation of football athletes from their healthy peers even before the start of the season suggests a neurological change that has accumulated over the years of playing the sport. Football athletes also demonstrate short-term changes relative to their own baseline at the start of the season. Football athletes exhibited hyperconnectivity in the DMN compared to controls for most of the sessions, which indicates that, despite the absence of symptoms typically associated with concussion, the repetitive trauma accrued produced long-term brain changes compared to their healthy peers.

  17. Spontaneous brain activity in type 2 diabetics revealed by amplitude of low-frequency fluctuations and its association with diabetic vascular disease: a resting-state FMRI study.

    Directory of Open Access Journals (Sweden)

    Chun-Xia Wang

    Full Text Available To investigate correlations between altered spontaneous brain activity, diabetic vascular disease, and cognitive function for patients with type 2 diabetes mellitus (T2DM using resting-state functional magnetic resonance imaging (rs-fMRI.Rs-fMRI was performed for T2DM patients (n = 26 and age-, gender-, and education-matched non-diabetic control subjects (n = 26. Amplitude of low frequency fluctuations (ALFF were computed from fMRI signals to measure spontaneous neuronal activity. Differences in the ALFF patterns between patients and controls, as well as their correlations with clinical variables, were evaluated.Compared with healthy controls, T2DM patients exhibited significantly decreased ALFF values mainly in the frontal and parietal lobes, the bilateral thalumi, the posterior lobe of the cerebellum, and increased ALFF values mainly in the visual cortices. Furthermore, lower ALFF values in the left subcallosal gyrus correlated with lower ankle-brachial index values (r = 0.481, p = 0.020, while lower ALFF values in the bilateral medial prefrontal gyri correlated with higher urinary albumin-creatinine ratio (r =  -0.418, p = 0.047. In addition, most of the regions with increased ALFF values in the visual cortices were found to negatively correlate with MoCA scores.These results confirm that ALFF are altered in many brain regions in T2DM patients, and this is associated with the presence of diabetic vascular disease and poor cognitive performance. These findings may provide additional insight into the neurophysiological mechanisms that mediate T2DM-related cognitive dysfunction, and may also serve as a reference for future research.

  18. Resting state functional connectivity in anorexia nervosa.

    Science.gov (United States)

    Phillipou, Andrea; Abel, Larry Allen; Castle, David Jonathan; Hughes, Matthew Edward; Nibbs, Richard Grant; Gurvich, Caroline; Rossell, Susan Lee

    2016-05-30

    Anorexia Nervosa (AN) is a serious psychiatric illness characterised by a disturbance in body image, a fear of weight gain and significantly low body weight. The factors involved in the genesis and maintenance of AN are unclear, though the potential neurobiological underpinnings of the condition are of increasing interest. Through the investigation of functional connectivity of the brain at rest, information relating to neuronal communication and integration of information that may relate to behaviours and cognitive symptoms can be explored. The aim of this study was to investigate functional connectivity of the default mode network, and sensorimotor and visual networks in AN. 26 females with AN and 27 healthy control participants matched for age, gender and premorbid intelligence underwent a resting state functional magnetic resonance imaging scan. Default mode network functional connectivity did not differ between groups. AN participants displayed reduced functional connectivity between the sensorimotor and visual networks, in comparison to healthy controls. This finding is discussed in terms of differences in visuospatial processing in AN and the distortion of body image experienced by these individuals. Overall, the findings suggest that sensorimotor and visual network connectivity may be related to visuospatial processing in AN, though, further research is required. PMID:27111812

  19. Moderating effects of music on resting state networks

    OpenAIRE

    Kay, Benjamin P; Meng, Xiangxiang; DiFrancesco, Mark; Holland, Scott K.; Szaflarski, Jerzy P.

    2012-01-01

    Resting state networks (RSNs) are spontaneous, synchronous, low-frequency oscillations observed in the brains of subjects who are awake but at rest. A particular RSN called the default mode network (DMN) has been shown to exhibit changes associated with neurological disorders such as temporal lobe epilepsy or Alzheimer’s disease. Previous studies have also found that differing experimental conditions such as eyes-open versus eyes-closed can produce measurable changes in the DMN. These conditi...

  20. Altered intrinsic regional brain spontaneous activity and subjective sleep quality in patients with chronic primary insomnia: a resting-state fMRI study

    Directory of Open Access Journals (Sweden)

    Dai XJ

    2014-11-01

    Full Text Available Xi-Jian Dai,1,2 De-Chang Peng,1 Hong-Han Gong,1 Ai-Lan Wan,3 Xiao Nie,1 Hai-Jun Li,1 Yi-Xiang J Wang2 1Department of Radiology, The First Affiliated Hospital of Nanchang University, Nangchang, Jiangxi, People’s Republic of China; 2Department of Imaging and Interventional Radiology, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong; 3Department of Psychosomatic Medicine, the First Affiliated Hospital of Nangchang University, Nangchang, Jiangxi, People’s Republic of China Study objective: To prospectively explore the underlying regional homogeneity (ReHo brain-activity deficit in patients with chronic primary insomnia (PCPIs and its relationship with clinical features.Design: The ReHo method and Statistical Parametric Mapping 8 software were used to evaluate whether resting-state localized brain activity was modulated between PCPIs and good sleepers (GSs, and correlation analysis between altered regional brain areas and clinical features was calculated. Patients and participants: Twenty-four PCPIs (17 females, seven males and 24 (12 females, 12 males age-, sex-, and education-matched GSs.Measurements and results: PCPIs disturbed subjective sleep quality, split positive mood, and exacerbated negative moods. Compared with GSs, PCPIs showed higher ReHo in left fusiform gyrus, and lower ReHo in bilateral cingulate gyrus and right cerebellum anterior lobe. Compared with female GSs, female PCPIs showed higher ReHo in the left fusiform gyrus and right posterior cingulate, and lower ReHo in the left cerebellum anterior lobe and left superior frontal gyrus. Compared with male GSs, male PCPIs showed higher ReHo in the right temporal lobe and lower ReHo in the bilateral frontal lobe. The fusiform gyrus showed strong positive correlations and the frontal lobe showed negative correlations with the clinical measurements.Conclusion: The ReHo analysis is a useful noninvasive imaging tool for the detection of cerebral changes and

  1. Alteration of Interictal Brain Activity in Patients with Temporal Lobe Epilepsy in the Left Dominant Hemisphere: A Resting-State MEG Study

    Directory of Open Access Journals (Sweden)

    Haitao Zhu

    2014-01-01

    Full Text Available Resting MEG activities were compared between patients with left temporal lobe epilepsy (LTLE and normal controls. Using SAMg2, the activities of MEG data were reconstructed and normalized. Significantly elevated SAMg2 signals were found in LTLE patients in the left temporal lobe and medial structures. Marked decreases of SAMg2 signals were found in the wide extratemporal lobe regions, such as the bilateral visual cortex. The study also demonstrated a positive correlation between the seizure frequency and brain activities of the abnormal regions after the multiple linear regression analysis. These results suggested that the aberrant brain activities not only were related to the epileptogenic zones, but also existed in other extratemporal regions in patients with LTLE. The activities of the aberrant regions could be further damaged with the increase of the seizure frequency. Our findings indicated that LTLE could be a multifocal disease, including complex epileptic networks and brain dysfunction networks.

  2. Resting state EEG correlates of memory consolidation.

    Science.gov (United States)

    Brokaw, Kate; Tishler, Ward; Manceor, Stephanie; Hamilton, Kelly; Gaulden, Andrew; Parr, Elaine; Wamsley, Erin J

    2016-04-01

    Numerous studies demonstrate that post-training sleep benefits human memory. At the same time, emerging data suggest that other resting states may similarly facilitate consolidation. In order to identify the conditions under which non-sleep resting states benefit memory, we conducted an EEG (electroencephalographic) study of verbal memory retention across 15min of eyes-closed rest. Participants (n=26) listened to a short story and then either rested with their eyes closed, or else completed a distractor task for 15min. A delayed recall test was administered immediately following the rest period. We found, first, that quiet rest enhanced memory for the short story. Improved memory was associated with a particular EEG signature of increased slow oscillatory activity (<1Hz), in concert with reduced alpha (8-12Hz) activity. Mindwandering during the retention interval was also associated with improved memory. These observations suggest that a short period of quiet rest can facilitate memory, and that this may occur via an active process of consolidation supported by slow oscillatory EEG activity and characterized by decreased attention to the external environment. Slow oscillatory EEG rhythms are proposed to facilitate memory consolidation during sleep by promoting hippocampal-cortical communication. Our findings suggest that EEG slow oscillations could play a significant role in memory consolidation during other resting states as well. PMID:26802698

  3. Brain regional homogeneity changes following transjugular intrahepatic portosystemic shunt in cirrhotic patients support cerebral adaptability theory—A resting-state functional MRI study

    Energy Technology Data Exchange (ETDEWEB)

    Ni, Ling; Qi, Rongfeng [Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002 (China); Zhang, Long Jiang, E-mail: kevinzhlj@163.com [Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002 (China); Zhong, Jianhui [Department of Biomedical Engineering, Zhejiang University, Hangzhou, Zhejiang 310027 (China); Zheng, Gang [Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002 (China); Wu, Xingjiang; Fan, Xinxin [Department of General Surgery, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002 (China); Lu, Guang Ming, E-mail: cjr.luguangming@vip.163.com [Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002 (China)

    2014-03-15

    Purpose: The exact neuro-pathophysiological effect of transjugular intrahepatic portosystemic shunt (TIPS) on brain function remains unclear. The purpose of this study was to investigate the longitudinal brain activity changes in cirrhotic patients with TIPS insertion using resting-state functional MRI (fMRI) with regional homogeneity (ReHo) method. Methods: Fifteen cirrhotic patients without overt hepatic encephalopathy (OHE) planned for TIPS procedure and 15 age- and gender-matched healthy controls were included in this study. Eleven of the 15 patients underwent repeated fMRI examinations at median 7-day following TIPS, 8 patients in median 3-month, and 7 patients in median 1-year follow-up duration, respectively. Regional homogeneity was calculated by the Kendall's coefficient of concordance (KCC) and compared between patients before TIPS and healthy controls with two-sample t test as well as pre-and post-TIPS patients with paired t test. Correlations between the pre- and post-TIPS changes of ReHo and the changes of venous blood ammonia level and number connection test type A (NCT-A)/digit symbol test (DST) scores were calculated by crossing subjects. Results: Compared with healthy controls, 15 cirrhotic patients before TIPS procedure showed decreased ReHo in the bilateral frontal, parietal, temporal and occipital lobes and increased ReHo in the bilateral caudate. Compared with the pre-TIPS patients, 11 post-TIPS patients in the median 7-day follow-up examinations demonstrated decreased ReHo in the medial frontal gyrus (MFG), superior parietal gyrus (SPG), middle/superior temporal gyrus (M/STG), anterior cingulate cortex (ACC), caudate, and increased ReHo in the insula. Eight post-TIPS patients in the median 3-month follow-up examinations showed widespread decreased ReHo in the bilateral frontal and parietal lobes, ACC, caudate, and increased ReHo in the insula and precuneus/cuneus. In the median 1-year follow-up studies, seven post-TIPS patients displayed

  4. Brain regional homogeneity changes following transjugular intrahepatic portosystemic shunt in cirrhotic patients support cerebral adaptability theory—A resting-state functional MRI study

    International Nuclear Information System (INIS)

    Purpose: The exact neuro-pathophysiological effect of transjugular intrahepatic portosystemic shunt (TIPS) on brain function remains unclear. The purpose of this study was to investigate the longitudinal brain activity changes in cirrhotic patients with TIPS insertion using resting-state functional MRI (fMRI) with regional homogeneity (ReHo) method. Methods: Fifteen cirrhotic patients without overt hepatic encephalopathy (OHE) planned for TIPS procedure and 15 age- and gender-matched healthy controls were included in this study. Eleven of the 15 patients underwent repeated fMRI examinations at median 7-day following TIPS, 8 patients in median 3-month, and 7 patients in median 1-year follow-up duration, respectively. Regional homogeneity was calculated by the Kendall's coefficient of concordance (KCC) and compared between patients before TIPS and healthy controls with two-sample t test as well as pre-and post-TIPS patients with paired t test. Correlations between the pre- and post-TIPS changes of ReHo and the changes of venous blood ammonia level and number connection test type A (NCT-A)/digit symbol test (DST) scores were calculated by crossing subjects. Results: Compared with healthy controls, 15 cirrhotic patients before TIPS procedure showed decreased ReHo in the bilateral frontal, parietal, temporal and occipital lobes and increased ReHo in the bilateral caudate. Compared with the pre-TIPS patients, 11 post-TIPS patients in the median 7-day follow-up examinations demonstrated decreased ReHo in the medial frontal gyrus (MFG), superior parietal gyrus (SPG), middle/superior temporal gyrus (M/STG), anterior cingulate cortex (ACC), caudate, and increased ReHo in the insula. Eight post-TIPS patients in the median 3-month follow-up examinations showed widespread decreased ReHo in the bilateral frontal and parietal lobes, ACC, caudate, and increased ReHo in the insula and precuneus/cuneus. In the median 1-year follow-up studies, seven post-TIPS patients displayed

  5. Resting-state fMRI studies in epilepsy

    Institute of Scientific and Technical Information of China (English)

    Wurina; Yu-Feng Zang; Shi-Gang Zhao

    2012-01-01

    Epilepsy is a disease characterized by abnormal spontaneous activity in the brain.Resting-state functional magnetic resonance imaging (RS-fMRI) is a powerful technique for exploring this activity.With good spatial and temporal resolution,RS-fMRI is a promising approach for accurate localization of the focus of seizure activity.Although simultaneous electroencephalogram-fMR1 has been performed with patients in the resting state,most studies focused on activation.This mini-review focuses on RS-fMRI alone,including its computational methods and its application to epilepsy.

  6. Resting state functional connectivity in perfusion imaging: correlation maps with BOLD connectivity and resting state perfusion.

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    Roberto Viviani

    Full Text Available Functional connectivity is a property of the resting state that may provide biomarkers of brain function and individual differences. Classically, connectivity is estimated as the temporal correlation of spontaneous fluctuations of BOLD signal. We investigated differences in connectivity estimated from the BOLD and CBF signal present in volumes acquired with arterial spin labeling technique in a large sample (N = 265 of healthy individuals. Positive connectivity was observable in both BOLD and CBF signal, and was present in the CBF signal also at frequencies lower than 0.009 Hz, here investigated for the first time. Negative connectivity was more variable. The validity of positive connectivity was confirmed by the existence of correlation across individuals in its intensity estimated from the BOLD and CBF signal. In contrast, there was little or no correlation across individuals between intensity of connectivity and mean perfusion levels, suggesting that these two biomarkers correspond to distinct sources of individual differences.

  7. Visual Learning Alters the Spontaneous Activity of the Resting Human Brain: An fNIRS Study

    OpenAIRE

    Haijing Niu; Hao Li; Li Sun; Yongming Su; Jing Huang; Yan Song

    2014-01-01

    Resting-state functional connectivity (RSFC) has been widely used to investigate spontaneous brain activity that exhibits correlated fluctuations. RSFC has been found to be changed along the developmental course and after learning. Here, we investigated whether and how visual learning modified the resting oxygenated hemoglobin (HbO) functional brain connectivity by using functional near-infrared spectroscopy (fNIRS). We demonstrate that after five days of training on an orientation discrimina...

  8. Resting Network Plasticity Following Brain Injury

    OpenAIRE

    Toru Nakamura; Hillary, Frank G.; Biswal, Bharat B.

    2009-01-01

    The purpose of this study was to examine neural network properties at separate time-points during recovery from traumatic brain injury (TBI) using graph theory. Whole-brain analyses of the topological properties of the fMRI signal were conducted in 6 participants at 3 months and 6 months following severe TBI. Results revealed alterations of network properties including a change in the degree distribution, reduced overall strength in connectivity, and increased "small-worldness" from 3 months ...

  9. Your resting brain CAREs about your risky behavior.

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    Christine L Cox

    Full Text Available BACKGROUND: Research on the neural correlates of risk-related behaviors and personality traits has provided insight into mechanisms underlying both normal and pathological decision-making. Task-based neuroimaging studies implicate a distributed network of brain regions in risky decision-making. What remains to be understood are the interactions between these regions and their relation to individual differences in personality variables associated with real-world risk-taking. METHODOLOGY/PRINCIPAL FINDINGS: We employed resting state functional magnetic resonance imaging (R-fMRI and resting state functional connectivity (RSFC methods to investigate differences in the brain's intrinsic functional architecture associated with beliefs about the consequences of risky behavior. We obtained an individual measure of expected benefit from engaging in risky behavior, indicating a risk seeking or risk-averse personality, for each of 21 participants from whom we also collected a series of R-fMRI scans. The expected benefit scores were entered in statistical models assessing the RSFC of brain regions consistently implicated in both the evaluation of risk and reward, and cognitive control (i.e., orbitofrontal cortex, nucleus accumbens, lateral prefrontal cortex, dorsal anterior cingulate. We specifically focused on significant brain-behavior relationships that were stable across R-fMRI scans collected one year apart. Two stable expected benefit-RSFC relationships were observed: decreased expected benefit (increased risk-aversion was associated with 1 stronger positive functional connectivity between right inferior frontal gyrus (IFG and right insula, and 2 weaker negative functional connectivity between left nucleus accumbens and right parieto-occipital cortex. CONCLUSIONS/SIGNIFICANCE: Task-based activation in the IFG and insula has been associated with risk-aversion, while activation in the nucleus accumbens and parietal cortex has been associated with both

  10. Intensive reasoning training alters patterns of brain connectivity at rest.

    Science.gov (United States)

    Mackey, Allyson P; Miller Singley, Alison T; Bunge, Silvia A

    2013-03-13

    Patterns of correlated activity among brain regions reflect functionally relevant networks that are widely assumed to be stable over time. We hypothesized that if these correlations reflect the prior history of coactivation of brain regions, then a marked shift in cognition could alter the strength of coupling between these regions. We sought to test whether intensive reasoning training in humans would result in tighter coupling among regions in the lateral frontoparietal network, as measured with resting-state fMRI (rs-fMRI). Rather than designing an artificial training program, we studied individuals who were preparing for a standardized test that places heavy demands on relational reasoning, the Law School Admissions Test (LSAT). LSAT questions require test takers to group or sequence items according to a set of complex rules. We recruited young adults who were enrolled in an LSAT course that offers 70 h of reasoning instruction (n = 25), and age- and IQ-matched controls intending to take the LSAT in the future (n = 24). rs-fMRI data were collected for all subjects during two scanning sessions separated by 90 d. An analysis of pairwise correlations between brain regions implicated in reasoning showed that fronto-parietal connections were strengthened, along with parietal-striatal connections. These findings provide strong evidence for neural plasticity at the level of large-scale networks supporting high-level cognition. PMID:23486950

  11. Whole scalp resting state EEG of oscillatory brain activity shows no parametric relationship with psychoacoustic and psychosocial assessment of tinnitus: A repeated measures study.

    Science.gov (United States)

    Pierzycki, Robert H; McNamara, Adam J; Hoare, Derek J; Hall, Deborah A

    2016-01-01

    Tinnitus is a perception of sound that can occur in the absence of an external stimulus. A brief review of electroencephalography (EEG) and magnetoencephalography (MEG) literature demonstrates that there is no clear relationship between tinnitus presence and frequency band power in whole scalp or source oscillatory activity. Yet a preconception persists that such a relationship exists and that resting state EEG could be utilised as an outcome measure for clinical trials of tinnitus interventions, e.g. as a neurophysiological marker of therapeutic benefit. To address this issue, we first examined the test-retest correlation of EEG band power measures in tinnitus patients (n = 42). Second we examined the evidence for a parametric relationship between numerous commonly used tinnitus variables (psychoacoustic and psychosocial) and whole scalp EEG power spectra, directly and after applying factor reduction techniques. Test-retest correlation for both EEG band power measures and tinnitus variables were high. Yet we found no relationship between whole scalp EEG band powers and psychoacoustic or psychosocial variables. We conclude from these data that resting state whole scalp EEG should not be used as a biomarker for tinnitus and that greater caution should be exercised in regard to reporting of findings to avoid confirmation bias. The data was collected during a randomised controlled trial registered at ClinicalTrials.gov (Identifier: NCT01541969).

  12. Large-Scale Brain Networks in Board Game Experts: Insights from a Domain-Related Task and Task-Free Resting State

    OpenAIRE

    Duan, Xujun; Liao, Wei; Liang, Dongmei; Qiu, Lihua; Gao, Qing; Liu, Chengyi; Gong, Qiyong; Chen, Huafu

    2012-01-01

    Cognitive performance relies on the coordination of large-scale networks of brain regions that are not only temporally correlated during different tasks, but also networks that show highly correlated spontaneous activity during a task-free state. Both task-related and task-free network activity has been associated with individual differences in cognitive performance. Therefore, we aimed to examine the influence of cognitive expertise on four networks associated with cognitive task performance...

  13. Resting network plasticity following brain injury.

    Directory of Open Access Journals (Sweden)

    Toru Nakamura

    Full Text Available The purpose of this study was to examine neural network properties at separate time-points during recovery from traumatic brain injury (TBI using graph theory. Whole-brain analyses of the topological properties of the fMRI signal were conducted in 6 participants at 3 months and 6 months following severe TBI. Results revealed alterations of network properties including a change in the degree distribution, reduced overall strength in connectivity, and increased "small-worldness" from 3 months to 6 months post injury. The findings here indicate that, during recovery from injury, the strength but not the number of network connections diminishes, so that over the course of recovery, the network begins to approximate what is observed in healthy adults. These are the first data examining functional connectivity in a disrupted neural system during recovery.

  14. Rapid geodesic mapping of brain functional connectivity: implementation of a dedicated co-processor in a field-programmable gate array (FPGA) and application to resting state functional MRI.

    Science.gov (United States)

    Minati, Ludovico; Cercignani, Mara; Chan, Dennis

    2013-10-01

    Graph theory-based analyses of brain network topology can be used to model the spatiotemporal correlations in neural activity detected through fMRI, and such approaches have wide-ranging potential, from detection of alterations in preclinical Alzheimer's disease through to command identification in brain-machine interfaces. However, due to prohibitive computational costs, graph-based analyses to date have principally focused on measuring connection density rather than mapping the topological architecture in full by exhaustive shortest-path determination. This paper outlines a solution to this problem through parallel implementation of Dijkstra's algorithm in programmable logic. The processor design is optimized for large, sparse graphs and provided in full as synthesizable VHDL code. An acceleration factor between 15 and 18 is obtained on a representative resting-state fMRI dataset, and maps of Euclidean path length reveal the anticipated heterogeneous cortical involvement in long-range integrative processing. These results enable high-resolution geodesic connectivity mapping for resting-state fMRI in patient populations and real-time geodesic mapping to support identification of imagined actions for fMRI-based brain-machine interfaces.

  15. Rapid geodesic mapping of brain functional connectivity: implementation of a dedicated co-processor in a field-programmable gate array (FPGA) and application to resting state functional MRI.

    Science.gov (United States)

    Minati, Ludovico; Cercignani, Mara; Chan, Dennis

    2013-10-01

    Graph theory-based analyses of brain network topology can be used to model the spatiotemporal correlations in neural activity detected through fMRI, and such approaches have wide-ranging potential, from detection of alterations in preclinical Alzheimer's disease through to command identification in brain-machine interfaces. However, due to prohibitive computational costs, graph-based analyses to date have principally focused on measuring connection density rather than mapping the topological architecture in full by exhaustive shortest-path determination. This paper outlines a solution to this problem through parallel implementation of Dijkstra's algorithm in programmable logic. The processor design is optimized for large, sparse graphs and provided in full as synthesizable VHDL code. An acceleration factor between 15 and 18 is obtained on a representative resting-state fMRI dataset, and maps of Euclidean path length reveal the anticipated heterogeneous cortical involvement in long-range integrative processing. These results enable high-resolution geodesic connectivity mapping for resting-state fMRI in patient populations and real-time geodesic mapping to support identification of imagined actions for fMRI-based brain-machine interfaces. PMID:23746911

  16. Moderating effects of music on resting state networks

    Science.gov (United States)

    Kay, Benjamin P.; Meng, Xiangxiang; DiFrancesco, Mark; Holland, Scott K.; Szaflarski, Jerzy P.

    2012-01-01

    Resting state networks (RSNs) are spontaneous, synchronous, low-frequency oscillations observed in the brains of subjects who are awake but at rest. A particular RSN called the default mode network (DMN) has been shown to exhibit changes associated with neurological disorders such as temporal lobe epilepsy or Alzheimer’s disease. Previous studies have also found that differing experimental conditions such as eyes-open versus eyes-closed can produce measurable changes in the DMN. These condition-associated changes have the potential of confounding the measurements of changes in RSNs related to or caused by disease state(s). In this study, we use fMRI measurements of resting-state connectivity paired with EEG measurements of alpha rhythm and employ independent component analysis, undirected graphs of partial spectral coherence, and spatiotemporal regression to investigate the effect of music-listening on RSNs and the DMN in particular. We observed similar patterns of DMN connectivity in subjects who were listening to music compared with those who were not, with a trend towards a more introspective pattern of resting-state connectivity during music-listening. We conclude that music-listening is a valid condition under which the DMN can be studied. PMID:22365746

  17. Strength of Default Mode Resting-State Connectivity Relates to White Matter Integrity in Children

    Science.gov (United States)

    Gordon, Evan M.; Lee, Philip S.; Maisog, Jose M.; Foss-Feig, Jennifer; Billington, Michael E.; VanMeter, John; Vaidya, Chandan J.

    2011-01-01

    A default mode network of brain regions is known to demonstrate coordinated activity during the resting state. While the default mode network is well characterized in adults, few investigations have focused upon its development. We scanned 9-13-year-old children with diffusion tensor imaging and resting-state functional magnetic resonance imaging.…

  18. Efficient resting-state EEG network facilitates motor imagery performance

    Science.gov (United States)

    Zhang, Rui; Yao, Dezhong; Valdés-Sosa, Pedro A.; Li, Fali; Li, Peiyang; Zhang, Tao; Ma, Teng; Li, Yongjie; Xu, Peng

    2015-12-01

    Objective. Motor imagery-based brain-computer interface (MI-BCI) systems hold promise in motor function rehabilitation and assistance for motor function impaired people. But the ability to operate an MI-BCI varies across subjects, which becomes a substantial problem for practical BCI applications beyond the laboratory. Approach. Several previous studies have demonstrated that individual MI-BCI performance is related to the resting state of brain. In this study, we further investigate offline MI-BCI performance variations through the perspective of resting-state electroencephalography (EEG) network. Main results. Spatial topologies and statistical measures of the network have close relationships with MI classification accuracy. Specifically, mean functional connectivity, node degrees, edge strengths, clustering coefficient, local efficiency and global efficiency are positively correlated with MI classification accuracy, whereas the characteristic path length is negatively correlated with MI classification accuracy. The above results indicate that an efficient background EEG network may facilitate MI-BCI performance. Finally, a multiple linear regression model was adopted to predict subjects’ MI classification accuracy based on the efficiency measures of the resting-state EEG network, resulting in a reliable prediction. Significance. This study reveals the network mechanisms of the MI-BCI and may help to find new strategies for improving MI-BCI performance.

  19. Resting-state neuronal oscillatory correlates of working memory performance.

    Directory of Open Access Journals (Sweden)

    David Heister

    Full Text Available PURPOSE: Working memory (WM represents the brain's ability to maintain information in a readily available state for short periods of time. This study examines the resting-state cortical activity patterns that are most associated with performance on a difficult working-memory task. METHODS: Magnetoencephalographic (MEG band-passed (delta/theta (1-7 Hz, alpha (8-13 Hz, beta (14-30 Hz and sensor based regional power was collected in a population of adult men (18-28 yrs, n = 24 in both an eyes-closed and eyes-open resting state. The normalized power within each resting state condition as well as the normalized change in power between eyes closed and open (zECO were correlated with performance on a WM task. The regional and band-limited measures that were most associated with performance were then combined using singular value decomposition (SVD to determine the degree to which zECO power was associated with performance on the three-back verbal WM task. RESULTS: Changes in power from eyes closed to open revealed a significant decrease in power in all band-widths that was most pronounced in the posterior brain regions (delta/theta band. zECO right posterior frontal and parietal cortex delta/theta power were found to be inversely correlated with three-back working memory performance. The SVD evaluation of the most correlated zECO metrics then provided a singular measure that was highly correlated with three-back performance (r = -0.73, p<0.0001. CONCLUSION: Our results indicate that there is an association between WM performance and changes in resting-state power (right posterior frontal and parietal delta/theta power. Moreover, an SVD of the most associated zECO measures produces a composite resting-state metric of regional neural oscillatory power that has an improved association with WM performance. To our knowledge, this is the first investigation that has found that changes in resting state electromagnetic neural patterns are highly

  20. Physiological and psychological individual differences influence resting brain function measured by ASL perfusion.

    Science.gov (United States)

    Kano, M; Coen, S J; Farmer, A D; Aziz, Q; Williams, S C R; Alsop, D C; Fukudo, S; O'Gorman, R L

    2014-09-01

    Effects of physiological and/or psychological inter-individual differences on the resting brain state have not been fully established. The present study investigated the effects of individual differences in basal autonomic tone and positive and negative personality dimensions on resting brain activity. Whole-brain resting cerebral perfusion images were acquired from 32 healthy subjects (16 males) using arterial spin labeling perfusion MRI. Neuroticism and extraversion were assessed with the Eysenck Personality Questionnaire-Revised. Resting autonomic activity was assessed using a validated measure of baseline cardiac vagal tone (CVT) in each individual. Potential associations between the perfusion data and individual CVT (27 subjects) and personality score (28 subjects) were tested at the level of voxel clusters by fitting a multiple regression model at each intracerebral voxel. Greater baseline perfusion in the dorsal anterior cingulate cortex (ACC) and cerebellum was associated with lower CVT. At a corrected significance threshold of p personality traits (amygdala, caudate, etc.) during active task processing. The resting brain state may therefore need to be taken into account when interpreting the neurobiology of individual differences in structural and functional brain activity.

  1. Altered resting brain connectivity in persistent cancer related fatigue

    Directory of Open Access Journals (Sweden)

    Johnson P. Hampson

    2015-01-01

    Full Text Available There is an estimated 3 million women in the US living as breast cancer survivors and persistent cancer related fatigue (PCRF disrupts the lives of an estimated 30% of these women. PCRF is associated with decreased quality of life, decreased sleep quality, impaired cognition and depression. The mechanisms of cancer related fatigue are not well understood; however, preliminary findings indicate dysfunctional activity in the brain as a potential factor. Here we investigate the relationship between PCRF on intrinsic resting state connectivity in this population. Twenty-three age matched breast cancer survivors (15 fatigued and 8 non-fatigued who completed all cancer-related treatments at least 12 weeks prior to the study, were recruited to undergo functional connectivity magnetic resonance imaging (fcMRI. Intrinsic resting state networks were examined with both seed based and independent component analysis methods. Comparisons of brain connectivity patterns between groups as well as correlations with self-reported fatigue symptoms were performed. Fatigued patients displayed greater left inferior parietal lobule to superior frontal gyrus connectivity as compared to non-fatigued patients (P < 0.05 FDR corrected. This enhanced connectivity was associated with increased physical fatigue (P = 0.04, r = 0.52 and poor sleep quality (P = 0.04, r = 0.52 in the fatigued group. In contrast greater connectivity in the non-fatigued group was found between the right precuneus to the periaqueductal gray as well as the left IPL to subgenual cortex (P < 0.05 FDR corrected. Mental fatigue scores were associated with greater default mode network (DMN connectivity to the superior frontal gyrus (P = 0.05 FDR corrected among fatigued subjects (r = 0.82 and less connectivity in the non-fatigued group (r = −0.88. These findings indicate that there is enhanced intrinsic DMN connectivity to the frontal gyrus in breast cancer survivors with persistent

  2. Altered resting-state functional connectivity in patients with chronic bilateral vestibular failure

    Directory of Open Access Journals (Sweden)

    Martin Göttlich

    2014-01-01

    Using whole brain resting-state connectivity analysis in BVF patients we show that enduring bilateral deficient or missing vestibular input leads to changes in resting-state connectivity of the brain. These changes in the resting brain are robust and task-independent as they were found in the absence of sensory stimulation and without a region-related a priori hypothesis. Therefore they may indicate a fundamental disease-related change in the resting brain. They may account for the patients' persistent deficits in visuo-spatial attention, spatial orientation and unsteadiness. The relation of increasing connectivity in the inferior parietal lobe, specifically SMG, to improvement of VOR during active head movements reflects cortical plasticity in BVF and may play a clinical role in vestibular rehabilitation.

  3. Altered pattern of spontaneous brain activity in the patients with end-stage renal disease: a resting-state functional MRI study with regional homogeneity analysis.

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    Xue Liang

    Full Text Available PURPOSE: To investigate the pattern of spontaneous neural activity in patients with end-stage renal disease (ESRD with and without neurocognitive dysfunction using resting-state functional magnetic resonance imaging (rs-fMRI with a regional homogeneity (ReHo algorithm. MATERIALS AND METHODS: rs-fMRI data were acquired in 36 ESRD patients (minimal nephro-encephalopathy [MNE], n = 19, 13 male, 37±12.07 years; non-nephro-encephalopathy [non-NE], n = 17, 11 male, 38±12.13 years and 20 healthy controls (13 male, 7 female, 36±10.27 years. Neuropsychological (number connection test type A [NCT-A], digit symbol test [DST] and laboratory tests were performed in all patients. The Kendall's coefficient of concordance (KCC was used to measure the regional homogeneity for each subject. The regional homogeneity maps were compared using ANOVA tests among MNE, non-NE, and healthy control groups and post hoc t -tests between each pair in a voxel-wise way. A multiple regression analysis was performed to evaluate the relationships between ReHo index and NCT-A, DST scores, serum creatinine and urea levels, disease and dialysis duration. RESULTS: Compared with healthy controls, both MNE and non-NE patients showed decreased ReHo in the multiple areas of bilateral frontal, parietal and temporal lobes. Compared with the non-NE, MNE patients showed decreased ReHo in the right inferior parietal lobe (IPL, medial frontal cortex (MFC and left precuneus (PCu. The NCT-A scores and serum urea levels of ESRD patients negatively correlated with ReHo values in the frontal and parietal lobes, while DST scores positively correlated with ReHo values in the bilateral PCC/precuneus, MFC and inferior parietal lobe (IPL (all P0.05, AlphaSim corrected. CONCLUSION: Diffused decreased ReHo values were found in both MNE and non-NE patients. The progressively decreased ReHo in the default mode network (DMN, frontal and parietal lobes might be trait-related in MNE. The Re

  4. Resting brain metabolic correlates of neuroticism and extraversion in young men.

    Science.gov (United States)

    Kim, Sang Hee; Hwang, Ji Hee; Park, Hyun Soo; Kim, Sang Eun

    2008-05-28

    Neuroticism and extraversion are two core dimensions of personality and are considered to be associated with emotional disorders. We investigated resting state brain metabolic correlates of neuroticism and extraversion using a positron emission tomography. Twenty healthy young men completed an F-flurodeoxyglucose-PET scan at rest and the Korean version of the revised Eysenck Personality Questionnaire. Neuroticism was negatively correlated with regional glucose metabolism in prefrontal regions including the medial prefrontal cortex. Extraversion was positively correlated with metabolism in the right putamen. These results suggest close associations between resting state brain activity in the prefrontal and striatal regions and specific personality traits and thus contribute to the understanding of the neurobiological bases of predisposition to psychiatric disorders.

  5. Resting-state beta and gamma activity in Internet addiction.

    Science.gov (United States)

    Choi, Jung-Seok; Park, Su Mi; Lee, Jaewon; Hwang, Jae Yeon; Jung, Hee Yeon; Choi, Sam-Wook; Kim, Dai Jin; Oh, Sohee; Lee, Jun-Young

    2013-09-01

    Internet addiction is the inability to control one's use of the Internet and is related to impulsivity. Although a few studies have examined neurophysiological activity as individuals with Internet addiction engage in cognitive processing, no information on spontaneous EEG activity in the eyes-closed resting-state is available. We investigated resting-state EEG activities in beta and gamma bands and examined their relationships with impulsivity among individuals with Internet addiction and healthy controls. Twenty-one drug-naïve patients with Internet addiction (age: 23.33 ± 3.50 years) and 20 age-, sex-, and IQ-matched healthy controls (age: 22.40 ± 2.33 years) were enrolled in this study. Severity of Internet addiction was identified by the total score on Young's Internet Addiction Test. Impulsivity was measured with the Barratt Impulsiveness Scale-11 and a stop-signal task. Resting-state EEG during eyes closed was recorded, and the absolute/relative power of beta and gamma bands was analyzed. The Internet addiction group showed high impulsivity and impaired inhibitory control. The generalized estimating equation showed that the Internet-addiction group showed lower absolute power on the beta band than did the control group (estimate = -3.370, p Internet-addiction group showed higher absolute power on the gamma band than did the control group (estimate = 0.434, p Internet addiction as well as with the extent of impulsivity. The present study suggests that resting-state fast-wave brain activity is related to the impulsivity characterizing Internet addiction. These differences may be neurobiological markers for the pathophysiology of Internet addiction.

  6. The Effects of Long Duration Bed Rest on Brain Functional Connectivity and Sensorimotor Functioning

    Science.gov (United States)

    Cassady, K.; Koppelmans, V.; De Dios, Y.; Stepanyan, V.; Szecsy, D.; Gadd, N.; Wood, S.; Reuter-Lorenz, P.; Castenada, R. Riascos; Kofman, I.; Bloomberg, J.; Mulavara, A; Seidler, R.

    2016-01-01

    Long duration spaceflight has been associated with detrimental alterations in human sensorimotor functioning. Prolonged exposure to a head-down tilt (HDT) position during long duration bed rest can resemble several effects of the microgravity environment such as reduced sensory inputs, body unloading and increased cephalic fluid distribution. The question of whether microgravity affects other central nervous system functions such as brain functional connectivity and its relationship with behavior is largely unknown, but of importance to the health and performance of astronauts both during and post-flight. In the present study, we investigate the effects of prolonged exposure to HDT bed rest on resting state brain functional connectivity and its association with behavioral changes in 17 male participants. To validate that our findings were not due to confounding factors such as time or task practice, we also acquired resting state functional magnetic resonance imaging (rs-fMRI) and behavioral measurements from 14 normative control participants at four time points. Bed rest participants remained in bed with their heads tilted down six degrees below their feet for 70 consecutive days. Rs-fMRI and behavioral data were obtained at seven time points averaging around: 12 and 8 days prior to bed rest; 7, 50, and 70 days during bed rest; and 8 and 12 days after bed rest. 70 days of HDT bed rest resulted in significant increases in functional connectivity during bed rest followed by a reversal of changes in the post bed rest recovery period between motor cortical and somatosensory areas of the brain. In contrast, decreases in connectivity were observed between temporoparietal regions. Furthermore, post-hoc correlation analyses revealed a significant relationship between motor-somatosensory network connectivity and standing balance performance changes; participants that exhibited the greatest increases in connectivity strength showed the least deterioration in postural

  7. Increased interhemispheric resting-state functional connectivity after sleep deprivation: a resting-state fMRI study.

    Science.gov (United States)

    Zhu, Yuanqiang; Feng, Zhiyan; Xu, Junling; Fu, Chang; Sun, Jinbo; Yang, Xuejuan; Shi, Dapeng; Qin, Wei

    2016-09-01

    Several functional imaging studies have investigated the regional effects of sleep deprivation (SD) on impaired brain function; however, potential changes in the functional interactions between the cerebral hemispheres after SD are not well understood. In this study, we used a recently validated approach, voxel-mirrored homotopic connectivity (VMHC), to directly examine the changes in interhemispheric homotopic resting-state functional connectivity (RSFC) after SD. Resting-state functional MRI (fMRI) was performed in 28 participants both after rest wakefulness (RW) and a total night of SD. An interhemispheric RSFC map was obtained by calculating the Pearson correlation (Fisher Z transformed) between each pair of homotopic voxel time series for each subject in each condition. The between-condition differences in interhemispheric RSFC were then examined at global and voxelwise levels separately. Significantly increased global VMHC was found after sleep deprivation; specifically, a significant increase in VMHC was found in specific brain regions, including the thalamus, paracentral lobule, supplementary motor area, postcentral gyrus and lingual gyrus. No regions showed significantly reduced VMHC after sleep deprivation. Further analysis indicates that these findings did not depend on the various sizes of smoothing kernels that were adopted in the preprocessing steps and that the differences in these regions were still significant with or without global signal regression. Our data suggest that the increased VMHC might reflect the compensatory involvement of bilateral brain areas, especially the bilateral thalamus, to prevent cognitive performance deterioration when sleep pressure is elevated after sleep deprivation. Our findings provide preliminary evidence of interhemispheric correlation changes after SD and contribute to a better understanding of the neural mechanisms of SD. PMID:26634366

  8. 抑郁症脑网络的静息态功能磁共振研究%Resting-state fMRI study on brain network in depression

    Institute of Scientific and Technical Information of China (English)

    胡丹; 丁彩霞; 盛蕾

    2015-01-01

    Objective Depression is a mood disorder that causes a persistent feeling of sadness,with high morbidity rates and great social impairment.Increasingly studies show the abnormalities of brain networks.We summarized the results of resting state functional magnetic resonance imaging study of depression,and demonstrated the neural loops mechanism from neuroimaing perspective.Methods The key words "depression"," resting state" and" network" were searched in PubMed,CNKI and Wan Fang databases from January 2000 to December 2014.The nodes of depression related network and the alterations of cortex resting-state networks were summarized.Results 24 studies focusing on resting state network of depression were identified.40 studies based on ROI (region of interest) analysis,which included amygdala,frontal lobe,pregenual anterior cingulate cortex and cerebellum.The functional connectivity of ROIs were calculated and compared between groups.8 studies based on ICA (independent component analysis),the resting state networks were extracted and compared between groups.Two based on graph theory,the functional connectivity of whole brain were analyzed and compared.Conclusion There are abnormalities of functional connectivity among limbic system-thalamus-frontal cortex,and the changes of functional connectivity were associated with clinical symptom and drug efficacy of depression.%目的 抑郁症发病率高,危害大,目前对于抑郁症发病的原因和机制并不清楚,越来越多的研究表明其存在脑网络的改变,本综述总结了抑郁症脑网络的静息态功能磁共振研究结果,旨在从神经影像的角度探讨其神经环路的机制.方法 2014年12月在Medline、中国知网、万方等数据库.利用“抑郁症”、“静息态”、“脑网络”等检索词,检索2000年1月至2014年12月的文献,分析抑郁症相关的脑网络的关键脑区、抑郁症皮层静息态网络的改变.结果 共24篇关于抑郁症的静

  9. 基于静息态fMRI和DTI的大脑性别差异性研究%Research on the Differences of Brain between the Sexes based on the fMRI and DTI of Resting state

    Institute of Scientific and Technical Information of China (English)

    宋建太; 陶玲; 钱志余; 俞宙; 武江芬

    2014-01-01

    本研究从功能和结构两个方面来研究大脑存在的性别差异。利用I C A方法从大脑静息态fMRI数据中分离出大脑默认网络和感觉运动网络,通过双样本t检验来分析男女两性在脑皮层功能上所表现出来的异同;通过构建大脑白质纤维束结构网络,利用网络特征参数来分析男女脑部纤维结构上所存在的差异;通过二者联合技术来探讨两性大脑功能差异和结构差异的关系。结果发现两性大脑功能差异和结构差异在某些脑区有一定的一致性。男女两性大脑生理结构和功能有一定的关联性,两性大脑在功能上的差别可认为与两性在负责相关功能的脑区所具有的差异相关。%To study the brain function and structure of gender differces based on the fMRI and DTI technology of resting state.De-fault network and sensorimotor metwork were isolated from the fMRI data of brain′s resting state with the ICA method.The similarities and differences on cerebral function between the male and female were analyzed by two sample t-test.The relationship on the brain′s differences of functional structure between male and female were discused.The differences on the fiber structure of the male and fe-male were analyzed using the ntework characteristic parameters.The results showed that the differences on the brain′s function and structure between the male and female had certain consistency in some brain′s areas.It is concluded that the structure and function of brain between the male and female had certain relevance.It show that the functional differences of brain between the male and female have certain relevance with the difference of functional brain area charged by the male and female respectively.

  10. I am resting but rest less well with you. The Moderating Effect of Anxious Attachment Style on Alpha Power during EEG Resting State in a Social Context

    Directory of Open Access Journals (Sweden)

    Willem J.M.I. Verbeke

    2014-07-01

    Full Text Available We took EEG recordings to measure task-free resting-state cortical brain activity in 35 participants under two conditions, alone (A or together (T. We also investigated whether psychological attachment styles shape human cortical activity differently in these two settings. The results indicate that social context matters and that participants’ cortical activity is moderated by the anxious, but not avoidant attachment style. We found enhanced alpha, beta and theta band activity in the T rather than the A resting-state condition, which was more pronounced in posterior brain regions. We further found a positive correlation between anxious attachment style and enhanced alpha power in the T versus A condition over frontal and parietal scalp regions. There was no significant correlation between the absolute powers registered in the other two frequency bands and the participants’ anxious attachment style.

  11. Spatiotemporal Psychopathology II: How does a psychopathology of the brain's resting state look like? Spatiotemporal approach and the history of psychopathology.

    Science.gov (United States)

    Northoff, Georg

    2016-01-15

    Psychopathology as the investigation and classification of experience, behavior and symptoms in psychiatric patients is an old discipline that ranges back to the end of the 19th century. Since then different approaches to psychopathology have been suggested. Recent investigations showing abnormalities in the brain on different levels raise the question how the gap between brain and psyche, between neural abnormalities and alteration in experience and behavior can be bridged. Historical approaches like descriptive (Jaspers) and structural (Minkoswki) psychopathology as well as the more current phenomenological psychopathology (Paarnas, Fuchs, Sass, Stanghellini) remain on the side of the psyche giving detailed description of the phenomenal level of experience while leaving open the link to the brain. In contrast, the recently introduced Research Domain Classification (RDoC) aims at explicitly linking brain and psyche by starting from so-called 'neuro-behavioral constructs'. How does Spatiotemporal Psychopathology, as demonstrated in the first paper on depression, stand in relation to these approaches? In a nutshell, Spatiotemporal Psychopathology aims to bridge the gap between brain and psyche. Specifically, as demonstrated in depression in the first paper, the focus is on the spatiotemporal features of the brain's intrinsic activity and how they are transformed into corresponding spatiotemporal features in experience on the phenomenal level and behavioral changes, which can well account for the symptoms in these patients. This second paper focuses on some of the theoretical background assumptions in Spatiotemporal Psychopathology by directly comparing it to descriptive, structural, and phenomenological psychopathology as well as to RDoC. PMID:26071797

  12. Mitochondrial functional state impacts spontaneous neocortical activity and resting state FMRI.

    Directory of Open Access Journals (Sweden)

    Basavaraju G Sanganahalli

    Full Text Available Mitochondrial Ca(2+ uptake, central to neural metabolism and function, is diminished in aging whereas enhanced after acute/sub-acute traumatic brain injury. To develop relevant translational models for these neuropathologies, we determined the impact of perturbed mitochondrial Ca(2+ uptake capacities on intrinsic brain activity using clinically relevant markers. From a multi-compartment estimate of probable baseline Ca(2+ ranges in the brain, we hypothesized that reduced or enhanced mitochondrial Ca(2+ uptake capacity would decrease or increase spontaneous neuronal activity respectively. As resting state fMRI-BOLD fluctuations and stimulus-evoked BOLD responses have similar physiological origins [1] and stimulus-evoked neuronal and hemodynamic responses are modulated by mitochondrial Ca(2+ uptake capacity [2], [3] respectively, we tested our hypothesis by measuring hemodynamic fluctuations and spontaneous neuronal activities during normal and altered mitochondrial functional states. Mitochondrial Ca(2+ uptake capacity was perturbed by pharmacologically inhibiting or enhancing the mitochondrial Ca(2+ uniporter (mCU activity. Neuronal electrical activity and cerebral blood flow (CBF fluctuations were measured simultaneously and integrated with fMRI-BOLD fluctuations at 11.7T. mCU inhibition reduced spontaneous neuronal activity and the resting state functional connectivity (RSFC, whereas mCU enhancement increased spontaneous neuronal activity but reduced RSFC. We conclude that increased or decreased mitochondrial Ca(2+ uptake capacities lead to diminished resting state modes of brain functional connectivity.

  13. Disruption of Functional Brain Networks in Alzheimer’s Disease: What Can We Learn from Graph Spectral Analysis of Resting-State Magnetoencephalography?

    NARCIS (Netherlands)

    De Haan, W.; Van der Flier, W.M.; Wang, H.; Van Mieghem, P.F.A.; Scheltens, P.; Stam, C.J.

    2012-01-01

    In Alzheimer’s disease (AD), structural and functional brain network organization is disturbed. However, many of the present network analysis measures require a priori assumptions and methodological choices that influence outcomes and interpretations. Graph spectral analysis (GSA) is a more direct a

  14. Neuroticism and Functional Connectomics of the Resting Adolescent Brain - Insights from a Danish Child Cohort

    DEFF Research Database (Denmark)

    Baruël Johansen, Louise

    (MRI). Resting-state functional MRI is a widely used technique for studies of brain development due to the task-free condition. Furthermore, this imaging modality can be used to study the functional network of the brain that subserves communication between regions of the brain. Properties...... in a cohort of typically-developing children and adolescents aged 10 to 18 years to study the association between neuroticism and network organization. In the first part of the project, cross-sectional data was used to study whether netvi work characteristics associated with neuroticism observed in adults...

  15. Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia.

    Science.gov (United States)

    Kim, Junghoe; Calhoun, Vince D; Shim, Eunsoo; Lee, Jong-Hwan

    2016-01-01

    Functional connectivity (FC) patterns obtained from resting-state functional magnetic resonance imaging data are commonly employed to study neuropsychiatric conditions by using pattern classifiers such as the support vector machine (SVM). Meanwhile, a deep neural network (DNN) with multiple hidden layers has shown its ability to systematically extract lower-to-higher level information of image and speech data from lower-to-higher hidden layers, markedly enhancing classification accuracy. The objective of this study was to adopt the DNN for whole-brain resting-state FC pattern classification of schizophrenia (SZ) patients vs. healthy controls (HCs) and identification of aberrant FC patterns associated with SZ. We hypothesized that the lower-to-higher level features learned via the DNN would significantly enhance the classification accuracy, and proposed an adaptive learning algorithm to explicitly control the weight sparsity in each hidden layer via L1-norm regularization. Furthermore, the weights were initialized via stacked autoencoder based pre-training to further improve the classification performance. Classification accuracy was systematically evaluated as a function of (1) the number of hidden layers/nodes, (2) the use of L1-norm regularization, (3) the use of the pre-training, (4) the use of framewise displacement (FD) removal, and (5) the use of anatomical/functional parcellation. Using FC patterns from anatomically parcellated regions without FD removal, an error rate of 14.2% was achieved by employing three hidden layers and 50 hidden nodes with both L1-norm regularization and pre-training, which was substantially lower than the error rate from the SVM (22.3%). Moreover, the trained DNN weights (i.e., the learned features) were found to represent the hierarchical organization of aberrant FC patterns in SZ compared with HC. Specifically, pairs of nodes extracted from the lower hidden layer represented sparse FC patterns implicated in SZ, which was

  16. Task-induced deactivation from rest extends beyond the default mode brain network.

    Directory of Open Access Journals (Sweden)

    Ben J Harrison

    Full Text Available Activity decreases, or deactivations, of midline and parietal cortical brain regions are routinely observed in human functional neuroimaging studies that compare periods of task-based cognitive performance with passive states, such as rest. It is now widely held that such task-induced deactivations index a highly organized 'default-mode network' (DMN: a large-scale brain system whose discovery has had broad implications in the study of human brain function and behavior. In this work, we show that common task-induced deactivations from rest also occur outside of the DMN as a function of increased task demand. Fifty healthy adult subjects performed two distinct functional magnetic resonance imaging tasks that were designed to reliably map deactivations from a resting baseline. As primary findings, increases in task demand consistently modulated the regional anatomy of DMN deactivation. At high levels of task demand, robust deactivation was observed in non-DMN regions, most notably, the posterior insular cortex. Deactivation of this region was directly implicated in a performance-based analysis of experienced task difficulty. Together, these findings suggest that task-induced deactivations from rest are not limited to the DMN and extend to brain regions typically associated with integrative sensory and interoceptive processes.

  17. The Time Course of Task-Specific Memory Consolidation Effects in Resting State Networks

    OpenAIRE

    Sami, Saber; Edwin M Robertson; Miall, R. Chris

    2014-01-01

    Previous studies have reported functionally localized changes in resting-state brain activity following a short period of motor learning, but their relationship with memory consolidation and their dependence on the form of learning is unclear. We investigate these questions with implicit or explicit variants of the serial reaction time task (SRTT). fMRI resting-state functional connectivity was measured in human subjects before the tasks, and 0.1, 0.5, and 6 h after learning. There was signif...

  18. An Eight Month Randomized Controlled Exercise Intervention Alters Resting State Synchrony in Overweight Children

    OpenAIRE

    Krafft, Cynthia E.; Pierce, Jordan E.; Schwarz, Nicolette F.; Chi, Lingxi; Weinberger, Abby L.; Schaeffer, David J.; Rodrigue, Amanda L.; Camchong, Jazmin; Allison, Jerry D.; Yanasak, Nathan E.; Liu, Tianming; Davis, Catherine L.; McDowell, Jennifer E.

    2013-01-01

    Children with low aerobic fitness have altered brain function compared to higher-fit children. This study examined the effect of an 8-month exercise intervention on resting state synchrony. Twenty-two sedentary, overweight (body mass index ≥ 85th percentile) children 8–11 years old were randomly assigned to one of two after-school programs: aerobic exercise (n=13) or sedentary attention control (n=9). Before and after the 8-month programs, all subjects participated in resting state functional...

  19. Functional independence in resting-state connectivity facilitates higher-order cognition.

    Science.gov (United States)

    James, G Andrew; Kearney-Ramos, Tonisha E; Young, Jonathan A; Kilts, Clinton D; Gess, Jennifer L; Fausett, Jennifer S

    2016-06-01

    Growing evidence suggests that intrinsic functional connectivity (i.e. highly structured patterns of communication between brain regions during wakeful rest) may encode cognitive ability. However, the generalizability of these findings is limited by between-study differences in statistical methodology and cognitive domains evaluated. To address this barrier, we evaluated resting-state neural representations of multiple cognitive domains within a relatively large normative adult sample. Forty-four participants (mean(sd) age=31(10) years; 18 male and 26 female) completed a resting-state functional MRI scan and neuropsychological assessments spanning motor, visuospatial, language, learning, memory, attention, working memory, and executive function performance. Robust linear regression related cognitive performance to resting-state connectivity among 200 a priori determined functional regions of interest (ROIs). Only higher-order cognitions (such as learning and executive function) demonstrated significant relationships between brain function and behavior. Additionally, all significant relationships were negative - characterized by moderately positive correlations among low performers and weak to moderately negative correlations among high performers. These findings suggest that functional independence among brain regions at rest facilitates cognitive performance. Our interpretation is consistent with graph theoretic analyses which represent the brain as independent functional nodes that undergo dynamic reorganization with task demand. Future work will build upon these findings by evaluating domain-specific variance in resting-state neural representations of cognitive impairment among patient populations. PMID:27105037

  20. Increased resting-state functional connectivity of visual- and cognitive-control brain networks after training in children with reading difficulties

    Directory of Open Access Journals (Sweden)

    Tzipi Horowitz-Kraus

    2015-01-01

    Full Text Available The Reading Acceleration Program, a computerized reading-training program, increases activation in neural circuits related to reading. We examined the effect of the training on the functional connectivity between independent components related to visual processing, executive functions, attention, memory, and language during rest after the training. Children 8–12 years old with reading difficulties and typical readers participated in the study. Behavioral testing and functional magnetic resonance imaging were performed before and after the training. Imaging data were analyzed using an independent component analysis approach. After training, both reading groups showed increased single-word contextual reading and reading comprehension scores. Greater positive correlations between the visual-processing component and the executive functions, attention, memory, or language components were found after training in children with reading difficulties. Training-related increases in connectivity between the visual and attention components and between the visual and executive function components were positively correlated with increased word reading and reading comprehension, respectively. Our findings suggest that the effect of the Reading Acceleration Program on basic cognitive domains can be detected even in the absence of an ongoing reading task.

  1. Utility of resting fMRI and connectivity in patients with brain tumor

    Directory of Open Access Journals (Sweden)

    Sandhya Manglore

    2013-01-01

    Full Text Available Background: Resting state (task independent Functional Magnetic Resonance Imaging (fMRI has opened a new avenue in cognitive studies and has found practical clinical applications. Materials and Methods: Resting fMRI analysis was performed in six patients with brain tumor in the motor cortex. For comparison, task-related mapping of the motor cortex was done. Connectivity analysis to study the connections and strength of the connections between the primary motor cortex, premotor cortex, and primary somatosensory cortex on the affected side was also performed and compared with the contralateral normal side and the controls. Results: Resting fMRI in patients with brain tumor in the motor cortex mapped the motor cortex in a task-free state and the results were comparable to the motor task paradigm. Decreased connectivity on the tumor-affected side was observed, as compared to the unaffected side. Conclusion: Resting fMRI and connectivity analysis are useful in the presurgical evaluation of patients with brain tumors and may help in uncooperative or pediatric patients. They can also prognosticate the postoperative outcome. This method also has significant applications due to the ease of image acquisition.

  2. Preliminary Study of Brain Activity in Internet Addiction Adolescents:Revealed by Resting State Functional MRI%静息态脑功能成像在青少年网络成瘾中的初步研究

    Institute of Scientific and Technical Information of China (English)

    秦玲娣; 周滟; 赵志明; 路青; 戈欣; 李磊; 杜亚松; 许建荣

    2011-01-01

    目的 运用静息态脑功能磁共振成像局部一致性(ReHo)方法探索网络成瘾(intemet addiction,IA)青少年静息态脑功能的变化.资料与方法 采用3.0 T MBI对18名IA青少年和18名年龄、性别相匹配的正常对照组进行静息态脑功能扫描.采用静息态功能磁共振数据处理工具包(DPABSF)进行数据预处理和ReHo分析,采用双样本t检验分析,P<0.001,体素个数>10个被认为有统计学意义.结果 在静息状态下,与正常组比较,IA组以下脑区ReHo降低有统计意义,包括右侧海马旁回、右侧舌回、左侧脑岛、右侧中央后回和左侧顶下小叶.结论 IA青少年静息状态下脑默认网络与正常对照组存在差异,这可能为研究IA的发病机制提供新的依据.%Objective In the study,we used a regional homogeneity(ReHo) method to investigate Internet adolescents (IA) related modulations of neural activity in the resting state. Materials and Methods FMRIs were acquired in 18 adolescents with IA and 18 age-, sex-and education-matched normal adolescents. The data preprocessing and analysis were performed by Data Processing Assistant for Resting-State fMRI (DPARSF). A two-sample t-test was used to examine the difference of ReHo between the two groups(P <0.001 ,voxel size > 10). Results Compared with healthy controls,IA adolescents had lower ReHo in some areas including right parahippocampa gyrus, right posterior cingulated, left insula, right postcentral gyrus,left superior parietal lobule. Conclusion Our findings suggested that resting-state brain function changes were present in IA adolescents, and this finding may provide a new insight into the pathogenesis of IA.

  3. Decreased regional homogeneity in major depression as revealed by resting-state functional magnetic resonance imaging

    Institute of Scientific and Technical Information of China (English)

    PENG Dai-hui; JIANG Kai-da; FANG Yi-ru; XU Yi-feng; SHEN Ting; LONG Xiang-yu; LIU Jun; ZANG Yu-feng

    2011-01-01

    Backgroud Functional imaging studies indicate abnormal activities in cortico-limbic network in depression during either task or resting state. The present work was to explore the abnormal spontaneous activity shown with regional homogeneity (ReHo) in depression by resting-state functional magnetic resonance imaging (fMRI).Methods Using fMRI, the differences of regional brain activity were measured in resting state in depressed vs. healthy participants. Sixteen participants firstly diagnosed with major depressive disorder and 16 controls were scanned during resting state. A novel method based on ReHo was used to detect spontaneous hemodynamic responses across the whole brain.Results ReHo in the left thalamus, left temporal lobe, left cerebellar posterior lobe, and the bilateral occipital lobe was found to be significantly decreased in depression compared to healthy controls in resting state of depression.Conclusions Abnormal spontaneous activity exists in the left thalamus, left temporal lobe, left cerebellar posterior lobe,and the bilateral occipital lobe. And the ReHo may be a potential reference in understanding the distinct brain activity in resting state of depression.

  4. Resting State Functional Connectivity in Early Blind Humans

    Directory of Open Access Journals (Sweden)

    Harold eBurton

    2014-04-01

    Full Text Available Task-based neuroimaging studies in early blind humans (EB have demonstrated heightened visual cortex responses to non-visual paradigms. Several prior functional connectivity studies in EB have shown altered connections consistent with these task-based results. But these studies generally did not consider behavioral adaptations to lifelong blindness typically observed in EB. Enhanced cognitive abilities shown in EB include greater serial recall and attention to memory. Here, we address the question of the extent to which brain intrinsic activity in EB reflects such adaptations. We performed a resting-state functional magnetic resonance imaging study contrasting 14 EB with 14 age/gender matched normally sighted controls (NS. A principal finding was markedly greater functional connectivity in EB between visual cortex and regions typically associated with memory and cognitive control of attention. In contrast, correlations between visual cortex and non-deprived sensory cortices were significantly lower in EB. Thus, the available data, including that obtained in prior task-based and resting state fMRI studies, as well as the present results, indicate that visual cortex in EB becomes more heavily incorporated into functional systems instantiating episodic recall and attention to non-visual events. Moreover, EB appear to show a reduction in interactions between visual and non-deprived sensory cortices, possibly reflecting suppression of inter-sensory distracting activity.

  5. Low frequency overactivation in dyslexia: Evidence from resting state Magnetoencephalography.

    Science.gov (United States)

    Pagnotta, Mattia F; Zouridakis, George; Lianyang Li; Lizarazu, Mikel; Lallier, Marie; Molinaro, Nicola; Carreiras, Manuel

    2015-01-01

    In this study, we compared the brain activation profiles obtained from resting state Magnetoencephalographic (MEG) activity in 15 dyslexic patients with the profiles of 15 normal controls, using power spectral density (PSD) analysis. We first estimated intracranial dipolar MEG sources on a dense grid on the cortical surface and then projected these sources on a standardized atlas with 68 regions of interest (ROIs). Averaging the PSD values of all sources in each ROI across all control subjects resulted in a normative database that was used to convert the PSD values of dyslexic patients into z-scores in eight distinct frequency bands. We found that dyslexic patients exhibited statistically significant overactivation in the delta band (0.1-4 Hz) in the right temporal (entorhinal and insula), left inferior frontal (Broca's area), and right inferior frontal regions. Overactivation may be interpreted as a compensatory mechanism for reading characterizing dyslexic patients. These findings suggest that resting-state MEG activation maps may be used as specific biomarkers that can help with the diagnosis of and assess the efficacy of intervention in dyslexia.

  6. A baseline for the multivariate comparison of resting state networks

    Directory of Open Access Journals (Sweden)

    Elena A Allen

    2011-02-01

    Full Text Available As the size of functional and structural MRI datasets expands, it becomes increasingly important to establish a baseline from which diagnostic relevance may be determined, a processing strategy that efficiently prepares data for analysis, and a statistical approach that identifies important effects in a manner that is both robust and reproducible. In this paper, we introduce a multivariate analytic approach that optimizes sensitivity and reduces unnecessary testing. We demonstrate the utility of this mega-analytic approach by identifying the effects of age and gender on the resting state networks of 603 healthy adolescents and adults (mean age: 23.4 years, range: 12 to 71 years. Data were collected on the same scanner, preprocessed using an automated analysis pipeline based in SPM, and studied using group independent component analysis. Resting state networks were identified and evaluated in terms of three primary outcome measures: time course spectral power, spatial map intensity, and functional network connectivity. Results revealed robust effects of age on all three outcome measures, largely indicating decreases in network coherence and connectivity with increasing age. Gender effects were of smaller magnitude but suggested stronger intra-network connectivity in females and more inter-network connectivity in males, particularly with regard to sensorimotor networks. These findings, along with the analysis approach and statistical framework described here, provide a useful baseline for future investigations of brain networks in health and disease.

  7. Influences of acupuncture with effects of awakening consciousness and improving intelligence in group acupoints on brain resting state function*%针刺"醒神益智"组穴对脑静息态功能的影响

    Institute of Scientific and Technical Information of China (English)

    朱小棠; 冯天骄; 郑璐; 邱蕾; 张瑶; 张占军

    2011-01-01

    目的 应用功能磁共振成像(fMRI)技术研究针刺穴位、非穴位对大脑静息态功能网络的影响,从而为进一步阐释针刺的神经机制提供科学依据.方法 选取健康大学生20名,随机分为穴位组和非穴位组,穴位组针刺百会、双侧风池、双侧内关,非穴位组针刺上述各穴位旁开1.5~2.0 cm非穴位处.针刺30 min后,受试者即刻接受磁共振扫描,所采集到的fMRI数据,通过大脑活动局部一致性(ReHo)计算,获得穴位、非穴位组ReHo差异脑区;再以其中的差异脑区为种子点,计算其与大脑其他体素的功能连接(FC)情况.结果 穴位、非穴位组静息态脑活动差异主要表现在脑左侧梭状回、左侧颞下回和左侧脑岛,差异有统计学意义;以左侧脑岛为种子点进行FC分析发现,穴位、非穴位针刺后对脑内FC模式的影响不同,穴位组左侧脑岛与右侧额中回FC显著增强.结论 针刺百会、风池、内关对脑静患功能态的影响显示出了穴位具有特异性,临床选用上述组穴所发挥的益智醒神、改善记忆的功用,可能与其在静息功能状态下增强了脑左侧梭状回、左侧颞下回和左侧脑岛活动有关,如通过左侧脑岛与右侧额中回FC的显著增强,加强了记忆、学习等相关脑区的功能联系.%Objective To study the influences of acupuncture in acupoints and non-acupoints on brain resting state function network by applying functional magnetic resonance imaging (fMRI), and to provide scientific evidence for exploring further the neural mechanism of acupuncture. Methods Twenty health university students were selected and divided randomly into the acupoint group and non-acupoint group. The acupoint group was given acupuncture in Baihui (GV20), Fengchi (GB20, both sides) and Neiguan ( PC6, both sides), while the non-acupoint group was given acupuncture in the sites 1.5 cm to 2. 0 cm asides of the above mentioned acupoints. After 30 minutes, all

  8. Resting-state functional brain magnetic resonance imaging of vestibular function%前庭功能的静息态脑功能磁共振成像

    Institute of Scientific and Technical Information of China (English)

    王雪杰; 霍晓婷; 龙淼淼; 尹建忠; 陈太生

    2015-01-01

    目的 探讨基于局部一致性(ReHo)、低频振幅(ALFF)和低频振幅分数(fALFF)的静息态脑fMRI技术对于前庭冰水刺激诱导后脑内前庭功能相关区域的BOLD信号变化.方法 纳入20名正常志愿者,在10 s内将15 ml 0℃冰水注入受试者右侧外耳道,采用平面回波序列和32通道头线圈采集受试者的BOLD静息态脑功能成像数据,采用MatLab 7.1和SPM 8进行数据预处理,预处理后的数据采用REST 1.4软件计算获得ReHo、ALFF和fALFF图像.结果 ReHo、ALFF和fALFF图像均出现多个脑区激活增加或减低,其中3个参数值增加即激活脑区主要包括岛叶皮层、颞上回、顶下小叶、脑干、海马旁回、小脑半球等,减低即负激活脑区主要包括额上回、额中回、额下回、颞中回、枕下回、楔前叶等.结论 人类存在广泛的涉及前庭信息处理的脑皮层及皮层下网络区域,静息态脑功能成像ReHo、ALFF、fALFF分析方法具有较好的一致性,具备定位前庭功能区的潜在能力.

  9. Local signal time-series during rest used for areal boundary mapping in individual human brains.

    Directory of Open Access Journals (Sweden)

    Satoshi Hirose

    Full Text Available It is widely thought that resting state functional connectivity likely reflects functional interaction among brain areas and that different functional areas interact with different sets of brain areas. A method for mapping areal boundaries has been formulated based on the large-scale spatial characteristics of regional interaction revealed by resting state functional connectivity. In the present study, we present a novel analysis for areal boundary mapping that requires only the signal timecourses within a region of interest, without reference to the information from outside the region. The areal boundaries were generated by the novel analysis and were compared with those generated by the previously-established standard analysis. The boundaries were robust and reproducible across the two analyses, in two regions of interest tested. These results suggest that the information for areal boundaries is readily available inside the region of interest.

  10. 静息态功能磁共振在新生儿脑损伤中的应用研究%Application research of resting state functional magnetic resonance imaging in newborn brain damage

    Institute of Scientific and Technical Information of China (English)

    李红新; 屠文娟; 高敏; 江凯华; 董选

    2014-01-01

    新生儿脑损伤是新生儿死亡和儿童期致残的主要原因,现阶段的主要问题是对该部分患儿脑损伤的特点、客观的预后评估和早期干预的定位判断及康复后的疗效分析等方面存在一定困难,静息态功能磁共振(rs-fMRI)不需要受试者完成复杂的任务,适合新生儿脑功能的研究.目前关于rs-fMRI脑损伤方面的报道多是来自成人的研究,新生儿方面的研究甚少,国外目前也主要集中在新生儿脑发育的研究上.如果能够对新生儿脑损伤方面开展此项的研究,并获得有价值的研究成果,将不仅有助于更加全面、准确地了解新生儿缺氧缺血性脑病患儿脑损伤组织的结构和功能,而且还可以为临床提供更多更有价值的信息.%Newborn brain damage is the main cause of new-borns' death and disabilities.Current research difficulties lie in analyzing characteristics of cerebral injuries,making objective prognosis and early intervention,as well as analysis of therapeutic effects after recovery.Since subjects are not requested to complete complex tasks while doing resting state functional MRI (rs-fMRI) tests,rs-fMRI is reckoned to be suitable for neonatal brain function research.So far,most rs-fMRI reports regarding cerebral injury are for adults,with only a few have been done on neonates.Foreign research are mainly focused on new borns' brain development.If relevant rs-fMRI research can be done on newborn brain damage,it would be helpful to accurately evaluate structure and function of patients' brain tissue damage.Further research can provide more valuable information in clinics.

  11. Altered Regional Homogeneity in Pediatric Bipolar Disorder during Manic State: A Resting-State fMRI Study

    OpenAIRE

    Qian Xiao; Yuan Zhong; Dali Lu; Weijia Gao; Qing Jiao; Guangming Lu; Linyan Su

    2013-01-01

    UNLABELLED: Pediatric bipolar disorder (PBD) is a severely debilitating illness, which is characterized by episodes of mania and depression separated by periods of remission. Previous fMRI studies investigating PBD were mainly task-related. However, little is known about the abnormalities in PBD, especially during resting state. Resting state brain activity measured by fMRI might help to explore neurobiological biomarkers of the disorder. METHODS: Regional homogeneity (ReHo) was examined with...

  12. Functional connectivity dynamics: modeling the switching behavior of the resting state.

    Science.gov (United States)

    Hansen, Enrique C A; Battaglia, Demian; Spiegler, Andreas; Deco, Gustavo; Jirsa, Viktor K

    2015-01-15

    Functional connectivity (FC) sheds light on the interactions between different brain regions. Besides basic research, it is clinically relevant for applications in Alzheimer's disease, schizophrenia, presurgical planning, epilepsy, and traumatic brain injury. Simulations of whole-brain mean-field computational models with realistic connectivity determined by tractography studies enable us to reproduce with accuracy aspects of average FC in the resting state. Most computational studies, however, did not address the prominent non-stationarity in resting state FC, which may result in large intra- and inter-subject variability and thus preclude an accurate individual predictability. Here we show that this non-stationarity reveals a rich structure, characterized by rapid transitions switching between a few discrete FC states. We also show that computational models optimized to fit time-averaged FC do not reproduce these spontaneous state transitions and, thus, are not qualitatively superior to simplified linear stochastic models, which account for the effects of structure alone. We then demonstrate that a slight enhancement of the non-linearity of the network nodes is sufficient to broaden the repertoire of possible network behaviors, leading to modes of fluctuations, reminiscent of some of the most frequently observed Resting State Networks. Because of the noise-driven exploration of this repertoire, the dynamics of FC qualitatively change now and display non-stationary switching similar to empirical resting state recordings (Functional Connectivity Dynamics (FCD)). Thus FCD bear promise to serve as a better biomarker of resting state neural activity and of its pathologic alterations. PMID:25462790

  13. Infinite Relational Modeling of Functional Connectivity in Resting State fMRI

    DEFF Research Database (Denmark)

    Mørup, Morten; Madsen, Kristoffer H.; Dogonowski, Anne Marie;

    2010-01-01

    Functional magnetic resonance imaging (fMRI) can be applied to study the functional connectivity of the neural elements which form complex network at a whole brain level. Most analyses of functional resting state networks (RSN) have been based on the analysis of correlation between the temporal...... dynamics of various regions of the brain. While these models can identify coherently behaving groups in terms of correlation they give little insight into how these groups interact. In this paper we take a different view on the analysis of functional resting state networks. Starting from the definition...

  14. Overlapping communities reveal rich structure in large-scale brain networks during rest and task conditions.

    Science.gov (United States)

    Najafi, Mahshid; McMenamin, Brenton W; Simon, Jonathan Z; Pessoa, Luiz

    2016-07-15

    Large-scale analysis of functional MRI data has revealed that brain regions can be grouped into stable "networks" or communities. In many instances, the communities are characterized as relatively disjoint. Although recent work indicates that brain regions may participate in multiple communities (for example, hub regions), the extent of community overlap is poorly understood. To address these issues, here we investigated large-scale brain networks based on "rest" and task human functional MRI data by employing a mixed-membership Bayesian model that allows each brain region to belong to all communities simultaneously with varying membership strengths. The approach allowed us to 1) compare the structure of disjoint and overlapping communities; 2) determine the relationship between functional diversity (how diverse is a region's functional activation repertoire) and membership diversity (how diverse is a region's affiliation to communities); 3) characterize overlapping community structure; 4) characterize the degree of non-modularity in brain networks; 5) study the distribution of "bridges", including bottleneck and hub bridges. Our findings revealed the existence of dense community overlap that was not limited to "special" hubs. Furthermore, the findings revealed important differences between community organization during rest and during specific task states. Overall, we suggest that dense overlapping communities are well suited to capture the flexible and task dependent mapping between brain regions and their functions. PMID:27129758

  15. Oral contraceptive pill use and menstrual cycle phase are associated with altered resting state functional connectivity

    OpenAIRE

    Petersen, Nicole; Kilpatrick, Lisa A.; Goharzad, Azaadeh; Cahill, Larry

    2013-01-01

    At rest, brain activity can be characterized not by an absence of organized activity but instead by spatially and temporally correlated patterns of activity. In this experiment, we investigated whether and to what extent resting state functional connectivity is modulated by sex hormones in women, both across the menstrual cycle and when altered by oral contraceptive pills. Sex hormones have been shown to have important effects on task-related activity, but few studies have investigated the ex...

  16. Dynamic and static contributions of the cerebrovasculature to the resting-state BOLD signal.

    Science.gov (United States)

    Tak, Sungho; Wang, Danny J J; Polimeni, Jonathan R; Yan, Lirong; Chen, J Jean

    2014-01-01

    Functional magnetic resonance imaging (fMRI) in the resting state, particularly fMRI based on the blood-oxygenation level-dependent (BOLD) signal, has been extensively used to measure functional connectivity in the brain. However, the mechanisms of vascular regulation that underlie the BOLD fluctuations during rest are still poorly understood. In this work, using dual-echo pseudo-continuous arterial spin labeling and MR angiography (MRA), we assess the spatio-temporal contribution of cerebral blood flow (CBF) to the resting-state BOLD signals and explore how the coupling of these signals is associated with regional vasculature. Using a general linear model analysis, we found that statistically significant coupling between resting-state BOLD and CBF fluctuations is highly variable across the brain, but the coupling is strongest within the major nodes of established resting-state networks, including the default-mode, visual, and task-positive networks. Moreover, by exploiting MRA-derived large vessel (macrovascular) volume fraction, we found that the degree of BOLD-CBF coupling significantly decreased as the ratio of large vessels to tissue volume increased. These findings suggest that the portion of resting-state BOLD fluctuations at the sites of medium-to-small vessels (more proximal to local neuronal activity) is more closely regulated by dynamic regulations in CBF, and that this CBF regulation decreases closer to large veins, which are more distal to neuronal activity.

  17. The neural basis of unwanted thoughts during resting state.

    Science.gov (United States)

    Kühn, Simone; Vanderhasselt, Marie-Anne; De Raedt, Rudi; Gallinat, Jürgen

    2014-09-01

    Human beings are constantly engaged in thought. Sometimes thoughts occur repetitively and can become distressing. Up to now the neural bases of these intrusive or unwanted thoughts is largely unexplored. To study the neural correlates of unwanted thoughts, we acquired resting-state fMRI data of 41 female healthy subjects and assessed the self-reported amount of unwanted thoughts during measurement. We analyzed local connectivity by means of regional homogeneity (ReHo) and functional connectivity of a seed region. More unwanted thoughts (state) were associated with lower ReHo in right dorsolateral prefrontal cortex (DLPFC) and higher ReHo in left striatum (putamen). Additional seed-based analysis revealed higher functional connectivity of the left striatum with left inferior frontal gyrus (IFG) in participants reporting more unwanted thoughts. The state-dependent higher connectivty in left striatum was positively correlated with rumination assessed with a dedicated questionnaire focussing on trait aspects. Unwanted thoughts are associated with activity in the fronto-striatal brain circuitry. The reduction of local connectivity in DLPFC could reflect deficiencies in thought suppression processes, whereas the hightened activity in left striatum could imply an imbalance of gating mechanisms housed in basal ganglia. Its functional connectivity to left IFG is discussed as the result of thought-related speech processes. PMID:23929943

  18. Dynamic Resting-State Functional Connectivity in Major Depression.

    Science.gov (United States)

    Kaiser, Roselinde H; Whitfield-Gabrieli, Susan; Dillon, Daniel G; Goer, Franziska; Beltzer, Miranda; Minkel, Jared; Smoski, Moria; Dichter, Gabriel; Pizzagalli, Diego A

    2016-06-01

    Major depressive disorder (MDD) is characterized by abnormal resting-state functional connectivity (RSFC), especially in medial prefrontal cortical (MPFC) regions of the default network. However, prior research in MDD has not examined dynamic changes in functional connectivity as networks form, interact, and dissolve over time. We compared unmedicated individuals with MDD (n=100) to control participants (n=109) on dynamic RSFC (operationalized as SD in RSFC over a series of sliding windows) of an MPFC seed region during a resting-state functional magnetic resonance imaging scan. Among participants with MDD, we also investigated the relationship between symptom severity and RSFC. Secondary analyses probed the association between dynamic RSFC and rumination. Results showed that individuals with MDD were characterized by decreased dynamic (less variable) RSFC between MPFC and regions of parahippocampal gyrus within the default network, a pattern related to sustained positive connectivity between these regions across sliding windows. In contrast, the MDD group exhibited increased dynamic (more variable) RSFC between MPFC and regions of insula, and higher severity of depression was related to increased dynamic RSFC between MPFC and dorsolateral prefrontal cortex. These patterns of highly variable RSFC were related to greater frequency of strong positive and negative correlations in activity across sliding windows. Secondary analyses indicated that increased dynamic RSFC between MPFC and insula was related to higher levels of recent rumination. These findings provide initial evidence that depression, and ruminative thinking in depression, are related to abnormal patterns of fluctuating communication among brain systems involved in regulating attention and self-referential thinking. PMID:26632990

  19. First-episode depression resting state of brain function low frequency amplitude research%首发抑郁症静息态脑功能低频振幅研究

    Institute of Scientific and Technical Information of China (English)

    郭冬玲; 高阳; 牛广明; 谢生辉

    2016-01-01

    Objective: We used the method of resting-state functional magnetic resonance imaging (rfMRI) to explore the abnormal brain activity under the basic statusofpatientswithfirst-episode depression and its significance.Materials and Methods: Thirty patients with depression(the DSM-IV diagnostic criteria for depression) and thirty healthy volunteers matched with it were examined using resting-state functional MRI. Data analysis was processed by using the method of low-frequency amplitude (ALFF). Results:Intergroup analysis between depression and normal ALFF group:ALFF values of the parts of bilateral frontal lobes, temporal lobe and the cingulate gyrus and the right angular gyrus in depression groups are significantly higher than those in the control group; and ALFF values of bilateral medial prefrontal cortex, cuneus, precuneus, cerebellar hemisphere decreased. Conclusion:ALFF technology which can directly reflect the change of BOLD signal caused by abnormal metabolism of depressions with emotion disorder would contribute to exploration of the pathophysiological mechanisms of depression.%目的:采用静息态功能磁共振成像(resting-state functional magnetic resonance imaging, rfMRI)研究方法,探讨首发抑郁症患者基础状态下异常脑活动区及其意义。材料与方法对30例抑郁症患者(符合DSM-IV抑郁症的诊断标准)和与之匹配的30例健康志愿者进行静息态脑功能扫描。运用低频振幅(amplitude of low frequence fluctuation, ALFF)方法对数据分析,并采用双样本检验方法进行组间对比处理。结果抑郁症组与正常对照组ALFF图组间分析:抑郁症组大脑的双侧部分额叶、颞叶、扣带回及右侧角回等区域ALFF值显著高于正常对照组;而在双侧内侧前额叶、楔叶、楔前叶、小脑半球的ALFF值显著减低。结论ALFF技术可以直接反映抑郁症患者情绪异常引起的血氧水平依赖(blood oxygen level dependent, BOLD)信号代谢的改

  20. Resting-state magnetoencephalography study of “small world” characteristics and cognitive dysfunction in patients with glioma

    OpenAIRE

    Hu X; Lei T; Xu HZ; Zou YJ; Liu HY

    2013-01-01

    Xin-Hua Hu, Ting Lei, Hua-Zhong Xu, Yuan-Jie Zou, Hong-Yi Liu Department of Neurosurgery, Brain Hospital Affiliated to Nanjing Medical University, Nanjing, People's Republic of China Background: The purpose of this study was to analyze “small world” characteristics in glioma patients in order to understand the relationship between cognitive dysfunction and brain functional connectivity network in the resting state. Methods: Resting-state magnetoencephalography was performed in...

  1. Resting-state magnetoencephalography study of “small world” characteristics and cognitive dysfunction in patients with glioma

    OpenAIRE

    Hu, Xin-Hua

    2013-01-01

    Xin-Hua Hu, Ting Lei, Hua-Zhong Xu, Yuan-Jie Zou, Hong-Yi Liu Department of Neurosurgery, Brain Hospital Affiliated to Nanjing Medical University, Nanjing, People's Republic of China Background: The purpose of this study was to analyze “small world” characteristics in glioma patients in order to understand the relationship between cognitive dysfunction and brain functional connectivity network in the resting state. Methods: Resting-state magnetoencephalography was...

  2. Quantum Brain States

    CERN Document Server

    Mould, R A

    2003-01-01

    If conscious observers are to be included in the quantum mechanical universe, we need to find the rules that engage observers with quantum mechanical systems. The author has proposed five rules that are discovered by insisting on empirical completeness; that is, by requiring the rules to draw empirical information from Schrodinger's solutions that is more complete than is currently possible with the (Born) probability interpretation. I discard Born's interpretation, introducing probability solely through probability current. These rules tell us something about brains. They require the existence of observer brain states that are neither conscious nor unconscious. I call them 'ready' brain states because they are on stand-by, ready to become conscious the moment they are stochastically chosen. Two of the rules are selection rules involving ready brain states. The place of these rules in a wider theoretical context is discussed. Key Words: boundary conditions, consciousness, decoherence, macroscopic superpositio...

  3. The relation between resting state connectivity and creativity in adolescents before and after training

    NARCIS (Netherlands)

    Cousijn, Janna; Zanolie, Kiki; Munsters, Robbert J M; Kleibeuker, Sietske W; Crone, Eveline A

    2014-01-01

    An important component of creativity is divergent thinking, which involves the ability to generate novel and useful problem solutions. In this study, we tested the relation between resting-state functional connectivity of brain areas activated during a divergent thinking task (i.e., supramarginal gy

  4. How reliable are MEG resting-state connectivity metrics?

    OpenAIRE

    Colclough, GL; Woolrich, MW; Tewarie, PK; Brookes, MJ; Quinn, AJ; Smith, SM

    2016-01-01

    MEG offers dynamic and spectral resolution for resting-state connectivity which is unavailable in fMRI. However, there are a wide range of available network estimation methods for MEG, and little in the way of existing guidance on which ones to employ. In this technical note, we investigate the extent to which many popular measures of stationary connectivity are suitable for use in resting-state MEG, localising magnetic sources with a scalar beamformer. We use as empirical criteria that netwo...

  5. Exercise Effects on the Brain and Sensorimotor Function in Bed Rest

    Science.gov (United States)

    Koppelmans, V.; Cassady, K.; De Dios, Y. E.; Szecsy, D.; Gadd, N.; Wood, S. J.; Reuter-Lorenz, R. A.; Kofman, I.; Bloomberg, J. J.; Mulavara, A. P.; Ploutz-Snyder, L.; Seidler, R. D.

    2016-01-01

    Long duration spaceflight microgravity results in cephalad fluid shifts and deficits in posture control and locomotion. Effects of microgravity on sensorimotor function have been investigated on Earth using head down tilt bed rest (HDBR). HDBR serves as a spaceflight analogue because it mimics microgravity in body unloading and bodily fluid shifts. Preliminary results from our prior 70 days HDBR studies showed that HDBR is associated with focal gray matter (GM) changes and gait and balance deficits, as well as changes in brain functional connectivity. In consideration of the health and performance of crewmembers we investigated whether exercise reduces the effects of HDBR on GM, functional connectivity, and motor performance. Numerous studies have shown beneficial effects of exercise on brain health. We therefore hypothesized that an exercise intervention during HDBR could potentially mitigate the effects of HDBR on the central nervous system. Eighteen subjects were assessed before (12 and 7 days), during (7, 30, and 70 days) and after (8 and 12 days) 70 days of 6-degrees HDBR at the NASA HDBR facility in UTMB, Galveston, TX, US. Each subject was randomly assigned to a control group or one of two exercise groups. Exercise consisted of daily supine exercise which started 20 days before the start of HDBR. The exercise subjects participated either in regular aerobic and resistance exercise (e.g. squat, heel raise, leg press, cycling and treadmill running), or aerobic and resistance exercise using a flywheel apparatus (rowing). Aerobic and resistance exercise intensity in both groups was similar, which is why we collapsed the two exercise groups for the current experiment. During each time point T1-weighted MRI scans and resting state functional connectivity scans were obtained using a 3T Siemens scanner. Focal changes over time in GM density were assessed using voxel based morphometry (VBM8) under SPM. Changes in resting state functional connectivity was assessed

  6. Quantitative comparisons on hand motor functional areas determined by resting state and task BOLD fMRI and anatomical MRI for pre-surgical planning of patients with brain tumors

    Directory of Open Access Journals (Sweden)

    Bob L. Hou

    2016-01-01

    Full Text Available For pre-surgical planning we present quantitative comparison of the location of the hand motor functional area determined by right hand finger tapping BOLD fMRI, resting state BOLD fMRI, and anatomically using high resolution T1 weighted images. Data were obtained on 10 healthy subjects and 25 patients with left sided brain tumors. Our results show that there are important differences in the locations (i.e., >20 mm of the determined hand motor voxels by these three MR imaging methods. This can have significant effect on the pre-surgical planning of these patients depending on the modality used. In 13 of the 25 cases (i.e., 52% the distances between the task-determined and the rs-fMRI determined hand areas were more than 20 mm; in 13 of 25 cases (i.e., 52% the distances between the task-determined and anatomically determined hand areas were >20 mm; and in 16 of 25 cases (i.e., 64% the distances between the rs-fMRI determined and anatomically determined hand areas were more than 20 mm. In just three cases, the distances determined by all three modalities were within 20 mm of each other. The differences in the location or fingerprint of the hand motor areas, as determined by these three MR methods result from the different underlying mechanisms of these three modalities and possibly the effects of tumors on these modalities.

  7. Information Gain in the Brain’s Resting State: A New Perspective on Autism

    Directory of Open Access Journals (Sweden)

    José Luis ePérez Velázquez

    2013-12-01

    Full Text Available Along with the study of brain activity evoked by external stimuli, an increased interest in the research of background, noisy brain activity is fast developing in current neuroscience. It is becoming apparent that this resting-state activity is a major factor determining other, more particular, responses to stimuli and hence it can be argued that background activity carries important information used by the nervous systems for adaptive behaviors. In this context, we investigated the generation of information in ongoing brain activity recorded with magnetoencephalography (MEG in children with autism spectrum disorder (ASD and non-autistic children. Using a stochastic dynamical model of brain dynamics, we are able to resolve not only the deterministic interactions between brain regions, i.e. the brain’s functional connectivity, but also the stochastic inputs to the brain in the resting state; an important component of large-scale neural dynamics that no other method can resolve to date. We then computed the Kullback-Leibler divergence, also known as information gain or relative entropy, between the stochastic inputs and the brain activity at different locations (outputs in children with ASD compared to controls. The divergence between the input noise and the brain’s ongoing activity extracted from our stochastic model was significantly higher in autistic relative to non-autistic children. This suggests that more information is produced in the brains of subjects with autism at rest. We propose that the excessive production of information in the absence of relevant sensory stimuli or attention to external cues underlies the cognitive differences between individuals with and without autism. We conclude that the information gain in the brain’s resting state provides quantitative evidence for perhaps the most typical characteristic in autism: withdrawal into one's inner world.

  8. Spatially distributed effects of mental exhaustion on resting-state FMRI networks.

    Directory of Open Access Journals (Sweden)

    Fabrizio Esposito

    Full Text Available Brain activity during rest is spatially coherent over functional connectivity networks called resting-state networks. In resting-state functional magnetic resonance imaging, independent component analysis yields spatially distributed network representations reflecting distinct mental processes, such as intrinsic (default or extrinsic (executive attention, and sensory inhibition or excitation. These aspects can be related to different treatments or subjective experiences. Among these, exhaustion is a common psychological state induced by prolonged mental performance. Using repeated functional magnetic resonance imaging sessions and spatial independent component analysis, we explored the effect of several hours of sustained cognitive performances on the resting human brain. Resting-state functional magnetic resonance imaging was performed on the same healthy volunteers in two days, with and without, and before, during and after, an intensive psychological treatment (skill training and sustained practice with a flight simulator. After each scan, subjects rated their level of exhaustion and performed an N-back task to evaluate eventual decrease in cognitive performance. Spatial maps of selected resting-state network components were statistically evaluated across time points to detect possible changes induced by the sustained mental performance. The intensive treatment had a significant effect on exhaustion and effort ratings, but no effects on N-back performances. Significant changes in the most exhausted state were observed in the early visual processing and the anterior default mode networks (enhancement and in the fronto-parietal executive networks (suppression, suggesting that mental exhaustion is associated with a more idling brain state and that internal attention processes are facilitated to the detriment of more extrinsic processes. The described application may inspire future indicators of the level of fatigue in the neural attention system.

  9. Neural correlates of establishing, maintaining, and switching brain states.

    Science.gov (United States)

    Tang, Yi-Yuan; Rothbart, Mary K; Posner, Michael I

    2012-06-01

    Although the study of brain states is an old one in neuroscience, there has been growing interest in brain state specification owing to MRI studies tracing brain connectivity at rest. In this review, we summarize recent research on three relatively well-described brain states: the resting, alert, and meditation states. We explore the neural correlates of maintaining a state or switching between states, and argue that the anterior cingulate cortex and striatum play a critical role in state maintenance, whereas the insula has a major role in switching between states. Brain state may serve as a predictor of performance in a variety of perceptual, memory, and problem solving tasks. Thus, understanding brain states is critical for understanding human performance.

  10. DPARSF: a MATLAB toolbox for pipeline data analysis of resting-state fMRI

    Directory of Open Access Journals (Sweden)

    Chaogan Yan

    2010-05-01

    Full Text Available Resting-state functional magnetic resonance imaging (fMRI has attracted more and more attention because of its effectiveness, simplicity and non-invasiveness in exploration of the intrinsic functional architecture of the human brain. However, user-friendly toolbox for pipeline data analysis of resting-state fMRI is still lacking. Based on some functions in Statistical Parametric Mapping (SPM and Resting-State fMRI Data Analysis Toolkit (REST, we have developed a MATLAB toolbox called Data Processing Assistant for Resting-State fMRI (DPARSF for pipeline data analysis of resting-state fMRI. After the user arranges the DICOM files and click a few buttons to set parameters, DPARSF will then give all the preprocessed (slice timing, realign, normalize, smooth data and results for functional connectivity (FC, regional homogeneity (ReHo, amplitude of low-frequency fluctuation (ALFF, and fractional ALFF (fALFF. DPARSF can also create a report for excluding subjects with excessive head motion and generate a set of pictures for easily checking the effect of normalization. In addition, users can also use DPARSF to extract time courses from regions of interest.

  11. GABA concentration in posterior cingulate cortex predicts putamen response during resting state fMRI.

    Directory of Open Access Journals (Sweden)

    Jorge Arrubla

    Full Text Available The role of neurotransmitters in the activity of resting state networks has been gaining attention and has become a field of research with magnetic resonance spectroscopy (MRS being one of the key techniques. MRS permits the measurement of γ-aminobutyric acid (GABA and glutamate levels, the central biochemical constituents of the excitation-inhibition balance in vivo. The inhibitory effects of GABA in the brain have been largely investigated in relation to the activity of resting state networks in functional magnetic resonance imaging (fMRI. In this study GABA concentration in the posterior cingulate cortex (PCC was measured using single voxel spectra acquired with standard point resolved spectroscopy (PRESS from 20 healthy male volunteers at 3 T. Resting state fMRI was consecutively measured and the values of GABA/Creatine+Phosphocreatine ratio (GABA ratio were included in a general linear model matrix as a step of dual regression analysis in order to identify voxels whose neuroimaging metrics during rest were related to individual levels of the GABA ratio. Our data show that the connection strength of putamen to the default-mode network during resting state has a negative linear relationship with the GABA ratio measured in the PCC. These findings highlight the role of PCC and GABA in segregation of the motor input, which is an inherent condition that characterises resting state.

  12. Graph-based network analysis of resting-state functional MRI.

    Science.gov (United States)

    Wang, Jinhui; Zuo, Xinian; He, Yong

    2010-01-01

    In the past decade, resting-state functional MRI (R-fMRI) measures of brain activity have attracted considerable attention. Based on changes in the blood oxygen level-dependent signal, R-fMRI offers a novel way to assess the brain's spontaneous or intrinsic (i.e., task-free) activity with both high spatial and temporal resolutions. The properties of both the intra- and inter-regional connectivity of resting-state brain activity have been well documented, promoting our understanding of the brain as a complex network. Specifically, the topological organization of brain networks has been recently studied with graph theory. In this review, we will summarize the recent advances in graph-based brain network analyses of R-fMRI signals, both in typical and atypical populations. Application of these approaches to R-fMRI data has demonstrated non-trivial topological properties of functional networks in the human brain. Among these is the knowledge that the brain's intrinsic activity is organized as a small-world, highly efficient network, with significant modularity and highly connected hub regions. These network properties have also been found to change throughout normal development, aging, and in various pathological conditions. The literature reviewed here suggests that graph-based network analyses are capable of uncovering system-level changes associated with different processes in the resting brain, which could provide novel insights into the understanding of the underlying physiological mechanisms of brain function. We also highlight several potential research topics in the future.

  13. Bottom up modeling of the connectome: Linking structure and function in the resting brain and their changes in aging.

    OpenAIRE

    Nakagawa, Tristan T.; Jirsa, Viktor K.; Spiegler, Andreas; McIntosh, Anthony R.; Deco, Gustavo

    2013-01-01

    With the increasing availability of advanced imaging technologies, we are entering a new era of neuroscience. Detailed descriptions of the complex brain network enable us to map out a structural connectome, characterize it with graph theoretical methods, and compare it to the functional networks with increasing detail. To link these two aspects and understand how dynamics and structure interact to form functional brain networks in task and in the resting state, we use theore...

  14. Patients with Chronic Visceral Pain Show Sex-Related Alterations in Intrinsic Oscillations of the Resting Brain

    OpenAIRE

    Hong, Jui-Yang; Kilpatrick, Lisa A.; Labus, Jennifer; Gupta, Arpana; Jiang, Zhiguo; Ashe-McNalley, Cody; Stains, Jean; Heendeniya, Nuwanthi; EBRAT, BAHAR; Smith, Suzanne; Tillisch, Kirsten; Naliboff, Bruce; Mayer, Emeran A.

    2013-01-01

    Abnormal responses of the brain to delivered and expected aversive gut stimuli have been implicated in the pathophysiology of irritable bowel syndrome (IBS), a visceral pain syndrome occurring more commonly in women. Task-free resting-state functional magnetic resonance imaging (fMRI) can provide information about the dynamics of brain activity that may be involved in altered processing and/or modulation of visceral afferent signals. Fractional amplitude of low-frequency fluctuation is a meas...

  15. Functional connectivity analysis of resting-state fMRI networks in nicotine dependent patients

    Science.gov (United States)

    Smith, Aria; Ehtemami, Anahid; Fratte, Daniel; Meyer-Baese, Anke; Zavala-Romero, Olmo; Goudriaan, Anna E.; Schmaal, Lianne; Schulte, Mieke H. J.

    2016-03-01

    Brain imaging studies identified brain networks that play a key role in nicotine dependence-related behavior. Functional connectivity of the brain is dynamic; it changes over time due to different causes such as learning, or quitting a habit. Functional connectivity analysis is useful in discovering and comparing patterns between functional magnetic resonance imaging (fMRI) scans of patients' brains. In the resting state, the patient is asked to remain calm and not do any task to minimize the contribution of external stimuli. The study of resting-state fMRI networks have shown functionally connected brain regions that have a high level of activity during this state. In this project, we are interested in the relationship between these functionally connected brain regions to identify nicotine dependent patients, who underwent a smoking cessation treatment. Our approach is on the comparison of the set of connections between the fMRI scans before and after treatment. We applied support vector machines, a machine learning technique, to classify patients based on receiving the treatment or the placebo. Using the functional connectivity (CONN) toolbox, we were able to form a correlation matrix based on the functional connectivity between different regions of the brain. The experimental results show that there is inadequate predictive information to classify nicotine dependent patients using the SVM classifier. We propose other classification methods be explored to better classify the nicotine dependent patients.

  16. Oxytocin's effect on resting-state functional connectivity varies by age and sex.

    Science.gov (United States)

    Ebner, Natalie C; Chen, Huaihou; Porges, Eric; Lin, Tian; Fischer, Håkan; Feifel, David; Cohen, Ronald A

    2016-07-01

    The neuropeptide oxytocin plays a role in social cognition and affective processing. The neural processes underlying these effects are not well understood. Modulation of connectivity strength between subcortical and cortical regions has been suggested as one possible mechanism. The current study investigated effects of intranasal oxytocin administration on resting-state functional connectivity between amygdala and medial prefrontal cortex (mPFC), as two regions involved in social-cognitive and affective processing. Going beyond previous work that largely examined young male participants, our study comprised young and older men and women to identify age and sex variations in oxytocin's central processes. This approach was based on known hormonal differences among these groups and emerging evidence of sex differences in oxytocin's effects on amygdala reactivity and age-by-sex-modulated effects of oxytocin in affective processing. In a double-blind design, 79 participants were randomly assigned to self-administer either intranasal oxytocin or placebo before undergoing resting-state functional magnetic resonance imaging. Using a targeted region-to-region approach, resting-state functional connectivity strength between bilateral amygdala and mPFC was examined. Participants in the oxytocin compared to the placebo group and men compared to women had overall greater amygdala-mPFC connectivity strength at rest. These main effects were qualified by a significant three-way interaction: while oxytocin compared to placebo administration increased resting-state amygdala-mPFC connectivity for young women, oxytocin did not significantly influence connectivity in the other age-by-sex subgroups. This study provides novel evidence of age-by-sex differences in how oxytocin modulates resting-state brain connectivity, furthering our understanding of how oxytocin affects brain networks at rest. PMID:27032063

  17. Reduction of resting state network segregation is linked to disorders of consciousness

    Science.gov (United States)

    Rudas, Jorge; Martínez, Darwin; Guaje, Javier; Demertzi, Athena; Heine, Lizette; Tshibanda, Luaba; Soddu, Andrea; Laureys, Steven; Gómez, Francisco

    2015-12-01

    Recent evidence suggests that healthy brain is organized on large-scale in regions spatially distant and partially temporally synchronized. These regions commonly are called Resting State Networks (RSNs). Many RSNs has been identified in multiples spatial scales in healthy subjects and their interactions has been used to define the functional network connectivity (FNC). The main idea in FNC is that the dynamic shown in the interactions among RSNs in control subjects, can change in pathological and pharmacological conditions. However, this hypothesis assumes that functional structure of healthy brain, remains in other brain states or conditions. In this work, we proposed a novel methodology in order to find the new brain functional structure for disorders of consciousness conditions, based on multi-objective optimization approach. Particularly, we find the best partition of RSNs set, that maximize two modularity measures (Kapur and Otsu measures). Our results suggest that the brain segregation level, may be linked to consciousness level.

  18. Hypothalamus-Related Resting Brain Network Underlying Short-Term Acupuncture Treatment in Primary Hypertension

    Directory of Open Access Journals (Sweden)

    Hongyan Chen

    2013-01-01

    Full Text Available The present study attempted to explore modulated hypothalamus-seeded resting brain network underlying the cardiovascular system in primary hypertensive patients after short-term acupuncture treatment. Thirty right-handed patients (14 male were divided randomly into acupuncture and control groups. The acupuncture group received a continuous five-day acupuncture treatment and undertook three resting-state fMRI scans and 24-hour ambulatory blood pressure monitoring (ABPM as well as SF-36 questionnaires before, after, and one month after acupuncture treatment. The control group undertook fMRI scans and 24-hour ABPM. For verum acupuncture, average blood pressure (BP and heart rate (HR decreased after treatment but showed no statistical differences. There were no significant differences in BP and HR between the acupuncture and control groups. Notably, SF-36 indicated that bodily pain (P = 0.005 decreased and vitality (P = 0.036 increased after acupuncture compared to the baseline. The hypothalamus-related brain network showed increased functional connectivity with the medulla, brainstem, cerebellum, limbic system, thalamus, and frontal lobes. In conclusion, short-term acupuncture did not decrease BP significantly but appeared to improve body pain and vitality. Acupuncture may regulate the cardiovascular system through a complicated brain network from the cortical level, the hypothalamus, and the brainstem.

  19. Resting-brain functional connectivity predicted by analytic measures of network communication

    Science.gov (United States)

    Goñi, Joaquín; van den Heuvel, Martijn P.; Avena-Koenigsberger, Andrea; Velez de Mendizabal, Nieves; Betzel, Richard F.; Griffa, Alessandra; Hagmann, Patric; Corominas-Murtra, Bernat; Thiran, Jean-Philippe; Sporns, Olaf

    2014-01-01

    The complex relationship between structural and functional connectivity, as measured by noninvasive imaging of the human brain, poses many unresolved challenges and open questions. Here, we apply analytic measures of network communication to the structural connectivity of the human brain and explore the capacity of these measures to predict resting-state functional connectivity across three independently acquired datasets. We focus on the layout of shortest paths across the network and on two communication measures—search information and path transitivity—which account for how these paths are embedded in the rest of the network. Search information is an existing measure of information needed to access or trace shortest paths; we introduce path transitivity to measure the density of local detours along the shortest path. We find that both search information and path transitivity predict the strength of functional connectivity among both connected and unconnected node pairs. They do so at levels that match or significantly exceed path length measures, Euclidean distance, as well as computational models of neural dynamics. This capacity suggests that dynamic couplings due to interactions among neural elements in brain networks are substantially influenced by the broader network context adjacent to the shortest communication pathways. PMID:24379387

  20. Resting states are resting traits - an fMRI study of sex differences and menstrual cycle effects in resting state cognitive control networks.

    OpenAIRE

    Helene Hjelmervik; Markus Hausmann; Berge Osnes; René Westerhausen; Karsten Specht

    2014-01-01

    To what degree resting state fMRI is stable or susceptible to internal mind states of the individual is currently an issue of debate. To address this issue, the present study focuses on sex differences and investigates whether resting state fMRI is stable in men and women or changes within relative short-term periods (i.e., across the menstrual cycle). Due to the fact that we recently reported menstrual cycle effects on cognitive control based on data collected during the same sessions, the c...

  1. GPi Oscillatory Activity Differentiates Tics from the Resting State, Voluntary Movements, and the Unmedicated Parkinsonian State

    Science.gov (United States)

    Jimenez-Shahed, Joohi; Telkes, Ilknur; Viswanathan, Ashwin; Ince, Nuri F.

    2016-01-01

    Background: Deep brain stimulation (DBS) is an emerging treatment strategy for severe, medication-refractory Tourette syndrome (TS). Thalamic (Cm-Pf) and pallidal (including globus pallidus interna, GPi) targets have been the most investigated. While the neurophysiological correlates of Parkinson's disease (PD) in the GPi and subthalamic nucleus (STN) are increasingly recognized, these patterns are not well characterized in other disease states. Recent findings indicate that the cross-frequency coupling (CFC) between beta band and high frequency oscillations (HFOs) within the STN in PD patients is pathologic. Methods: We recorded intraoperative local field potentials (LFPs) from the postero-ventrolateral GPi in three adult patients with TS at rest, during voluntary movements, and during tic activity and compared them to the intraoperative GPi-LFP activity recorded from four unmedicated PD patients at rest. Results: In all PD patients, we noted excessive beta band activity (13–30 Hz) at rest which consistently modulated the amplitude of the co-existent HFOs observed between 200 and 400 Hz, indicating the presence of beta-HFO CFC. In all 3TS patients at rest, we observed theta band activity (4–7 Hz) and HFOs. Two patients had beta band activity, though at lower power than theta oscillations. Tic activity was associated with increased high frequency (200–400 Hz) and gamma band (35–200 Hz) activity. There was no beta-HFO CFC in TS patients at rest. However, CFC between the phase of 5–10 Hz band activity and the amplitude of HFOs was found in two TS patients. During tics, this shifted to CFC between the phase of beta band activity and the amplitude of HFOs in all subjects. Conclusions: To our knowledge this is the first study that shows that beta-HFO CFC exists in the GPi of TS patients during tics and at rest in PD patients, and suggests that this pattern might be specific to pathologic/involuntary movements. Furthermore, our findings suggest that during tics

  2. Face Patch Resting State Networks Link Face Processing to Social Cognition.

    Science.gov (United States)

    Schwiedrzik, Caspar M; Zarco, Wilbert; Everling, Stefan; Freiwald, Winrich A

    2015-01-01

    Faces transmit a wealth of social information. How this information is exchanged between face-processing centers and brain areas supporting social cognition remains largely unclear. Here we identify these routes using resting state functional magnetic resonance imaging in macaque monkeys. We find that face areas functionally connect to specific regions within frontal, temporal, and parietal cortices, as well as subcortical structures supporting emotive, mnemonic, and cognitive functions. This establishes the existence of an extended face-recognition system in the macaque. Furthermore, the face patch resting state networks and the default mode network in monkeys show a pattern of overlap akin to that between the social brain and the default mode network in humans: this overlap specifically includes the posterior superior temporal sulcus, medial parietal, and dorsomedial prefrontal cortex, areas supporting high-level social cognition in humans. Together, these results reveal the embedding of face areas into larger brain networks and suggest that the resting state networks of the face patch system offer a new, easily accessible venue into the functional organization of the social brain and into the evolution of possibly uniquely human social skills.

  3. Face Patch Resting State Networks Link Face Processing to Social Cognition.

    Directory of Open Access Journals (Sweden)

    Caspar M Schwiedrzik

    Full Text Available Faces transmit a wealth of social information. How this information is exchanged between face-processing centers and brain areas supporting social cognition remains largely unclear. Here we identify these routes using resting state functional magnetic resonance imaging in macaque monkeys. We find that face areas functionally connect to specific regions within frontal, temporal, and parietal cortices, as well as subcortical structures supporting emotive, mnemonic, and cognitive functions. This establishes the existence of an extended face-recognition system in the macaque. Furthermore, the face patch resting state networks and the default mode network in monkeys show a pattern of overlap akin to that between the social brain and the default mode network in humans: this overlap specifically includes the posterior superior temporal sulcus, medial parietal, and dorsomedial prefrontal cortex, areas supporting high-level social cognition in humans. Together, these results reveal the embedding of face areas into larger brain networks and suggest that the resting state networks of the face patch system offer a new, easily accessible venue into the functional organization of the social brain and into the evolution of possibly uniquely human social skills.

  4. Changes in cognitive state alter human functional brain networks

    Directory of Open Access Journals (Sweden)

    Malaak Nasser Moussa

    2011-08-01

    Full Text Available The study of the brain as a whole system can be accomplished using network theory principles. Research has shown that human functional brain networks during a resting state exhibit small-world properties and high degree nodes, or hubs, localized to brain areas consistent with the default mode network (DMN. However, the study of brain networks across different tasks and or cognitive states has been inconclusive. Research in this field is important because the underpinnings of behavioral output are inherently dependent on whether or not brain networks are dynamic. This is the first comprehensive study to evaluate multiple network metrics at a voxel-wise resolution in the human brain at both the whole brain and regional level under various conditions: resting state, visual stimulation, and multisensory (auditory and visual stimulation. Our results show that despite global network stability, functional brain networks exhibit considerable task-induced changes in connectivity, efficiency, and community structure at the regional level.

  5. Acupuncture modulates resting state hippocampal functional connectivity in Alzheimer disease.

    Directory of Open Access Journals (Sweden)

    Zhiqun Wang

    Full Text Available Our objective is to clarify the effects of acupuncture on hippocampal connectivity in patients with Alzheimer disease (AD using functional magnetic resonance imaging (fMRI. Twenty-eight right-handed subjects (14 AD patients and 14 healthy elders participated in this study. Clinical and neuropsychological examinations were performed on all subjects. MRI was performed using a SIEMENS verio 3-Tesla scanner. The fMRI study used a single block experimental design. We first acquired baseline resting state data during the initial 3 minutes and then performed acupuncture stimulation on the Tai chong and He gu acupoints for 3 minutes. Last, we acquired fMRI data for another 10 minutes after the needle was withdrawn. The preprocessing and data analysis were performed using statistical parametric mapping (SPM5 software. Two-sample t-tests were performed using data from the two groups in different states. We found that during the resting state, several frontal and temporal regions showed decreased hippocampal connectivity in AD patients relative to control subjects. During the resting state following acupuncture, AD patients showed increased connectivity in most of these hippocampus related regions compared to the first resting state. In conclusion, we investigated the effect of acupuncture on AD patients by combing fMRI and traditional acupuncture. Our fMRI study confirmed that acupuncture at Tai chong and He gu can enhance the hippocampal connectivity in AD patients.

  6. A study on resting-state magnetoencephalography of interictal brain activity in patients with temporal lobe epilepsy%颞叶癫痫患者发作间期脑活动的静息态脑磁图研究

    Institute of Scientific and Technical Information of China (English)

    朱旭昌; 朱海涛; 朱劲龙; 张锐

    2015-01-01

    目的:用脑磁图合成孔径磁场测定(SAMg2)技术分析左侧颞叶癫痫患者与正常对照者的脑电活动差异,评估左侧颞叶癫痫患者发作间期脑活动的改变。方法给20例左侧颞叶癫痫患者及20名健康志愿者(正常对照组)进行静息态脑磁图检查,通过 CTF 软件中的合成孔径磁场测定技术计算所有受试者的SAMg2值;计算后,使每位受试者的 SAMg2值与其对应的3D-MRI 进行融合。结果与正常对照组比较,左侧颞叶癫痫患者颞叶及其内侧结构的 SAMg2值显著升高,而双侧视觉皮质等颞叶以外脑区的 SAMg2值降低。左侧颞叶癫痫患者异常区域的脑活动与癫痫发作频率密切相关,而性别、年龄的影响无统计学意义。结论左侧颞叶癫痫是一种多灶性的网络疾病,具有复杂的癫痫网络和脑功能缺失网络。%Objective To analyze the activity differences between patients with left temporal lobe epilepsy(LTLE)and normal controls by magnetoencephalography(MEG)synthetic aperture magnetometry(SAM),and assess the alteration of interictal brain activity in patients with LTLE. Methods Resting-state MEG data were collected from 20 patients with LTLE and 20 healthy volunteers(normal control group).The SAMg2 Z-map of each subject were calculated by the SAMg2 script of the CTF software.After the calculation,the SAMg2 Z-map of each subject were registered with their corresponding 3D MRI.Results Compared with the normal control group,significantly elevated SAMg2 signals were found in left temporal lobe epilepsy patients in the left temporal lobe and medial structures.Marked decreases of SAMg2 signals were found in wide extratemporal lobe, such as the bilateral visual cortex.Abnormal regions of left temporal lobe epilepsy patients were significantly associated with frequency of seizures.There were no significant differences in age and gender between the two groups.Conclusion Left temporal lobe epilepsy

  7. Automatic classification of schizophrenia using resting-state functional language network via an adaptive learning algorithm

    Science.gov (United States)

    Zhu, Maohu; Jie, Nanfeng; Jiang, Tianzi

    2014-03-01

    A reliable and precise classification of schizophrenia is significant for its diagnosis and treatment of schizophrenia. Functional magnetic resonance imaging (fMRI) is a novel tool increasingly used in schizophrenia research. Recent advances in statistical learning theory have led to applying pattern classification algorithms to access the diagnostic value of functional brain networks, discovered from resting state fMRI data. The aim of this study was to propose an adaptive learning algorithm to distinguish schizophrenia patients from normal controls using resting-state functional language network. Furthermore, here the classification of schizophrenia was regarded as a sample selection problem where a sparse subset of samples was chosen from the labeled training set. Using these selected samples, which we call informative vectors, a classifier for the clinic diagnosis of schizophrenia was established. We experimentally demonstrated that the proposed algorithm incorporating resting-state functional language network achieved 83.6% leaveone- out accuracy on resting-state fMRI data of 27 schizophrenia patients and 28 normal controls. In contrast with KNearest- Neighbor (KNN), Support Vector Machine (SVM) and l1-norm, our method yielded better classification performance. Moreover, our results suggested that a dysfunction of resting-state functional language network plays an important role in the clinic diagnosis of schizophrenia.

  8. Graph-based network analysis of resting-state functional MRI

    Directory of Open Access Journals (Sweden)

    Jinhui Wang

    2010-06-01

    Full Text Available In the past decade, resting-state functional MRI (R-fMRI measures of brain activity have attracted considerable attention. Based on changes in the blood oxygen level-dependent signal, R-fMRI offers a novel way to assess the brain’s spontaneous or intrinsic (i.e., task-free activity with both high spatial and temporal resolutions. The properties of both the intra- and inter-regional connectivity of resting-state brain activity have been well documented, promoting our understanding of the brain as a complex network. Specifically, the topological organization of brain networks has been recently studied with graph theory. In this review, we will summarize the recent advances in graph-based brain network analyses of R-fMRI signals, both in typical and atypical populations. Application of these approaches to R-fMRI data has demonstrated non-trivial topological properties of functional networks in the human brain. Among these is the knowledge that the brain’s intrinsic activity is organized as a small-world, highly efficient network, with significant modularity and highly connected hub regions. These network properties have also been found to change throughout normal development, aging and in various pathological conditions. The literature reviewed here suggests that graph-based network analyses are capable of uncovering system-level changes associated with different processes in the resting brain, which could provide novel insights into the understanding of the underlying physiological mechanisms of brain function. We also highlight several potential research topics in the future.

  9. Resting cerebral metabolism correlates with skin conductance and functional brain activation during fear conditioning

    OpenAIRE

    Linnman, Clas; Zeidan, Mohamed A.; Pitman, Roger K.; Milad, Mohammed R.

    2011-01-01

    We investigated whether resting brain metabolism can be used to predict autonomic and neuronal responses during fear conditioning in 20 healthy humans. Regional cerebral metabolic rate for glucose was measured via positron emission tomography at rest. During conditioning, autonomic responses were measured via skin conductance, and blood oxygen level dependent signal was measured via functional magnetic resonance imaging. Resting dorsal anterior cingulate metabolism positively predicted differ...

  10. Non-stationarity in the "resting brain's" modular architecture.

    Directory of Open Access Journals (Sweden)

    David T Jones

    Full Text Available Task-free functional magnetic resonance imaging (TF-fMRI has great potential for advancing the understanding and treatment of neurologic illness. However, as with all measures of neural activity, variability is a hallmark of intrinsic connectivity networks (ICNs identified by TF-fMRI. This variability has hampered efforts to define a robust metric of connectivity suitable as a biomarker for neurologic illness. We hypothesized that some of this variability rather than representing noise in the measurement process, is related to a fundamental feature of connectivity within ICNs, which is their non-stationary nature. To test this hypothesis, we used a large (n = 892 population-based sample of older subjects to construct a well characterized atlas of 68 functional regions, which were categorized based on independent component analysis network of origin, anatomical locations, and a functional meta-analysis. These regions were then used to construct dynamic graphical representations of brain connectivity within a sliding time window for each subject. This allowed us to demonstrate the non-stationary nature of the brain's modular organization and assign each region to a "meta-modular" group. Using this grouping, we then compared dwell time in strong sub-network configurations of the default mode network (DMN between 28 subjects with Alzheimer's dementia and 56 cognitively normal elderly subjects matched 1:2 on age, gender, and education. We found that differences in connectivity we and others have previously observed in Alzheimer's disease can be explained by differences in dwell time in DMN sub-network configurations, rather than steady state connectivity magnitude. DMN dwell time in specific modular configurations may also underlie the TF-fMRI findings that have been described in mild cognitive impairment and cognitively normal subjects who are at risk for Alzheimer's dementia.

  11. 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.

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

    Directory of Open Access Journals (Sweden)

    C. Rondinoni

    2013-12-01

    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.

  13. Resting-State Oscillatory Activity in Autism Spectrum Disorders

    Science.gov (United States)

    Cornew, Lauren; Roberts, Timothy P. L.; Blaskey, Lisa; Edgar, J. Christopher

    2012-01-01

    Neural oscillatory anomalies in autism spectrum disorders (ASD) suggest an excitatory/inhibitory imbalance; however, the nature and clinical relevance of these anomalies are unclear. Whole-cortex magnetoencephalography data were collected while 50 children (27 with ASD, 23 controls) underwent an eyes-closed resting-state exam. A Fast Fourier…

  14. Altered regional homogeneity in pediatric bipolar disorder during manic state: a resting-state fMRI study.

    Directory of Open Access Journals (Sweden)

    Qian Xiao

    Full Text Available UNLABELLED: Pediatric bipolar disorder (PBD is a severely debilitating illness, which is characterized by episodes of mania and depression separated by periods of remission. Previous fMRI studies investigating PBD were mainly task-related. However, little is known about the abnormalities in PBD, especially during resting state. Resting state brain activity measured by fMRI might help to explore neurobiological biomarkers of the disorder. METHODS: Regional homogeneity (ReHo was examined with resting-state fMRI (RS-fMRI on 15 patients with PBD in manic state, with 15 age-and sex-matched healthy youth subjects as controls. RESULTS: Compared with the healthy controls, the patients with PBD showed altered ReHo in the cortical and subcortical structures. The ReHo measurement of the PBD group was negatively correlated with the score of Young Mania Rating Scale (YMRS in the superior frontal gyrus. Positive correlations between the ReHo measurement and the score of YMRS were found in the hippocampus and the anterior cingulate cortex in the PBD group. CONCLUSIONS: Altered regional brain activity is present in patients with PBD during manic state. This study presents new evidence for abnormal ventral-affective and dorsal-cognitive circuits in PBD during resting state and may add fresh insights into the pathophysiological mechanisms underlying PBD.

  15. Decreased resting functional connectivity after traumatic brain injury in the rat.

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    Asht Mangal Mishra

    Full Text Available Traumatic brain injury (TBI contributes to about 10% of acquired epilepsy. Even though the mechanisms of post-traumatic epileptogenesis are poorly known, a disruption of neuronal networks predisposing to altered neuronal synchrony remains a viable candidate mechanism. We tested a hypothesis that resting state BOLD-fMRI functional connectivity can reveal network abnormalities in brain regions that are connected to the lesioned cortex, and that these changes associate with functional impairment, particularly epileptogenesis. TBI was induced using lateral fluid-percussion injury in seven adult male Sprague-Dawley rats followed by functional imaging at 9.4T 4 months later. As controls we used six sham-operated animals that underwent all surgical operations but were not injured. Electroencephalogram (EEG-functional magnetic resonance imaging (fMRI was performed to measure resting functional connectivity. A week after functional imaging, rats were implanted with bipolar skull electrodes. After recovery, rats underwent pentyleneterazol (PTZ seizure-susceptibility test under EEG. For image analysis, four pairs of regions of interests were analyzed in each hemisphere: ipsilateral and contralateral frontal and parietal cortex, hippocampus, and thalamus. High-pass and low-pass filters were applied to functional imaging data. Group statistics comparing injured and sham-operated rats and correlations over time between each region were calculated. In the end, rats were perfused for histology. None of the rats had epileptiform discharges during functional imaging. PTZ-test, however revealed increased seizure susceptibility in injured rats as compared to controls. Group statistics revealed decreased connectivity between the ipsilateral and contralateral parietal cortex and between the parietal cortex and hippocampus on the side of injury as compared to sham-operated animals. Injured animals also had abnormal negative connectivity between the ipsilateral and

  16. EEG-fMRI study of resting-state networks in childhood absence epilepsy

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    ZHENG Ling

    2012-10-01

    Full Text Available Objective To observe the alterations of resting-state brain functional networks in childhood absence epilepsy (CAE using resting-state functional magnetic resonance imaging (fMRI analysis, and to explore the cognitive disorders of children in epileptic seizures. Methods According to case selection criteria, 12 children with absence seizure were selected, from whom 17 fMRI data with generalized slow-wave discharges (GSWD and the matched data without discharges were collected by using electroencephalogram (EEG-fMRI synchronization. Independent component analysis was used to investigate the alterations in different states of 7 resting-state networks including the thalamus, default-mode network, dorsal attention network, central execution network and perceptive networks. Results Paired t-test and correlation analysis were used for statistical analysis. The thalamus showed increased coherence of brain activity in GSWD state, and the increased coherence was positively correlated with the durations of GSWD (r = 0.890, P = 0.000. The default-mode network (r = - 0.706, P = 0.000, dorsal attention network (r = - 0.829, P = 0.000 and central execution network (r = - 0.905, P = 0.000, which dealt with high -grade cognitive functions, showed decreased coherence, and the brain activity coherence in these networks were negatively correlated with GSWD durations. However, none of low-grade perceptive networks was found to have significant alteration in GSWD state. Conclusion The increased coherence of brain activity in the thalamus may be associated with the generation of GSWD in childhood absence epilepsy. Besides the default brain function, the processes of attention and cognitive execution may also be impaired in childhood absence epilepsy, while low-grade perceptive functions may not be greatly impacted. This study may contribute to the understanding of pathophysiological mechanism of impaired consciousness in childhood absence epilepsy.

  17. An eight month randomized controlled exercise intervention alters resting state synchrony in overweight children.

    Science.gov (United States)

    Krafft, C E; Pierce, J E; Schwarz, N F; Chi, L; Weinberger, A L; Schaeffer, D J; Rodrigue, A L; Camchong, J; Allison, J D; Yanasak, N E; Liu, T; Davis, C L; McDowell, J E

    2014-01-01

    Children with low aerobic fitness have altered brain function compared to higher-fit children. This study examined the effect of an 8-month exercise intervention on resting state synchrony. Twenty-two sedentary, overweight (body mass index ≥85th percentile) children 8-11 years old were randomly assigned to one of two after-school programs: aerobic exercise (n=13) or sedentary attention control (n=9). Before and after the 8-month programs, all subjects participated in resting state functional magnetic resonance imaging scans. Independent components analysis identified several networks, with four chosen for between-group analysis: salience, default mode, cognitive control, and motor networks. The default mode, cognitive control, and motor networks showed more spatial refinement over time in the exercise group compared to controls. The motor network showed increased synchrony in the exercise group with the right medial frontal gyrus compared to controls. Exercise behavior may enhance brain development in children. PMID:24096138

  18. Resting-state fMRI can reliably map neural networks in children.

    Science.gov (United States)

    Thomason, Moriah E; Dennis, Emily L; Joshi, Anand A; Joshi, Shantanu H; Dinov, Ivo D; Chang, Catie; Henry, Melissa L; Johnson, Rebecca F; Thompson, Paul M; Toga, Arthur W; Glover, Gary H; Van Horn, John D; Gotlib, Ian H

    2011-03-01

    Resting-state MRI (rs-fMRI) is a powerful procedure for studying whole-brain neural connectivity. In this study we provide the first empirical evidence of the longitudinal reliability of rs-fMRI in children. We compared rest-retest measurements across spatial, temporal and frequency domains for each of six cognitive and sensorimotor intrinsic connectivity networks (ICNs) both within and between scan sessions. Using Kendall'sW, concordance of spatial maps ranged from .60 to .86 across networks, for various derived measures. The Pearson correlation coefficient for temporal coherence between networks across all Time 1-Time 2 (T1/T2) z-converted measures was .66 (p<.001). There were no differences between T1/T2 measurements in low-frequency power of the ICNs. For the visual network, within-session T1 correlated with the T2 low-frequency power, across participants. These measures from resting-state data in children were consistent across multiple domains (spatial, temporal, and frequency). Resting-state connectivity is therefore a reliable method for assessing large-scale brain networks in children. PMID:21134471

  19. Adolescent Resting State Networks and Their Associations with Schizotypal Trait Expression

    OpenAIRE

    Annalaura Lagioia; Dimitri Van de Ville; Martin Debbané; François Lazeyras; Stephan Eliez

    2010-01-01

    The rising interest in temporally coherent brain networks during baseline adult cerebral activity finds convergent evidence for an identifiable set of resting state networks (RSNs). To date, little is know concerning the earlier developmental stages of functional connectivity in RSNs. This study's main objective is to characterize the RSNs in a sample of adolescents. We further examine our data from a developmental psychopathology perspective of psychosis-proneness, by testing the hypothesis ...

  20. Neurobiological Changes of Schizotypy: Evidence From Both Volume-Based Morphometric Analysis and Resting-State Functional Connectivity

    OpenAIRE

    Wang, Yi; Yan, Chao; Yin, Da-zhi; Fan, Ming-Xia; Eric F C Cheung; Pantelis, Christos; Chan, Raymond C. K.

    2014-01-01

    The current study sought to examine the underlying brain changes in individuals with high schizotypy by integrating networks derived from brain structural and functional imaging. Individuals with high schizotypy (n = 35) and low schizotypy (n = 34) controls were screened using the Schizotypal Personality Questionnaire and underwent brain structural and resting-state functional magnetic resonance imaging on a 3T scanner. Voxel-based morphometric analysis and graph theory-based functional netwo...

  1. Increased resting state functional connectivity in the fronto-parietal and default mode network in anorexia nervosa

    OpenAIRE

    Boehm, Ilka; Geisler, Daniel; King, Joseph A; Ritschel, Franziska; Seidel, Maria; Deza Araujo, Yacila; Petermann, Juliane; Lohmeier, Heidi; Weiss, Jessika; Walter, Martin; Roessner, Veit; Ehrlich, Stefan

    2014-01-01

    The etiology of anorexia nervosa (AN) is poorly understood. Results from functional brain imaging studies investigating the neural profile of AN using cognitive and emotional task paradigms are difficult to reconcile. Task-related imaging studies often require a high level of compliance and can only partially explore the distributed nature and complexity of brain function. In this study, resting state functional connectivity imaging was used to investigate well-characterized brain networks po...

  2. Large-scale Granger causality analysis on resting-state functional MRI

    Science.gov (United States)

    D'Souza, Adora M.; Abidin, Anas Zainul; Leistritz, Lutz; Wismüller, Axel

    2016-03-01

    We demonstrate an approach to measure the information flow between each pair of time series in resting-state functional MRI (fMRI) data of the human brain and subsequently recover its underlying network structure. By integrating dimensionality reduction into predictive time series modeling, large-scale Granger Causality (lsGC) analysis method can reveal directed information flow suggestive of causal influence at an individual voxel level, unlike other multivariate approaches. This method quantifies the influence each voxel time series has on every other voxel time series in a multivariate sense and hence contains information about the underlying dynamics of the whole system, which can be used to reveal functionally connected networks within the brain. To identify such networks, we perform non-metric network clustering, such as accomplished by the Louvain method. We demonstrate the effectiveness of our approach to recover the motor and visual cortex from resting state human brain fMRI data and compare it with the network recovered from a visuomotor stimulation experiment, where the similarity is measured by the Dice Coefficient (DC). The best DC obtained was 0.59 implying a strong agreement between the two networks. In addition, we thoroughly study the effect of dimensionality reduction in lsGC analysis on network recovery. We conclude that our approach is capable of detecting causal influence between time series in a multivariate sense, which can be used to segment functionally connected networks in the resting-state fMRI.

  3. Association between heart rate variability and fluctuations in resting-state functional connectivity

    Science.gov (United States)

    Chang, Catie; Metzger, Coraline D.; Glover, Gary H.; Duyn, Jeff H.; Heinze, Hans-Jochen; Walter, Martin

    2012-01-01

    Functional connectivity has been observed to fluctuate across the course of a resting state scan, though the origins and functional relevance of this phenomenon remain to be shown. The present study explores the link between endogenous dynamics of functional connectivity and autonomic state in an eyes-closed resting condition. Using a sliding window analysis on resting state fMRI data from 35 young, healthy male subjects, we examined how heart rate variability (HRV) covaries with temporal changes in whole-brain functional connectivity with seed regions previously described to mediate effects of vigilance and arousal (amygdala and dorsal anterior cingulate cortex; dACC). We identified a set of regions, including brainstem, thalamus, putamen, and dorsolateral prefrontal cortex, that became more strongly coupled with the dACC and amygdala seeds during states of elevated HRV. Effects differed between high and low frequency components of HRV, suggesting specific contributions of parasympathetic and sympathetic tone on individual connections. Furthermore, dynamics of functional connectivity could be separated from those primarily related to BOLD signal fluctuations. The present results contribute novel information about the neural basis of transient changes of autonomic nervous system states, and suggest physiological and psychological components of the recently observed non-stationarity in resting state functional connectivity. PMID:23246859

  4. Brain network adaptability across task states.

    Directory of Open Access Journals (Sweden)

    Elizabeth N Davison

    2015-01-01

    Full Text Available Activity in the human brain moves between diverse functional states to meet the demands of our dynamic environment, but fundamental principles guiding these transitions remain poorly understood. Here, we capitalize on recent advances in network science to analyze patterns of functional interactions between brain regions. We use dynamic network representations to probe the landscape of brain reconfigurations that accompany task performance both within and between four cognitive states: a task-free resting state, an attention-demanding state, and two memory-demanding states. Using the formalism of hypergraphs, we identify the presence of groups of functional interactions that fluctuate coherently in strength over time both within (task-specific and across (task-general brain states. In contrast to prior emphases on the complexity of many dyadic (region-to-region relationships, these results demonstrate that brain adaptability can be described by common processes that drive the dynamic integration of cognitive systems. Moreover, our results establish the hypergraph as an effective measure for understanding functional brain dynamics, which may also prove useful in examining cross-task, cross-age, and cross-cohort functional change.

  5. Resting-state low-frequency fluctuations reflect individual differences in spoken language learning.

    Science.gov (United States)

    Deng, Zhizhou; Chandrasekaran, Bharath; Wang, Suiping; Wong, Patrick C M

    2016-03-01

    A major challenge in language learning studies is to identify objective, pre-training predictors of success. Variation in the low-frequency fluctuations (LFFs) of spontaneous brain activity measured by resting-state functional magnetic resonance imaging (RS-fMRI) has been found to reflect individual differences in cognitive measures. In the present study, we aimed to investigate the extent to which initial spontaneous brain activity is related to individual differences in spoken language learning. We acquired RS-fMRI data and subsequently trained participants on a sound-to-word learning paradigm in which they learned to use foreign pitch patterns (from Mandarin Chinese) to signal word meaning. We performed amplitude of spontaneous low-frequency fluctuation (ALFF) analysis, graph theory-based analysis, and independent component analysis (ICA) to identify functional components of the LFFs in the resting-state. First, we examined the ALFF as a regional measure and showed that regional ALFFs in the left superior temporal gyrus were positively correlated with learning performance, whereas ALFFs in the default mode network (DMN) regions were negatively correlated with learning performance. Furthermore, the graph theory-based analysis indicated that the degree and local efficiency of the left superior temporal gyrus were positively correlated with learning performance. Finally, the default mode network and several task-positive resting-state networks (RSNs) were identified via the ICA. The "competition" (i.e., negative correlation) between the DMN and the dorsal attention network was negatively correlated with learning performance. Our results demonstrate that a) spontaneous brain activity can predict future language learning outcome without prior hypotheses (e.g., selection of regions of interest--ROIs) and b) both regional dynamics and network-level interactions in the resting brain can account for individual differences in future spoken language learning success. PMID

  6. Time course based artifact identification for independent components of resting state fMRI

    Directory of Open Access Journals (Sweden)

    Christian eRummel

    2013-05-01

    Full Text Available In functional magnetic resonance imaging (fMRI coherent oscillations of the blood oxygen level dependent (BOLD signal can be detected. These arise when brain regions respond to external stimuli or are activated by tasks. The same networks have been characterized during wakeful rest when functional connectivity of the human brain is organized in generic resting state networks (RSN. Alterations of RSN emerge as neurobiological markers of pathological conditions such as altered mental state. In single-subject fMRI data the coherent components can be identified by blind source separation of the pre-processed BOLD data using spatial independent component analysis (ICA and related approaches. The resulting maps may represent physiological RSNs or may be due to various artifacts. In this methodological study, we propose a conceptually simple and fully automatic time course based filtering procedure to detect obvious artifacts in the ICA output for resting state fMRI. The filter is trained on six and tested on 29 healthy subjects, yielding mean filter accuracy, sensitivity and specificity of 0.80, 0.82 and 0.75 in out-of-sample tests. To estimate the impact of clearly artifactual single-subject components on group resting state studies we analyze unfiltered and filtered output with a second level ICA procedure. Although the automated filter does not reach performance values of visual analysis by human raters, we propose that resting state compatible analysis of ICA time courses could be very useful to complement the existing map or task/event oriented artifact classification algorithms.

  7. Intensive reasoning training alters patterns of brain connectivity at rest

    OpenAIRE

    Mackey, AP; Singley, ATM; Bunge, SA

    2013-01-01

    Patterns of correlated activity among brain regions reflect functionally relevant networks that are widely assumed to be stable over time. We hypothesized that if these correlations reflect the prior history of coactivation of brain regions, then a marked shift in cognition could alter the strength of coupling between these regions. We sought to test whether intensive reasoning training in humans would result in tighter coupling among regions in the lateral frontoparietal network, as measured...

  8. Relationships between the resting-state network and the P3: Evidence from a scalp EEG study

    Science.gov (United States)

    Li, Fali; Liu, Tiejun; Wang, Fei; Li, He; Gong, Diankun; Zhang, Rui; Jiang, Yi; Tian, Yin; Guo, Daqing; Yao, Dezhong; Xu, Peng

    2015-10-01

    The P3 is an important event-related potential that can be used to identify neural activity related to the cognitive processes of the human brain. However, the relationships, especially the functional correlations, between resting-state brain activity and the P3 have not been well established. In this study, we investigated the relationships between P3 properties (i.e., amplitude and latency) and resting-state brain networks. The results indicated that P3 amplitude was significantly correlated with resting-state network topology, and in general, larger P3 amplitudes could be evoked when the resting-state brain network was more efficient. However, no significant relationships were found for the corresponding P3 latency. Additionally, the long-range connections between the prefrontal/frontal and parietal/occipital brain regions, which represent the synchronous activity of these areas, were functionally related to the P3 parameters, especially P3 amplitude. The findings of the current study may help us better understand inter-subject variation in the P3, which may be instructive for clinical diagnosis, cognitive neuroscience studies, and potential subject selection for brain-computer interface applications.

  9. Resting cerebral metabolism correlates with skin conductance and functional brain activation during fear conditioning.

    Science.gov (United States)

    Linnman, Clas; Zeidan, Mohamed A; Pitman, Roger K; Milad, Mohammed R

    2012-02-01

    We investigated whether resting brain metabolism can be used to predict autonomic and neuronal responses during fear conditioning in 20 healthy humans. Regional cerebral metabolic rate for glucose was measured via positron emission tomography at rest. During conditioning, autonomic responses were measured via skin conductance, and blood oxygen level dependent signal was measured via functional magnetic resonance imaging. Resting dorsal anterior cingulate metabolism positively predicted differentially conditioned skin conductance responses. Midbrain and insula resting metabolism negatively predicted midbrain and insula functional reactivity, while dorsal anterior cingulate resting metabolism positively predicted midbrain functional reactivity. We conclude that resting metabolism in limbic areas can predict some aspects of psychophysiological and neuronal reactivity during fear learning. PMID:22207247

  10. Regional Patterns of Cortical Phase Synchrony in the Resting State.

    Science.gov (United States)

    Casimo, Kaitlyn; Darvas, Felix; Wander, Jeremiah; Ko, Andrew; Grabowski, Thomas J; Novotny, Edward; Poliakov, Andrew; Ojemann, Jeffrey G; Weaver, Kurt E

    2016-07-01

    Synchronized phase estimates between oscillating neuronal signals at the macroscale level reflect coordinated activities between neuronal assemblies. Recent electrophysiological evidence suggests the presence of significant spontaneous phase synchrony within the resting state. The purpose of this study was to investigate phase synchrony, including directional interactions, in resting state subdural electrocorticographic recordings to better characterize patterns of regional phase interactions across the lateral cortical surface during the resting state. We estimated spontaneous phase locking value (PLV) as a measure of functional connectivity, and phase slope index (PSI) as a measure of pseudo-causal phase interactions, across a broad range of canonical frequency bands and the modulation of the amplitude envelope of high gamma (amHG), a band that is believed to best reflect the physiological processes giving rise to the functional magnetic resonance imaging BOLD signal. Long-distance interactions had higher PLVs in slower frequencies (≤theta) than in higher ones (≥beta) with amHG behaving more like slow frequencies, and a general trend of increasing frequency band of significant PLVs when moving across the lateral surface along an anterior-posterior axis. Moreover, there was a strong trend of frontal-to-parietal directional phase synchronization, measured by PSI across multiple frequencies. These findings, which are likely indicative of coordinated and structured spontaneous cortical interactions, are important in the study of time scales and directional nature of resting state functional connectivity, and may ultimately contribute to a better understanding of how spontaneous synchrony is linked to variation in regional architecture across the lateral cortical surface. PMID:27019319

  11. The neural basis of unwanted thoughts during resting state

    OpenAIRE

    Kühn, Simone; Vanderhasselt, Marie-Anne; Raedt, Rudi; Gallinar, J

    2013-01-01

    Human beings are constantly engaged in thought. Sometimes thoughts occur repetitively and can become distressing. Up to now the neural bases of these intrusive or unwanted thoughts is largely unexplored. To study the neural correlates of unwanted thoughts, we acquired resting-state fMRI data of 41 female healthy subjects and assessed the self-reported amount of unwanted thoughts during measurement. We analyzed local connectivity by means of regional homogeneity (ReHo) and functional connectiv...

  12. How Anatomy Shapes Dynamics: A Semi-Analytical Study of the Brain at Rest by a Simple Spin Model

    Directory of Open Access Journals (Sweden)

    Gustavo eDeco

    2012-09-01

    Full Text Available Resting state networks show a surprisingly coherent and robust spatiotemporal organization. Previous theoretical studies demonstrated that these patterns can be understood as emergent on the basis of the underlying neuroanatomical connectivity skeleton. Integrating the biologically realistic DTI/DSI based neuroanatomical connectivity into a brain model of Ising spin dynamics, we found the presence of latent ghost multi-stable attractors, which can be studied analytically. The multistable attractor landscape defines a functionally meaningful dynamic repertoire of the brain network that is inherently present in the neuroanatomical connectivity. We demonstrate that the more entropy of attractors exists, the richer is the dynamical repertoire and consequently the brain network displays more capabilities of computation. We hypothesize therefore that human brain connectivity developed a scale free type of architecture in order to be able to store a large number of different and flexibly accessible brain functions

  13. Identification of resting and active state EEG features of Alzheimer's disease using discrete wavelet transform.

    Science.gov (United States)

    Ghorbanian, Parham; Devilbiss, David M; Verma, Ajay; Bernstein, Allan; Hess, Terry; Simon, Adam J; Ashrafiuon, Hashem

    2013-06-01

    Alzheimer's disease (AD) is associated with deficits in a number of cognitive processes and executive functions. Moreover, abnormalities in the electroencephalogram (EEG) power spectrum develop with the progression of AD. These features have been traditionally characterized with montage recordings and conventional spectral analysis during resting eyes-closed and resting eyes-open (EO) conditions. In this study, we introduce a single lead dry electrode EEG device which was employed on AD and control subjects during resting and activated battery of cognitive and sensory tasks such as Paced Auditory Serial Addition Test (PASAT) and auditory stimulations. EEG signals were recorded over the left prefrontal cortex (Fp1) from each subject. EEG signals were decomposed into sub-bands approximately corresponding to the major brain frequency bands using several different discrete wavelet transforms and developed statistical features for each band. Decision tree algorithms along with univariate and multivariate statistical analysis were used to identify the most predictive features across resting and active states, separately and collectively. During resting state recordings, we found that the AD patients exhibited elevated D4 (~4-8 Hz) mean power in EO state as their most distinctive feature. During the active states, however, the majority of AD patients exhibited larger minimum D3 (~8-12 Hz) values during auditory stimulation (18 Hz) combined with increased kurtosis of D5 (~2-4 Hz) during PASAT with 2 s interval. When analyzed using EEG recording data across all tasks, the most predictive AD patient features were a combination of the first two feature sets. However, the dominant discriminating feature for the majority of AD patients were still the same features as the active state analysis. The results from this small sample size pilot study indicate that although EEG recordings during resting conditions are able to differentiate AD from control subjects, EEG activity

  14. Multimodal analysis of cortical chemoarchitecture and macroscale fMRI resting-state functional connectivity.

    Science.gov (United States)

    van den Heuvel, Martijn P; Scholtens, Lianne H; Turk, Elise; Mantini, Dante; Vanduffel, Wim; Feldman Barrett, Lisa

    2016-09-01

    The cerebral cortex is well known to display a large variation in excitatory and inhibitory chemoarchitecture, but the effect of this variation on global scale functional neural communication and synchronization patterns remains less well understood. Here, we provide evidence of the chemoarchitecture of cortical regions to be associated with large-scale region-to-region resting-state functional connectivity. We assessed the excitatory versus inhibitory chemoarchitecture of cortical areas as an ExIn ratio between receptor density mappings of excitatory (AMPA, M1 ) and inhibitory (GABAA , M2 ) receptors, computed on the basis of data collated from pioneering studies of autoradiography mappings as present in literature of the human (2 datasets) and macaque (1 dataset) cortex. Cortical variation in ExIn ratio significantly correlated with total level of functional connectivity as derived from resting-state functional connectivity recordings of cortical areas across all three datasets (human I: P = 0.0004; human II: P = 0.0008; macaque: P = 0.0007), suggesting cortical areas with an overall more excitatory character to show higher levels of intrinsic functional connectivity during resting-state. Our findings are indicative of the microscale chemoarchitecture of cortical regions to be related to resting-state fMRI connectivity patterns at the global system's level of connectome organization. Hum Brain Mapp 37:3103-3113, 2016. © 2016 Wiley Periodicals, Inc. PMID:27207489

  15. Tobacco Smoking and the Resting Maternal Brain: A Preliminary Study of Frontal EEG

    Science.gov (United States)

    Wilbanks, Haley E.; Von Mohr, Mariana; Potenza, Marc N.; Mayes, Linda C.; Rutherford, Helena J.V.

    2016-01-01

    Tobacco smoking has been attributed to a wide range of detrimental health consequences for both women and their children. In addition to its known physical health effects, smoking may also impact maternal neural responses and subsequent caregiving behavior. To begin investigating this issue, we employed electroencephalography (EEG) to examine resting neural oscillations of tobacco-smoking mothers (n = 35) and non-smoking mothers (n = 35). We examined seven EEG frequency bands recorded from frontal electrode sites (delta, theta, alpha, alpha1, alpha2, beta, and gamma). While no between-group differences were present in high-frequency bands (alpha2, beta, gamma), smokers showed greater spectral power in low-frequency bands (delta, theta, alpha, alpha1) compared to non-smokers. This increased power in low-frequency bands of tobacco-smoking mothers is consistent with a less aroused state and may be one mechanism through which smoking might affect the maternal brain and caregiving behavior. PMID:27354838

  16. Tobacco Smoking and the Resting Maternal Brain: A Preliminary Study of Frontal EEG.

    Science.gov (United States)

    Wilbanks, Haley E; Von Mohr, Mariana; Potenza, Marc N; Mayes, Linda C; Rutherford, Helena J V

    2016-06-01

    Tobacco smoking has been attributed to a wide range of detrimental health consequences for both women and their children. In addition to its known physical health effects, smoking may also impact maternal neural responses and subsequent caregiving behavior. To begin investigating this issue, we employed electroencephalography (EEG) to examine resting neural oscillations of tobacco-smoking mothers (n = 35) and non-smoking mothers (n = 35). We examined seven EEG frequency bands recorded from frontal electrode sites (delta, theta, alpha, alpha1, alpha2, beta, and gamma). While no between-group differences were present in high-frequency bands (alpha2, beta, gamma), smokers showed greater spectral power in low-frequency bands (delta, theta, alpha, alpha1) compared to non-smokers. This increased power in low-frequency bands of tobacco-smoking mothers is consistent with a less aroused state and may be one mechanism through which smoking might affect the maternal brain and caregiving behavior.

  17. How Anatomy Shapes Dynamics: A Semi-Analytical Study of the Brain at Rest by a Simple Spin Model

    OpenAIRE

    Gustavo eDeco; Mario eSenden; Viktor eJirsa

    2012-01-01

    Resting state networks (RSNs) show a surprisingly coherent and robust spatiotemporal organization. Previous theoretical studies demonstrated that these patterns can be understood as emergent on the basis of the underlying neuroanatomical connectivity skeleton. Integrating the biologically realistic DTI/DSI-(Diffusion Tensor Imaging/Diffusion Spectrum Imaging)based neuroanatomical connectivity into a brain model of Ising spin dynamics, we found a system with multiple attractors,...

  18. EEG Bands of Wakeful Rest, Slow-Wave and Rapid-Eye-Movement Sleep at Different Brain Areas in Rats.

    Science.gov (United States)

    Jing, Wei; Wang, Yanran; Fang, Guangzhan; Chen, Mingming; Xue, Miaomiao; Guo, Daqing; Yao, Dezhong; Xia, Yang

    2016-01-01

    Accumulating evidence reveals that neuronal oscillations with various frequency bands in the brain have different physiological functions. However, the frequency band divisions in rats were typically based on empirical spectral distribution from limited channels information. In the present study, functionally relevant frequency bands across vigilance states and brain regions were identified using factor analysis based on 9 channels EEG signals recorded from multiple brain areas in rats. We found that frequency band divisions varied both across vigilance states and brain regions. In particular, theta oscillations during REM sleep were subdivided into two bands, 5-7 and 8-11 Hz corresponding to the tonic and phasic stages, respectively. The spindle activities of SWS were different along the anterior-posterior axis, lower oscillations (~16 Hz) in frontal regions and higher in parietal (~21 Hz). The delta and theta activities co-varied in the visual and auditory cortex during wakeful rest. In addition, power spectra of beta oscillations were significantly decreased in association cortex during REM sleep compared with wakeful rest. These results provide us some new insights into understand the brain oscillations across vigilance states, and also indicate that the spatial factor should not be ignored when considering the frequency band divisions in rats. PMID:27536231

  19. EEG Bands of Wakeful Rest, Slow-Wave and Rapid-Eye-Movement Sleep at Different Brain Areas in Rats

    Science.gov (United States)

    Jing, Wei; Wang, Yanran; Fang, Guangzhan; Chen, Mingming; Xue, Miaomiao; Guo, Daqing; Yao, Dezhong; Xia, Yang

    2016-01-01

    Accumulating evidence reveals that neuronal oscillations with various frequency bands in the brain have different physiological functions. However, the frequency band divisions in rats were typically based on empirical spectral distribution from limited channels information. In the present study, functionally relevant frequency bands across vigilance states and brain regions were identified using factor analysis based on 9 channels EEG signals recorded from multiple brain areas in rats. We found that frequency band divisions varied both across vigilance states and brain regions. In particular, theta oscillations during REM sleep were subdivided into two bands, 5–7 and 8–11 Hz corresponding to the tonic and phasic stages, respectively. The spindle activities of SWS were different along the anterior-posterior axis, lower oscillations (~16 Hz) in frontal regions and higher in parietal (~21 Hz). The delta and theta activities co-varied in the visual and auditory cortex during wakeful rest. In addition, power spectra of beta oscillations were significantly decreased in association cortex during REM sleep compared with wakeful rest. These results provide us some new insights into understand the brain oscillations across vigilance states, and also indicate that the spatial factor should not be ignored when considering the frequency band divisions in rats. PMID:27536231

  20. Training brain networks and states.

    Science.gov (United States)

    Tang, Yi-Yuan; Posner, Michael I

    2014-07-01

    Brain training refers to practices that alter the brain in a way that improves cognition, and performance in domains beyond those involved in the training. We argue that brain training includes network training through repetitive practice that exercises specific brain networks and state training, which changes the brain state in a way that influences many networks. This opinion article considers two widely used methods - working memory training (WMT) and meditation training (MT) - to demonstrate the similarities and differences between network and state training. These two forms of training involve different areas of the brain and different forms of generalization. We propose a distinction between network and state training methods to improve understanding of the most effective brain training.

  1. Effects of white matter injury on resting state fMRI measures in prematurely born infants.

    Directory of Open Access Journals (Sweden)

    Christopher D Smyser

    Full Text Available The cerebral white matter is vulnerable to injury in very preterm infants (born prior to 30 weeks gestation, resulting in a spectrum of lesions. These range from severe forms, including cystic periventricular leukomalacia and periventricular hemorrhagic infarction, to minor focal punctate lesions. Moderate to severe white matter injury in preterm infants has been shown to predict later neurodevelopmental disability, although outcomes can vary widely in infants with qualitatively comparable lesions. Resting state functional connectivity magnetic resonance imaging has been increasingly utilized in neurodevelopmental investigations and may provide complementary information regarding the impact of white matter injury on the developing brain. We performed resting state functional connectivity magnetic resonance imaging at term equivalent postmenstrual age in fourteen preterm infants with moderate to severe white matter injury secondary to periventricular hemorrhagic infarction. In these subjects, resting state networks were identifiable throughout the brain. Patterns of aberrant functional connectivity were observed and depended upon injury severity. Comparisons were performed against data obtained from prematurely-born infants with mild white matter injury and healthy, term-born infants and demonstrated group differences. These results reveal structural-functional correlates of preterm white matter injury and carry implications for future investigations of neurodevelopmental disability.

  2. Effects of a Resting Foot Splint in Early Brain Injury Patients

    OpenAIRE

    Sung, Eun Jung; Chun, Min Ho; Hong, Ja Young; Do, Kyung Hee

    2016-01-01

    Objective To assess the effectiveness of the resting foot splint to prevent ankle contracture. Methods We performed a randomized controlled trial in 33 patients with brain injury with ankle dorsiflexor weakness (muscle power ≤grade 2). Both groups continued conventional customized physical therapy, but the patients in the foot splint group were advised to wear a resting foot splint for more than 12 hours per day for 3 weeks. The data were assessed before and 3 weeks after the study. The prima...

  3. Predicting risk-taking behavior from prefrontal resting-state activity and personality.

    Directory of Open Access Journals (Sweden)

    Bettina Studer

    Full Text Available Risk-taking is subject to considerable individual differences. In the current study, we tested whether resting-state activity in the prefrontal cortex and trait sensitivity to reward and punishment can help predict risk-taking behavior. Prefrontal activity at rest was assessed in seventy healthy volunteers using electroencephalography, and compared to their choice behavior on an economic risk-taking task. The Behavioral Inhibition System/Behavioral Activation System scale was used to measure participants' trait sensitivity to reward and punishment. Our results confirmed both prefrontal resting-state activity and personality traits as sources of individual differences in risk-taking behavior. Right-left asymmetry in prefrontal activity and scores on the Behavioral Inhibition System scale, reflecting trait sensitivity to punishment, were correlated with the level of risk-taking on the task. We further discovered that scores on the Behavioral Inhibition System scale modulated the relationship between asymmetry in prefrontal resting-state activity and risk-taking. The results of this study demonstrate that heterogeneity in risk-taking behavior can be traced back to differences in the basic physiology of decision-makers' brains, and suggest that baseline prefrontal activity and personality traits might interplay in guiding risk-taking behavior.

  4. Consistency of network modules in resting-state FMRI connectome data.

    Directory of Open Access Journals (Sweden)

    Malaak N Moussa

    Full Text Available At rest, spontaneous brain activity measured by fMRI is summarized by a number of distinct resting state networks (RSNs following similar temporal time courses. Such networks have been consistently identified across subjects using spatial ICA (independent component analysis. Moreover, graph theory-based network analyses have also been applied to resting-state fMRI data, identifying similar RSNs, although typically at a coarser spatial resolution. In this work, we examined resting-state fMRI networks from 194 subjects at a voxel-level resolution, and examined the consistency of RSNs across subjects using a metric called scaled inclusivity (SI, which summarizes consistency of modular partitions across networks. Our SI analyses indicated that some RSNs are robust across subjects, comparable to the corresponding RSNs identified by ICA. We also found that some commonly reported RSNs are less consistent across subjects. This is the first direct comparison of RSNs between ICAs and graph-based network analyses at a comparable resolution.

  5. Behavioral, Brain Imaging and Genomic Measures to Predict Functional Outcomes Post - Bed Rest and Spaceflight

    Science.gov (United States)

    Mulavara, A. P.; DeDios, Y. E.; Gadd, N. E.; Caldwell, E. E.; Batson, C. D.; Goel, R.; Seidler, R. D.; Oddsson, L.; Zanello, S.; Clarke, T.; Peters, B.; Cohen, H. S.; Reschke, M.; Wood, S.; Bloomberg, J. J.

    2016-01-01

    Astronauts experience sensorimotor disturbances during their initial exposure to microgravity and during the re-adaptation phase following a return to an Earth-gravitational environment. These alterations may disrupt crewmembers' ability to perform mission critical functional tasks requiring ambulation, manual control and gaze stability. Interestingly, astronauts who return from spaceflight show substantial differences in their abilities to readapt to a gravitational environment. The ability to predict the manner and degree to which individual astronauts would be affected would improve the effectiveness of countermeasure training programs designed to enhance sensorimotor adaptability. For such an approach to succeed, we must develop predictive measures of sensorimotor adaptability that will allow us to foresee, before actual spaceflight, which crewmembers are likely to experience the greatest challenges to their adaptive capacities. The goals of this project are to identify and characterize this set of predictive measures. Our approach includes: 1) behavioral tests to assess sensory bias and adaptability quantified using both strategic and plastic-adaptive responses; 2) imaging to determine individual brain morphological and functional features, using structural magnetic resonance imaging (MRI), diffusion tensor imaging, resting state functional connectivity MRI, and sensorimotor adaptation task-related functional brain activation; and 3) assessment of genotypic markers of genetic polymorphisms in the catechol-O-methyl transferase, dopamine receptor D2, and brain-derived neurotrophic factor genes and genetic polymorphisms of alpha2-adrenergic receptors that play a role in the neural pathways underlying sensorimotor adaptation. We anticipate that these predictive measures will be significantly correlated with individual differences in sensorimotor adaptability after long-duration spaceflight and exposure to an analog bed rest environment. We will be conducting a

  6. Visual Learning Induces Changes in Resting-State fMRI Multivariate Pattern of Information.

    Science.gov (United States)

    Guidotti, Roberto; Del Gratta, Cosimo; Baldassarre, Antonello; Romani, Gian Luca; Corbetta, Maurizio

    2015-07-01

    When measured with functional magnetic resonance imaging (fMRI) in the resting state (R-fMRI), spontaneous activity is correlated between brain regions that are anatomically and functionally related. Learning and/or task performance can induce modulation of the resting synchronization between brain regions. Moreover, at the neuronal level spontaneous brain activity can replay patterns evoked by a previously presented stimulus. Here we test whether visual learning/task performance can induce a change in the patterns of coded information in R-fMRI signals consistent with a role of spontaneous activity in representing task-relevant information. Human subjects underwent R-fMRI before and after perceptual learning on a novel visual shape orientation discrimination task. Task-evoked fMRI patterns to trained versus novel stimuli were recorded after learning was completed, and before the second R-fMRI session. Using multivariate pattern analysis on task-evoked signals, we found patterns in several cortical regions, as follows: visual cortex, V3/V3A/V7; within the default mode network, precuneus, and inferior parietal lobule; and, within the dorsal attention network, intraparietal sulcus, which discriminated between trained and novel visual stimuli. The accuracy of classification was strongly correlated with behavioral performance. Next, we measured multivariate patterns in R-fMRI signals before and after learning. The frequency and similarity of resting states representing the task/visual stimuli states increased post-learning in the same cortical regions recruited by the task. These findings support a representational role of spontaneous brain activity. PMID:26156982

  7. Machine learning classification of resting state functional connectivity predicts smoking status

    Directory of Open Access Journals (Sweden)

    Vani ePariyadath

    2014-06-01

    Full Text Available Machine learning-based approaches are now able to examine functional magnetic resonance imaging data in a multivariate manner and extract features predictive of group membership. We applied support vector machine-based classification to resting state functional connectivity data from nicotine-dependent smokers and healthy controls to identify brain-based features predictive of nicotine dependence. By employing a network-centered approach, we observed that within-network functional connectivity measures offered maximal information for predicting smoking status, as opposed to between-network connectivity, or the representativeness of each individual node with respect to its parent network. Further, our analysis suggests that connectivity measures within the executive control and frontoparietal networks are particularly informative in predicting smoking status. Our findings suggest that machine learning-based approaches to classifying resting state functional connectivity data offer a valuable alternative technique to understanding large-scale differences in addiction-related neurobiology.

  8. Different Resting-State Functional Connectivity Alterations in Smokers and Nonsmokers with Internet Gaming Addiction

    Directory of Open Access Journals (Sweden)

    Xue Chen

    2014-01-01

    Full Text Available This study investigated changes in resting-state functional connectivity (rsFC of posterior cingulate cortex (PCC in smokers and nonsmokers with Internet gaming addiction (IGA. Twenty-nine smokers with IGA, 22 nonsmokers with IGA, and 30 healthy controls (HC group underwent a resting-state fMRI scan. PCC connectivity was determined in all subjects by investigating synchronized low-frequency fMRI signal fluctuations using a temporal correlation method. Compared with the nonsmokers with IGA, the smokers with IGA exhibited decreased rsFC with PCC in the right rectus gyrus. Left middle frontal gyrus exhibited increased rsFC. The PCC connectivity with the right rectus gyrus was found to be negatively correlated with the CIAS scores in the smokers with IGA before correction. Our results suggested that smokers with IGA had functional changes in brain areas related to motivation and executive function compared with the nonsmokers with IGA.

  9. Automatic selection of resting-state networks with functional magnetic resonance imaging

    Directory of Open Access Journals (Sweden)

    Silvia Francesca eStorti

    2013-05-01

    Full Text Available Functional magnetic resonance imaging (fMRI during a resting-state condition can reveal the co-activation of specific brain regions in distributed networks, called resting-state networks, which are selected by independent component analysis (ICA of the fMRI data. One of the major difficulties with component analysis is the automatic selection of the ICA features related to brain activity. In this study we describe a method designed to automatically select networks of potential functional relevance, specifically, those regions known to be involved in motor function, visual processing, executive functioning, auditory processing, memory, and the default-mode network. To do this, image analysis was based on probabilistic ICA as implemented in FSL software. After decomposition, the optimal number of components was selected by applying a novel algorithm which takes into account, for each component, Pearson's median coefficient of skewness of the spatial maps generated by FSL, followed by clustering, segmentation, and spectral analysis. To evaluate the performance of the approach, we investigated the resting-state networks in 25 subjects. For each subject, three resting-state scans were obtained with a Siemens Allegra 3 T scanner (NYU data set. Comparison of the visually and the automatically identified neuronal networks showed that the algorithm had high accuracy (first scan: 95%, second scan: 95%, third scan: 93% and precision (90%, 90%, 84%. The reproducibility of the networks for visual and automatic selection was very close: it was highly consistent in each subject for the default-mode network (≥ 92% and the occipital network, which includes the medial visual cortical areas (≥ 94%, and consistent for the attention network (≥ 80%, the right and/or left lateralized frontoparietal attention networks, and the temporal-motor network (≥ 80%. The automatic selection method may be used to detect neural networks and reduce subjectivity in ICA

  10. Frequency of Maternal Touch Predicts Resting Activity and Connectivity of the Developing Social Brain.

    Science.gov (United States)

    Brauer, Jens; Xiao, Yaqiong; Poulain, Tanja; Friederici, Angela D; Schirmer, Annett

    2016-08-01

    Previous behavioral research points to a positive relationship between maternal touch and early social development. Here, we explored the brain correlates of this relationship. The frequency of maternal touch was recorded for 43 five-year-old children during a 10 min standardized play session. Additionally, all children completed a resting-state functional magnetic resonance imaging session. Investigating the default mode network revealed a positive relation between the frequency of maternal touch and activity in the right posterior superior temporal sulcus (pSTS) extending into the temporo-parietal junction. Using this effect as a seed in a functional connectivity analysis identified a network including extended bilateral regions along the temporal lobe, bilateral frontal cortex, and left insula. Compared with children with low maternal touch, children with high maternal touch showed additional connectivity with the right dorso-medial prefrontal cortex. Together these results support the notion that childhood tactile experiences shape the developing "social brain" with a particular emphasis on a network involved in mentalizing.

  11. Frequency of Maternal Touch Predicts Resting Activity and Connectivity of the Developing Social Brain.

    Science.gov (United States)

    Brauer, Jens; Xiao, Yaqiong; Poulain, Tanja; Friederici, Angela D; Schirmer, Annett

    2016-08-01

    Previous behavioral research points to a positive relationship between maternal touch and early social development. Here, we explored the brain correlates of this relationship. The frequency of maternal touch was recorded for 43 five-year-old children during a 10 min standardized play session. Additionally, all children completed a resting-state functional magnetic resonance imaging session. Investigating the default mode network revealed a positive relation between the frequency of maternal touch and activity in the right posterior superior temporal sulcus (pSTS) extending into the temporo-parietal junction. Using this effect as a seed in a functional connectivity analysis identified a network including extended bilateral regions along the temporal lobe, bilateral frontal cortex, and left insula. Compared with children with low maternal touch, children with high maternal touch showed additional connectivity with the right dorso-medial prefrontal cortex. Together these results support the notion that childhood tactile experiences shape the developing "social brain" with a particular emphasis on a network involved in mentalizing. PMID:27230216

  12. Reduced resting state functional connectivity of the somatosensory cortex predicts psychopathological symptoms in women with bulimia nervosa

    OpenAIRE

    Luca eLavagnino; Federico eAmianto; Federico eD'Agata; Zirui eHuang; Paolo eMortara; Giovanni eAbbate Daga; Enrica eMarzola; Angela eSpalatro; Secondo eFassino; Georg eNorthoff

    2014-01-01

    BackgroundAlterations in the resting state functional connectivity (rs-FC) of several brain networks have been demonstrated in eating disorders. However, very few studies are currently available on brain network dysfunctions in bulimia nervosa (BN). The somatosensory network is central in processing body-related stimuli and it may be altered in BN. The present study therefore aimed to investigate rs-FC in the somatosensory network in bulimic women. MethodsSixteen medication-free women with B...

  13. Reduced resting-state functional connectivity of the somatosensory cortex predicts psychopathological symptoms in women with bulimia nervosa.

    OpenAIRE

    Lavagnino, Luca; Amianto, Federico; D’Agata, Federico; Huang, Zirui; Mortara, Paolo; Abbate-Daga, Giovanni; Marzola, Enrica; Spalatro, Angela; Fassino, Secondo; Northoff, Georg

    2014-01-01

    Background: Alterations in the resting-state functional connectivity (rs-FC) of several brain networks have been demonstrated in eating disorders. However, very few studies are currently available on brain network dysfunctions in bulimia nervosa (BN). The somatosensory network is central in processing body-related stimuli and it may be altered in BN. The present study therefore aimed to investigate rs-FC in the somatosensory network in bulimic women. Methods: Sixteen medication-free women ...

  14. Resting-state functional connectivity abnormalities in limbic and salience networks in social anxiety disorder without comorbidity

    NARCIS (Netherlands)

    Pannekoek, J. Nienke; Veer, Ilya M.; van Tol, Marie-Jose; van der Werff, Steven J. A.; Demenescu, Liliana R.; Aleman, Andre; Veltman, Dick J.; Zitman, Frans G.; Rombouts, Serge A. R. B.; van der Wee, Nic J. A.

    2013-01-01

    The neurobiology of social anxiety disorder (SAD) is not yet fully understood. Structural and functional neuroimaging studies in SAD have identified abnormalities in various brain areas, particularly the amygdala and elements of the salience network. This study is the first to examine resting-state

  15. Resting-state functional connectivity changes in aging apoE4 and apoE-KO mice

    NARCIS (Netherlands)

    Zerbi, V.; Wiesmann, M.; Emmerzaal, T.L.; Jansen, D.; Beek, M. van; Mutsaers, M.P.C.; Beckmann, C.F.; Heerschap, A.; Kiliaan, A.J.

    2014-01-01

    It is well established that the cholesterol-transporter apolipoprotein epsilon (APOE) genotype is associated with the risk of developing neuro-degenerative diseases. Recently, brain functional connectivity (FC) in apoE-epsilon 4 carriers has been investigated by means of resting-state fMRI, showing

  16. Resting-state functional connectivity changes in aging apoE4 and apoE-KO mice

    NARCIS (Netherlands)

    Zerbi, V.; Wiesmann, M.; Emmerzaal, T.L.; Jansen, D.; Beek, M. van; Mutsaers, M.P.; Beckmann, C.F.; Heerschap, A.; Kiliaan, A.J.

    2014-01-01

    It is well established that the cholesterol-transporter apolipoprotein epsilon (APOE) genotype is associated with the risk of developing neurodegenerative diseases. Recently, brain functional connectivity (FC) in apoE-epsilon4 carriers has been investigated by means of resting-state fMRI, showing a

  17. Coupling between intrinsic prefrontal HbO2 and central EEG beta power oscillations in the resting brain.

    Science.gov (United States)

    Pfurtscheller, Gert; Daly, Ian; Bauernfeind, Günther; Müller-Putz, Gernot R

    2012-01-01

    There is increasing interest in the intrinsic activity in the resting brain, especially that of ultraslow and slow oscillations. Using near-infrared spectroscopy (NIRS), electroencephalography (EEG), blood pressure (BP), respiration and heart rate recordings during 5 minutes of rest, combined with cross spectral and sliding cross correlation calculations, we identified a short-lasting coupling (duration [Formula: see text] s) between prefrontal oxyhemoglobin (HbO2) in the frequency band between 0.07 and 0.13 Hz and central EEG alpha and/or beta power oscillations in 8 of the 9 subjects investigated. The HbO2 peaks preceded the EEG band power peaks by 3.7 s in 6 subjects, with moderate or no coupling between BP and HbO2 oscillations. HbO2 and EEG band power oscillations were approximately in phase with BP oscillations in the 2 subjects with an extremely high coupling (squared coherence [Formula: see text]) between BP and HbO2 oscillation. No coupling was identified in one subject. These results indicate that slow precentral (de)oxyhemoglobin concentration oscillations during awake rest can be temporarily coupled with EEG fluctuations in sensorimotor areas and modulate the excitability level in the brains' motor areas, respectively. Therefore, this provides support for the idea that resting state networks fluctuate with frequencies of between 0.01 and 0.1 Hz (Mantini et.al. PNAS 2007).

  18. Coupling between intrinsic prefrontal HbO2 and central EEG beta power oscillations in the resting brain.

    Directory of Open Access Journals (Sweden)

    Gert Pfurtscheller

    Full Text Available There is increasing interest in the intrinsic activity in the resting brain, especially that of ultraslow and slow oscillations. Using near-infrared spectroscopy (NIRS, electroencephalography (EEG, blood pressure (BP, respiration and heart rate recordings during 5 minutes of rest, combined with cross spectral and sliding cross correlation calculations, we identified a short-lasting coupling (duration [Formula: see text] s between prefrontal oxyhemoglobin (HbO2 in the frequency band between 0.07 and 0.13 Hz and central EEG alpha and/or beta power oscillations in 8 of the 9 subjects investigated. The HbO2 peaks preceded the EEG band power peaks by 3.7 s in 6 subjects, with moderate or no coupling between BP and HbO2 oscillations. HbO2 and EEG band power oscillations were approximately in phase with BP oscillations in the 2 subjects with an extremely high coupling (squared coherence [Formula: see text] between BP and HbO2 oscillation. No coupling was identified in one subject. These results indicate that slow precentral (deoxyhemoglobin concentration oscillations during awake rest can be temporarily coupled with EEG fluctuations in sensorimotor areas and modulate the excitability level in the brains' motor areas, respectively. Therefore, this provides support for the idea that resting state networks fluctuate with frequencies of between 0.01 and 0.1 Hz (Mantini et.al. PNAS 2007.

  19. Increased regional homogeneity in internet addiction disorder: a resting state functional magnetic resonance imaging study

    Institute of Scientific and Technical Information of China (English)

    LIU Jun; GAO Xue-ping; Isoken Osunde; LI Xin; ZHOU Shun-ke; ZHENG Hui-rong; LI Ling-jiang

    2010-01-01

    Background Internet addition disorder (lAD) is currently becoming a serious mental health problem among Chinese adolescents. The pathogenesis of IAD, however, remains unclear. The purpose of this study applied regional homogeneity (ReHo) method to analyze encephalic functional characteristic of IAD college students under resting state. Methods Functional magnetic resonanc image (fMRI) was performed in 19 IAD college students and 19 controls under resting state. ReHo method was used to analyze the differences between the average ReHo in two groups. Results The following increased ReHo brain regions were found in IAD group compared with control group: cerebellum,brainstem, right cingulate gyrus, bilateral parahippocampus, right frontal lobe (rectal gyrus, inferior frontal gyrus and middle frontal gyrus), left superior frontal gyrus, left precuneus, right postcentral gyrus, right middle occipital gyrus, right inferior temporal gyrus, left superior temporal gyrus and middle temporal gyrus. The decreased ReHo brain regions were not found in the IAD group compared with the control group. Conclusions There are abnormalities in regional homogeneity in IAD college students compared with the controls and enhancement of synchronization in most encephalic regions can be found. The results reflect the functional change of brain in IAD college students. The connections between the enhancement of synchronization among cerebellum, brainstem, limbic lobe, frontal lobe and apical lobe may be relative to reward pathways.

  20. Effects of Physical Exercise on Individual Resting State EEG Alpha Peak Frequency

    Directory of Open Access Journals (Sweden)

    Boris Gutmann

    2015-01-01

    Full Text Available Previous research has shown that both acute and chronic physical exercises can induce positive effects on brain function and this is associated with improvements in cognitive performance. However, the neurophysiological mechanisms underlying the beneficial effects of exercise on cognitive processing are not well understood. This study examined the effects of an acute bout of physical exercise as well as four weeks of exercise training on the individual resting state electroencephalographic (EEG alpha peak frequency (iAPF, a neurophysiological marker of the individual’s state of arousal and attention, in healthy young adults. The subjects completed a steady state exercise (SSE protocol or an exhaustive exercise (EE protocol, respectively, on two separate days. EEG activity was recorded for 2 min before exercise, immediately after exercise, and after 10 min of rest. All assessments were repeated following four weeks of exercise training to investigate whether an improvement in physical fitness modulates the resting state iAPF and/or the iAPF response to an acute bout of SSE and EE. The iAPF was significantly increased following EE (P=0.012 but not following SSE. It is concluded that the iAPF is increased following intense exercise, indicating a higher level of arousal and preparedness for external input.

  1. [Vulnerability to Depression and Oscillatory Resting-State Networks].

    Science.gov (United States)

    Knyazev, G G; Savostyanov, A N; Bocharov, A V; Saprygin, A E; Tamozhnikov, S S

    2015-01-01

    Depression is the most commonly observed mood disorder, which is accompanied by changes in emotional processes and the default mode network (DMN) activity. In this study, we aimed to investigate how predisposition to depression shows up in the emotional coloring of spontaneous thoughts and the activity of oscillatory resting-state networks, as revealed by source localization and independent component analysis techniques. Depressive symptoms correlated positively with the prevalence of negative emotion during EEG registration and with delta and theta activity in the orbitofrontal cortex and negatively with theta activity in the DMN. Since an increase of low-frequency oscillations in the orbitofrontal cortex is observed in aversive states, whereas their decrease in the DMN reflects an activation of this network, which is related to self-referenced processing, our results are consistent with the notion that vulnerability to depression is associated with general negative emotional disposition and excessive focus on the self. PMID:26281232

  2. Impairments of thalamic resting-state functional connectivity in patients with chronic tinnitus

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Jian [Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing (China); Chen, Yu-Chen [Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing (China); Center for Hearing and Deafness, University at Buffalo, State University of New York, Buffalo, NY (United States); Feng, Xu [Department of Otolaryngology, Zhongda Hospital, Medical School, Southeast University, Nanjing (China); Yang, Ming; Liu, Bin; Qian, Cheng [Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing (China); Wang, Jian [Department of Physiology, Southeast University, Nanjing (China); School of Human Communication Disorders, Dalhousie University, Halifax, NS (Canada); Salvi, Richard [Center for Hearing and Deafness, University at Buffalo, State University of New York, Buffalo, NY (United States); Teng, Gao-Jun, E-mail: gjteng@vip.sina.com [Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing (China)

    2015-07-15

    Highlights: • Tinnitus patients have aberrant thalamic connectivity to many brain regions. • Decreased thalamic connectivity is linked with tinnitus characteristics. • Thalamocortical connectivity disturbances can reflect tinnitus-related networks. - Abstract: Purpose: The phantom sound of tinnitus is believed to arise from abnormal functional coupling between the thalamus and cerebral cortex. To explore this hypothesis, we used resting-state functional magnetic resonance imaging (fMRI) to compare the degree of thalamocortical functional connectivity in chronic tinnitus patients and controls. Materials and methods: Resting-state fMRI scans were obtained from 31 chronic tinnitus patients and 33 well-matched healthy controls. Thalamocortical functional connectivity was characterized using a seed-based whole-brain correlation method. The resulting thalamic functional connectivity measures were correlated with other clinical data. Results: We found decreased functional connectivity between the seed region in left thalamus and right middle temporal gyrus (MTG), right middle orbitofrontal cortex, left middle frontal gyrus, right precentral gyrus, and bilateral calcarine cortex. Decreased functional connectivity was detected between the seed in the right thalamus and the left superior temporal gyrus (STG), left amygdala, right superior frontal gyrus, left precentral gyrus, and left middle occipital gyrus. Tinnitus distress correlated negatively with thalamic functional connectivity in right MTG; tinnitus duration correlated negatively with thalamic functional connectivity in left STG. Increased functional connectivity between the bilateral thalamus and a set of regions were also observed. Conclusions: Chronic tinnitus patients have disrupted thalamocortical functional connectivity to selected brain regions which is associated with specific tinnitus characteristics. Resting-state thalamic functional connectivity disturbances may play an important role in

  3. Expanded functional coupling of subcortical nuclei with the motor resting-state network in multiple sclerosis

    DEFF Research Database (Denmark)

    Dogonowski, Anne-Marie; Siebner, Hartwig R; Sørensen, Per Soelberg;

    2013-01-01

    controls underwent a 20-minute resting-state fMRI session at 3 Tesla. Independent component analysis was applied to the fMRI data to identify disease-related changes in motor resting-state connectivity. RESULTS: Patients with MS showed a spatial expansion of motor resting-state connectivity in deep...

  4. Neural encoding of objects relevant for navigation and resting state correlations with navigational ability.

    Science.gov (United States)

    Wegman, Joost; Janzen, Gabriele

    2011-12-01

    Objects along a route can help us to successfully navigate through our surroundings. Previous neuroimaging research has shown that the parahippocampal gyrus (PHG) distinguishes between objects that were previously encountered at navigationally relevant locations (decision points) and irrelevant locations (nondecision points) during simple object recognition. This study aimed at unraveling how this neural marking of objects relevant for navigation is established during learning and postlearning rest. Twenty-four participants were scanned using fMRI while they were viewing a route through a virtual environment. Eye movements were measured, and brain responses were time-locked to viewing each object. The PHG showed increased responses to decision point objects compared with nondecision point objects during route learning. We compared functional connectivity between the PHG and the rest of the brain in a resting state scan postlearning with such a scan prelearning. Results show that functional connectivity between the PHG and the hippocampus is positively related to participants' self-reported navigational ability. On the other hand, connectivity with the caudate nucleus correlated negatively with navigational ability. These results are in line with a distinction between egocentric and allocentric spatial representations in the caudate nucleus and the hippocampus, respectively. Our results thus suggest a relation between navigational ability and a neural preference for a specific type of spatial representation. Together, these results show that the PHG is immediately involved in the encoding of navigationally relevant object information. Furthermore, they provide insight into the neural correlates of individual differences in spatial ability. PMID:21671733

  5. Using Coherence to Measure Regional Homogeneity of Resting-State fMRI Signal

    OpenAIRE

    Dongqiang Liu; Chaogan Yan; Juejing Ren; Li Yao; Vesa J Kiviniemi; Yufeng Zang

    2010-01-01

    In this study, we applied coherence to voxel-wise measurement of regional homogeneity of resting-state functional magnetic resonance imaging (RS-fMRI) signal. We compared the current method, regional homogeneity based on coherence (Cohe-ReHo), with previously proposed method, ReHo based on Kendall’s coefficient of concordance (KCC-ReHo), in terms of correlation and paired t-test in a large sample of healthy participants. We found the two measurements differed mainly in some brain region...

  6. Resting-state functional connectivity abnormalities in ifrst-onset unmedicated depression

    Institute of Scientific and Technical Information of China (English)

    Hao Guo; Chen Cheng; Xiaohua Cao; Jie Xiang; Junjie Chen; Kerang Zhang

    2014-01-01

    Depression is closely linked to the morphology and functional abnormalities of multiple brain regions;however, its topological structure throughout the whole brain remains unclear. We col-lected resting-state functional MRI data from 36 ifrst-onset unmedicated depression patients and 27 healthy controls. The resting-state functional connectivity was constructed using the Auto-mated Anatomical Labeling template with a partial correlation method. The metrics calculation and statistical analysis were performed using complex network theory. The results showed that both depressive patients and healthy controls presented typical small-world attributes. Compared with healthy controls, characteristic path length was signiifcantly shorter in depressive patients, suggesting development toward randomization. Patients with depression showed apparently abnormal node attributes at key areas in cortical-striatal-pallidal-thalamic circuits. In addition, right hippocampus and right thalamus were closely linked with the severity of depression. We se-lected 270 local attributes as the classiifcation features and their P values were regarded as criteria for statistically significant differences. An artificial neural network algorithm was applied for classiifcation research. The results showed that brain network metrics could be used as an effec-tive feature in machine learning research, which brings about a reasonable application prospect for brain network metrics. The present study also highlighted a signiifcant positive correlation between the importance of the attributes and the intergroup differences;that is, the more sig-niifcant the differences in node attributes, the stronger their contribution to the classiifcation. Experimental ifndings indicate that statistical signiifcance is an effective quantitative indicator of the selection of brain network metrics and can assist the clinical diagnosis of depression.

  7. Resting-state oscillatory activity in children born small for gestational age: a magnetoencephalographic study

    Directory of Open Access Journals (Sweden)

    Maria eBoersma

    2013-09-01

    Full Text Available Growth restriction in utero during a period that is critical for normal growth of the brain, has previously been associated with deviations in cognitive abilities and brain anatomical and functional changes. We measured magnetoencephalography (MEG in 4-7 year old children to test if children born small for gestational age (SGA show deviations in resting-state brain oscillatory activity. Children born SGA children with postnatally spontaneous catch-up growth (SGA+; 6 boys, 7 girls; mean age 6.3 y (SD=0.9 and children born appropriate for gestational age (AGA; 7 boys, 3 girls; mean age 6.0 y (SD=1.2 participated in a resting-state MEG study. We calculated absolute and relative power spectra and used nonparametric statistics to test for group differences. SGA+ and AGA born children showed no significant differences in absolute and relative power except for reduced absolute gamma band power in SGA children. At time of MEG investigation, SGA+ children showed was significantly lower head circumference (HC and a trend toward lower IQ, however there was no association of HC or IQ with absolute or relative power. Except for reduced absolute gamma band power, our findings suggest normal brain activity patterns at school age in a group of children born SGA in which spontaneous catch-up growth of bodily length after birth occurred. Although previous findings suggest that being born SGA alters brain oscillatory activity early in neonatal life, we show that these neonatal alterations do not persist at early school age when spontaneous postnatal catch-up growth occurs after birth.

  8. Resting-state slow wave power, healthy aging and cognitive performance.

    Science.gov (United States)

    Vlahou, Eleni L; Thurm, Franka; Kolassa, Iris-Tatjana; Schlee, Winfried

    2014-05-29

    Cognitive functions and spontaneous neural activity show significant changes over the life-span, but the interrelations between age, cognition and resting-state brain oscillations are not well understood. Here, we assessed performance on the Trail Making Test and resting-state magnetoencephalographic (MEG) recordings from 53 healthy adults (18-89 years old) to investigate associations between age-dependent changes in spontaneous oscillatory activity and cognitive performance. Results show that healthy aging is accompanied by a marked and linear decrease of resting-state activity in the slow frequency range (0.5-6.5 Hz). The effects of slow wave power on cognitive performance were expressed as interactions with age: For older (>54 years), but not younger participants, enhanced delta and theta power in temporal and central regions was positively associated with perceptual speed and executive functioning. Consistent with previous work, these findings substantiate further the important role of slow wave oscillations in neurocognitive function during healthy aging.

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

    Science.gov (United States)

    Wong, Chi Wah; Olafsson, Valur; Plank, Markus; Snider, Joseph; Halgren, Eric; Poizner, Howard; Liu, Thomas T

    2014-01-01

    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. PMID:25286145

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

    Directory of Open Access Journals (Sweden)

    Chi Wah Wong

    Full Text Available In the real world, learning often proceeds in an unsupervised manner without explicit instructions or feedback. In this study, we employed an experimental paradigm in which subjects explored an immersive virtual reality environment on each of two days. On day 1, subjects implicitly learned the location of 39 objects in an unsupervised fashion. On day 2, the locations of some of the objects were changed, and object location recall performance was assessed and found to vary across subjects. As prior work had shown that functional magnetic resonance imaging (fMRI measures of resting-state brain activity can predict various measures of brain performance across individuals, we examined whether resting-state fMRI measures could be used to predict object location recall performance. We found a significant correlation between performance and the variability of the resting-state fMRI signal in the basal ganglia, hippocampus, amygdala, thalamus, insula, and regions in the frontal and temporal lobes, regions important for spatial exploration, learning, memory, and decision making. In addition, performance was significantly correlated with resting-state fMRI connectivity between the left caudate and the right fusiform gyrus, lateral occipital complex, and superior temporal gyrus. Given the basal ganglia's role in exploration, these findings suggest that tighter integration of the brain systems responsible for exploration and visuospatial processing may be critical for learning in a complex environment.

  11. Monkey in the middle: Why nonhuman primates are needed to bridge the gap in resting-state investigations

    Directory of Open Access Journals (Sweden)

    R. Matthew eHutchison

    2012-07-01

    Full Text Available Resting-state investigations based on the evaluation of intrinsic low-frequency fluctuations of the BOLD fMRI signal have been extensively utilized to map the structure and dynamics of large-scale functional network organization in humans. In addition to increasing our knowledge of normal brain connectivity, disruptions of the spontaneous hemodynamic fluctuations have been suggested as possible diagnostic indicators of neurological and psychiatric disease states. Though the non-invasive technique has been received with much acclamation, open questions remain regarding the origin, organization, phylogenesis, as well as the basis of disease-related alterations underlying the signal patterns. Experimental work utilizing animal models, including the use of neurophysiological recordings and pharmacological manipulations, therefore, represents a critical component in the understanding and successful application of resting-state analysis as it affords a range of experimental manipulations not possible in human subjects. In this article, we review recent rodent and nonhuman primate studies and based on the examination of the homologous functional architecture propose the latter to be the best-suited model for exploring these unresolved resting-state concerns. Ongoing work examining the correspondence of functional and structural connectivity, state-dependency and the neuronal correlates of the hemodynamic oscillations are discussed. We then consider the potential experiments that will allow insight into different brain states and disease-related network disruptions that can extend the clinical applications of resting-state fMRI.

  12. Modulation of the COMT Val158Met polymorphism on resting-state EEG power in postmenopausal healthy women

    Directory of Open Access Journals (Sweden)

    Silvia eSolis-Ortiz

    2015-04-01

    Full Text Available The catechol-O-methyltransferase (COMT Val158Met polymorphism impacts cortical dopamine levels and may influence cortical electrical activity in the human brain. This study investigated whether COMT genotype influences resting-state electroencephalogram (EEG power in the frontal, parietal and midline regions in healthy volunteers. EEG recordings were conducted in the resting-state in 13 postmenopausal healthy woman carriers of the Val/Val genotype and 11 with the Met/Met genotype. The resting EEG spectral absolute power in the frontal (F3, F4, F7, F8, FC3 and FC4, parietal (CP3, CP4, P3 and P4 and midline (Fz, FCz, Cz, CPz, Pz and Oz was analyzed during the eyes-open and eyes-closed conditions. The frequency bands considered were the delta, theta, alpha1, alpha2, beta1 and beta2. EEG data of the Val/Val and Met/Met genotypes, brain regions and conditions were analyzed using a general linear model analysis. In the individuals with the Met/Met genotype, delta activity was increased in the eyes-closed condition, theta activity was increased in the eyes-closed and in the eyes-open conditions, and alpha1 band, alpha2 band and beta1band activity was increased in the eyes-closed condition.A significant interaction between COMT genotypes and spectral bands was observed. Met homozygote individuals exhibited more delta, theta and beta1 activity than individuals with the Val/Val genotype. No significant interaction between COMT genotypes and the resting-state EEG regional power and conditions were observed for the three brain regions studied. Our findings indicate that the COMT Val158Met polymorphism does not directly impact resting-state EEG regional power, but instead suggest that COMT genotype can modulate resting-state EEG spectral power in postmenopausal healthy women.

  13. Chronic whiplash symptoms are related to altered regional cerebral blood flow in the resting state.

    Science.gov (United States)

    Linnman, Clas; Appel, Lieuwe; Söderlund, Anne; Frans, Orjan; Engler, Henry; Furmark, Tomas; Gordh, Torsten; Långström, Bengt; Fredrikson, Mats

    2009-01-01

    The neural pathogenic mechanisms involved in mediating chronic pain and whiplash associated disorders (WAD) after rear impact car collisions are largely unknown. This study's first objective was to compare resting state regional cerebral blood flow (rCBF) by means of positron emission tomography with (15)O labelled water in 21 WAD patients with 18 healthy, pain-free controls. A second objective was to investigate the relations between brain areas with altered rCBF to pain experience, somatic symptoms, posttraumatic stress symptoms and personality traits in the patient group. Patients had heightened resting rCBF bilaterally in the posterior parahippocampal and the posterior cingulate gyri, in the right thalamus and the right medial prefrontal gyrus as well as lowered tempero-occipital blood flow compared with healthy controls. The altered rCBF in the patient group was correlated to neck disability ratings. We thus suggest an involvement of the posterior cingulate, parahippocampal and medial prefrontal gyri in WAD and speculate that alterations in the resting state are linked to an increased self-relevant evaluation of pain and stress. PMID:18486506

  14. Resting-State fMRI in MS: General Concepts and Brief Overview of Its Application

    Directory of Open Access Journals (Sweden)

    Emilia Sbardella

    2015-01-01

    Full Text Available Brain functional connectivity (FC is defined as the coherence in the activity between cerebral areas under a task or in the resting-state (RS. By applying functional magnetic resonance imaging (fMRI, RS FC shows several patterns which define RS brain networks (RSNs involved in specific functions, because brain function is known to depend not only on the activity within individual regions, but also on the functional interaction of different areas across the whole brain. Region-of-interest analysis and independent component analysis are the two most commonly applied methods for RS investigation. Multiple sclerosis (MS is characterized by multiple lesions mainly affecting the white matter, determining both structural and functional disconnection between various areas of the central nervous system. The study of RS FC in MS is mainly aimed at understanding alterations in the intrinsic functional architecture of the brain and their role in disease progression and clinical impairment. In this paper, we will examine the results obtained by the application of RS fMRI in different multiple sclerosis (MS phenotypes and the correlations of FC changes with clinical features in this pathology. The knowledge of RS FC changes may represent a substantial step forward in the MS research field, both for clinical and therapeutic purposes.

  15. Identifying individuals with antisocial personality disorder using resting-state FMRI.

    Directory of Open Access Journals (Sweden)

    Yan Tang

    Full Text Available Antisocial personality disorder (ASPD is closely connected to criminal behavior. A better understanding of functional connectivity in the brains of ASPD patients will help to explain abnormal behavioral syndromes and to perform objective diagnoses of ASPD. In this study we designed an exploratory data-driven classifier based on machine learning to investigate changes in functional connectivity in the brains of patients with ASPD using resting state functional magnetic resonance imaging (fMRI data in 32 subjects with ASPD and 35 controls. The results showed that the classifier achieved satisfactory performance (86.57% accuracy, 77.14% sensitivity and 96.88% specificity and could extract stabile information regarding functional connectivity that could be used to discriminate ASPD individuals from normal controls. More importantly, we found that the greatest change in the ASPD subjects was uncoupling between the default mode network and the attention network. Moreover, the precuneus, superior parietal gyrus and cerebellum exhibited high discriminative power in classification. A voxel-based morphometry analysis was performed and showed that the gray matter volumes in the parietal lobule and white matter volumes in the precuneus were abnormal in ASPD compared to controls. To our knowledge, this study was the first to use resting-state fMRI to identify abnormal functional connectivity in ASPD patients. These results not only demonstrated good performance of the proposed classifier, which can be used to improve the diagnosis of ASPD, but also elucidate the pathological mechanism of ASPD from a resting-state functional integration viewpoint.

  16. Test-retest reliability of resting-state magnetoencephalography power in sensor and source space.

    Science.gov (United States)

    Martín-Buro, María Carmen; Garcés, Pilar; Maestú, Fernando

    2016-01-01

    Several studies have reported changes in spontaneous brain rhythms that could be used as clinical biomarkers or in the evaluation of neuropsychological and drug treatments in longitudinal studies using magnetoencephalography (MEG). There is an increasing necessity to use these measures in early diagnosis and pathology progression; however, there is a lack of studies addressing how reliable they are. Here, we provide the first test-retest reliability estimate of MEG power in resting-state at sensor and source space. In this study, we recorded 3 sessions of resting-state MEG activity from 24 healthy subjects with an interval of a week between each session. Power values were estimated at sensor and source space with beamforming for classical frequency bands: delta (2-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), low beta (13-20 Hz), high beta (20-30 Hz), and gamma (30-45 Hz). Then, test-retest reliability was evaluated using the intraclass correlation coefficient (ICC). We also evaluated the relation between source power and the within-subject variability. In general, ICC of theta, alpha, and low beta power was fairly high (ICC > 0.6) while in delta and gamma power was lower. In source space, fronto-posterior alpha, frontal beta, and medial temporal theta showed the most reliable profiles. Signal-to-noise ratio could be partially responsible for reliability as low signal intensity resulted in high within-subject variability, but also the inherent nature of some brain rhythms in resting-state might be driving these reliability patterns. In conclusion, our results described the reliability of MEG power estimates in each frequency band, which could be considered in disease characterization or clinical trials.

  17. 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.

  18. Alterations of Functional Connectivity Among Resting-State Networks in Hypothyroidism.

    Science.gov (United States)

    Singh, S; Kumar, M; Modi, S; Kaur, P; Shankar, L R; Khushu, S

    2015-07-01

    Hypothyroidism affects brain functioning as suggested by various neuroimaging studies. The primary focus of the present study was to examine whether hypothyroidism would impact connectivity among resting-state networks (RSNs) using resting-state functional magnetic resonance imaging (rsfMRI). Twenty-two patients with hypothyroidism and 22 healthy controls were recruited and scanned using rsfMRI. The data were analysed using independent component analysis and a dual regression approach that was applied on five RSNs that were identified using fsl software (http://fsl.fmrib.ox.ac.uk). Hypothyroid patients showed significantly decreased functional connectivity in the regions of the right frontoparietal network (frontal pole), the medial visual network (lateral occipital gyrus, precuneus cortex and cuneus) and the motor network (precentral gyrus, postcentral gyrus, precuneus cortex, paracingulate gyrus, cingulate gyrus and supramarginal gyrus) compared to healthy controls. The reduced functional connectivity in the right frontoparietal network, the medial visual network and the motor network suggests neurocognitive alterations in hypothyroid patients in the corresponding functions. However, the study would be further continued to investigate the effects of thyroxine treatment and correlation with neurocognitive scores. The findings of the present study provide further interesting insights into our understanding of the action of thyroid hormone on the adult human brain.

  19. Altered resting-state amygdala functional connectivity after 36 hours of total sleep deprivation.

    Directory of Open Access Journals (Sweden)

    Yongcong Shao

    Full Text Available Recent neuroimaging studies have identified a potentially critical role of the amygdala in disrupted emotion neurocircuitry in individuals after total sleep deprivation (TSD. However, connectivity between the amygdala and cerebral cortex due to TSD remains to be elucidated. In this study, we used resting-state functional MRI (fMRI to investigate the functional connectivity changes of the basolateral amygdala (BLA and centromedial amygdala (CMA in the brain after 36 h of TSD.Fourteen healthy adult men aged 25.9 ± 2.3 years (range, 18-28 years were enrolled in a within-subject crossover study. Using the BLA and CMA as separate seed regions, we examined resting-state functional connectivity with fMRI during rested wakefulness (RW and after 36 h of TSD.TSD resulted in a significant decrease in the functional connectivity between the BLA and several executive control regions (left dorsolateral prefrontal cortex [DLPFC], right dorsal anterior cingulate cortex [ACC], right inferior frontal gyrus [IFG]. Increased functional connectivity was found between the BLA and areas including the left posterior cingulate cortex/precuneus (PCC/PrCu and right parahippocampal gyrus. With regard to CMA, increased functional connectivity was observed with the rostral anterior cingulate cortex (rACC and right precentral gyrus.These findings demonstrate that disturbance in amygdala related circuits may contribute to TSD psychophysiology and suggest that functional connectivity studies of the amygdala during the resting state may be used to discern aberrant patterns of coupling within these circuits after TSD.

  20. Oppositional COMT Val158Met effects on resting state functional connectivity in adolescents and adults.

    Science.gov (United States)

    Meyer, Bernhard M; Huemer, Julia; Rabl, Ulrich; Boubela, Roland N; Kalcher, Klaudius; Berger, Andreas; Banaschewski, Tobias; Barker, Gareth; Bokde, Arun; Büchel, Christian; Conrod, Patricia; Desrivières, Sylvane; Flor, Herta; Frouin, Vincent; Gallinat, Jurgen; Garavan, Hugh; Heinz, Andreas; Ittermann, Bernd; Jia, Tianye; Lathrop, Mark; Martinot, Jean-Luc; Nees, Frauke; Rietschel, Marcella; Smolka, Michael N; Bartova, Lucie; Popovic, Ana; Scharinger, Christian; Sitte, Harald H; Steiner, Hans; Friedrich, Max H; Kasper, Siegfried; Perkmann, Thomas; Praschak-Rieder, Nicole; Haslacher, Helmuth; Esterbauer, Harald; Moser, Ewald; Schumann, Gunter; Pezawas, Lukas

    2016-01-01

    Prefrontal dopamine levels are relatively increased in adolescence compared to adulthood. Genetic variation of COMT (COMT Val158Met) results in lower enzymatic activity and higher dopamine availability in Met carriers. Given the dramatic changes of synaptic dopamine during adolescence, it has been suggested that effects of COMT Val158Met genotypes might have oppositional effects in adolescents and adults. The present study aims to identify such oppositional COMT Val158Met effects in adolescents and adults in prefrontal brain networks at rest. Resting state functional connectivity data were collected from cross-sectional and multicenter study sites involving 106 healthy young adults (mean age 24 ± 2.6 years), gender matched to 106 randomly chosen 14-year-olds. We selected the anterior medial prefrontal cortex (amPFC) as seed due to its important role as nexus of the executive control and default mode network. We observed a significant age-dependent reversal of COMT Val158Met effects on resting state functional connectivity between amPFC and ventrolateral as well as dorsolateral prefrontal cortex, and parahippocampal gyrus. Val homozygous adults exhibited increased and adolescents decreased connectivity compared to Met homozygotes for all reported regions. Network analyses underscored the importance of the parahippocampal gyrus as mediator of observed effects. Results of this study demonstrate that adolescent and adult resting state networks are dose-dependently and diametrically affected by COMT genotypes following a hypothetical model of dopamine function that follows an inverted U-shaped curve. This study might provide cues for the understanding of disease onset or dopaminergic treatment mechanisms in major neuropsychiatric disorders such as schizophrenia and attention deficit hyperactivity disorder.

  1. Resting-State fMRI Functional Connectivity Is Associated with Sleepiness, Imagery, and Discontinuity of Mind

    Science.gov (United States)

    Chen, Gang; den Braber, Anouk; van ‘t Ent, Dennis; Boomsma, Dorret I.; Mansvelder, Huibert D.; de Geus, Eco; Van Someren, Eus J. W.; Linkenkaer-Hansen, Klaus

    2015-01-01

    Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used to investigate the functional architecture of the healthy human brain and how it is affected by learning, lifelong development, brain disorders or pharmacological intervention. Non-sensory experiences are prevalent during rest and must arise from ongoing brain activity, yet little is known about this relationship. Here, we used two runs of rs-fMRI both immediately followed by the Amsterdam Resting-State Questionnaire (ARSQ) to investigate the relationship between functional connectivity within ten large-scale functional brain networks and ten dimensions of thoughts and feelings experienced during the scan in 106 healthy participants. We identified 11 positive associations between brain-network functional connectivity and ARSQ dimensions. ‘Sleepiness’ exhibited significant associations with functional connectivity within Visual, Sensorimotor and Default Mode networks. Similar associations were observed for ‘Visual Thought’ and ‘Discontinuity of Mind’, which may relate to variation in imagery and thought control mediated by arousal fluctuations. Our findings show that self-reports of thoughts and feelings experienced during a rs-fMRI scan help understand the functional significance of variations in functional connectivity, which should be of special relevance to clinical studies. PMID:26540239

  2. Brain metabolism in autism. Resting cerebral glucose utilization rates as measured with positron emission tomography

    International Nuclear Information System (INIS)

    The cerebral metabolic rate for glucose was studied in ten men (mean age = 26 years) with well-documented histories of infantile autism and in 15 age-matched normal male controls using positron emission tomography and (F-18) 2-fluoro-2-deoxy-D-glucose. Positron emission tomography was completed during rest, with reduced visual and auditory stimulation. While the autistic group as a whole showed significantly elevated glucose utilization in widespread regions of the brain, there was considerable overlap between the two groups. No brain region showed a reduced metabolic rate in the autistic group. Significantly more autistic, as compared with control, subjects showed extreme relative metabolic rates (ratios of regional metabolic rates to whole brain rates and asymmetries) in one or more brain regions

  3. Neural Correlates of the Severity of Cocaine, Heroin, Alcohol, MDMA and Cannabis Use in Polysubstance Abusers: A Resting-PET Brain Metabolism Study

    OpenAIRE

    Laura Moreno-López; Stamatakis, Emmanuel A.; Maria José Fernández-Serrano; Manuel Gómez-Río; Antonio Rodríguez-Fernández; Miguel Pérez-García; Antonio Verdejo-García

    2012-01-01

    INTRODUCTION: Functional imaging studies of addiction following protracted abstinence have not been systematically conducted to look at the associations between severity of use of different drugs and brain dysfunction. Findings from such studies may be relevant to implement specific interventions for treatment. The aim of this study was to examine the association between resting-state regional brain metabolism (measured with 18F-fluorodeoxyglucose Positron Emission Tomography (FDG-PET) and th...

  4. A Comparison of Brain Wave Patterns of High and Low Grade Point Average Students During Rest, Problem Solving, and Stress Situations.

    Science.gov (United States)

    Montor, Karel

    The purpose of this study was to compare brain wave patterns produced by high and low grade point average students, while they were resting, solving problems, and subjected to stress situations. The study involved senior midshipmen at the United States Naval Academy. The high group was comprised of those whose cumulative grade point average was…

  5. Local activity determines functional connectivity in the resting human brain: a simultaneous FDG-PET/fMRI study.

    Science.gov (United States)

    Riedl, Valentin; Bienkowska, Katarzyna; Strobel, Carola; Tahmasian, Masoud; Grimmer, Timo; Förster, Stefan; Friston, Karl J; Sorg, Christian; Drzezga, Alexander

    2014-04-30

    Over the last decade, synchronized resting-state fluctuations of blood oxygenation level-dependent (BOLD) signals between remote brain areas [so-called BOLD resting-state functional connectivity (rs-FC)] have gained enormous relevance in systems and clinical neuroscience. However, the neural underpinnings of rs-FC are still incompletely understood. Using simultaneous positron emission tomography/magnetic resonance imaging we here directly investigated the relationship between rs-FC and local neuronal activity in humans. Computational models suggest a mechanistic link between the dynamics of local neuronal activity and the functional coupling among distributed brain regions. Therefore, we hypothesized that the local activity (LA) of a region at rest determines its rs-FC. To test this hypothesis, we simultaneously measured both LA (glucose metabolism) and rs-FC (via synchronized BOLD fluctuations) during conditions of eyes closed or eyes open. During eyes open, LA increased in the visual system, and the salience network (i.e., cingulate and insular cortices) and the pattern of elevated LA coincided almost exactly with the spatial pattern of increased rs-FC. Specifically, the voxelwise regional profile of LA in these areas strongly correlated with the regional pattern of rs-FC among the same regions (e.g., LA in primary visual cortex accounts for ∼ 50%, and LA in anterior cingulate accounts for ∼ 20% of rs-FC with the visual system). These data provide the first direct evidence in humans that local neuronal activity determines BOLD FC at rest. Beyond its relevance for the neuronal basis of coherent BOLD signal fluctuations, our procedure may translate into clinical research particularly to investigate potentially aberrant links between local dynamics and remote functional coupling in patients with neuropsychiatric disorders. PMID:24790196

  6. The Transliminal Brain at Rest: Baseline EEG, Unusual Experiences, and Access to Unconscious Mental Activity

    OpenAIRE

    Fleck, Jessica I.; Green, Deborah L.; Stevenson, Jennifer L.; Payne, Lisa; Edward M. Bowden; Jung-Beeman, Mark; Kounios, John

    2008-01-01

    Transliminality reflects individual differences in the threshold at which unconscious processes or external stimuli enter into consciousness. Individuals high in transliminality possess characteristics such as magical ideation, belief in the paranormal, and creative personality traits, and also report the occurrence of manic/mystic experiences. The goal of the present research was to determine if resting brain activity differs for individuals high versus low in transliminality. We compared ba...

  7. Evaluation of Multiband EPI Acquisitions for Resting State fMRI.

    Directory of Open Access Journals (Sweden)

    Christine Preibisch

    Full Text Available Functional magnetic resonance imaging (fMRI and particularly resting state fMRI (rs-fMRI is widely used to investigate resting state brain networks (RSNs on the systems level. Echo planar imaging (EPI is the state-of-the-art imaging technique for most fMRI studies. Therefore, improvements of EPI might lead to increased sensitivity for a large amount of studies performed every day. A number of developments to shorten acquisition time have been recently proposed and the multiband technique, allowing the simultaneous acquisition of multiple slices yielding an equivalent reduction of measurement time, is the most promising among them. While the prospect to significantly reduce acquisition time by means of high multiband acceleration factors (M appears tempting, signal quality parameters and the sensitivity to detect common RSNs with increasing M-factor have only been partially investigated up to now. In this study, we therefore acquired rs-fMRI data from 20 healthy volunteers to systematically investigate signal characteristics and sensitivity for brain network activity in datasets with increasing M-factor, M = 2 - 4. Combined with an inplane, sensitivity encoding (SENSE, acceleration factor, S = 2, we applied a maximal acceleration factor of 8 (S2×M4. Our results suggest that an M-factor of 2 (total acceleration of 4 only causes negligible SNR decrease but reveals common RSN with increased sensitivity and stability. Further M-factor increase produced random artifacts as revealed by signal quality measures that may affect interpretation of RSNs under common scanning conditions. Given appropriate hardware, a mb-EPI sequence with a total acceleration of 4 significantly reduces overall scanning time and clearly increases sensitivity to detect common RSNs. Together, our results suggest mb-EPI at moderate acceleration factors as a novel standard for fMRI that might increase our understanding of network dynamics in healthy and diseased brains.

  8. Characterising resting-state functional connectivity in a large sample of adults with ADHD.

    Science.gov (United States)

    Mostert, Jeanette C; Shumskaya, Elena; Mennes, Maarten; Onnink, A Marten H; Hoogman, Martine; Kan, Cornelis C; Arias Vasquez, Alejandro; Buitelaar, Jan; Franke, Barbara; Norris, David G

    2016-06-01

    Attention-deficit/hyperactivity disorder (ADHD) is a common childhood psychiatric disorder that often persists into adulthood. While several studies have identified altered functional connectivity in brain networks during rest in children with ADHD, few studies have been performed on adults with ADHD. Existing studies have generally investigated small samples. We therefore investigated aberrant functional connectivity in a large sample of adult patients with childhood-onset ADHD, using a data-driven, whole-brain approach. Adults with a clinical ADHD diagnosis (N=99) and healthy, adult comparison subjects (N=113) underwent a 9-minute resting-state fMRI session in a 1.5T MRI scanner. After elaborate preprocessing including a thorough head-motion correction procedure, group independent component analysis (ICA) was applied from which we identified six networks of interest: cerebellum, executive control, left and right frontoparietal and two default-mode networks. Participant-level network maps were obtained using dual-regression and tested for differences between patients with ADHD and controls using permutation testing. Patients showed significantly stronger connectivity in the anterior cingulate gyrus of the executive control network. Trends were also observed for stronger connectivity in the cerebellum network in ADHD patients compared to controls. However, there was considerable overlap in connectivity values between patients and controls, leading to relatively low effect sizes despite the large sample size. These effect sizes were slightly larger when testing for correlations between hyperactivity/impulsivity symptoms and connectivity strength in the executive control and cerebellum networks. This study provides important insights for studies on the neurobiology of adult ADHD; it shows that resting-state functional connectivity differences between adult patients and controls exist, but have smaller effect sizes than existing literature suggested. PMID:26825495

  9. Tremor frequency characteristics in Parkinson's disease under resting-state and stress-state conditions.

    Science.gov (United States)

    Lee, Hong Ji; Lee, Woong Woo; Kim, Sang Kyong; Park, Hyeyoung; Jeon, Hyo Seon; Kim, Han Byul; Jeon, Beom S; Park, Kwang Suk

    2016-03-15

    Tremor characteristics-amplitude and frequency components-are primary quantitative clinical factors for diagnosis and monitoring of tremors. Few studies have investigated how different patient's conditions affect tremor frequency characteristics in Parkinson's disease (PD). Here, we analyzed tremor characteristics under resting-state and stress-state conditions. Tremor was recorded using an accelerometer on the finger, under resting-state and stress-state (calculation task) conditions, during rest tremor and postural tremor. The changes of peak power, peak frequency, mean frequency, and distribution of power spectral density (PSD) of tremor were evaluated across conditions. Patients whose tremors were considered more than "mild" were selected, for both rest (n=67) and postural (n=25) tremor. Stress resulted in both greater peak powers and higher peak frequencies for rest tremor (pcharacteristics, namely a lower frequency as amplitude increases, are different in stressful condition. Patient's conditions directly affect neural oscillations related to tremor frequencies. Therefore, tremor characteristics in PD should be systematically standardized across patient's conditions such as attention and stress levels.

  10. Decreased thalamocortical functional connectivity after 36 hours of total sleep deprivation: evidence from resting state FMRI.

    Directory of Open Access Journals (Sweden)

    Yongcong Shao

    Full Text Available OBJECTIVES: The thalamus and cerebral cortex are connected via topographically organized, reciprocal connections, which hold a key function in segregating internally and externally directed awareness information. Previous task-related studies have revealed altered activities of the thalamus after total sleep deprivation (TSD. However, it is still unclear how TSD impacts on the communication between the thalamus and cerebral cortex. In this study, we examined changes of thalamocortical functional connectivity after 36 hours of total sleep deprivation by using resting state function MRI (fMRI. MATERIALS AND METHODS: Fourteen healthy volunteers were recruited and performed fMRI scans before and after 36 hours of TSD. Seed-based functional connectivity analysis was employed and differences of thalamocortical functional connectivity were tested between the rested wakefulness (RW and TSD conditions. RESULTS: We found that the right thalamus showed decreased functional connectivity with the right parahippocampal gyrus, right middle temporal gyrus and right superior frontal gyrus in the resting brain after TSD when compared with that after normal sleep. As to the left thalamus, decreased connectivity was found with the right medial frontal gyrus, bilateral middle temporal gyri and left superior frontal gyrus. CONCLUSION: These findings suggest disruptive changes of the thalamocortical functional connectivity after TSD, which may lead to the decline of the arousal level and information integration, and subsequently, influence the human cognitive functions.

  11. Resting-state magnetoencephalography study of “small world” characteristics and cognitive dysfunction in patients with glioma

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    Hu X

    2013-04-01

    Full Text Available Xin-Hua Hu, Ting Lei, Hua-Zhong Xu, Yuan-Jie Zou, Hong-Yi Liu Department of Neurosurgery, Brain Hospital Affiliated to Nanjing Medical University, Nanjing, People's Republic of China Background: The purpose of this study was to analyze “small world” characteristics in glioma patients in order to understand the relationship between cognitive dysfunction and brain functional connectivity network in the resting state. Methods: Resting-state magnetoencephalography was performed in 20 patients with glioma and 20 healthy subjects. The clustering coefficient of the resting functional connectivity network in the brain, average path length, and “small world” index (SWI were calculated. Cognitive function was estimated by testing of attention, verbal fluency, memory, athletic ability, visual-spatial ability, and intelligence. Results: Compared with healthy controls, patients with glioma showed decreased cognitive function, and diminished low and high gamma band “small world” characteristics in the resting functional connectivity network. Conclusion: The SWI is associated with cognitive function and is diminished in patients with glioma, and is therefore correlated with cognition dysfunction. Keywords: glioma, cognitive dysfunction, “small world”, functional connectivity network, magnetoencephalography

  12. Automatic identification of resting state networks: an extended version of multiple template-matching

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    Guaje, Javier; Molina, Juan; Rudas, Jorge; Demertzi, Athena; Heine, Lizette; Tshibanda, Luaba; Soddu, Andrea; Laureys, Steven; Gómez, Francisco

    2015-12-01

    Functional magnetic resonance imaging in resting state (fMRI-RS) constitutes an informative protocol to investigate several pathological and pharmacological conditions. A common approach to study this data source is through the analysis of changes in the so called resting state networks (RSNs). These networks correspond to well-defined functional entities that have been associated to different low and high brain order functions. RSNs may be characterized by using Independent Component Analysis (ICA). ICA provides a decomposition of the fMRI-RS signal into sources of brain activity, but it lacks of information about the nature of the signal, i.e., if the source is artifactual or not. Recently, a multiple template-matching (MTM) approach was proposed to automatically recognize RSNs in a set of Independent Components (ICs). This method provides valuable information to assess subjects at individual level. Nevertheless, it lacks of a mechanism to quantify how much certainty there is about the existence/absence of each network. This information may be important for the assessment of patients with severely damaged brains, in which RSNs may be greatly affected as a result of the pathological condition. In this work we propose a set of changes to the original MTM that improves the RSNs recognition task and also extends the functionality of the method. The key points of this improvement is a standardization strategy and a modification of method's constraints that adds flexibility to the approach. Additionally, we also introduce an analysis to the trustworthiness measurement of each RSN obtained by using template-matching approach. This analysis consists of a thresholding strategy applied over the computed Goodness-of-Fit (GOF) between the set of templates and the ICs. The proposed method was validated on 2 two independent studies (Baltimore, 23 healthy subjects and Liege, 27 healthy subjects) with different configurations of MTM. Results suggest that the method will provide

  13. A resting state network in the motor control circuit of the basal ganglia

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    Bruzzone Lorenzo

    2009-11-01

    Full Text Available Abstract Background In the absence of overt stimuli, the brain shows correlated fluctuations in functionally related brain regions. Approximately ten largely independent resting state networks (RSNs showing this behaviour have been documented to date. Recent studies have reported the existence of an RSN in the basal ganglia - albeit inconsistently and without the means to interpret its function. Using two large study groups with different resting state conditions and MR protocols, the reproducibility of the network across subjects, behavioural conditions and acquisition parameters is assessed. Independent Component Analysis (ICA, combined with novel analyses of temporal features, is applied to establish the basis of signal fluctuations in the network and its relation to other RSNs. Reference to prior probabilistic diffusion tractography work is used to identify the basal ganglia circuit to which these fluctuations correspond. Results An RSN is identified in the basal ganglia and thalamus, comprising the pallidum, putamen, subthalamic nucleus and substantia nigra, with a projection also to the supplementary motor area. Participating nuclei and thalamo-cortical connection probabilities allow this network to be identified as the motor control circuit of the basal ganglia. The network was reproducibly identified across subjects, behavioural conditions (fixation, eyes closed, field strength and echo-planar imaging parameters. It shows a frequency peak at 0.025 ± 0.007 Hz and is most similar in spectral composition to the Default Mode (DM, a network of regions that is more active at rest than during task processing. Frequency features allow the network to be classified as an RSN rather than a physiological artefact. Fluctuations in this RSN are correlated with those in the task-positive fronto-parietal network and anticorrelated with those in the DM, whose hemodynamic response it anticipates. Conclusion Although the basal ganglia RSN has not been

  14. Abnormalities of resting state functional connectivity are related to sustained attention deficits in MS.

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    Marisa Loitfelder

    Full Text Available OBJECTIVES: Resting state (RS functional MRI recently identified default network abnormalities related to cognitive impairment in MS. fMRI can also be used to map functional connectivity (FC while the brain is at rest and not adhered to a specific task. Given the importance of the anterior cingulate cortex (ACC for higher executive functioning in MS, we here used the ACC as seed-point to test for differences and similarities in RS-FC related to sustained attention between MS patients and controls. DESIGN: Block-design rest phases of 3 Tesla fMRI data were analyzed to assess RS-FC in 31 patients (10 clinically isolated syndromes, 16 relapsing-remitting, 5 secondary progressive MS and 31 age- and gender matched healthy controls (HC. Participants underwent extensive cognitive testing. OBSERVATIONS: In both groups, signal changes in several brain areas demonstrated significant correlation with RS-activity in the ACC. These comprised the posterior cingulate cortex (PCC, insular cortices, the right caudate, right middle temporal gyrus, angular gyri, the right hippocampus, and the cerebellum. Compared to HC, patients showed increased FC between the ACC and the left angular gyrus, left PCC, and right postcentral gyrus. Better cognitive performance in the patients was associated with increased FC to the cerebellum, middle temporal gyrus, occipital pole, and the angular gyrus. CONCLUSION: We provide evidence for adaptive changes in RS-FC in MS patients compared to HC in a sustained attention network. These results extend and partly mirror findings of task-related fMRI, suggesting FC may increase our understanding of cognitive dysfunction in MS.

  15. Abnormal resting-state cortical coupling in chronic tinnitus

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    Langguth Berthold

    2009-02-01

    Full Text Available Abstract Background Subjective tinnitus is characterized by an auditory phantom perception in the absence of any physical sound source. Consequently, in a quiet environment, tinnitus patients differ from control participants because they constantly perceive a sound whereas controls do not. We hypothesized that this difference is expressed by differential activation of distributed cortical networks. Results The analysis was based on a sample of 41 participants: 21 patients with chronic tinnitus and 20 healthy control participants. To investigate the architecture of these networks, we used phase locking analysis in the 1–90 Hz frequency range of a minute of resting-state MEG recording. We found: 1 For tinnitus patients: A significant decrease of inter-areal coupling in the alpha (9–12 Hz band and an increase of inter-areal coupling in the 48–54 Hz gamma frequency range relative to the control group. 2 For both groups: an inverse relationship (r = -.71 of the alpha and gamma network coupling. 3 A discrimination of 83% between the patient and the control group based on the alpha and gamma networks. 4 An effect of manifestation on the distribution of the gamma network: In patients with a tinnitus history of less than 4 years, the left temporal cortex was predominant in the gamma network whereas in patients with tinnitus duration of more than 4 years, the gamma network was more widely distributed including more frontal and parietal regions. Conclusion In the here presented data set we found strong support for an alteration of long-range coupling in tinnitus. Long-range coupling in the alpha frequency band was decreased for tinnitus patients while long-range gamma coupling was increased. These changes discriminate well between tinnitus and control participants. We propose a tinnitus model that integrates this finding in the current knowledge about tinnitus. Furthermore we discuss the impact of this finding to tinnitus therapies using Transcranial

  16. Altered resting-state functional connectivity in post-traumatic stress disorder: a perfusion MRI study

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    Li, Baojuan; Liu, Jian; Liu, Yang; Lu, Hong-Bing; Yin, Hong

    2013-03-01

    The majority of studies on posttraumatic stress disorder (PTSD) so far have focused on delineating patterns of activations during cognitive processes. Recently, more and more researches have started to investigate functional connectivity in PTSD subjects using BOLD-fMRI. Functional connectivity analysis has been demonstrated as a powerful approach to identify biomarkers of different brain diseases. This study aimed to detect resting-state functional connectivity abnormities in patients with PTSD using arterial spin labeling (ASL) fMRI. As a completely non-invasive technique, ASL allows quantitative estimates of cerebral blood flow (CBF). Compared with BOLD-fMRI, ASL fMRI has many advantages, including less low-frequency signal drifts, superior functional localization, etc. In the current study, ASL images were collected from 10 survivors in mining disaster with recent onset PTSD and 10 survivors without PTSD. Decreased regional CBF in the right middle temporal gyrus, lingual gyrus, and postcentral gyrus was detected in the PTSD patients. Seed-based resting-state functional connectivity analysis was performed using an area in the right middle temporal gyrus as region of interest. Compared with the non-PTSD group, the PTSD subjects demonstrated increased functional connectivity between the right middle temporal gyrus and the right superior temporal gyrus, the left middle temporal gyrus. Meanwhile, decreased functional connectivity between the right middle temporal gyrus and the right postcentral gyrus, the right superior parietal lobule was also found in the PTSD patients. This is the first study which investigated resting-state functional connectivity in PTSD using ASL images. The results may provide new insight into the neural substrates of PTSD.

  17. In search of neural mechanisms of mirror neuron dysfunction in schizophrenia: resting state functional connectivity approach.

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    Zaytseva, Yuliya; Bendova, Marie; Garakh, Zhanna; Tintera, Jaroslav; Rydlo, Jan; Spaniel, Filip; Horacek, Jiri

    2015-09-01

    It has been repeatedly shown that schizophrenia patients have immense alterations in goal-directed behaviour, social cognition, and social interactions, cognitive abilities that are presumably driven by the mirror neurons system (MNS). However, the neural bases of these deficits still remain unclear. Along with the task-related fMRI and EEG research tapping into the mirror neuron system, the characteristics of the resting state activity in the particular areas that encompass mirror neurons might be of interest as they obviously determine the baseline of the neuronal activity. Using resting state fMRI, we investigated resting state functional connectivity (FC) in four predefined brain structures, ROIs (inferior frontal gyrus, superior parietal lobule, premotor cortex and superior temporal gyrus), known for their mirror neurons activity, in 12 patients with first psychotic episode and 12 matched healthy individuals. As a specific hypothesis, based on the knowledge of the anatomical inputs of thalamus to all preselected ROIs, we have investigated the FC between thalamus and the ROIs. Of all ROIs included, seed-to-voxel connectivity analysis revealed significantly decreased FC only in left posterior superior temporal gyrus (STG) and the areas in visual cortex and cerebellum in patients as compared to controls. Using ROI-to-ROI analysis (thalamus and selected ROIs), we have found an increased FC of STG and bilateral thalamus whereas the FC of these areas was decreased in controls. Our results suggest that: (1) schizophrenia patients exhibit FC of STG which corresponds to the previously reported changes of superior temporal gyrus in schizophrenia and might contribute to the disturbances of specific functions, such as emotional processing or spatial awareness; (2) as the thalamus plays a pivotal role in the sensory gating, providing the filtering of the redundant stimulation, the observed hyperconnectivity between the thalami and the STGs in patients with schizophrenia

  18. Altered default network resting-state functional connectivity in adolescents with Internet gaming addiction.

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    Wei-na Ding

    Full Text Available PURPOSE: Excessive use of the Internet has been linked to a variety of negative psychosocial consequences. This study used resting-state functional magnetic resonance imaging (fMRI to investigate whether functional connectivity is altered in adolescents with Internet gaming addiction (IGA. METHODS: Seventeen adolescents with IGA and 24 normal control adolescents underwent a 7.3 minute resting-state fMRI scan. Posterior cingulate cortex (PCC connectivity was determined in all subjects by investigating synchronized low-frequency fMRI signal fluctuations using a temporal correlation method. To assess the relationship between IGA symptom severity and PCC connectivity, contrast images representing areas correlated with PCC connectivity were correlated with the scores of the 17 subjects with IGA on the Chen Internet Addiction Scale (CIAS and Barratt Impulsiveness Scale-11 (BIS-11 and their hours of Internet use per week. RESULTS: There were no significant differences in the distributions of the age, gender, and years of education between the two groups. The subjects with IGA showed longer Internet use per week (hours (p<0.0001 and higher CIAS (p<0.0001 and BIS-11 (p = 0.01 scores than the controls. Compared with the control group, subjects with IGA exhibited increased functional connectivity in the bilateral cerebellum posterior lobe and middle temporal gyrus. The bilateral inferior parietal lobule and right inferior temporal gyrus exhibited decreased connectivity. Connectivity with the PCC was positively correlated with CIAS scores in the right precuneus, posterior cingulate gyrus, thalamus, caudate, nucleus accumbens, supplementary motor area, and lingual gyrus. It was negatively correlated with the right cerebellum anterior lobe and left superior parietal lobule. CONCLUSION: Our results suggest that adolescents with IGA exhibit different resting-state patterns of brain activity. As these alterations are partially consistent with those in patients

  19. Detection of EEG-Resting State Networks by LORETA-ICA method

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    Yasunori eAoki

    2015-02-01

    Full Text Available Recent fMRI studies have shown that functional networks can be extracted even from resting state data, the so called resting state networks (RSNs by applying independent component analysis (ICA. However, compared to fMRI, EEG and MEG have much higher temporal resolution and provide a direct estimation of cortical activity. To date, MEG studies have applied ICA for separate frequency bands only, disregarding cross-frequency couplings. In this study, we aimed to detect EEG-RSNs and their interactions in all frequency bands. We applied low resolution brain electromagnetic tomography-ICA (LORETA-ICA to resting-state EEG data in 80 healthy subjects using five frequency bands (delta, theta, alpha, beta and gamma band and found five RSNs in alpha, beta and gamma frequency bands. Next, taking into account these frequency properties, five RSNs were identified; 1 the visual network, 2 dual-process of visual perception network, characterized by a negative correlation between the right ventral visual pathway (VVP and left posterior dorsal visual pathway (DVP, 3 self-referential processing network, characterized by a positive correlation between the medial PFC and right VVP, 4 dual-process of memory perception network, functionally related to a negative correlation between the left VVP and the precuneus and 5 sensorimotor network. To detect aging-related changes of these five RSNs, the subjects were divided into three age groups: younger, middle aged, and elderly group, and Student's t test with Bonferroni correction on each coefficient of five independent components were performed. We found a significant attenuation in dual-process of visual perception network in elderly relative to middle aged subjects. Overall findings indicate that LORETA-ICA with EEG data can precisely identify five RSNs in their intrinsic frequency bands, and correct correlations and aging-related changes between and within RSNs.

  20. Cerebral White Matter Integrity and Resting-State Functional Connectivity in Middle-aged Patients With Type 2 Diabetes

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    Hoogenboom, Wouter S.; Marder, Thomas J.; Flores, Veronica L.; Huisman, Susanne; Eaton, Hana P.; Schneiderman, Jason S.; Bolo, Nicolas R.; Simonson, Donald C.; Jacobson, Alan M.; Kubicki, Marek; Martha E. Shenton; Musen, Gail

    2014-01-01

    Early detection of brain abnormalities at the preclinical stage can be useful for developing preventive interventions to abate cognitive decline. We examined whether middle-aged type 2 diabetic patients show reduced white matter integrity in fiber tracts important for cognition and whether this abnormality is related to preestablished altered resting-state functional connectivity in the default mode network (DMN). Diabetic and nondiabetic participants underwent diffusion tensor imaging, funct...

  1. Impaired resting-state functional integrations within default mode network of generalized tonic-clonic seizures epilepsy.

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    Ming Song

    Full Text Available Generalized tonic-clonic seizures (GTCS are characterized by unresponsiveness and convulsions, which cause complete loss of consciousness. Many recent studies have found that the ictal alterations in brain activity of the GTCS epilepsy patients are focally involved in some brain regions, including thalamus, upper brainstem, medial prefrontal cortex, posterior midbrain regions, and lateral parietal cortex. Notably, many of these affected brain regions are the same and overlap considerably with the components of the so-called default mode network (DMN. Here, we hypothesize that the brain activity of the DMN of the GTCS epilepsy patients are different from normal controls, even in the resting state. To test this hypothesis, we compared the DMN of the GTCS epilepsy patients and the controls using the resting state functional magnetic resonance imaging. Thirteen brain areas in the DMN were extracted, and a complete undirected weighted graph was used to model the DMN for each participant. When directly comparing the edges of the graph, we found significant decreased functional connectivities within the DMN of the GTCS epilepsy patients comparing to the controls. As for the nodes of the graph, we found that the degree of some brain areas within the DMN was significantly reduced in the GTCS epilepsy patients, including the anterior medial prefrontal cortex, the bilateral superior frontal cortex, and the posterior cingulate cortex. Then we investigated into possible mechanisms of how GTCS epilepsy could cause the reduction of the functional integrations of DMN. We suggested the damaged functional integrations of the DMN in the GTCS epilepsy patients even during the resting state, which could help to understand the neural correlations of the impaired consciousness of GTCS epilepsy patients.

  2. Resting-state hippocampal connectivity correlates with symptom severity in post-traumatic stress disorder

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    B.T. Dunkley

    2014-01-01

    Full Text Available Post-traumatic stress disorder (PTSD is a serious mental health injury which can manifest after experiencing a traumatic life event. The disorder is characterized by symptoms of re-experiencing, avoidance, emotional numbing and hyper-arousal. Whilst its aetiology and resultant symptomology are better understood, relatively little is known about the underlying cortical pathophysiology, and in particular whether changes in functional connectivity may be linked to the disorder. Here, we used non-invasive neuroimaging with magnetoencephalography to examine functional connectivity in a resting-state protocol in the combat-related PTSD group (n = 23, and a military control group (n = 21. We identify atypical long-range hyperconnectivity in the high-gamma-band resting-state networks in a combat-related PTSD population compared to soldiers who underwent comparable environmental exposure but did not develop PTSD. Using graph analysis, we demonstrate that apparent network connectivity of relevant brain regions is associated with cognitive-behavioural outcomes. We also show that left hippocampal connectivity in the PTSD group correlates with scores on the well-established PTSD Checklist (PCL. These findings indicate that atypical synchronous neural interactions may underlie the psychological symptoms of PTSD, whilst also having utility as a potential biomarker to aid in the diagnosis and monitoring of the disorder.

  3. Using coherence to measure regional homogeneity of resting-state fMRI signal

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    Dongqiang Liu

    2010-06-01

    Full Text Available In this study, we applied coherence to voxel-wise measurement of regional homogeneity of resting-state functional magnetic resonance imaging (RS-fMRI signal. We compared the current method, regional homogeneity based on coherence (Cohe-ReHo, with previously proposed method, ReHo based on Kendall’s coefficient of concordance (KCC-ReHo, in terms of correlation and paired t-test in a large sample of healthy participants. We found the two measurements differed mainly in some brain regions where physiological noise is dominant. We also compared the sensitivity of these methods in detecting difference between resting-state conditions (eyes open (EO vs. eyes closed (EC and in detecting abnormal local synchronization between two groups (attention deficit hyperactivity disorder (ADHD patients vs. normal controls. Our results indicated that Cohe-ReHo is more sensitive than KCC-ReHo to the difference between two conditions (EO vs. EC as well as that between ADHD and normal controls. These preliminary results suggest that Cohe-ReHo is superior to KCC-ReHo. A possible reason is that coherence is not susceptible to random noise induced by phase delay among the timecourses to be measured. However, further investigation is still needed to elucidate the sensitivity and specificity of these methods.

  4. Using coherence to measure regional homogeneity of resting-state FMRI signal.

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    Liu, Dongqiang; Yan, Chaogan; Ren, Juejing; Yao, Li; Kiviniemi, Vesa J; Zang, Yufeng

    2010-01-01

    In this study, we applied coherence to voxel-wise measurement of regional homogeneity of resting-state functional magnetic resonance imaging (RS-fMRI) signal. We compared the current method, regional homogeneity based on coherence (Cohe-ReHo), with previously proposed method, ReHo based on Kendall's coefficient of concordance (KCC-ReHo), in terms of correlation and paired t-test in a large sample of healthy participants. We found the two measurements differed mainly in some brain regions where physiological noise is dominant. We also compared the sensitivity of these methods in detecting difference between resting-state conditions [eyes open (EO) vs. eyes closed (EC)] and in detecting abnormal local synchronization between two groups [attention deficit hyperactivity disorder (ADHD) patients vs. normal controls]. Our results indicated that Cohe-ReHo is more sensitive than KCC-ReHo to the difference between two conditions (EO vs. EC) as well as that between ADHD and normal controls. These preliminary results suggest that Cohe-ReHo is superior to KCC-ReHo. A possible reason is that coherence is not susceptible to random noise induced by phase delay among the time courses to be measured. However, further investigation is still needed to elucidate the sensitivity and specificity of these methods. PMID:20589093

  5. Asymmetrical hippocampal connectivity in mesial temporal lobe epilepsy: evidence from resting state fMRI

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    Castellano Gabriela

    2010-06-01

    Full Text Available Abstract Background Mesial temporal lobe epilepsy (MTLE, the most common type of focal epilepsy in adults, is often caused by hippocampal sclerosis (HS. Patients with HS usually present memory dysfunction, which is material-specific according to the hemisphere involved and has been correlated to the degree of HS as measured by postoperative histopathology as well as by the degree of hippocampal atrophy on magnetic resonance imaging (MRI. Verbal memory is mostly affected by left-sided HS, whereas visuo-spatial memory is more affected by right HS. Some of these impairments may be related to abnormalities of the network in which individual hippocampus takes part. Functional connectivity can play an important role to understand how the hippocampi interact with other brain areas. It can be estimated via functional Magnetic Resonance Imaging (fMRI resting state experiments by evaluating patterns of functional networks. In this study, we investigated the functional connectivity patterns of 9 control subjects, 9 patients with right MTLE and 9 patients with left MTLE. Results We detected differences in functional connectivity within and between hippocampi in patients with unilateral MTLE associated with ipsilateral HS by resting state fMRI. Functional connectivity resulted to be more impaired ipsilateral to the seizure focus in both patient groups when compared to control subjects. This effect was even more pronounced for the left MTLE group. Conclusions The findings presented here suggest that left HS causes more reduction of functional connectivity than right HS in subjects with left hemisphere dominance for language.

  6. Altered regional and circuit resting-state activity associated with unilateral hearing loss.

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    Xingchao Wang

    Full Text Available The deprivation of sensory input after hearing damage results in functional reorganization of the brain including cross-modal plasticity in the sensory cortex and changes in cognitive processing. However, it remains unclear whether partial deprivation from unilateral auditory loss (UHL would similarly affect the neural circuitry of cognitive processes in addition to the functional organization of sensory cortex. Here, we used resting-state functional magnetic resonance imaging to investigate intrinsic activity in 34 participants with UHL from acoustic neuroma in comparison with 22 matched normal controls. In sensory regions, we found decreased regional homogeneity (ReHo in the bilateral calcarine cortices in UHL. However, there was an increase of ReHo in the right anterior insular cortex (rAI, the key node of cognitive control network (CCN and multimodal sensory integration, as well as in the left parahippocampal cortex (lPHC, a key node in the default mode network (DMN. Moreover, seed-based resting-state functional connectivity analysis showed an enhanced relationship between rAI and several key regions of the DMN. Meanwhile, lPHC showed more negative relationship with components in the CCN and greater positive relationship in the DMN. Such reorganizations of functional connectivity within the DMN and between the DMN and CCN were confirmed by a graph theory analysis. These results suggest that unilateral sensory input damage not only alters the activity of the sensory areas but also reshapes the regional and circuit functional organization of the cognitive control network.

  7. Classification and Extraction of Resting State Networks Using Healthy and Epilepsy fMRI Data

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    Vergun, Svyatoslav; Gaggl, Wolfgang; Nair, Veena A.; Suhonen, Joshua I.; Birn, Rasmus M.; Ahmed, Azam S.; Meyerand, M. Elizabeth; Reuss, James; DeYoe, Edgar A.; Prabhakaran, Vivek

    2016-01-01

    Functional magnetic resonance imaging studies have significantly expanded the field's understanding of functional brain activity of healthy and patient populations. Resting state (rs-) fMRI, which does not require subjects to perform a task, eliminating confounds of task difficulty, allows examination of neural activity and offers valuable functional mapping information. The purpose of this work was to develop an automatic resting state network (RSN) labeling method which offers value in clinical workflow during rs-fMRI mapping by organizing and quickly labeling spatial maps into functional networks. Here independent component analysis (ICA) and machine learning were applied to rs-fMRI data with the goal of developing a method for the clinically oriented task of extracting and classifying spatial maps into auditory, visual, default-mode, sensorimotor, and executive control RSNs from 23 epilepsy patients (and for general comparison, separately for 30 healthy subjects). ICA revealed distinct and consistent functional network components across patients and healthy subjects. Network classification was successful, achieving 88% accuracy for epilepsy patients with a naïve Bayes algorithm (and 90% accuracy for healthy subjects with a perceptron). The method's utility to researchers and clinicians is the provided RSN spatial maps and their functional labeling which offer complementary functional information to clinicians' expert interpretation. PMID:27729846

  8. Is Love Right? Prefrontal Resting Brain Asymmetry is Related to the Affiliation Motive

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    Markus eQuirin

    2013-12-01

    Full Text Available Previous research on relationships between affective-motivational traits and hemispheric asymmetries in resting frontal alpha band power as measured by electroencephalography (EEG has focused on individual differences in motivational direction (approach vs. withdrawal or behavioral activation. The present study investigated resting frontal alpha asymmetries in 72 participants as a function of individual differences in the implicit affiliation motive as measured with the operant motive test (OMT and explored the brain source thereof. As predicted, relative right frontal activity as indexed by increased alpha band suppression was related to the implicit affiliation motive. No relationships were found for explicit personality measures. Intracranial current density distributions of alpha based on Variable Resolution Electromagnetic Tomography (VARETA source estimations suggests that the source of cortical alpha distribution is located within the right ventromedial prefrontal cortex (PFC. The present results are discussed with respect to differential roles of the two hemispheres in social motivation.

  9. Universal Organization of Resting Brain Activity at the Thermodynamic Critical Point

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    Shan eYu

    2013-08-01

    Full Text Available Thermodynamic criticality describes emergent phenomena in a wide variety of complex systems. In the mammalian cortex, one type of complex dynamics that spontaneously emerges from neuronal interactions has been characterized as neuronal avalanches. Several aspects of neuronal avalanches such as their size and life time distributions are described by power laws with unique exponents, indicating an underlying critical branching process that governs avalanche formation. Here, we show that neuronal avalanches also reflect an organization of brain dynamics close to a thermodynamic critical point. We recorded spontaneous cortical activity in monkeys and humans at rest using high-density intracranial microelectrode arrays and magnetoencephalography, respectively. By numerically changing a control parameter equivalent to thermodynamic temperature, we observed typical critical behavior in cortical activities near the actual physiological condition, including the phase transition of an order parameter, as well as the divergence of susceptibility and specific heat. Finite-size scaling of these quantities allowed us to derive robust critical exponents highly consistent across monkey and humans that uncover a distinct, yet universal organization of brain dynamics. Our results demonstrate that normal brain dynamics at rest resides near or at criticality, which maximizes several aspects of information processing such as input sensitivity and dynamic range.

  10. State-space model with deep learning for functional dynamics estimation in resting-state fMRI.

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    Suk, Heung-Il; Wee, Chong-Yaw; Lee, Seong-Whan; Shen, Dinggang

    2016-04-01

    Studies on resting-state functional Magnetic Resonance Imaging (rs-fMRI) have shown that different brain regions still actively interact with each other while a subject is at rest, and such functional interaction is not stationary but changes over time. In terms of a large-scale brain network, in this paper, we focus on time-varying patterns of functional networks, i.e., functional dynamics, inherent in rs-fMRI, which is one of the emerging issues along with the network modelling. Specifically, we propose a novel methodological architecture that combines deep learning and state-space modelling, and apply it to rs-fMRI based Mild Cognitive Impairment (MCI) diagnosis. We first devise a Deep Auto-Encoder (DAE) to discover hierarchical non-linear functional relations among regions, by which we transform the regional features into an embedding space, whose bases are complex functional networks. Given the embedded functional features, we then use a Hidden Markov Model (HMM) to estimate dynamic characteristics of functional networks inherent in rs-fMRI via internal states, which are unobservable but can be inferred from observations statistically. By building a generative model with an HMM, we estimate the likelihood of the input features of rs-fMRI as belonging to the corresponding status, i.e., MCI or normal healthy control, based on which we identify the clinical label of a testing subject. In order to validate the effectiveness of the proposed method, we performed experiments on two different datasets and compared with state-of-the-art methods in the literature. We also analyzed the functional networks learned by DAE, estimated the functional connectivities by decoding hidden states in HMM, and investigated the estimated functional connectivities by means of a graph-theoretic approach. PMID:26774612

  11. State-space model with deep learning for functional dynamics estimation in resting-state fMRI.

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    Suk, Heung-Il; Wee, Chong-Yaw; Lee, Seong-Whan; Shen, Dinggang

    2016-04-01

    Studies on resting-state functional Magnetic Resonance Imaging (rs-fMRI) have shown that different brain regions still actively interact with each other while a subject is at rest, and such functional interaction is not stationary but changes over time. In terms of a large-scale brain network, in this paper, we focus on time-varying patterns of functional networks, i.e., functional dynamics, inherent in rs-fMRI, which is one of the emerging issues along with the network modelling. Specifically, we propose a novel methodological architecture that combines deep learning and state-space modelling, and apply it to rs-fMRI based Mild Cognitive Impairment (MCI) diagnosis. We first devise a Deep Auto-Encoder (DAE) to discover hierarchical non-linear functional relations among regions, by which we transform the regional features into an embedding space, whose bases are complex functional networks. Given the embedded functional features, we then use a Hidden Markov Model (HMM) to estimate dynamic characteristics of functional networks inherent in rs-fMRI via internal states, which are unobservable but can be inferred from observations statistically. By building a generative model with an HMM, we estimate the likelihood of the input features of rs-fMRI as belonging to the corresponding status, i.e., MCI or normal healthy control, based on which we identify the clinical label of a testing subject. In order to validate the effectiveness of the proposed method, we performed experiments on two different datasets and compared with state-of-the-art methods in the literature. We also analyzed the functional networks learned by DAE, estimated the functional connectivities by decoding hidden states in HMM, and investigated the estimated functional connectivities by means of a graph-theoretic approach.

  12. Decoding Spontaneous Emotional States in the Human Brain

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    Kragel, Philip A.; Knodt, Annchen R.; Hariri, Ahmad R.; LaBar, Kevin S.

    2016-01-01

    Pattern classification of human brain activity provides unique insight into the neural underpinnings of diverse mental states. These multivariate tools have recently been used within the field of affective neuroscience to classify distributed patterns of brain activation evoked during emotion induction procedures. Here we assess whether neural models developed to discriminate among distinct emotion categories exhibit predictive validity in the absence of exteroceptive emotional stimulation. In two experiments, we show that spontaneous fluctuations in human resting-state brain activity can be decoded into categories of experience delineating unique emotional states that exhibit spatiotemporal coherence, covary with individual differences in mood and personality traits, and predict on-line, self-reported feelings. These findings validate objective, brain-based models of emotion and show how emotional states dynamically emerge from the activity of separable neural systems. PMID:27627738

  13. Decoding Spontaneous Emotional States in the Human Brain.

    Science.gov (United States)

    Kragel, Philip A; Knodt, Annchen R; Hariri, Ahmad R; LaBar, Kevin S

    2016-09-01

    Pattern classification of human brain activity provides unique insight into the neural underpinnings of diverse mental states. These multivariate tools have recently been used within the field of affective neuroscience to classify distributed patterns of brain activation evoked during emotion induction procedures. Here we assess whether neural models developed to discriminate among distinct emotion categories exhibit predictive validity in the absence of exteroceptive emotional stimulation. In two experiments, we show that spontaneous fluctuations in human resting-state brain activity can be decoded into categories of experience delineating unique emotional states that exhibit spatiotemporal coherence, covary with individual differences in mood and personality traits, and predict on-line, self-reported feelings. These findings validate objective, brain-based models of emotion and show how emotional states dynamically emerge from the activity of separable neural systems. PMID:27627738

  14. Connectome hubs at resting state in children and adolescents: Reproducibility and psychopathological correlation

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    João Ricardo Sato

    2016-08-01

    Full Text Available Functional brain hubs are key integrative regions in brain networks. Recently, brain hubs identified through resting-state fMRI have emerged as interesting targets to increase understanding of the relationships between large-scale functional networks and psychopathology. However, few studies have directly addressed the replicability and consistency of the hub regions identified and their association with symptoms. Here, we used the eigenvector centrality (EVC measure obtained from graph analysis of two large, independent population-based samples of children and adolescents (7–15 years old; total N = 652; 341 subjects for site 1 and 311 for site 2 to evaluate the replicability of hub identification. Subsequently, we tested the association between replicable hub regions and psychiatric symptoms. We identified a set of hubs consisting of the anterior medial prefrontal cortex and inferior parietal lobule/intraparietal sulcus (IPL/IPS. Moreover, lower EVC values in the right IPS were associated with psychiatric symptoms in both samples. Thus, low centrality of the IPS was a replicable sign of potential vulnerability to mental disorders in children. The identification of critical and replicable hubs in functional cortical networks in children and adolescents can foster understanding of the mechanisms underlying mental disorders.

  15. EEG resting state functional connectivity analysis in children with benign epilepsy with centrotemporal spikes

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    Azeez eAdebimpe

    2016-03-01

    Full Text Available In this study, we investigated changes in functional connectivity of the brain networks in patients with benign epilepsy with centrotemporal spikes compared to healthy controls using high-density EEG data collected under eyes-closed resting state condition. EEG source reconstruction was performed with exact Low Resolution Electromagnetic Tomography (eLORETA. We investigated functional connectivity (FC between 84 Brodmann areas using lagged phase synchronization (LPS in four frequency bands (δ, θ, α, and β. We further computed the network degree, clustering coefficient and efficiency. Compared to controls, patients displayed higher θ and α and lower β lagged phase synchronization values. In these frequency bands, patients were also characterized by less well ordered brain networks exhibiting higher global degrees and efficiencies and lower clustering coefficients. In the beta band, patients exhibited reduced functional segregation and integration due to loss of both local and long-distance functional connections. These findings suggest that benign epileptic brain networks might be functionally disrupted due to their altered functional organization especially in the α and β frequency bands.

  16. Resting state functional MRI reveals abnormal network connectivity in neurofibromatosis 1.

    Science.gov (United States)

    Tomson, Steffie N; Schreiner, Matthew J; Narayan, Manjari; Rosser, Tena; Enrique, Nicole; Silva, Alcino J; Allen, Genevera I; Bookheimer, Susan Y; Bearden, Carrie E

    2015-11-01

    Neurofibromatosis type I (NF1) is a genetic disorder caused by mutations in the neurofibromin 1 gene at locus 17q11.2. Individuals with NF1 have an increased incidence of learning disabilities, attention deficits, and autism spectrum disorders. As a single-gene disorder, NF1 represents a valuable model for understanding gene-brain-behavior relationships. While mouse models have elucidated molecular and cellular mechanisms underlying learning deficits associated with this mutation, little is known about functional brain architecture in human subjects with NF1. To address this question, we used resting state functional connectivity magnetic resonance imaging (rs-fcMRI) to elucidate the intrinsic network structure of 30 NF1 participants compared with 30 healthy demographically matched controls during an eyes-open rs-fcMRI scan. Novel statistical methods were employed to quantify differences in local connectivity (edge strength) and modularity structure, in combination with traditional global graph theory applications. Our findings suggest that individuals with NF1 have reduced anterior-posterior connectivity, weaker bilateral edges, and altered modularity clustering relative to healthy controls. Further, edge strength and modular clustering indices were correlated with IQ and internalizing symptoms. These findings suggest that Ras signaling disruption may lead to abnormal functional brain connectivity; further investigation into the functional consequences of these alterations in both humans and in animal models is warranted. PMID:26304096

  17. Connectome hubs at resting state in children and adolescents: Reproducibility and psychopathological correlation.

    Science.gov (United States)

    Sato, João Ricardo; Biazoli, Claudinei Eduardo; Salum, Giovanni Abrahão; Gadelha, Ary; Crossley, Nicolas; Vieira, Gilson; Zugman, André; Picon, Felipe Almeida; Pan, Pedro Mario; Hoexter, Marcelo Queiroz; Anés, Mauricio; Moura, Luciana Monteiro; Del'Aquilla, Marco Antonio Gomes; Junior, Edson Amaro; Mcguire, Philip; Rohde, Luis Augusto; Miguel, Euripedes Constantino; Bressan, Rodrigo Affonseca; Jackowski, Andrea Parolin

    2016-08-01

    Functional brain hubs are key integrative regions in brain networks. Recently, brain hubs identified through resting-state fMRI have emerged as interesting targets to increase understanding of the relationships between large-scale functional networks and psychopathology. However, few studies have directly addressed the replicability and consistency of the hub regions identified and their association with symptoms. Here, we used the eigenvector centrality (EVC) measure obtained from graph analysis of two large, independent population-based samples of children and adolescents (7-15 years old; total N=652; 341 subjects for site 1 and 311 for site 2) to evaluate the replicability of hub identification. Subsequently, we tested the association between replicable hub regions and psychiatric symptoms. We identified a set of hubs consisting of the anterior medial prefrontal cortex and inferior parietal lobule/intraparietal sulcus (IPL/IPS). Moreover, lower EVC values in the right IPS were associated with psychiatric symptoms in both samples. Thus, low centrality of the IPS was a replicable sign of potential vulnerability to mental disorders in children. The identification of critical and replicable hubs in functional cortical networks in children and adolescents can foster understanding of the mechanisms underlying mental disorders. PMID:27288820

  18. Multiscale entropy analysis of resting-state magnetoencephalogram with tensor factorisations in Alzheimer's disease.

    Science.gov (United States)

    Escudero, Javier; Acar, Evrim; Fernández, Alberto; Bro, Rasmus

    2015-10-01

    Tensor factorisations have proven useful to model amplitude and spectral information of brain recordings. Here, we assess the usefulness of tensor factorisations in the multiway analysis of other brain signal features in the context of complexity measures recently proposed to inspect multiscale dynamics. We consider the "refined composite multiscale entropy" (rcMSE), which computes entropy "profiles" showing levels of physiological complexity over temporal scales for individual signals. We compute the rcMSE of resting-state magnetoencephalogram (MEG) recordings from 36 patients with Alzheimer's disease and 26 control subjects. Instead of traditional simple visual examinations, we organise the entropy profiles as a three-way tensor to inspect relationships across temporal and spatial scales and subjects with multiway data analysis techniques based on PARAFAC and PARAFAC2 factorisations. A PARAFAC2 model with two factors was appropriate to account for the interactions in the entropy tensor between temporal scales and MEG channels for all subjects. Moreover, the PARAFAC2 factors had information related to the subjects' diagnosis, achieving a cross-validated area under the ROC curve of 0.77. This confirms the suitability of tensor factorisations to represent electrophysiological brain data efficiently despite the unsupervised nature of these techniques. This article is part of a Special Issue entitled 'Neural data analysis'. PMID:25982737

  19. Resting-state functional connectivity in anterior cingulate cortex in normal aging

    Directory of Open Access Journals (Sweden)

    Weifang eCao

    2014-10-01

    Full Text Available Growing evidence suggests that normal aging is associated with cognitive decline and well-maintained emotional well-being. The anterior cingulate cortex (ACC is an important brain region involved in emotional and cognitive processing. We investigated resting-state functional connectivity (FC of two ACC subregions in 30 healthy older adults versus 33 healthy younger adults, by parcellating into rostral (rACC and dorsal (dACC ACC based on clustering of FC profiles. Compared with younger adults, older adults demonstrated greater connection between rACC and anterior insula, suggesting that older adults recruit more proximal dACC brain regions connected with insula to maintain a salient response. Older adults also demonstrated increased FC between rACC and superior temporal gyrus and inferior frontal gyrus, decreased integration between rACC and default mode, and decreased dACC-hippocampal and dACC-thalamic connectivity. These altered FCs reflected rACC and dACC reorganization, and might be related to well emotion regulation and cognitive decline in older adults. Our findings provide further insight into potential functional substrates of emotional and cognitive alterations in the aging brain.

  20. Self, cortical midline structures and the resting state: Implications for Alzheimer's disease.

    Science.gov (United States)

    Weiler, Marina; Northoff, Georg; Damasceno, Benito Pereira; Balthazar, Marcio Luiz Figueredo

    2016-09-01

    Different aspects of the self have been reported to be affected in many neurological or psychiatric diseases such as Alzheimer's disease (AD), including mainly higher-level cognitive self-unawareness. This higher sense of self-awareness is most likely related to and dependent on episodic memory, due to the proper integration of ourselves in time, with a permanent conservation of ourselves (i.e., sense of continuity across time). Reviewing studies in this field, our objective is thus to raise possible explanations, especially with the help of neuroimaging studies, for where such self-awareness deficits originate in AD patients. We describe not only episodic (and autobiographical memory) impairment in patients, but also the important role of cortical midline structures, the Default Mode Network, and the resting state (intrinsic brain activity) for the processing of self-related information.

  1. Adolescent resting state networks and their associations to schizotypal trait expression

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    Annalaura Lagioia

    2010-08-01

    Full Text Available The rising interest in temporally coherent brain networks during baseline adult cerebral activity finds convergent evidence for an identifiable set of resting state networks (RSNs. To date, little is know concerning the earlier developmental stages of functional connectivity in RSNs. This study’s main objective is to characterize the RSNs in a sample of adolescents. We further examine our data from a developmental psychopathology perspective of psychosis-proneness, by testing the hypothesis that early schizotypal symptoms are linked to disconnection in RSNs. In this perspective, this study examines the expression of adolescent schizotypal traits and their potential associations to dysfunctional RSNs. Thirty-nine adolescents aged between 12 and 20 years old underwent an eight minute fMRI “resting state” session. In order to explore schizotypal trait manifestations, the entire population was assessed by the Schizotypal Personality Questionnaire (SPQ. After conventional processing of the fMRI data, we applied group-level independent component analysis (ICA. Twenty ICA maps and associated time-courses were obtained, among which there were resting state networks (RSNs that are consistent with findings in the literature. We applied a regression analysis at group level between the energy of RSN-associated time courses in different temporal frequency bins and the clinical measures (3 in total. Our results highlight the engagement of six relevant RSNs; 1 a default-mode network; 2 a dorso-lateral attention network; 3 a visual network; 4 an auditory network; 5 a sensory motor network; 6 a self-referential network. The regression analysis reveals a statistically significant correlation between the clinical measures and some of the RSNs, specifically the visual and the auditory network. In particular, a positive correlation is obtained for the visual network in the low frequency range (0.05 Hz with SPQ measures, while the auditory network correlates

  2. What kind of noise is brain noise? Anomalous scaling behavior of the resting brain activity fluctuations.

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    Daniel eFraiman

    2012-07-01

    Full Text Available The study of spontaneous fluctuations of brain activity, often referred as brain noise, is getting increasing attention in functional magnetic resonance imaging (fMRI studies. Despite important efforts, much of the statistical properties of such fluctuations remain largely unknown. This work scrutinize these fluctuations looking at specific statistical properties which are relevant to clarify its dynamical origins. Here, three statistical features which clearly differentiate brain data from naive expectations for random processes are uncovered: First, the variance of the fMRI mean signal as a function of the number of averaged voxels remains constant across a wide range of observed clusters sizes. Second, the anomalous behavior of the variance is originated by bursts of synchronized activity across regions, regardless of their widely different sizes. Finally, the correlation length (i.e., the length at which the correlation strength between two regions vanishes as well as mutual information diverges with the cluster's size considered, such that arbitrarily large clusters exhibit the same collective dynamics than smaller ones. These three properties are known to be exclusive of complex systems exhibiting critical dynamics, where the spatio-temporal dynamics show these peculiar type of fluctuations. Thus, these findings are fully consistent with previous reports of brain critical dynamics, and are relevant for the interpretation of the role of fluctuations and variability in brain function in health and disease.

  3. Neural correlates of verbal creativity: differences in resting-state functional connectivity associated with expertise in creative writing.

    Science.gov (United States)

    Lotze, Martin; Erhard, Katharina; Neumann, Nicola; Eickhoff, Simon B; Langner, Robert

    2014-01-01

    Neural characteristics of verbal creativity as assessed by word generation tasks have been recently identified, but differences in resting-state functional connectivity (rFC) between experts and non-experts in creative writing have not been reported yet. Previous electroencephalography (EEG) coherence measures during rest demonstrated a decreased cooperation between brain areas in association with creative thinking ability. Here, we used resting-state functional magnetic resonance imaging to compare 20 experts in creative writing and 23 age-matched non-experts with respect to rFC strengths within a brain network previously found to be associated with creative writing. Decreased rFC for experts was found between areas 44 of both hemispheres. Increased rFC for experts was observed between right hemispheric caudate and intraparietal sulcus. Correlation analysis of verbal creativity indices (VCIs) with rFC values in the expert group revealed predominantly negative associations, particularly of rFC between left area 44 and left temporal pole. Overall, our data support previous findings of reduced connectivity between interhemispheric areas and increased right-hemispheric connectivity during rest in highly verbally creative individuals. PMID:25076885

  4. 注意缺陷多动障碍儿童静息态的脑功能磁共振成像研究%Brain function in children with attention-deficit hyperactivity disorder: a resting-state functional magnetic resonance imaging study

    Institute of Scientific and Technical Information of China (English)

    庞高峰; 王苏弘; 任艳玲; 马岭; 华飞; 陈杰; 邢伟; 董选

    2009-01-01

    Objective To investigate the characteristics of brain function in children with attentiondeficit hyperactivity disorder(ADHD)in resting state using functional magnetic resonance imaging(fMRI).Methods Fifteen healty school children and 14 children with ADHD were experienced resting-state fMRI scans,A regional homogeneity (ReHo)approach was used to analyze blood oxygen level-dependent fMRI (BOLD-fMRI)data in resting state.The fMRI data were processed with software SPM2 and REST 1.2.Results Compared with controls.ADHD showed decreased ReHo in bilateral inferior parietal lobule (Z=3.73,Z=3.34),bilateral cuneus(Z=3.42,Z=3.86),left middle frontal gyrus(Z=3.24),left middle temporal gyrus(Z=3.24),left precuneus(Z=3.45),right insula(Z=3.09)and risht cerebellum (Z=3.42),and increased ReHo in the bilateral inferior frontal gyrus(Z=3.19,Z=2.93).Conclusion Compared with the normal controls,children with ADHD children may have abnormal neural activity in several brain regions which are related to execution control,attention and default mode network.%目的 探讨注意缺陷多动障碍(ADHD)儿童静息态脑功能磁共振成像的特点.方法 对15名正常学龄期儿童(对照组)和14例ADHD儿童(ADHD组)进行静息态功能磁共振成像(fMRI)扫描,采用局部一致性(ReHo)作为测最指标.结果 ADHD组在双侧顶下小叶(Z=3.73,Z=3.34)、双侧楔叶(Z=3.42,Z=3.86)、左侧额中回(Z=3.24)、左侧颢中同(Z=3.24)、左侧楔前叶(Z=3.45)及右侧岛叶(Z=3.09)、右侧小脑(Z=3.42)等区域的ReHo值低于对照组,而双侧额下回(Z=3.19,Z=2.93)的ReHo值高于对照组.结论与对照组比较,静息态下ADHD患者与执行控制功能、注意认知功能及默认网络功能等相关区域存在异常.

  5. Default network connectivity decodes brain states with simulated microgravity.

    Science.gov (United States)

    Zeng, Ling-Li; Liao, Yang; Zhou, Zongtan; Shen, Hui; Liu, Yadong; Liu, Xufeng; Hu, Dewen

    2016-04-01

    With great progress of space navigation technology, it becomes possible to travel beyond Earth's gravity. So far, it remains unclear whether the human brain can function normally within an environment of microgravity and confinement. Particularly, it is a challenge to figure out some neuroimaging-based markers for rapid screening diagnosis of disrupted brain function in microgravity environment. In this study, a 7-day -6° head down tilt bed rest experiment was used to simulate the microgravity, and twenty healthy male participants underwent resting-state functional magnetic resonance imaging scans at baseline and after the simulated microgravity experiment. We used a multivariate pattern analysis approach to distinguish the brain states with simulated microgravity from normal gravity based on the functional connectivity within the default network, resulting in an accuracy of no less than 85 % via cross-validation. Moreover, most discriminative functional connections were mainly located between the limbic system and cortical areas and were enhanced after simulated microgravity, implying a self-adaption or compensatory enhancement to fulfill the need of complex demand in spatial navigation and motor control functions in microgravity environment. Overall, the findings suggest that the brain states in microgravity are likely different from those in normal gravity and that brain connectome could act as a biomarker to indicate the brain state in microgravity. PMID:27066149

  6. Resting-state network disruption and APOE genotype in Alzheimer's disease: a lagged functional connectivity study.

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    Leonides Canuet

    Full Text Available BACKGROUND: The apolipoprotein E epsilon 4 (APOE-4 is associated with a genetic vulnerability to Alzheimer's disease (AD and with AD-related abnormalities in cortical rhythms. However, it is unclear whether APOE-4 is linked to a specific pattern of intrinsic functional disintegration of the brain after the development of the disease or during its different stages. This study aimed at identifying spatial patterns and effects of APOE genotype on resting-state oscillations and functional connectivity in patients with AD, using a physiological connectivity index called "lagged phase synchronization". METHODOLOGY/PRINCIPAL FINDINGS: Resting EEG was recorded during awake, eyes-closed state in 125 patients with AD and 60 elderly controls. Source current density and functional connectivity were determined using eLORETA. Patients with AD exhibited reduced parieto-occipital alpha oscillations compared with controls, and those carrying the APOE-4 allele had reduced alpha activity in the left inferior parietal and temporo-occipital cortex relative to noncarriers. There was a decreased alpha2 connectivity pattern in AD, involving the left temporal and bilateral parietal cortex. Several brain regions exhibited increased lagged phase synchronization in low frequencies, specifically in the theta band, across and within hemispheres, where temporal lobe connections were particularly compromised. Areas with abnormal theta connectivity correlated with cognitive scores. In patients with early AD, we found an APOE-4-related decrease in interhemispheric alpha connectivity in frontal and parieto-temporal regions. CONCLUSIONS/SIGNIFICANCE: In addition to regional cortical dysfunction, as indicated by abnormal alpha oscillations, there are patterns of functional network disruption affecting theta and alpha bands in AD that associate with the level of cognitive disturbance or with the APOE genotype. These functional patterns of nonlinear connectivity may potentially

  7. Resting state functional connectivity correlates of inhibitory control in children with Attention-Deficit/Hyperactivity Disorder

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    Maarten eMennes

    2012-01-01

    Full Text Available Motor inhibition is among the most commonly studied executive functions in Attention-Deficit/Hyperactivity Disorder (ADHD. Imaging studies using probes of motor inhibition such as the Stop Signal Task (SST consistently demonstrate ADHD-related dysfunction within a right-hemisphere fronto-striatal network that includes inferior frontal gyrus and pre-supplementary motor area (pre-SMA. Beyond findings of focal hypo- or hyper-function, emerging models of ADHD psychopathology highlight disease-related changes in functional interactions between network components. Resting state fMRI (R-fMRI approaches have emerged as powerful tools for mapping such interactions (i.e., resting state functional connectivity, RSFC, and for relating behavioral and diagnostic variables to network properties. We used R-fMRI data collected from 17 typically developing controls (TDC and 17 age-matched children with ADHD (aged 8-13 years to identify neural correlates of SST performance measured outside the scanner. We examined two related inhibition indices: stop signal reaction time (SSRT, indexing inhibitory speed, and stop signal delay (SSD, indexing inhibitory success. Using 11 fronto-striatal seed regions-of-interest, we queried the brain for relationships between RSFC and each performance index, as well as for interactions with diagnostic status. Both SSRT and SSD exhibited connectivity-behavior relationships independent of diagnosis. At the same time, we found differential connectivity-behavior relationships in children with ADHD relative to TDC. Our results demonstrate the utility of RSFC approaches for assessing brain/behavior relationships, and for identifying pathology-related differences in the contributions of neural circuits to cognition and behavior.

  8. Transient neuronal coactivations embedded in globally propagating waves underlie resting-state functional connectivity.

    Science.gov (United States)

    Matsui, Teppei; Murakami, Tomonari; Ohki, Kenichi

    2016-06-01

    Resting-state functional connectivity (FC), which measures the correlation of spontaneous hemodynamic signals (HemoS) between brain areas, is widely used to study brain networks noninvasively. It is commonly assumed that spatial patterns of HemoS-based FC (Hemo-FC) reflect large-scale dynamics of underlying neuronal activity. To date, studies of spontaneous neuronal activity cataloged heterogeneous types of events ranging from waves of activity spanning the entire neocortex to flash-like activations of a set of anatomically connected cortical areas. However, it remains unclear how these various types of large-scale dynamics are interrelated. More importantly, whether each type of large-scale dynamics contributes to Hemo-FC has not been explored. Here, we addressed these questions by simultaneously monitoring neuronal calcium signals (CaS) and HemoS in the entire neocortex of mice at high spatiotemporal resolution. We found a significant relationship between two seemingly different types of large-scale spontaneous neuronal activity-namely, global waves propagating across the neocortex and transient coactivations among cortical areas sharing high FC. Different sets of cortical areas, sharing high FC within each set, were coactivated at different timings of the propagating global waves, suggesting that spatial information of cortical network characterized by FC was embedded in the phase of the global waves. Furthermore, we confirmed that such transient coactivations in CaS were indeed converted into spatially similar coactivations in HemoS and were necessary to sustain the spatial structure of Hemo-FC. These results explain how global waves of spontaneous neuronal activity propagating across large-scale cortical network contribute to Hemo-FC in the resting state. PMID:27185944

  9. Increased Functional Connectivity Between Subcortical and Cortical Resting-State Networks in Autism Spectrum Disorder

    Science.gov (United States)

    Cerliani, Leonardo; Mennes, Maarten; Thomas, Rajat M.; Di Martino, Adriana; Thioux, Marc; Keysers, Christian

    2016-01-01

    Importance Individuals with autism spectrum disorder (ASD) exhibit severe difficulties in social interaction, motor coordination, behavioral flexibility, and atypical sensory processing, with considerable interindividual variability. This heterogeneous set of symptoms recently led to investigating the presence of abnormalities in the interaction across large-scale brain networks. To date, studies have focused either on constrained sets of brain regions or whole-brain analysis, rather than focusing on the interaction between brain networks. Objectives To compare the intrinsic functional connectivity between brain networks in a large sample of individuals with ASD and typically developing control subjects and to estimate to what extent group differences would predict autistic traits and reflect different developmental trajectories. Design, Setting, and Participants We studied 166 male individuals (mean age, 17.6 years; age range, 7-50 years) diagnosed as having DSM-IV-TR autism or Asperger syndrome and 193 typical developing male individuals (mean age, 16.9 years; age range, 6.5-39.4 years) using resting-state functional magnetic resonance imaging (MRI). Participants were matched for age, IQ, head motion, and eye status (open or closed) in the MRI scanner. We analyzed data from the Autism Brain Imaging Data Exchange (ABIDE), an aggregated MRI data set from 17 centers, made public in August 2012. Main Outcomes and Measures We estimated correlations between time courses of brain networks extracted using a data-driven method (independent component analysis). Subsequently, we associated estimates of interaction strength between networks with age and autistic traits indexed by the Social Responsiveness Scale. Results Relative to typically developing control participants, individuals with ASD showed increased functional connectivity between primary sensory networks and subcortical networks (thalamus and basal ganglia) (all t ≥ 3.13, P < .001 corrected). The strength of

  10. Effective Connectivity within the Default Mode Network: Dynamic Causal Modeling of Resting-State fMRI Data.

    Science.gov (United States)

    Sharaev, Maksim G; Zavyalova, Viktoria V; Ushakov, Vadim L; Kartashov, Sergey I; Velichkovsky, Boris M

    2016-01-01

    The Default Mode Network (DMN) is a brain system that mediates internal modes of cognitive activity, showing higher neural activation when one is at rest. Nowadays, there is a lot of interest in assessing functional interactions between its key regions, but in the majority of studies only association of Blood-oxygen-level dependent (BOLD) activation patterns is measured, so it is impossible to identify causal influences. There are some studies of causal interactions (i.e., effective connectivity), however often with inconsistent results. The aim of the current work is to find a stable pattern of connectivity between four DMN key regions: the medial prefrontal cortex (mPFC), the posterior cingulate cortex (PCC), left and right intraparietal cortex (LIPC and RIPC). For this purpose functional magnetic resonance imaging (fMRI) data from 30 healthy subjects (1000 time points from each one) was acquired and spectral dynamic causal modeling (DCM) on a resting-state fMRI data was performed. The endogenous brain fluctuations were explicitly modeled by Discrete Cosine Set at the low frequency band of 0.0078-0.1 Hz. The best model at the group level is the one where connections from both bilateral IPC to mPFC and PCC are significant and symmetrical in strength (p works on effective connectivity within the DMN as well as provide new insights on internal DMN relationships and brain's functioning at resting state.

  11. Universal Organization of Resting Brain Activity at the Thermodynamic Critical Point

    CERN Document Server

    Yu, Shan; Shriki, Oren; Plenz, Dietmar

    2013-01-01

    Thermodynamic criticality describes emergent phenomena in a wide variety of complex systems. In the mammalian brain, the complex dynamics that spontaneously emerge from neuronal interactions have been characterized as neuronal avalanches, a form of critical branching dynamics. Here, we show that neuronal avalanches also reflect that the brain dynamics are organized close to a thermodynamic critical point. We recorded spontaneous cortical activity in monkeys and humans at rest using high-density intracranial microelectrode arrays and magnetoencephalography, respectively. By numerically changing a control parameter equivalent to thermodynamic temperature, we observed typical critical behavior in cortical activities near the actual physiological condition, including the phase transition of an order parameter, as well as the divergence of susceptibility and specific heat. Finite-size scaling of these quantities allowed us to derive robust critical exponents highly consistent across monkey and humans that uncover ...

  12. Resting state alpha frequency is associated with menstrual cycle phase, estradiol and use of oral contraceptives

    OpenAIRE

    Brötzner, Christina P.; Klimesch, Wolfgang; Doppelmayr, Michael; Zauner, Andrea; Kerschbaum, Hubert H.

    2014-01-01

    Ongoing intrinsic brain activity in resting, but awake humans is dominated by alpha oscillations. In human, individual alpha frequency (IAF) is associated with cognitive performance. Noticeable, performance in cognitive and emotional tasks in women is associated with menstrual cycle phase and sex hormone levels, respectively. In the present study, we correlated frequency of alpha oscillation in resting women with menstrual cycle phase, sex hormone level, or use of oral contraceptives. Electro...

  13. The transliminal brain at rest: baseline EEG, unusual experiences, and access to unconscious mental activity.

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    Fleck, Jessica I; Green, Deborah L; Stevenson, Jennifer L; Payne, Lisa; Bowden, Edward M; Jung-Beeman, Mark; Kounios, John

    2008-01-01

    Transliminality reflects individual differences in the threshold at which unconscious processes or external stimuli enter into consciousness. Individuals high in transliminality possess characteristics such as magical ideation, belief in the paranormal, and creative personality traits, and also report the occurrence of manic/mystic experiences. The goal of the present research was to determine if resting brain activity differs for individuals high versus low in transliminality. We compared baseline EEG recordings (eyes-closed) between individuals high versus low in transliminality, assessed using The Revised Transliminality Scale of Lange et al. (2000). Identifying reliable differences at rest between high- and low-transliminality individuals would support a predisposition for transliminality-related traits. Individuals high in transliminality exhibited lower alpha, beta, and gamma power than individuals low in transliminality over left posterior association cortex and lower high alpha, low beta, and gamma power over the right superior temporal region. In contrast, when compared to individuals low in transliminality, individuals high in transliminality exhibited greater gamma power over the frontal-midline region. These results are consistent with prior research reporting reductions in left temporal/parietal activity, as well as the desynchronization of right temporal activity in schizotypy and related schizophrenia spectrum disorders. Further, differences between high- and low-transliminality groups extend existing theories linking altered hemispheric asymmetries in brain activity to a predisposition toward schizophrenia, paranormal beliefs, and unusual experiences.

  14. The transliminal brain at rest: baseline EEG, unusual experiences, and access to unconscious mental activity.

    Science.gov (United States)

    Fleck, Jessica I; Green, Deborah L; Stevenson, Jennifer L; Payne, Lisa; Bowden, Edward M; Jung-Beeman, Mark; Kounios, John

    2008-01-01

    Transliminality reflects individual differences in the threshold at which unconscious processes or external stimuli enter into consciousness. Individuals high in transliminality possess characteristics such as magical ideation, belief in the paranormal, and creative personality traits, and also report the occurrence of manic/mystic experiences. The goal of the present research was to determine if resting brain activity differs for individuals high versus low in transliminality. We compared baseline EEG recordings (eyes-closed) between individuals high versus low in transliminality, assessed using The Revised Transliminality Scale of Lange et al. (2000). Identifying reliable differences at rest between high- and low-transliminality individuals would support a predisposition for transliminality-related traits. Individuals high in transliminality exhibited lower alpha, beta, and gamma power than individuals low in transliminality over left posterior association cortex and lower high alpha, low beta, and gamma power over the right superior temporal region. In contrast, when compared to individuals low in transliminality, individuals high in transliminality exhibited greater gamma power over the frontal-midline region. These results are consistent with prior research reporting reductions in left temporal/parietal activity, as well as the desynchronization of right temporal activity in schizotypy and related schizophrenia spectrum disorders. Further, differences between high- and low-transliminality groups extend existing theories linking altered hemispheric asymmetries in brain activity to a predisposition toward schizophrenia, paranormal beliefs, and unusual experiences. PMID:18814870

  15. Hypothalamus-Anchored Resting Brain Network Changes before and after Sertraline Treatment in Major Depression

    Directory of Open Access Journals (Sweden)

    Rui Yang

    2014-01-01

    Full Text Available Sertraline, one of the oldest antidepressants, remains to be the most efficacious treatment for depression. However, major depression disorder (MDD is characterized by altered emotion processing and deficits in cognitive control. In cognitive interference tasks, patients with MDD have shown excessive hypothalamus activity. The purpose of this study was to examine the effects of antidepressant treatment (sertraline on hypothalamus-anchored resting brain circuitry. Functional magnetic resonance imaging was conducted on depressed patients (n=12 both before and after antidepressant treatment. After eight weeks of antidepressant treatment, patients with depression showed significantly increased connectivity between the hypothalamus and dorsolateral prefrontal cortex, orbitofrontal cortex, anterior cingulate cortex, insula, putamen, caudate, and claustrum. By contrast, decreased connectivity of the hypothalamus-related areas was primarily located in the inferior frontal gyrus, medial frontal gyrus, cingulated gyrus, precuneus, thalamus, and cerebellum. After eight weeks of antidepressant therapy, 8 out of the 12 depressed subjects achieved 70% reduction or better in depressive symptoms, as measured on the Hamilton depression rating scale. Our findings may infer that antidepressant treatment can alter the functional connectivity of the hypothalamus resting brain to achieve its therapeutic effect.

  16. Common resting brain dynamics indicate a possible mechanism underlying zolpidem response in severe brain injury

    OpenAIRE

    Williams, Shawniqua; Conte, Mary; Goldfine, Andrew; Noirhomme, Quentin; Gosseries, Olivia; Thonnard, Marie; Beattie, Bradley; Hersh, Jennifer; Katz, Douglas; Victor, Jonathan; Laureys, Steven; Schiff, Nicholas

    2013-01-01

    eLife digest Some individuals who experience severe brain damage are left with disorders of consciousness. While they can appear to be awake, these individuals lack awareness of their surroundings and cannot respond to events going on around them. Few treatments are available, but a minority of patients show striking improvements in speech, alertness and movement in response to the sleeping pill zolpidem. Although the idea of a sleeping pill increasing consciousness is paradoxical, it is poss...

  17. Loss of resting-state posterior cingulate flexibility is associated with memory disturbance in left temporal lobe epilepsy.

    Directory of Open Access Journals (Sweden)

    Linda Douw

    Full Text Available The association between cognition and resting-state fMRI (rs-fMRI has been the focus of many recent studies, most of which use stationary connectivity. The dynamics or flexibility of connectivity, however, may be seminal for understanding cognitive functioning. In temporal lobe epilepsy (TLE, stationary connectomic correlates of impaired memory have been reported mainly for the hippocampus and posterior cingulate cortex (PCC. We therefore investigate resting-state and task-based hippocampal and PCC flexibility in addition to stationary connectivity in left TLE (LTLE patients. Sixteen LTLE patients were analyzed with respect to rs-fMRI and task-based fMRI (t-fMRI, and underwent clinical neuropsychological testing. Flexibility of connectivity was calculated using a sliding-window approach by determining the standard deviation of Fisher-transformed Pearson correlation coefficients over all windows. Stationary connectivity was also calculated. Disturbed memory was operationalized as having at least one memory subtest score equal to or below the 5th percentile compared to normative data. Lower PCC flexibility, particularly in the contralateral (i.e. right hemisphere, was found in memory-disturbed LTLE patients, who had up to 22% less flexible connectivity. No significant group differences were found with respect to hippocampal flexibility, stationary connectivity during both rs-fMRI and t-fMRI, or flexibility during t-fMRI. Contralateral resting-state PCC flexibility was able to classify all but one patient with respect to their memory status (94% accuracy. Flexibility of the PCC during rest relates to memory functioning in LTLE patients. Loss of flexible connectivity to the rest of the brain originating from the PCC, particularly contralateral to the seizure focus, is able to discern memory disturbed patients from their preserved counterparts. This study indicates that the dynamics of resting-state connectivity are associated with cognitive status

  18. Gender differences in association between serotonin transporter gene polymorphism and resting-state EEG activity.

    Science.gov (United States)

    Volf, N V; Belousova, L V; Knyazev, G G; Kulikov, A V

    2015-01-22

    Human brain oscillations represent important features of information processing and are highly heritable. Gender has been observed to affect association between the 5-HTTLPR (serotonin-transporter-linked polymorphic region) polymorphism and various endophenotypes. This study aimed to investigate the effects of 5-HTTLPR on the spontaneous electroencephalography (EEG) activity in healthy male and female subjects. DNA samples extracted from buccal swabs and resting EEG recorded at 60 standard leads were collected from 210 (101 men and 109 women) volunteers. Spectral EEG power estimates and cortical sources of EEG activity were investigated. It was shown that effects of 5-HTTLPR polymorphism on electrical activity of the brain vary as a function of gender. Women with the S/L genotype had greater global EEG power compared to men with the same genotype. In men, current source density was markedly different among genotype groups in only alpha 2 and alpha 3 frequency ranges: S/S allele carriers had higher current source density estimates in the left inferior parietal lobule in comparison with the L/L group. In women, genotype difference in global power asymmetry was found in the central-temporal region. Contrasting L/L and S/L genotype carriers also yielded significant effects in the right hemisphere inferior parietal lobule and the right postcentral gyrus with L/L genotype carriers showing lower current source density estimates than S/L genotype carriers in all but gamma bands. So, in women, the effects of 5-HTTLPR polymorphism were associated with modulation of the EEG activity in a wide range of EEG frequencies. The significance of the results lies in the demonstration of gene by sex interaction with resting EEG that has implications for understanding sex-related differences in affective states, emotion and cognition. PMID:25450956

  19. Resting State EEG in Children With Learning Disabilities: An Independent Component Analysis Approach.

    Science.gov (United States)

    Jäncke, Lutz; Alahmadi, Nsreen

    2016-01-01

    In this study, the neurophysiological underpinnings of learning disabilities (LD) in children are examined using resting state EEG. We were particularly interested in the neurophysiological differences between children with learning disabilities not otherwise specified (LD-NOS), learning disabilities with verbal disabilities (LD-Verbal), and healthy control (HC) children. We applied 2 different approaches to examine the differences between the different groups. First, we calculated theta/beta and theta/alpha ratios in order to quantify the relationship between slow and fast EEG oscillations. Second, we used a recently developed method for analyzing spectral EEG, namely the group independent component analysis (gICA) model. Using these measures, we identified substantial differences between LD and HC children and between LD-NOS and LD-Verbal children in terms of their spectral EEG profiles. We obtained the following findings: (a) theta/beta and theta/alpha ratios were substantially larger in LD than in HC children, with no difference between LD-NOS and LD-Verbal children; (b) there was substantial slowing of EEG oscillations, especially for gICs located in frontal scalp positions, with LD-NOS children demonstrating the strongest slowing; (c) the estimated intracortical sources of these gICs were mostly located in brain areas involved in the control of executive functions, attention, planning, and language; and (d) the LD-Verbal children demonstrated substantial differences in EEG oscillations compared with LD-NOS children, and these differences were localized in language-related brain areas. The general pattern of atypical neurophysiological activation found in LD children suggests that they suffer from neurophysiological dysfunction in brain areas involved with the control of attention, executive functions, planning, and language functions. LD-Verbal children also demonstrate atypical activation, especially in language-related brain areas. These atypical

  20. Organizing heterogeneous samples using community detection of GIMME-derived resting state functional networks.

    Directory of Open Access Journals (Sweden)

    Kathleen M Gates

    Full Text Available Clinical investigations of many neuropsychiatric disorders rely on the assumption that diagnostic categories and typical control samples each have within-group homogeneity. However, research using human neuroimaging has revealed that much heterogeneity exists across individuals in both clinical and control samples. This reality necessitates that researchers identify and organize the potentially varied patterns of brain physiology. We introduce an analytical approach for arriving at subgroups of individuals based entirely on their brain physiology. The method begins with Group Iterative Multiple Model Estimation (GIMME to assess individual directed functional connectivity maps. GIMME is one of the only methods to date that can recover both the direction and presence of directed functional connectivity maps in heterogeneous data, making it an ideal place to start since it addresses the problem of heterogeneity. Individuals are then grouped based on similarities in their connectivity patterns using a modularity approach for community detection. Monte Carlo simulations demonstrate that using GIMME in combination with the modularity algorithm works exceptionally well--on average over 97% of simulated individuals are placed in the accurate subgroup with no prior information on functional architecture or group identity. Having demonstrated reliability, we examine resting-state data of fronto-parietal regions drawn from a sample (N = 80 of typically developing and attention-deficit/hyperactivity disorder (ADHD -diagnosed children. Here, we find 5 subgroups. Two subgroups were predominantly comprised of ADHD, suggesting that more than one biological marker exists that can be used to identify children with ADHD based from their brain physiology. Empirical evidence presented here supports notions that heterogeneity exists in brain physiology within ADHD and control samples. This type of information gained from the approach presented here can assist in

  1. Regional homogeneity analysis on acupoint specificity with resting-state functional magnetic resonance imaging

    Institute of Scientific and Technical Information of China (English)

    REN Xiu-jun; CHEN Hong-yan; WANG Bao-guo; ZHAO Bai-xiao; LI Shao-wu; ZHANG Lei; DAI Jian-ping; LIU Xiao-yuan; LUO Fang

    2012-01-01

    Background The mechanism of acupuncture analgesia in craniotomy has been widely studied.However,the theoretical basis for selection of acupoints has not been examined.In this study,we used the regional homogeneity method blood oxygen level-dependent (BOLD) signals to determine changes in brain activity in response to transcutaneous electrical stimulation on acupoints and non-acupoints in resting state functional magnetic resonance imaging (fMRI).Methods Twelve healthy volunteers were enrolled in this study.BOLD fMRI scanning of the brain was performed for 306 seconds before and 30 minutes after transcutaneous electrical stimulation on acupoints UB63 (Jinmen),LV3 (Tai chong),ST36 (Zusanli),and GB40 (Qiuxu).The procedure was repeated after one week with stimulation on non-acupoints (one was 9 above BL67,the second was 12 above BL67 (Kunlun),the third was 7 above Kl3,and the fourth was 10 above Kl3 (Taixi)).Results The regional homogeneity in the acupoint group was increased in the left thalamus,caudate,putamen,lentiform nucleus (BA19,30,39),postcentral gyrus,precentral gyrus (BA3,4,30,32),calcarine fissure,middle temporal gyrus (BA30),right superior temporal gyrus,inferior temporal gyrus (BA38),cuneus,and precuneus (BA7,19) when compared to the non-acupoint group.The regional homogeneity of the acupoint group was decreased in the left cerebellum posterior lobe,middle frontal gyrus (BA10),double-side precuneus (BA7),and the postcentral gyrus (BA40).Conclusions The brain region activated following acupoint stimulation is the ipsilateral pain-related brain region,which may relate to the therapeutic effect of acupuncture on pain relief.Further acupoint stimulation causes different central nervous responses compared to non-acupoint stimulation.

  2. Resting State EEG in Children With Learning Disabilities: An Independent Component Analysis Approach.

    Science.gov (United States)

    Jäncke, Lutz; Alahmadi, Nsreen

    2016-01-01

    In this study, the neurophysiological underpinnings of learning disabilities (LD) in children are examined using resting state EEG. We were particularly interested in the neurophysiological differences between children with learning disabilities not otherwise specified (LD-NOS), learning disabilities with verbal disabilities (LD-Verbal), and healthy control (HC) children. We applied 2 different approaches to examine the differences between the different groups. First, we calculated theta/beta and theta/alpha ratios in order to quantify the relationship between slow and fast EEG oscillations. Second, we used a recently developed method for analyzing spectral EEG, namely the group independent component analysis (gICA) model. Using these measures, we identified substantial differences between LD and HC children and between LD-NOS and LD-Verbal children in terms of their spectral EEG profiles. We obtained the following findings: (a) theta/beta and theta/alpha ratios were substantially larger in LD than in HC children, with no difference between LD-NOS and LD-Verbal children; (b) there was substantial slowing of EEG oscillations, especially for gICs located in frontal scalp positions, with LD-NOS children demonstrating the strongest slowing; (c) the estimated intracortical sources of these gICs were mostly located in brain areas involved in the control of executive functions, attention, planning, and language; and (d) the LD-Verbal children demonstrated substantial differences in EEG oscillations compared with LD-NOS children, and these differences were localized in language-related brain areas. The general pattern of atypical neurophysiological activation found in LD children suggests that they suffer from neurophysiological dysfunction in brain areas involved with the control of attention, executive functions, planning, and language functions. LD-Verbal children also demonstrate atypical activation, especially in language-related brain areas. These atypical

  3. Correlation between Brain Functional Connection with Resting State fMRI and Memory Func-tion in Patients with Temporal Lobe Epilepsy%颞叶癫痫患者 rs-fMRI 功能连接及其与记忆功能关系的研究

    Institute of Scientific and Technical Information of China (English)

    邓艳青; 黄华品; 车春晖; 邓丽霞; 陈琳; 魏笑凡; 孙斌; 林海龙; 林霖

    2015-01-01

    目的:分析颞叶癫痫患者静息态磁共振(rest-fMRI)功能连接及其与记忆功能之间的关系,探讨其脑功能连接的异常及其对记忆障碍诊治的应用价值。方法:对16例颞叶癫痫患者(癫痫组)和与之相匹配的16例健康对照者(对照组)进行静息态脑功能成像和记忆功能测评,比较2组间的脑区差异,分析与记忆功能相关的脑区。结果:癫痫组与对照组比较,海马与全脑功能连接增高的脑区有:左侧旁中央小叶、左侧中央前回、左侧中央后回、左侧前运动皮质和辅助运动区、左侧内侧额叶等;减低的脑区有:右侧小脑、左侧颞上回等。癫痫组海马与全脑功能连接与记忆商呈正相关的脑区有:双侧前扣带回、双侧楔前叶/后扣带回等;呈负相关的脑区有:左侧额下回、左侧中央后回等。结论:左侧旁中央小叶、左侧中央前回、左侧中央后回、左侧前运动皮质和辅助运动区、左侧内侧额叶等脑区可能构成颞叶癫痫患者的癫痫网络,在癫痫发生和发展过程中起重要作用;右侧小脑、左侧颞上回等脑区的功能异常可能与颞叶癫痫患者认知功能损伤有关。双侧前扣带回、双侧楔前叶/后扣带回、左侧额下回、左侧中央后回等脑区与海马之间的功能连接与记忆相关,其对记忆功能具有潜在临床预测价值。%Objective:To analyze the relationship between brain functional connection using resting state fMRI and memory function in patients with temporal lobe epilepsy; To explore the characteristics of connectivity of rest-fM-RI in patients with temporal lobe epilepsy and its value in evaluating the memory impairment. Methods: Rest-fMRI scanning and neuropsychological-scale memory function test were performed in 16 patients with temporal lobe epilepsy and 16 gender, age and educational levels matched normal controls. The difference of brain connectivity

  4. Fractional amplitude analysis of low frequency fluctuation in alcohol dependent individuals: a resting state functional MRI study

    International Nuclear Information System (INIS)

    Objective: To explore brain activity features during the resting state in alcohol dependent individuals, and study the relationship between the brain activity features and alcohol dependent individuals' clinical symptoms. Methods: Twenty-four alcohol dependent individuals and 22 healthy control subjects, well matched in gender, age, education and handedness, were enrolled as the alcohol dependent group and control group respectively. A GE 3.0 T MR scanner was used to acquire all the subjects' resting state data. DPARSF software was used to process resting functional MRI data, and then the whole brain fractional amplitudes of low frequency fluctuation (fALFF) data were acquired. Two-sample t test statistical analysis was made to access fALFF difference between the two groups. Results: In comparison with the control group, the alcohol dependent group showed reduced fALFF in bilateral medial prefrontal gyrus, right inferior occipital gyrus, left precuneus,left inferior temporal gyrus, and left posterior lobe of cerebellum (0.64-1.69 vs. 0.87-1.78, t=-4.23- -2.79, P<0.05). fALFF was increased in the alcohol dependent group at the anterior cingulate,bilateral inferior frontal gyrus,right middle frontal gyrus,bilateral insular lobe,bilateral dorsal thalamus (0.86-1.82 vs. 0.76-1.58, t=3.56-3.96, P<0.05). Conclusion: Alcohol dependent individuals had abnormal activity at the bilateral prefrontal lobe,anterior cingulate, bilateral dorsal thalamus, bilateral insular lobe, left posterior lobe of cerebellum et al, during the resting state, and these abnormal activities might be related with clinical manifestation and pathophysiology. (authors)

  5. Altered resting state neuromotor connectivity in men with chronic prostatitis/chronic pelvic pain syndrome: A MAPP

    Directory of Open Access Journals (Sweden)

    Jason J. Kutch

    2015-01-01

    Full Text Available Brain network activity associated with altered motor control in individuals with chronic pain is not well understood. Chronic Prostatitis/Chronic Pelvic Pain Syndrome (CP/CPPS is a debilitating condition in which previous studies have revealed altered resting pelvic floor muscle activity in men with CP/CPPS compared to healthy controls. We hypothesized that the brain networks controlling pelvic floor muscles would also show altered resting state function in men with CP/CPPS. Here we describe the results of the first test of this hypothesis focusing on the motor cortical regions, termed pelvic-motor, that can directly activate pelvic floor muscles. A group of men with CP/CPPS (N = 28, as well as group of age-matched healthy male controls (N = 27, had resting state functional magnetic resonance imaging scans as part of the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP Research Network study. Brain maps of the functional connectivity of pelvic-motor were compared between groups. A significant group difference was observed in the functional connectivity between pelvic-motor and the right posterior insula. The effect size of this group difference was among the largest effect sizes in functional connectivity between all pairs of 165 anatomically-defined subregions of the brain. Interestingly, many of the atlas region pairs with large effect sizes also involved other subregions of the insular cortices. We conclude that functional connectivity between motor cortex and the posterior insula may be among the most important markers of altered brain function in men with CP/CPPS, and may represent changes in the integration of viscerosensory and motor processing.

  6. The neural correlates of risk propensity in males and females using resting-state fMRI

    Directory of Open Access Journals (Sweden)

    Yuan eZhou

    2014-01-01

    Full Text Available Men are more risk prone than women, but the underlying basis remains unclear. To investigate this question, we developed a trait-like measure of risk propensity which we correlated with resting-state functional connectivity to identify sex differences. Specifically, we used short- and long-range functional connectivity densities to identify associated brain regions and examined their functional connectivities in resting-state functional magnetic resonance imaging (fMRI data collected from a large sample of healthy young volunteers. We found that men had a higher level of general risk propensity (GRP than women. At the neural level, although they shared a common neural correlate of GRP in a network centered at the right inferior frontal gyrus, men and women differed in a network centered at the right secondary somatosensory cortex, which included the bilateral dorsal anterior/middle insular cortices and the dorsal anterior cingulate cortex. In addition, men and women differed in a local network centered at the left inferior orbitofrontal cortex. Most of the regions identified by this resting-state fMRI study have been previously implicated in risk processing when people make risky decisions. This study provides a new perspective on the brain-behavioral relationships in risky decision making and contributes to our understanding of sex differences in risk propensity.

  7. Abnormal gray matter volume and resting-state functional connectivity in former heroin-dependent individuals abstinent for multiple years.

    Science.gov (United States)

    Wang, Lubin; Zou, Feng; Zhai, Tianye; Lei, Yu; Tan, Shuwen; Jin, Xiao; Ye, Enmao; Shao, Yongcong; Yang, Yihong; Yang, Zheng

    2016-05-01

    Previous studies have suggested that heroin addiction is associated with structural and functional brain abnormalities. However, it is largely unknown whether these characteristics of brain abnormalities would be persistent or restored after long periods of abstinence. Considering the very high rates of relapse, we hypothesized that there may exist some latent neural vulnerabilities in abstinent heroin users. In this study, structural and resting-state functional magnetic resonance imaging data were collected from 30 former heroin-dependent (FHD) subjects who were drug free for more than 3 years and 30 non-addicted control (CN) volunteers. Voxel-based morphometry was used to identify possible gray matter volume differences between the FHD and CN groups. Alterations in resting-state functional connectivity in FHD were examined using brain areas with gray matter deficits as seed regions. Significantly reduced gray matter volume was observed in FHD in an area surrounding the parieto-occipital sulcus, which included the precuneus and cuneus. Functional connectivity analyses revealed that the FHD subjects showed reduced positive correlation within the default mode network and visual network and decreased negative correlation between the default mode network, visual network and task positive network. Moreover, the altered functional connectivity was correlated with self-reported impulsivity scores in the FHD subjects. Our findings suggest that disruption of large-scale brain systems is present in former heroin users even after multi-year abstinence, which could serve as system-level neural underpinnings for behavioral dysfunctions associated with addiction. PMID:25727574

  8. Dedifferentiated face processing in older adults is linked to lower resting state metabolic activity in fusiform face area.

    Science.gov (United States)

    Zebrowitz, Leslie; Ward, Noreen; Boshyan, Jasmine; Gutchess, Angela; Hadjikhani, Nouchine

    2016-08-01

    We used multimodal brain imaging to examine possible mediators of age-related neural dedifferentiation (less specific neural activation) to different categories of stimuli that had been shown in previous research. Specifically, we examined resting blood flow and brain activation in areas involved in object, place and face perception. We observed lower activation, specificity, and resting blood flow for older adults (OA) than younger adults (YA) in the fusiform face area (FFA) but not in the other regions of interest. Mediation analyses further revealed that FFA resting state blood flow mediated age differences in FFA specificity, whereas age differences in visual and cognitive function and cortical thickness did not. Whole brain analyses also revealed more activated voxels for all categories in OA, as well as more frontal activation for faces but not for the other categories in OA than YA. Less FFA specificity coupled with more frontal activation when passively viewing faces suggest that OA have more difficulty recruiting specialized face processing mechanisms, and the lower FFA metabolic activity even when faces are not being processed suggests an OA deficiency in the neural substrate underlying face processing. Our data point to a detuning of face-selective mechanisms in older adults. PMID:27163722

  9. Resting-State Functional Connectivity in Patients with Long-Term Remission of Cushing's Disease.

    Science.gov (United States)

    van der Werff, Steven J A; Pannekoek, J Nienke; Andela, Cornelie D; Meijer, Onno C; van Buchem, Mark A; Rombouts, Serge A R B; van der Mast, Roos C; Biermasz, Nienke R; Pereira, Alberto M; van der Wee, Nic J A

    2015-07-01

    Glucocorticoid disturbance can be a cause of psychiatric symptoms. Cushing's disease represents a unique model for examining the effects of prolonged exposure to high levels of endogenous cortisol on the human brain as well as for examining the relation between these effects and psychiatric symptomatology. This study aimed to investigate resting-state functional connectivity (RSFC) of the limbic network, the default mode network (DMN), and the executive control network in patients with long-term remission of Cushing's disease. RSFC of these three networks of interest was compared between patients in remission of Cushing's disease (n=24; 4 male, mean age=44.96 years) and matched healthy controls (n=24; 4 male, mean age=46.5 years), using probabilistic independent component analysis to extract the networks and a dual regression method to compare both groups. Psychological and cognitive functioning was assessed with validated questionnaires and interviews. In comparison with controls, patients with remission of Cushing's disease showed an increased RSFC between the limbic network and the subgenual subregion of the anterior cingulate cortex (ACC) as well as an increased RSFC of the DMN in the left lateral occipital cortex. However, these findings were not associated with psychiatric symptoms in the patient group. Our data indicate that previous exposure to hypercortisolism is related to persisting changes in brain function.

  10. Age related changes in striatal resting state functional connectivity in autism

    Directory of Open Access Journals (Sweden)

    Aarthi ePadmanabhan

    2013-11-01

    Full Text Available Characterizing the nature of developmental change is critical to understanding the mechanisms that are impaired in complex neurodevelopment disorders such as autism spectrum disorder (ASD and, pragmatically, may allow us to pinpoint periods of plasticity when interventions are particularly useful. Although aberrant brain development has long been theorized as a characteristic feature of ASD, the neural substrates have been difficult to characterize, in part due to a lack of developmental data and to performance confounds. To address these issues, we examined the development of intrinsic functional connectivity with resting state fMRI from late childhood to early adulthood (8-36 years, using a seed based functional connectivity method with the striatum. Overall, we found that both groups show decreases in cortico-striatal circuits over age. However, when controlling for age, ASD participants showed increased connectivity with parietal cortex and decreased connectivity with prefrontal cortex relative to TD participants. In addition, ASD participants showed aberrant age-related changes in connectivity with anterior aspects of cerebellum, and posterior temporal regions (e.g. fusiform gyrus, inferior and superior temporal gyri. In sum, we found prominent differences in the development of striatal connectivity in ASD, most notably, atypical development of connectivity in striatal networks that may underlie cognitive and social reward processing. Our findings highlight the need to identify the biological mechanisms of perturbations in brain reorganization over development, which also may help clarify discrepant findings in the literature.

  11. Amplitude of low frequency fluctuations during resting state predicts social well-being.

    Science.gov (United States)

    Kong, Feng; Xue, Song; Wang, Xu

    2016-07-01

    Social well-being represents primarily public phenomena, which is crucial for mental and physical health. However, little is known about the neural basis of this construct, especially how it is maintained during resting state. To explore the neural correlates of social well-being, this study correlated the regional fractional amplitude of low frequency fluctuations (fALFF) with social well-being of healthy individuals. The results revealed that the fALFF in the bilateral posterior superior temporal gyrus (pSTG), right anterior cingulate cortex (ACC), right thalamus and right insula positively predicted individual differences in social well-being. Furthermore, we demonstrated the different role of three pursuits of human well-being (i.e., pleasure, meaning and engagement) in these associations. Specifically, the pursuits of meaning and engagement, not pleasure mediated the effect of the fALFF in right pSTG on social well-being, whereas the pursuit of engagement mediated the effect of the fALFF in right thalamus on social well-being. Taken together, we provide the first evidence that spontaneous brain activity in multiple regions related to self-regulatory and social-cognitive processes contributes to social well-being, suggesting that the spontaneous activity of the human brain reflects the efficiency of social well-being.

  12. Increased resting state functional connectivity in the fronto-parietal and default mode network in anorexia nervosa

    Directory of Open Access Journals (Sweden)

    Ilka eBoehm

    2014-10-01

    Full Text Available The etiology of anorexia nervosa (AN is poorly understood. Results from functional brain imaging studies investigating the neural profile of AN using cognitive and emotional task paradigms are difficult to reconcile. Task-related imaging studies often require a high level of compliance and can only partially explore the distributed nature and complexity of brain function. In this study, resting state functional connectivity imaging was used to investigate well-characterized brain networks potentially relevant to understand the neural mechanisms underlying the symptomatology and etiology of AN. Resting state functional magnetic resonance imaging data was obtained from 35 unmedicated female acute AN patients and 35 closely matched healthy female participants (HC and decomposed using spatial group independent component analyses. Using validated templates, we identified components covering the fronto-parietal control network, the default mode network (DMN, the salience network, the visual and the sensory-motor network. Group comparison revealed an increased functional connectivity between the angular gyrus and the other parts of the fronto-parietal network in patients with AN in comparison to HC. Connectivity of the angular gyrus was positively associated with self-reported persistence in HC. In the DMN, AN patients also showed an increased functional connectivity strength in the anterior insula in comparison to HC. Anterior insula connectivity was associated with self-reported problems with interoceptive awareness. This study, with one of the largest sample to date, shows that acute AN is associated with abnormal brain connectivity in two major resting state networks. The finding of an increased functional connectivity in the fronto-parietal network adds novel support for the notion of AN as a disorder of excessive cognitive control, whereas the elevated functional connectivity of the anterior insula with the DMN may reflect the high levels of self

  13. The resting state fMRI study of patients with Parkinson's disease associated with cognitive dysfunction

    International Nuclear Information System (INIS)

    Parkinson's disease (PD) is the most common neurodegenerative cause of Parkinsonism, but the high morbidity of PD accompanied cognitive dysfunction hasn't drawn enough attention by the clinicians. With the rapid development of the resting state functional MRI (fMRI) technique, the cause of PD patients with cognitive dysfunction may be associated with the damage of functional connectivity of the motor networks and the cognitive networks. The relationship between neuropathologic mechanism of PD patients with cognitive dysfunction and impaired cognitive circuits will be disclosed by building the changes of brain topological structure in patients. The resting state fMRI study can provide the rationale for prevention, diagnosis and treatment of PD. (authors)

  14. Optimal Trajectories of Brain State Transitions

    OpenAIRE

    Gu, Shi; Betzel, Richard F.; Cieslak, Matthew; Delio, Philip R; Grafton, Scott T; Pasqualetti, Fabio; Danielle S Bassett

    2016-01-01

    The complexity of neural dynamics stems in part from the complexity of the underlying anatomy. Yet how the organization of white matter architecture constrains how the brain transitions from one cognitive state to another remains unknown. Here we address this question from a computational perspective by defining a brain state as a pattern of activity across brain regions. Drawing on recent advances in network control theory, we model the underlying mechanisms of brain state transitions as eli...

  15. Posterior cingulated cortex functional connectivity in deficit schizophrenia: a resting state functional magnetic resonance imaging study

    Institute of Scientific and Technical Information of China (English)

    唐小伟

    2014-01-01

    Objective To explore the discrepancies of the network of resting brain functional connectivity related to posterior cingulated cortex(PCC)between deficit schizophrenia patients and normal control.Methods Thirty male patients of deficit schizophrenia,nondeficit schizophrenia and 30 healthy controls were enrolled,and the age,education level and sex were matched between three

  16. Altered regional homogeneity in post-traumatic stress disorder: a resting-state functional magnetic resonance imaging study

    Institute of Scientific and Technical Information of China (English)

    Yan Yin; Baoci Shan; Qiyong Gong; Lingjiang Li; Changfeng Jin; Lisa T.Eyler; Hua Jin; Xiaolei Hu; Lian Duan; Huirong Zheng; Bo Feng; Xuanyin Huang

    2012-01-01

    Objective Little is known about the brain systems that contribute to vulnerability to post-traumatic stress disorder (PTSD).Comparison of the resting-state patterns of intrinsic functional synchronization,as measured by functional magnetic resonance imaging (fMRI),between groups with and without PTSD following a traumatic event can help identify the neural mechanisms of the disorder and targets for intervention.Methods Fifty-four PTSD patients and 72 matched traumatized subjects who experienced the 2008 Sichuan earthquake were imaged with blood oxygen level-dependent (BOLD) fMRI and analyzed using the measure of regional homogeneity (ReHo) during the resting state.Results PTSD patients presented enhanced ReHo in the left inferior parietal lobule and right superior frontal gyrus,and reduced ReHo in the right middle temporal gyrus and lingual gyrus,relative to traumatized individuals without PTSD.Conclusion Our findings showed that abnormal brain activity exists under resting conditions in PTSD patients who had been exposed to a major earthquake.Alterations in the local functional connectivity of cortical regions are likely to contribute to the neural mechanisms underlying PTSD.

  17. Aberrant resting state in microRNA-30e rat model of cognitive impairment.

    Science.gov (United States)

    Xu, Cheng; Liu, Xiaopeng; Song, Xi; Gao, Qiang; Cheng, Long; Wang, Liang; Zhang, Kerang; Xu, Yong

    2016-08-01

    Increasing evidence suggests that microRNA (miRNA)-30e is implicated in the cognitive symptoms of many neuropsychiatric diseases. Our previous studies showed that miRNA-30e is associated with cognitive impairment in schizophrenia and depression. Neuroimaging studies have suggested that cognitive impairment is best characterized as abnormal local activity or a disconnection syndrome. Therefore, we constructed a cognitively impaired overexpressing miRNA-30e rat model for study using functional MRI (fMRI). The model was developed by transfected lentiviral particles carrying the miRNA-30e into the hippocampal dentate gyrus. The Morris water maze and open-field test were used to evaluate cognitive ability. We used the regional homogeneity approach to analyze resting-state fMRI data to explore the changes in regional synchronization. We then used Granger causality analysis to explore connectivity between the hippocampus, striatum, and thalamus. The model group showed higher regional homogeneity in the right hippocampus and striatum. One-way Granger causality connections were observed from the thalamus to the hippocampus in the model group, whereas connections from the thalamus to the striatum were observed in normal rats. After fluoxetine treatment, we found indirect connections between the thalamus and the striatum; we also found connections from the hippocampus to the striatum after Shuganjieyu capsule treatment. Our results support the hypothesis that cognitive impairment is related to disrupted local functionality or aberrant brain connectivity, with antidepressant drugs partially reversing cognitive impairment. The characteristics of resting-state fMRI in miRNA-30e overexpressing rats can provide further evidence for investigating the neural mechanisms of cognitive impairment in mental disorders. Video abstract; Supplemental digital content 1, http://links.lww.com/WNR/A385. PMID:27258654

  18. The time course of task-specific memory consolidation effects in resting state networks.

    Science.gov (United States)

    Sami, Saber; Robertson, Edwin M; Miall, R Chris

    2014-03-12

    Previous studies have reported functionally localized changes in resting-state brain activity following a short period of motor learning, but their relationship with memory consolidation and their dependence on the form of learning is unclear. We investigate these questions with implicit or explicit variants of the serial reaction time task (SRTT). fMRI resting-state functional connectivity was measured in human subjects before the tasks, and 0.1, 0.5, and 6 h after learning. There was significant improvement in procedural skill in both groups, with the group learning under explicit conditions showing stronger initial acquisition, and greater improvement at the 6 h retest. Immediately following acquisition, this group showed enhanced functional connectivity in networks including frontal and cerebellar areas and in the visual cortex. Thirty minutes later, enhanced connectivity was observed between cerebellar nuclei, thalamus, and basal ganglia, whereas at 6 h there was enhanced connectivity in a sensory-motor cortical network. In contrast, immediately after acquisition under implicit conditions, there was increased connectivity in a network including precentral and sensory-motor areas, whereas after 30 min a similar cerebello-thalamo-basal ganglionic network was seen as in explicit learning. Finally, 6 h after implicit learning, we found increased connectivity in medial temporal cortex, but reduction in precentral and sensory-motor areas. Our findings are consistent with predictions that two variants of the SRTT task engage dissociable functional networks, although there are also networks in common. We also show a converging and diverging pattern of flux between prefrontal, sensory-motor, and parietal areas, and subcortical circuits across a 6 h consolidation period. PMID:24623776

  19. Asymmetry in prefrontal resting-state EEG spectral power underlies individual differences in phasic and sustained cognitive control.

    Science.gov (United States)

    Ambrosini, Ettore; Vallesi, Antonino

    2016-01-01

    In our daily life, we constantly exert sustained and phasic cognitive control processes to manage multiple competing task sets and rapidly switch between them. Increasing research efforts are attempting to unveil how the brain mediates these processes, highlighting the importance of the prefrontal cortex. An intriguing question concerns the influence of hemispheric asymmetries and whether it may be generalized to different cognitive domains depending on lateralized processing. Another currently open question concerns the underlying causes of the observed huge inter-individual variability in cognitive control abilities. Here we tackle these issues by investigating whether participants' hemispheric asymmetry in intrinsic (i.e., resting-state-related) brain dynamics can reflect differences in their phasic and/or sustained cognitive control abilities regardless of the cognitive domain. To this aim, we recorded human participants' resting-state electroencephalographic activity and performed a source-based spectral analysis to assess their lateralized brain dynamics at rest. Moreover, we used three task-switching paradigms involving different cognitive domains to assess participants' domain-general phasic and sustained cognitive control abilities. By performing a series of correlations and an intersection analysis, we showed that participants with stronger left- and right-lateralized intrinsic brain activity in the middle frontal gyrus were more able, respectively, to exert phasic and sustained cognitive control. We propose that the variability in participants' prefrontal hemispheric asymmetry in the intrinsic electrophysiological spectral profile reflects individual differences in preferentially engaging either the left-lateralized, phasic or the right-lateralized, sustained cognitive control processes to regulate their behavior in response to changing task demands, regardless of the specific cognitive domain involved. PMID:26416650

  20. A magnetoencephalography analysis of resting state power spectrum of inpatients with major depressive disorder

    Institute of Scientific and Technical Information of China (English)

    汤浩

    2013-01-01

    Objective To explore the discrepancies of magne-toencephalography(MEG) spectral power between female patients with major depressive disorder and nondepressed subjects in resting state. Methods Whole head MEG recordings were obtained in 12 female patients with major

  1. The impact of "physiological correction" on functional connectivity analysis of pharmacological resting state fMRI

    NARCIS (Netherlands)

    Khalili-Mahani, N.; Chang, C.; Osch, M.J.; Veer, I.M.; Buchem, van M.A.; Dahan, A.; Beckmann, C.F.

    2013-01-01

    Growing interest in pharmacological resting state fMRI (RSfMRI) necessitates developing standardized and robust analytical approaches that are insensitive to spurious correlated physiological signals. However, in pharmacological experiments physiological variations constitute an important aspect of

  2. Altered Default Network Resting-State Functional Connectivity in Adolescents with Internet Gaming Addiction

    OpenAIRE

    Ding, Wei-na; Sun, Jin-Hua; Sun, Ya-Wen; Zhou, Yan; Li, Lei; Xu, Jian-Rong; Du, Ya-Song

    2013-01-01

    Purpose Excessive use of the Internet has been linked to a variety of negative psychosocial consequences. This study used resting-state functional magnetic resonance imaging (fMRI) to investigate whether functional connectivity is altered in adolescents with Internet gaming addiction (IGA). Methods Seventeen adolescents with IGA and 24 normal control adolescents underwent a 7.3 minute resting-state fMRI scan. Posterior cingulate cortex (PCC) connectivity was determined in all subjects by inve...

  3. Arterial CO2 Fluctuations Modulate Neuronal Rhythmicity: Implications for MEG and fMRI Studies of Resting-State Networks

    Science.gov (United States)

    Whittaker, Joseph R.; Bright, Molly G.; Muthukumaraswamy, Suresh D.; Murphy, Kevin

    2016-01-01

    A fast emerging technique for studying human resting state networks (RSNs) is based on spontaneous temporal fluctuations in neuronal oscillatory power, as measured by magnetoencephalography. However, it has been demonstrated recently that this power is sensitive to modulations in arterial CO2 concentration. Arterial CO2 can be modulated by natural fluctuations in breathing pattern, as might typically occur during the acquisition of an RSN experiment. Here, we demonstrate for the first time the fine-scale dependence of neuronal oscillatory power on arterial CO2 concentration, showing that reductions in alpha, beta, and gamma power are observed with even very mild levels of hypercapnia (increased arterial CO2). We use a graded hypercapnia paradigm and participant feedback to rule out a sensory cause, suggesting a predominantly physiological origin. Furthermore, we demonstrate that natural fluctuations in arterial CO2, without administration of inspired CO2, are of a sufficient level to influence neuronal oscillatory power significantly in the delta-, alpha-, beta-, and gamma-frequency bands. A more thorough understanding of the relationship between physiological factors and cortical rhythmicity is required. In light of these findings, existing results, paradigms, and analysis techniques for the study of resting-state brain data should be revisited. SIGNIFICANCE STATEMENT In this study, we show for the first time that neuronal oscillatory power is intimately linked to arterial CO2 concentration down to the fine-scale modulations that occur during spontaneous breathing. We extend these results to demonstrate a correlation between neuronal oscillatory power and spontaneous arterial CO2 fluctuations in awake humans at rest. This work identifies a need for studies investigating resting-state networks in the human brain to measure and account for the impact of spontaneous changes in arterial CO2 on the neuronal signals of interest. Changes in breathing pattern that are

  4. Brain imaging studies in children with attention-deficit hyperactivity disorder revealed by resting-state fMRI fALFF analysis%注意缺陷多动障碍儿童静息态功能磁共振比率低频振幅的研究

    Institute of Scientific and Technical Information of China (English)

    杨志龙; 王苏弘; 曹健; 任艳玲; 蔡婧; 张毅力; 马岭; 董选

    2010-01-01

    cerebellum ( t = 4.65,4.83, Z = 4.24,4.38 ). Conclusion The results suggest that lower activition of frontal may be the core deficit of executive control with ADHD in resting state,and high activation in several brain regions may be related to compensatory effect.

  5. Local synchronization of resting-state dynamics encodes Gray's trait Anxiety.

    Science.gov (United States)

    Hahn, Tim; Dresler, Thomas; Pyka, Martin; Notebaert, Karolien; Fallgatter, Andreas J

    2013-01-01

    The Behavioral Inhibition System (BIS) as defined within the Reinforcement Sensitivity Theory (RST) modulates reactions to stimuli indicating aversive events. Gray's trait Anxiety determines the extent to which stimuli activate the BIS. While studies have identified the amygdala-septo-hippocampal circuit as the key-neural substrate of this system in recent years and measures of resting-state dynamics such as randomness and local synchronization of spontaneous BOLD fluctuations have recently been linked to personality traits, the relation between resting-state dynamics and the BIS remains unexplored. In the present study, we thus examined the local synchronization of spontaneous fMRI BOLD fluctuations as measured by Regional Homogeneity (ReHo) in the hippocampus and the amygdala in twenty-seven healthy subjects. Correlation analyses showed that Gray's trait Anxiety was significantly associated with mean ReHo in both the amygdala and the hippocampus. Specifically, Gray's trait Anxiety explained 23% and 17% of resting-state ReHo variance in the left amygdala and the left hippocampus, respectively. In summary, we found individual differences in Gray's trait Anxiety to be associated with ReHo in areas previously associated with BIS functioning. Specifically, higher ReHo in resting-state neural dynamics corresponded to lower sensitivity to punishment scores both in the amygdala and the hippocampus. These findings corroborate and extend recent findings relating resting-state dynamics and personality while providing first evidence linking properties of resting-state fluctuations to Gray's BIS. PMID:23520499

  6. Local synchronization of resting-state dynamics encodes Gray's trait Anxiety.

    Directory of Open Access Journals (Sweden)

    Tim Hahn

    Full Text Available The Behavioral Inhibition System (BIS as defined within the Reinforcement Sensitivity Theory (RST modulates reactions to stimuli indicating aversive events. Gray's trait Anxiety determines the extent to which stimuli activate the BIS. While studies have identified the amygdala-septo-hippocampal circuit as the key-neural substrate of this system in recent years and measures of resting-state dynamics such as randomness and local synchronization of spontaneous BOLD fluctuations have recently been linked to personality traits, the relation between resting-state dynamics and the BIS remains unexplored. In the present study, we thus examined the local synchronization of spontaneous fMRI BOLD fluctuations as measured by Regional Homogeneity (ReHo in the hippocampus and the amygdala in twenty-seven healthy subjects. Correlation analyses showed that Gray's trait Anxiety was significantly associated with mean ReHo in both the amygdala and the hippocampus. Specifically, Gray's trait Anxiety explained 23% and 17% of resting-state ReHo variance in the left amygdala and the left hippocampus, respectively. In summary, we found individual differences in Gray's trait Anxiety to be associated with ReHo in areas previously associated with BIS functioning. Specifically, higher ReHo in resting-state neural dynamics corresponded to lower sensitivity to punishment scores both in the amygdala and the hippocampus. These findings corroborate and extend recent findings relating resting-state dynamics and personality while providing first evidence linking properties of resting-state fluctuations to Gray's BIS.

  7. The impact of "physiological correction" on functional connectivity analysis of pharmacological resting state fMRI.

    Science.gov (United States)

    Khalili-Mahani, Najmeh; Chang, Catie; van Osch, Matthias J; Veer, Ilya M; van Buchem, Mark A; Dahan, Albert; Beckmann, Christian F; van Gerven, Joop M A; Rombouts, Serge A R B

    2013-01-15

    Growing interest in pharmacological resting state fMRI (RSfMRI) necessitates developing standardized and robust analytical approaches that are insensitive to spurious correlated physiological signals. However, in pharmacological experiments physiological variations constitute an important aspect of the pharmacodynamic/pharmacokinetic profile of drug action; therefore retrospective corrective methods that discard physiological signals as noise may not be suitable. Previously, we have shown that template-based dual regression analysis is a sensitive method for model-free and objective detection of drug-specific effects on functional brain connectivity. In the current study, the robustness of this standard approach to physiological variations in a placebo controlled, repeated measures pharmacological RSfMRI study of morphine and alcohol in 12 healthy young men is tested. The impact of physiology-related variations on statistical inferences has been studied by: 1) modeling average physiological rates in higher level group analysis; 2) Regressing out the instantaneous respiration variation (RV); 3) applying retrospective image correction (RETROICOR) in the preprocessing stage; and 4) performing combined RV and heart rate correction (RVHRCOR) by regressing out physiological pulses convolved with canonical respiratory and cardiac hemodynamic response functions. Results indicate regional sensitivity of the BOLD signal to physiological variations, especially in the vicinity of large vessels, plus certain brain structures that are reported to be involved in physiological regulation, such as posterior cingulate, precuneus, medial prefrontal and insular cortices, as well as the thalamus, cerebellum and the brainstem. The largest impact of "correction" on final statistical test outcomes resulted from including the average respiration frequency and heart rate in the higher-level group analysis. Overall, the template-based dual regression method seems robust against physical

  8. Reduced resting state functional connectivity of the somatosensory cortex predicts psychopathological symptoms in women with bulimia nervosa

    Directory of Open Access Journals (Sweden)

    Luca eLavagnino

    2014-08-01

    Full Text Available BackgroundAlterations in the resting state functional connectivity (rs-FC of several brain networks have been demonstrated in eating disorders. However, very few studies are currently available on brain network dysfunctions in bulimia nervosa (BN. The somatosensory network is central in processing body-related stimuli and it may be altered in BN. The present study therefore aimed to investigate rs-FC in the somatosensory network in bulimic women. MethodsSixteen medication-free women with BN (age=23±5 years and 18 matched controls (age=23±3 years underwent a functional magnetic resonance resting state scan and assessment of eating disorder symptoms. Within-network and seed-based functional connectivity analyses were conducted to assess rs-FC within the somatosensory network and to other areas of the brain. ResultsBN patients showed a decreased resting state functional connectivity both within the somatosensory network (t=9.0, df=1, P=0.005 and with posterior cingulate cortex (PCC and two visual areas (the right middle occipital gyrus and the right cuneus(P=0.05 corrected for multiple comparison. The region in the right middle occipital gyrus is implicated in body processing and is known as extrastriate body area, or EBA. The rs-FC of the left paracentral lobule with the EBA correlated with psychopathology measures like bulimia (r=-0.4; P=0.02 and interoceptive awareness (r=-0.4; P=0.01. Analyses were conducted using age, BMI (body mass index and depressive symptoms as covariates. ConclusionsOur findings show a specific alteration of the rs-FC of the somatosensory cortex in BN patients, which correlates with eating disorder symptoms. The connectivity between the somatosensory cortex and the EBA might be related to dysfunctions in body image processing. The results should be considered preliminary due to the small sample size.

  9. State and Training Effects of Mindfulness Meditation on Brain Networks Reflect Neuronal Mechanisms of Its Antidepressant Effect

    OpenAIRE

    Chuan-Chih Yang; Alfonso Barrós-Loscertales; Daniel Pinazo; Noelia Ventura-Campos; Viola Borchardt; Juan-Carlos Bustamante; Aina Rodríguez-Pujadas; Paola Fuentes-Claramonte; Raúl Balaguer; César Ávila; Martin Walter

    2016-01-01

    The topic of investigating how mindfulness meditation training can have antidepressant effects via plastic changes in both resting state and meditation state brain activity is important in the rapidly emerging field of neuroplasticity. In the present study, we used a longitudinal design investigating resting state fMRI both before and after 40 days of meditation training in 13 novices. After training, we compared differences in network connectivity between rest and meditation using common res...

  10. Dynamic changes of ICA-derived EEG functional connectivity in the resting state.

    Science.gov (United States)

    Chen, Jean-Lon; Ros, Tomas; Gruzelier, John H

    2013-04-01

    An emerging issue in neuroscience is how to identify baseline state(s) and accompanying networks termed "resting state networks" (RSNs). Although independent component analysis (ICA) in fMRI studies has elucidated synchronous spatiotemporal patterns during cognitive tasks, less is known about the changes in EEG functional connectivity between eyes closed (EC) and eyes open (EO) states, two traditionally used baseline indices. Here we investigated healthy subjects (n = 27) in EC and EO employing a four-step analytic approach to the EEG: (1) group ICA to extract independent components (ICs), (2) standardized low-resolution tomography analysis (sLORETA) for cortical source localization of IC network nodes, followed by (3) graph theory for functional connectivity estimation of epochwise IC band-power, and (4) circumscribing IC similarity measures via hierarchical cluster analysis and multidimensional scaling (MDS). Our proof-of-concept results on alpha-band power demonstrate five statistically clustered groups with frontal, central, parietal, occipitotemporal, and occipital sources. Importantly, during EO compared with EC, graph analyses revealed two salient functional networks with frontoparietal connectivity: a more medial network with nodes in the mPFC/precuneus which overlaps with the "default-mode network" (DMN), and a more lateralized network comprising the middle frontal gyrus and inferior parietal lobule, coinciding with the "dorsal attention network" (DAN). Furthermore, a separate MDS analysis of ICs supported the emergence of a pattern of increased proximity (shared information) between frontal and parietal clusters specifically for the EO state. We propose that the disclosed component groups and their source-derived EEG functional connectivity maps may be a valuable method for elucidating direct neuronal (electrophysiological) RSNs in healthy people and those suffering from brain disorders. PMID:22344782

  11. Individual differences in brain structure and resting brain function underlie cognitive styles: evidence from the Embedded Figures Test.

    Directory of Open Access Journals (Sweden)

    Xin Hao

    Full Text Available Cognitive styles can be characterized as individual differences in the way people perceive, think, solve problems, learn, and relate to others. Field dependence/independence (FDI is an important and widely studied dimension of cognitive styles. Although functional imaging studies have investigated the brain activation of FDI cognitive styles, the combined structural and functional correlates with individual differences in a large sample have never been investigated. In the present study, we investigated the neural correlates of individual differences in FDI cognitive styles by analyzing the correlations between Embedded Figures Test (EFT score and structural neuroimaging data [regional gray matter volume (rGMV was assessed using voxel-based morphometry (VBM]/functional neuroimaging data [resting-brain functions were measured by amplitude of low-frequency fluctuation (ALFF] throughout the whole brain. Results showed that the increased rGMV in the left inferior parietal lobule (IPL was associated with the EFT score, which might be the structural basis of effective local processing. Additionally, a significant positive correlation between ALFF and EFT score was found in the fronto-parietal network, including the left inferior parietal lobule (IPL and the medial prefrontal cortex (mPFC. We speculated that the left IPL might be associated with superior feature identification, and mPFC might be related to cognitive inhibition of global processing bias. These results suggested that the underlying neuroanatomical and functional bases were linked to the individual differences in FDI cognitive styles and emphasized the important contribution of superior local processing ability and cognitive inhibition to field-independent style.

  12. Normalization of aberrant resting state functional connectivity in fibromyalgia patients following a three month physical exercise therapy.

    Science.gov (United States)

    Flodin, P; Martinsen, S; Mannerkorpi, K; Löfgren, M; Bileviciute-Ljungar, I; Kosek, E; Fransson, P

    2015-01-01

    Physical exercise is one of the most efficient interventions to mitigate chronic pain symptoms in fibromyalgia (FM). However, little is known about the neurophysiological mechanisms mediating these effects. In this study we investigated resting-state connectivity using functional magnetic resonance imaging (fMRI) before and after a 15 week standardized exercise program supervised by physical therapists. Our aim was to gain an understanding of how physical exercise influences previously shown aberrant patterns of intrinsic brain activity in FM. Fourteen FM patients and eleven healthy controls successfully completed the physical exercise treatment. We investigated post- versus pre-treatment changes of brain connectivity, as well as changes in clinical symptoms in the patient group. FM patients reported improvements in symptom severity. Although several brain regions showed a treatment-related change in connectivity, only the connectivity between the right anterior insula and the left primary sensorimotor area was significantly more affected by the physical exercise among the fibromyalgia patients compared to healthy controls. Our results suggest that previously observed aberrant intrinsic brain connectivity patterns in FM are partly normalized by the physical exercise therapy. However, none of the observed normalizations in intrinsic brain connectivity were significantly correlated with symptom changes. Further studies conducted in larger cohorts are warranted to investigate the precise relationship between improvements in fibromyalgia symptoms and changes in intrinsic brain activity.

  13. Normalization of aberrant resting state functional connectivity in fibromyalgia patients following a three month physical exercise therapy

    Directory of Open Access Journals (Sweden)

    P. Flodin

    2015-01-01

    Full Text Available Physical exercise is one of the most efficient interventions to mitigate chronic pain symptoms in fibromyalgia (FM. However, little is known about the neurophysiological mechanisms mediating these effects. In this study we investigated resting-state connectivity using functional magnetic resonance imaging (fMRI before and after a 15 week standardized exercise program supervised by physical therapists. Our aim was to gain an understanding of how physical exercise influences previously shown aberrant patterns of intrinsic brain activity in FM. Fourteen FM patients and eleven healthy controls successfully completed the physical exercise treatment. We investigated post- versus pre-treatment changes of brain connectivity, as well as changes in clinical symptoms in the patient group. FM patients reported improvements in symptom severity. Although several brain regions showed a treatment-related change in connectivity, only the connectivity between the right anterior insula and the left primary sensorimotor area was significantly more affected by the physical exercise among the fibromyalgia patients compared to healthy controls. Our results suggest that previously observed aberrant intrinsic brain connectivity patterns in FM are partly normalized by the physical exercise therapy. However, none of the observed normalizations in intrinsic brain connectivity were significantly correlated with symptom changes. Further studies conducted in larger cohorts are warranted to investigate the precise relationship between improvements in fibromyalgia symptoms and changes in intrinsic brain activity.

  14. Increased Brain Activation for Dual Tasking with 70-Days Head-Down Bed Rest

    Science.gov (United States)

    Yuan, Peng; Koppelmans, Vincent; Reuter-Lorenz, Patricia A.; De Dios, Yiri E.; Gadd, Nichole E.; Wood, Scott J.; Riascos, Roy; Kofman, Igor S.; Bloomberg, Jacob J.; Mulavara, Ajitkumar P.; Seidler, Rachael D.

    2016-01-01

    Head-down tilt bed rest (HDBR) has been used as a spaceflight analog to simulate the effects of microgravity exposure on human physiology, sensorimotor function, and cognition on Earth. Previous studies have reported that concurrent performance of motor and cognitive tasks can be impaired during space missions. Understanding the consequences of HDBR for neural control of dual tasking may possibly provide insight into neural efficiency during spaceflight. In the current study, we evaluated how dual task performance and the underlying brain activation changed as a function of HDBR. Eighteen healthy men participated in this study. They remained continuously in the 6° head-down tilt position for 70 days. Functional MRI for bimanual finger tapping was acquired during both single task and dual task conditions, and repeated at 7 time points pre-, during- and post-HDBR. Another 12 healthy males participated as controls who did not undergo HDBR. A widely distributed network involving the frontal, parietal, cingulate, temporal, and occipital cortices exhibited increased activation for dual tasking and increased activation differences between dual and single task conditions during HDBR relative to pre- or post-HDBR. This HDBR-related brain activation increase for dual tasking implies that more neurocognitive control is needed for dual task execution during HDBR compared to pre- and post-HDBR. We observed a positive correlation between pre-to-post HDBR changes in dual-task cost of reaction time and pre-to-post HDBR change in dual-task cost of brain activation in several cerebral and cerebellar regions. These findings could be predictive of changes in dual task processing during spaceflight. PMID:27601982

  15. Increased Brain Activation for Dual Tasking with 70-Days Head-Down Bed Rest.

    Science.gov (United States)

    Yuan, Peng; Koppelmans, Vincent; Reuter-Lorenz, Patricia A; De Dios, Yiri E; Gadd, Nichole E; Wood, Scott J; Riascos, Roy; Kofman, Igor S; Bloomberg, Jacob J; Mulavara, Ajitkumar P; Seidler, Rachael D

    2016-01-01

    Head-down tilt bed rest (HDBR) has been used as a spaceflight analog to simulate the effects of microgravity exposure on human physiology, sensorimotor function, and cognition on Earth. Previous studies have reported that concurrent performance of motor and cognitive tasks can be impaired during space missions. Understanding the consequences of HDBR for neural control of dual tasking may possibly provide insight into neural efficiency during spaceflight. In the current study, we evaluated how dual task performance and the underlying brain activation changed as a function of HDBR. Eighteen healthy men participated in this study. They remained continuously in the 6° head-down tilt position for 70 days. Functional MRI for bimanual finger tapping was acquired during both single task and dual task conditions, and repeated at 7 time points pre-, during- and post-HDBR. Another 12 healthy males participated as controls who did not undergo HDBR. A widely distributed network involving the frontal, parietal, cingulate, temporal, and occipital cortices exhibited increased activation for dual tasking and increased activation differences between dual and single task conditions during HDBR relative to pre- or post-HDBR. This HDBR-related brain activation increase for dual tasking implies that more neurocognitive control is needed for dual task execution during HDBR compared to pre- and post-HDBR. We observed a positive correlation between pre-to-post HDBR changes in dual-task cost of reaction time and pre-to-post HDBR change in dual-task cost of brain activation in several cerebral and cerebellar regions. These findings could be predictive of changes in dual task processing during spaceflight. PMID:27601982

  16. Functional network connectivity of pain-related resting state networks in somatoform pain disorder: an exploratory fMRI study

    Science.gov (United States)

    Otti, Alexander; Guendel, Harald; Henningsen, Peter; Zimmer, Claus; Wohlschlaeger, Afra M.; Noll-Hussong, Michael

    2013-01-01

    Background Without stimulation, the human brain spontaneously produces highly organized, low-frequency fluctuations of neural activity in intrinsic connectivity networks (ICNs). Furthermore, without adequate explanatory nociceptive input, patients with somatoform pain disorder experience pain symptoms, thus implicating a central dysregulation of pain homeostasis. The present study aimed to test whether interactions among pain-related ICNs, such as the default mode network (DMN), cingular–insular network (CIN) and sensorimotor network (SMN), are altered in somatoform pain during resting conditions. Methods Patients with somatoform pain disorder and healthy controls underwent resting functional magnetic resonance imaging that lasted 370 seconds. Using a data-driven approach, the ICNs were isolated, and the functional network connectivity (FNC) was computed. Results Twenty-one patients and 19 controls enrolled in the study. Significant FNC (p < 0.05, corrected for false discovery rate) was detected between the CIN and SMN/anterior DMN, the anterior DMN and posterior DMN/SMN, and the posterior DMN and SMN. Interestingly, no group differences in FNC were detected. Limitations The most important limitation of this study was the relatively short resting state paradigm. Conclusion To our knowledge, our results demonstrated for the first time the resting FNC among pain-related ICNs. However, our results suggest that FNC signatures alone are not able to characterize the putative central dysfunction underpinning somatoform pain disorder. PMID:22894821

  17. Resting and reactive frontal brain electrical activity (EEG among a non-clinical sample of socially anxious adults: Does concurrent depressive mood matter?

    Directory of Open Access Journals (Sweden)

    Elliott A Beaton

    2008-03-01

    Full Text Available Elliott A Beaton1, Louis A Schmidt2, Andrea R Ashbaugh2,5, Diane L Santesso2, Martin M Antony1,3,4, Randi E McCabe1,31Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada; 2Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, Ontario, Canada; 3Anxiety Treatment and Research Centre, St. Joseph’s Healthcare, Hamilton, Ontario, Canada; 4Department of Psychology, Ryerson University, Toronto, Ontario, Canada; 5Concordia University, Montreal, Quebec, CanadaAbstract: A number of studies have noted that the pattern of resting frontal brain electrical activity (EEG is related to individual differences in affective style in healthy infants, children, and adults and some clinical populations when symptoms are reduced or in remission. We measured self-reported trait shyness and sociability, concurrent depressive mood, and frontal brain electrical activity (EEG at rest and in anticipation of a speech task in a non-clinical sample of healthy young adults selected for high and low social anxiety. Although the patterns of resting and reactive frontal EEG asymmetry did not distinguish among individual differences in social anxiety, the pattern of resting frontal EEG asymmetry was related to trait shyness after controlling for concurrent depressive mood. Individuals who reported a higher degree of shyness were likely to exhibit greater relative right frontal EEG activity at rest. However, trait shyness was not related to frontal EEG asymmetry measured during the speech-preparation task, even after controlling for concurrent depressive mood. These findings replicate and extend prior work on resting frontal EEG asymmetry and individual differences in affective style in adults. Findings also highlight the importance of considering concurrent emotional states of participants when examining psychophysiological correlates of personality.Keywords: social anxiety, shyness, sociability

  18. Ketamine Decreases Resting State Functional Network Connectivity in Healthy Subjects: Implications for Antidepressant Drug Action

    Science.gov (United States)

    Walter, Martin; Lehmann, Mick; Metzger, Coraline; Grimm, Simone; Boeker, Heinz; Boesiger, Peter; Henning, Anke; Seifritz, Erich

    2012-01-01

    Increasing preclinical and clinical evidence underscores the strong and rapid antidepressant properties of the glutamate-modulating NMDA receptor antagonist ketamine. Targeting the glutamatergic system might thus provide a novel molecular strategy for antidepressant treatment. Since glutamate is the most abundant and major excitatory neurotransmitter in the brain, pathophysiological changes in glutamatergic signaling are likely to affect neurobehavioral plasticity, information processing and large-scale changes in functional brain connectivity underlying certain symptoms of major depressive disorder. Using resting state functional magnetic resonance imaging (rsfMRI), the „dorsal nexus “(DN) was recently identified as a bilateral dorsal medial prefrontal cortex region showing dramatically increased depression-associated functional connectivity with large portions of a cognitive control network (CCN), the default mode network (DMN), and a rostral affective network (AN). Hence, Sheline and colleagues (2010) proposed that reducing increased connectivity of the DN might play a critical role in reducing depression symptomatology and thus represent a potential therapy target for affective disorders. Here, using a randomized, placebo-controlled, double-blind, crossover rsfMRI challenge in healthy subjects we demonstrate that ketamine decreases functional connectivity of the DMN to the DN and to the pregenual anterior cingulate (PACC) and medioprefrontal cortex (MPFC) via its representative hub, the posterior cingulate cortex (PCC). These findings in healthy subjects may serve as a model to elucidate potential biomechanisms that are addressed by successful treatment of major depression. This notion is further supported by the temporal overlap of our observation of subacute functional network modulation after 24 hours with the peak of efficacy following an intravenous ketamine administration in treatment-resistant depression. PMID:23049758

  19. Ketamine decreases resting state functional network connectivity in healthy subjects: implications for antidepressant drug action.

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    Milan Scheidegger

    Full Text Available Increasing preclinical and clinical evidence underscores the strong and rapid antidepressant properties of the glutamate-modulating NMDA receptor antagonist ketamine. Targeting the glutamatergic system might thus provide a novel molecular strategy for antidepressant treatment. Since glutamate is the most abundant and major excitatory neurotransmitter in the brain, pathophysiological changes in glutamatergic signaling are likely to affect neurobehavioral plasticity, information processing and large-scale changes in functional brain connectivity underlying certain symptoms of major depressive disorder. Using resting state functional magnetic resonance imaging (rsfMRI, the "dorsal nexus "(DN was recently identified as a bilateral dorsal medial prefrontal cortex region showing dramatically increased depression-associated functional connectivity with large portions of a cognitive control network (CCN, the default mode network (DMN, and a rostral affective network (AN. Hence, Sheline and colleagues (2010 proposed that reducing increased connectivity of the DN might play a critical role in reducing depression symptomatology and thus represent a potential therapy target for affective disorders. Here, using a randomized, placebo-controlled, double-blind, crossover rsfMRI challenge in healthy subjects we demonstrate that ketamine decreases functional connectivity of the DMN to the DN and to the pregenual anterior cingulate (PACC and medioprefrontal cortex (MPFC via its representative hub, the posterior cingulate cortex (PCC. These findings in healthy subjects may serve as a model to elucidate potential biomechanisms that are addressed by successful treatment of major depression. This notion is further supported by the temporal overlap of our observation of subacute functional network modulation after 24 hours with the peak of efficacy following an intravenous ketamine administration in treatment-resistant depression.

  20. Abnormal amygdala connectivity in patients with primary insomnia: Evidence from resting state fMRI

    International Nuclear Information System (INIS)

    Background: Neurobiological mechanisms underlying insomnia are poorly understood. Previous findings indicated that dysfunction of the emotional circuit might contribute to the neurobiological mechanisms underlying insomnia. The present study will test this hypothesis by examining alterations in functional connectivity of the amygdala in patients with primary insomnia (PI). Methods: Resting-state functional connectivity analysis was used to examine the temporal correlation between the amygdala and whole-brain regions in 10 medication-naive PI patients and 10 age- and sex-matched healthy controls. Additionally, the relationship between the abnormal functional connectivity and insomnia severity was investigated. Results: We found decreased functional connectivity mainly between the amygdala and insula, striatum and thalamus, and increased functional connectivity mainly between the amygdala and premotor cortex, sensorimotor cortex in PI patients as compared to healthy controls. The connectivity of the amygdala with the premotor cortex in PI patients showed significant positive correlation with the total score of the Pittsburgh Sleep Quality Index (PSQI). Conclusions: The decreased functional connectivity between the amygdala and insula, striatum, and thalamus suggests that dysfunction in the emotional circuit might contribute to the neurobiological mechanisms underlying PI. The increased functional connectivity of the amygdala with the premotor and sensorimotor cortex demonstrates a compensatory mechanism to overcome the negative effects of sleep deficits and maintain the psychomotor performances in PI patients.

  1. Resting state BOLD functional connectivity at 3T: spin echo versus gradient echo EPI.

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    Piero Chiacchiaretta

    Full Text Available Previous evidence showed that, due to refocusing of static dephasing effects around large vessels, spin-echo (SE BOLD signals offer an increased linearity and promptness with respect to gradient-echo (GE acquisition, even at low field. These characteristics suggest that, despite the reduced sensitivity, SE fMRI might also provide a potential benefit when investigating spontaneous fluctuations of brain activity. However, there are no reports on the application of spin-echo fMRI for connectivity studies at low field. In this study we compared resting state functional connectivity as measured with GE and SE EPI sequences at 3T. Main results showed that, within subject, the GE sensitivity is overall larger with respect to that of SE, but to a less extent than previously reported for activation studies. Noteworthy, the reduced sensitivity of SE was counterbalanced by a reduced inter-subject variability, resulting in comparable group statistical connectivity maps for the two sequences. Furthermore, the SE method performed better in the ventral portion of the default mode network, a region affected by signal dropout in standard GE acquisition. Future studies should clarify if these features of the SE BOLD signal can be beneficial to distinguish subtle variations of functional connectivity across different populations and/or treatments when vascular confounds or regions affected by signal dropout can be a critical issue.

  2. Resting-state functional connectivity patterns predict Chinese word reading competency.

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    Xiaosha Wang

    Full Text Available Resting-state functional connectivity (RSFC offers a novel approach to reveal the temporal synchronization of functionally related brain regions. Recent studies have identified several RSFCs whose strength was associated with reading competence in alphabetic languages. In the present study, we examined the role of intrinsic functional relations for reading a non-alphabetic language--Chinese--by correlating RSFC maps of nine Chinese reading-related seed regions and reaction time in the single-character reading task. We found that Chinese reading efficiency was positively correlated with the connection between left inferior occipital gyrus and left superior parietal lobule, between right posterior fusiform gyrus and right superior parietal lobule, and between left inferior temporal gyrus and left inferior parietal lobule. These results could not be attributed to inter-individual differences arising from the peripheral processes of the reading task such as visual input detection and articulation. The observed RSFC-reading correlation relationships are discussed in the framework of Chinese character reading, including visuospatial analyses and semantic/phonological processes.

  3. Effective Preprocessing Procedures Virtually Eliminate Distance-Dependent Motion Artifacts in Resting State FMRI

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    Hang Joon Jo

    2013-01-01

    Full Text Available Artifactual sources of resting-state (RS FMRI can originate from head motion, physiology, and hardware. Of these sources, motion has received considerable attention and was found to induce corrupting effects by differentially biasing correlations between regions depending on their distance. Numerous corrective approaches have relied on the identification and censoring of high-motion time points and the use of the brain-wide average time series as a nuisance regressor to which the data are orthogonalized (Global Signal Regression, GSReg. We replicate the previously reported head-motion bias on correlation coefficients and then show that while motion can be the source of artifact in correlations, the distance-dependent bias is exacerbated by GSReg. Put differently, correlation estimates obtained after GSReg are more susceptible to the presence of motion and by extension to the levels of censoring. More generally, the effect of motion on correlation estimates depends on the preprocessing steps leading to the correlation estimate, with certain approaches performing markedly worse than others. For this purpose, we consider various models for RS FMRI preprocessing and show that the local white matter regressor (WMeLOCAL, a subset of ANATICOR, results in minimal sensitivity to motion and reduces by extension the dependence of correlation results on censoring.

  4. Effective Preprocessing Procedures Virtually Eliminate Distance-Dependent Motion Artifacts in Resting State FMRI.

    Science.gov (United States)

    Jo, Hang Joon; Gotts, Stephen J; Reynolds, Richard C; Bandettini, Peter A; Martin, Alex; Cox, Robert W; Saad, Ziad S

    2013-05-21

    Artifactual sources of resting-state (RS) FMRI can originate from head motion, physiology, and hardware. Of these sources, motion has received considerable attention and was found to induce corrupting effects by differentially biasing correlations between regions depending on their distance. Numerous corrective approaches have relied on the identification and censoring of high-motion time points and the use of the brain-wide average time series as a nuisance regressor to which the data are orthogonalized (Global Signal Regression, GSReg). We first replicate the previously reported head-motion bias on correlation coefficients using data generously contributed by Power et al. (2012). We then show that while motion can be the source of artifact in correlations, the distance-dependent bias-taken to be a manifestation of the motion effect on correlation-is exacerbated by the use of GSReg. Put differently, correlation estimates obtained after GSReg are more susceptible to the presence of motion and by extension to the levels of censoring. More generally, the effect of motion on correlation estimates depends on the preprocessing steps leading to the correlation estimate, with certain approaches performing markedly worse than others. For this purpose, we consider various models for RS FMRI preprocessing and show that WMeLOCAL, as subset of the ANATICOR discussed by Jo et al. (2010), denoising approach results in minimal sensitivity to motion and reduces by extension the dependence of correlation results on censoring.

  5. Aberrant Resting-State Functional Connectivity in the Salience Network of Adolescent Chronic Fatigue Syndrome

    Science.gov (United States)

    Endestad, Tor; Melinder, Annika Maria D.; Øie, Merete Glenne; Sevenius, Andre; Bruun Wyller, Vegard

    2016-01-01

    Neural network investigations are currently absent in adolescent chronic fatigue syndrome (CFS). In this study, we examine whether the core intrinsic connectivity networks (ICNs) are altered in adolescent CFS patients. Eighteen adolescent patients with CFS and 18 aged matched healthy adolescent control subjects underwent resting-state functional magnetic resonance imaging (rfMRI). Data was analyzed using dual-regression independent components analysis, which is a data-driven approach for the identification of independent brain networks. Intrinsic connectivity was evaluated in the default mode network (DMN), salience network (SN), and central executive network (CEN). Associations between network characteristics and symptoms of CFS were also explored. Adolescent CFS patients displayed a significant decrease in SN functional connectivity to the right posterior insula compared to healthy comparison participants, which was related to fatigue symptoms. Additionally, there was an association between pain intensity and SN functional connectivity to the left middle insula and caudate that differed between adolescent patients and healthy comparison participants. Our findings of insula dysfunction and its association with fatigue severity and pain intensity in adolescent CFS demonstrate an aberration of the salience network which might play a role in CFS pathophysiology. PMID:27414048

  6. Network complexity as a measure of information processing across resting-state networks: Evidence from the Human Connectome Project

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    Ian M Mcdonough

    2014-06-01

    Full Text Available An emerging field of research focused on fluctuations in brain signals has provided evidence that the complexity of those signals, as measured by entropy, conveys important information about network dynamics (e.g., local and distributed processing. While much research has focused on how neural complexity differs in populations with different age groups or clinical disorders, substantially less research has focused on the basic understanding of neural complexity in populations with young and healthy brain states. The present study used resting-state fMRI data from the Human Connectome Project (Van Essen et al., 2013 to test the extent that neural complexity in the BOLD signal, as measured by multiscale entropy 1 would differ from random noise, 2 would differ between four major resting-state networks previously associated with higher-order cognition, and 3 would be associated with the strength and extent of functional connectivity—a complementary method of estimating information processing. We found that complexity in the BOLD signal exhibited different patterns of complexity from white, pink, and red noise and that neural complexity was differentially expressed between resting-state networks, including the default mode, cingulo-opercular, left and right frontoparietal networks. Lastly, neural complexity across all networks was negatively associated with functional connectivity at fine scales, but was positively associated with functional connectivity at coarse scales. The present study is the first to characterize neural complexity in BOLD signals at a high temporal resolution and across different networks and might help clarify the inconsistencies between neural complexity and functional connectivity, thus informing the mechanisms underlying neural complexity.

  7. High-Speed Real-Time Resting State fMRI using Multi-Slab Echo-Volumar Imaging

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    Stefan ePosse

    2013-08-01

    Full Text Available We recently demonstrated that ultra-high-speed real-time fMRI using multi-slab echo-volumar imaging (MEVI significantly increases sensitivity for mapping task-related activation and resting state networks (RSNs compared to echo-planar imaging (Posse et al. 2012. In the present study we characterize the sensitivity of MEVI for mapping RSN connectivity dynamics, comparing independent component analysis (ICA and a novel seed-based connectivity analysis (SBCA that combines sliding-window correlation analysis with meta-statistics. This SBCA approach is shown to minimize the effects of confounds, such as movement, and CSF and white matter signal changes, and enables real-time monitoring of RSN dynamics at time scales of tens of seconds. We demonstrate highly sensitive mapping of eloquent cortex in the vicinity of brain tumors and arteriovenous malformations, and detection of abnormal resting state connectivity in epilepsy. In patients with motor impairment, resting state fMRI provided focal localization of sensorimotor cortex compared with more diffuse activation in task-based fMRI. The fast acquisition speed of MEVI enabled segregation of cardiac-related signal pulsation using ICA, which revealed distinct regional differences in pulsation amplitude and waveform, elevated signal pulsation in patients with arteriovenous malformations and a trend towards reduced pulsatility in gray matter of patients compared with healthy controls. Mapping cardiac pulsation in cortical gray matter may carry important functional information that distinguishes healthy from diseased tissue vasculature. This novel fMRI methodology is particularly promising for mapping eloquent cortex in patients with neurological disease, having variable degree of cooperation in task-based fMRI. In conclusion, ultra-high-real-time speed fMRI enhances the sensitivity of mapping the dynamics of resting state connectivity and cerebrovascular pulsatility for clinical and neuroscience research

  8. Resting state low-frequency fluctuations in prefrontal cortex reflect degrees of harm avoidance and novelty seeking: An exploratory NIRS study

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    Takashi eNakao

    2013-12-01

    Full Text Available Harm avoidance (HA and novelty seeking (NS are temperament dimensions defined by Temperament and Character Inventory (TCI, respectively reflecting a heritable bias for intense response to aversive stimuli or for excitement in response to novel stimuli. High HA is regarded as a risk factor for major depressive disorder and anxiety disorder. In contrast, higher NS is linked to increased risk for substance abuse and pathological gambling disorder. A growing body of evidence suggests that patients with these disorders show abnormality in the power of slow oscillations of resting-state brain activity. It is particularly interesting that previous studies have demonstrated that resting state activities in medial prefrontal cortex (MPFC are associated with HA or NS scores, although the relation between the power of resting state slow oscillations and these temperament dimensions remains poorly elucidated. This preliminary study investigated the biological bases of these temperament traits by particularly addressing the resting state low-frequency fluctuations in MPFC. Regional hemodynamic changes in channels covering MPFC during 5-min resting states were measured from 22 healthy participants using near-infrared spectroscopy (NIRS. These data were used for correlation analyses. Results show that the power of slow oscillations during resting state around the dorsal part of MPFC is negatively correlated with the HA score. In contrast, NS was positively correlated with the power of resting state slow oscillations around the ventral part of MPFC. These results suggest that the powers of slow oscillation at rest in dorsal or ventral MPFC respectively reflect the degrees of HA and NS. This exploratory study therefore uncovers novel neural bases of HA and NS. We discuss a neural mechanism underlying aversion-related and reward-related processing based on results obtained from this study.

  9. Frequency-dependent changes in the regional amplitude and synchronization of resting-state functional MRI in stroke.

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    Jianfang Zhu

    Full Text Available Resting-state functional magnetic resonance imaging (R-fMRI has been intensively used to assess alterations of inter-regional functional connectivity in patients with stroke, but the regional properties of brain activity in stroke have not yet been fully investigated. Additionally, no study has examined a frequency effect on such regional properties in stroke patients, although this effect has been shown to play important roles in both normal brain functioning and functional abnormalities. Here we utilized R-fMRI to measure the amplitude of low-frequency fluctuations (ALFF and regional homogeneity (ReHo, two major methods for characterizing the regional properties of R-fMRI, in three different frequency bands (slow-5: 0.01-0.027 Hz; slow-4: 0.027-0.73 Hz; and typical band: 0.01-0.1 Hz in 19 stroke patients and 15 healthy controls. Both the ALFF and ReHo analyses revealed changes in brain activity in a number of brain regions, particularly the parietal cortex, in stroke patients compared with healthy controls. Remarkably, the regions with changed activity as detected by the slow-5 band data were more extensive, and this finding was true for both the ALFF and ReHo analyses. These results not only confirm previous studies showing abnormality in the parietal cortex in patients with stroke, but also suggest that R-fMRI studies of stroke should take frequency effects into account when measuring intrinsic brain activity.

  10. Modular organization of functional network connectivity in healthy controls and patients with schizophrenia during the resting state

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    Qingbao eYu

    2012-01-01

    Full Text Available Neuroimaging studies have shown that functional brain networks composed from select regions of interest (ROIs have a modular community structure. However, the organization of functional network connectivity (FNC, comprising a purely data-driven network built from spatially independent brain components, is not yet clear. The aim of this study is to explore the modular organization of FNC in both healthy controls (HCs and patients with schizophrenia (SZs. Resting state functional magnetic resonance imaging (R-fMRI data of HCs and SZs were decomposed into independent components (ICs by group independent component analysis (ICA. Then weighted brain networks (in which nodes are brain components were built based on correlations among of ICA time courses. Clustering coefficients and connectivity strength of the networks were computed. A dynamic branch cutting algorithm was used to identify modules of the FNC in HCs and SZs. Results show stronger connectivity strength and higher clustering coefficient in HCs with more and smaller modules in SZs. In addition, HCs and SZs had some different hubs. Our findings demonstrate altered modular architecture of the FNC in schizophrenia and provide insights into abnormal topological organization of intrinsic brain networks in this mental illness.

  11. Prediction of individual clinical scores in patients with Parkinson's disease using resting-state functional magnetic resonance imaging.

    Science.gov (United States)

    Hou, YanBing; Luo, ChunYan; Yang, Jing; Ou, RuWei; Song, Wei; Wei, QianQian; Cao, Bei; Zhao, Bi; Wu, Ying; Shang, Hui-Fang; Gong, QiYong

    2016-07-15

    Neuroimaging holds the promise that it may one day aid the clinical assessment. However, the vast majority of studies using resting-state functional magnetic resonance imaging (fMRI) have reported average differences between Parkinson's disease (PD) patients and healthy controls, which do not permit inferences at the level of individuals. This study was to develop a model for the prediction of PD illness severity ratings from individual fMRI brain scan. The resting-state fMRI scans were obtained from 84 patients with PD and the Unified Parkinson's Disease Rating Scale-III (UPDRS-III) scores were obtained before scanning. The RVR method was used to predict clinical scores (UPDRS-III) from fMRI scans. The application of RVR to whole-brain resting-state fMRI data allowed prediction of UPDRS-III scores with statistically significant accuracy (correlation=0.35, P-value=0.001; mean sum of squares=222.17, P-value=0.002). This prediction was informed strongly by negative weight areas including prefrontal lobe and medial occipital lobe, and positive weight areas including medial parietal lobe. It was suggested that fMRI scans contained sufficient information about neurobiological change in patients with PD to permit accurate prediction about illness severity, on an individual subject basis. Our results provided preliminary evidence, as proof-of-concept, to support that fMRI might be possible to be a clinically useful quantitative assessment aid in PD at individual level. This may enable clinicians to target those uncooperative patients and machines to replace human for a more efficient use of health care resources. PMID:27288771

  12. Decreased prefrontal lobe interhemispheric functional connectivity in adolescents with internet gaming disorder: a primary study using resting-state FMRI.

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    Yao Wang

    Full Text Available Recent neuroimaging studies have shown that people with Internet gaming disorder (IGD have structural and functional abnormalities in specific brain areas and connections. However, little is known about the alterations of the interhemispheric resting-state functional connectivity (rsFC in participants with IGD. In the present study, we used a newly developed voxel-mirrored homotopic connectivity (VMHC method to investigate the interhemispheric rsFC of the whole brain in participants with IGD.We compared interhemispheric rsFC between 17 participants with IGD and 24 healthy controls, group-matched on age, gender, and education status. All participants were provided written informed consent. Resting-state functional and structural magnetic resonance images were acquired for all participants. The rsFC between bilateral homotopic voxels was calculated. Regions showing abnormal VMHC in IGD participants were adopted as regions of interest for correlation analyses.Compared to healthy controls, IGD participants showed decreased VMHC between the left and right superior frontal gyrus (orbital part, inferior frontal gyrus (orbital part, middle frontal gyrus and superior frontal gyrus. Further analyses showed Chen Internet Addiction Scale (CIAS-related VMHC in superior frontal gyrus (orbital part and CIAS (r = -0.55, p = 0.02, uncorrected.Our findings implicate the important role of altered interhemispheric rsFC in the bilateral prefrontal lobe in the neuropathological mechanism of IGD, and provide further supportive evidence for the reclassification of IGD as a behavioral addiction.

  13. Longitudinal Evidence for Dissociation of Anterior and Posterior MTL Resting-State Connectivity in Aging: Links to Perfusion and Memory.

    Science.gov (United States)

    Salami, Alireza; Wåhlin, Anders; Kaboodvand, Neda; Lundquist, Anders; Nyberg, Lars

    2016-10-01

    Neuroimaging studies of spontaneous signal fluctuations as measured by resting-state functional magnetic resonance imaging have revealed age-related alterations in the functional architecture of brain networks. One such network is located in the medial temporal lobe (MTL), showing structural and functional variations along the anterior-posterior axis. Past cross-sectional studies of MTL functional connectivity (FC) have yielded discrepant findings, likely reflecting the fact that specific MTL subregions are differentially affected in aging. Here, using longitudinal resting-state data from 198 participants, we investigated 5-year changes in FC of the anterior and posterior MTL. We found an opposite pattern, such that the degree of FC within the anterior MTL declined after age 60, whereas elevated FC within the posterior MTL was observed along with attenuated posterior MTL-cortical connectivity. A significant negative change-change relation was observed between episodic-memory decline and elevated FC in the posterior MTL. Additional analyses revealed age-related cerebral blood flow (CBF) increases in posterior MTL at the follow-up session, along with a positive relation of elevated FC and CBF, suggesting that elevated FC is a metabolically demanding alteration. Collectively, our findings indicate that elevated FC in posterior MTL along with increased local perfusion is a sign of brain aging that underlie episodic-memory decline. PMID:27522073

  14. Longitudinal Evidence for Dissociation of Anterior and Posterior MTL Resting-State Connectivity in Aging: Links to Perfusion and Memory

    Science.gov (United States)

    Salami, Alireza; Wåhlin, Anders; Kaboodvand, Neda; Lundquist, Anders; Nyberg, Lars

    2016-01-01

    Neuroimaging studies of spontaneous signal fluctuations as measured by resting-state functional magnetic resonance imaging have revealed age-related alterations in the functional architecture of brain networks. One such network is located in the medial temporal lobe (MTL), showing structural and functional variations along the anterior–posterior axis. Past cross-sectional studies of MTL functional connectivity (FC) have yielded discrepant findings, likely reflecting the fact that specific MTL subregions are differentially affected in aging. Here, using longitudinal resting-state data from 198 participants, we investigated 5-year changes in FC of the anterior and posterior MTL. We found an opposite pattern, such that the degree of FC within the anterior MTL declined after age 60, whereas elevated FC within the posterior MTL was observed along with attenuated posterior MTL-cortical connectivity. A significant negative change–change relation was observed between episodic-memory decline and elevated FC in the posterior MTL. Additional analyses revealed age-related cerebral blood flow (CBF) increases in posterior MTL at the follow-up session, along with a positive relation of elevated FC and CBF, suggesting that elevated FC is a metabolically demanding alteration. Collectively, our findings indicate that elevated FC in posterior MTL along with increased local perfusion is a sign of brain aging that underlie episodic-memory decline. PMID:27522073

  15. Resting-State Subjective Experience and EEG Biomarkers Are Associated with Sleep-Onset Latency.

    Science.gov (United States)

    Diaz, B Alexander; Hardstone, Richard; Mansvelder, Huibert D; Van Someren, Eus J W; Linkenkaer-Hansen, Klaus

    2016-01-01

    Difficulties initiating sleep are common in several disorders, including insomnia and attention deficit hyperactivity disorder. These disorders are prevalent, bearing significant societal and financial costs which require the consideration of new treatment strategies and a better understanding of the physiological and cognitive processes surrounding the time of preparing for sleep or falling asleep. Here, we search for neuro-cognitive associations in the resting state and examine their relevance for predicting sleep-onset latency using multi-level mixed models. Multiple EEG recordings were obtained from healthy male participants (N = 13) during a series of 5 min eyes-closed resting-state trials (in total, n = 223) followed by a period-varying in length up to 30 min-that either allowed subjects to transition into sleep ("sleep trials," n sleep = 144) or was ended while they were still awake ("wake trials," n wake = 79). After both eyes-closed rest, sleep and wake trials, subjective experience was assessed using the Amsterdam Resting-State Questionnaire (ARSQ). Our data revealed multiple associations between eyes-closed rest alpha and theta oscillations and ARSQ-dimensions Discontinuity of Mind, Self, Theory of Mind, Planning, and Sleepiness. The sleep trials showed that the transition toward the first sleep stage exclusively affected subjective experiences related to Theory of Mind, Planning, and Sleepiness. Importantly, sleep-onset latency was negatively associated both with eyes-closed rest ratings on the ARSQ dimension of Sleepiness and with the long-range temporal correlations of parietal theta oscillations derived by detrended fluctuation analysis (DFA). These results could be relevant to the development of personalized tools that help evaluate the success of falling asleep based on measures of resting-state cognition and EEG biomarkers. PMID:27148107

  16. The effects of psilocybin and MDMA on between-network resting state functional connectivity in healthy volunteers

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    Leor eRoseman

    2014-05-01

    Full Text Available Perturbing a system and observing the consequences is a classic scientific strategy for understanding a phenomenon. Psychedelic drugs perturb consciousness in a marked and novel way and thus are powerful tools for studying its mechanisms. In the present analysis, we measured changes in resting-state functional connectivity (RSFC between a standard template of different independent components analysis (ICA-derived resting state networks (RSNs under the influence of two different psychoactive drugs, the stimulant/psychedelic hybrid, MDMA, and the classic psychedelic, psilocybin. Both were given in placebo-controlled designs and produced marked subjective effects, although reports of more profound changes in consciousness were given after psilocybin. Between-network RSFC was generally increased under psilocybin, implying that networks become less differentiated from each other in the psychedelic state. Decreased RSFC between visual and sensorimotor RSNs was also observed. MDMA had a notably less marked effect on between-network RSFC, implying that the extensive changes observed under psilocybin may be exclusive to classic psychedelic drugs and related to their especially profound effects on consciousness. The novel analytical approach applied here may be applied to other altered states of consciousness to improve our characterization of different conscious states and ultimately advance our understanding of the brain mechanisms underlying them.

  17. The effects of psilocybin and MDMA on between-network resting state functional connectivity in healthy volunteers.

    Science.gov (United States)

    Roseman, Leor; Leech, Robert; Feilding, Amanda; Nutt, David J; Carhart-Harris, Robin L

    2014-01-01

    Perturbing a system and observing the consequences is a classic scientific strategy for understanding a phenomenon. Psychedelic drugs perturb consciousness in a marked and novel way and thus are powerful tools for studying its mechanisms. In the present analysis, we measured changes in resting-state functional connectivity (RSFC) between a standard template of different independent components analysis (ICA)-derived resting state networks (RSNs) under the influence of two different psychoactive drugs, the stimulant/psychedelic hybrid, MDMA, and the classic psychedelic, psilocybin. Both were given in placebo-controlled designs and produced marked subjective effects, although reports of more profound changes in consciousness were given after psilocybin. Between-network RSFC was generally increased under psilocybin, implying that networks become less differentiated from each other in the psychedelic state. Decreased RSFC between visual and sensorimotor RSNs was also observed. MDMA had a notably less marked effect on between-network RSFC, implying that the extensive changes observed under psilocybin may be exclusive to classic psychedelic drugs and related to their especially profound effects on consciousness. The novel analytical approach applied here may be applied to other altered states of consciousness to improve our characterization of different conscious states and ultimately advance our understanding of the brain mechanisms underlying them.

  18. The effects of dexamphetamine on the resting-state electroencephalogram and functional connectivity.

    Science.gov (United States)

    Albrecht, Matthew A; Roberts, Gareth; Price, Greg; Lee, Joseph; Iyyalol, Rajan; Martin-Iverson, Mathew T

    2016-02-01

    The catecholamines-dopamine and noradrenaline-play important roles in directing and guiding behavior. Disorders of these systems, particularly within the dopamine system, are associated with several severe and chronically disabling psychiatric and neurological disorders. We used the recently published group independent components analysis (ICA) procedure outlined by Chen et al. (2013) to present the first pharmaco-EEG ICA analysis of the resting-state EEG in healthy participants administered 0.45 mg/kg dexamphetamine. Twenty-eight healthy participants between 18 and 41 were recruited. Bayesian nested-domain models that explicitly account for spatial and functional relationships were used to contrast placebo and dexamphetamine on component spectral power and several connectivity metrics. Dexamphetamine led to reductions across delta, theta, and alpha spectral power bands that were predominantly localized to Frontal and Central regions. Beta 1 and beta 2 power were reduced by dexamphetamine at Frontal ICs, while beta 2 and gamma power was enhanced by dexamphetamine in posterior regions, including the parietal, occipital-temporal, and occipital regions. Power-power coupling under dexamphetamine was similar for both states, resembling the eyes open condition under placebo. However, orthogonalized measures of power coupling and phase coupling did not show the same effect of dexamphetamine as power-power coupling. We discuss the alterations of low- and high-frequency EEG power in response to dexamphetamine within the context of disorders of dopamine regulation, in particular schizophrenia, as well as in the context of a recently hypothesized association between low-frequency power and aspects of anhedonia. Hum Brain Mapp 37:570-588, 2016. © 2015 Wiley Periodicals, Inc.

  19. Effective connectivity within the default mode network: dynamic causal modeling of resting-state fMRI data

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    Maksim eSharaev

    2016-02-01

    Full Text Available The Default Mode Network (DMN is a brain system that mediates internal modes of cognitive activity, showing higher neural activation when one is at rest. Nowadays, there is a lot of interest in assessing functional interactions between its key regions, but in the majority of studies only association of BOLD (Blood-oxygen-level dependent activation patterns is measured, so it is impossible to identify causal influences. There are some studies of causal interactions (i.e. effective connectivity, however often with inconsistent results. The aim of the current work is to find a stable pattern of connectivity between four DMN key regions: the medial prefrontal cortex mPFC, the posterior cingulate cortex PCC, left and right intraparietal cortex LIPC and RIPC. For this purpose fMRI (functional magnetic resonance imaging data from 30 healthy subjects (1000 time points from each one was acquired and spectral dynamic causal modeling (DCM on a resting-state fMRI data was performed. The endogenous brain fluctuations were explicitly modeled by Discrete Cosine Set at the low frequency band of 0.0078–0.1 Hz. The best model at the group level is the one where connections from both bilateral IPC to mPFC and PCC are significant and symmetrical in strength (p<0.05. Connections between mPFC and PCC are bidirectional, significant in the group and weaker than connections originating from bilateral IPC. In general, all connections from LIPC/RIPC to other DMN regions are much stronger. One can assume that these regions have a driving role within the DMN. Our results replicate some data from earlier works on effective connectivity within the DMN as well as provide new insights on internal DMN relationships and brain’s functioning at resting state.

  20. 脑深部电刺激对帕金森病患者基底节环路的影响及其作用机制%The Effect of Deep Brain Stimulation(DBS) on Resting- state Cerebral Glucose Metabolism of Advanced Parkinson's Disease

    Institute of Scientific and Technical Information of China (English)

    赵永波; 李殿友; 孙伯民; 王乔树

    2003-01-01

    目的研究双侧丘脑底核(STN)慢性电刺激术(DBS)对晚期帕金森病(PD)患者静止期脑局部糖代谢的影响,并探讨DBS的作用机制.方法对7例进行双侧STNDBS的晚期PD患者,在术前和术后1个月电刺激条件下,分别进行18F-脱氧葡萄糖(FDG)/PET检查和UPDRS评分,并通过SPM99统计学软件进行数据分析,研究双侧STNDBS对PD患者脑内代谢的影响.结果双侧STN DBS使PD患者临床症状明显改善,同时脑局部糖代谢也发生了明显变化:双侧豆状核、脑干(中脑、脑桥)、双侧顶枕部、运动前区(BA6)及扣带回的脑代谢增加;前额叶底部、海马的脑代谢减少(P<0.05).结论双侧STN DBS可能通过兴奋STN轴突的方式,使轴突投射区域的基底节上行和下行通路代谢改善,并增加相应的额叶高级运动中枢的代谢,使PD患者临床症状改善.%Objective To study the effects of bilateral subthalamic nucleus (STN) stimulation onresting-state cerebral glucose metabolism of advanced Parkinson's disease, and investigate the mecha-nism of deep brain stimulation (DBS). Methods Seven consecutive advanced Parkinson' s diseasepatients (4 men, 3 women; mean age 64±4; mean H-Y disability scale 4.4±0. 65) with bilateral STNDBS underwent 2 times 18F-FDG/PET examinations at rest preoperatively and one month postopera-tively with STN stimulation on respectively. The unified Parkinson' s disease rating scale was used toevaluate the clinical state under each condition. Statistical parametric mapping (SPM) was used to inves-tigate regional cerebral metabolic rate of glucose (rCMRGlu) during STN stimulation in comparison withr CMRGlu preoperatively. Results STN stimulation improved the clinical symptoms obviously for eachpatient. The significant increase of rCMRGlu was found in bilateral lentiform nucleus, brainstem (mid-brain and pon), bilateral premotor area (BA6), parietal-occipital cortex and anterior cingulated cortex,and the marked decrease of it was

  1. Hyper-resting brain entropy within chronic smokers and its moderation by Sex

    OpenAIRE

    Zhengjun Li; Zhuo Fang; Nathan Hager; Hengyi Rao; Ze Wang

    2016-01-01

    Cigarette smoking is a chronic relapsing brain disorder, and remains a premier cause of morbidity and mortality. Functional neuroimaging has been used to assess differences in the mean strength of brain activity in smokers’ brains, however less is known about the temporal dynamics within smokers’ brains. Temporal dynamics is a key feature of a dynamic system such as the brain, and may carry information critical to understanding the brain mechanisms underlying cigarette smoking. We measured th...

  2. Hemodynamic correlates of spontaneous neural activity measured by human whole-head resting state EEG+fNIRS.

    Science.gov (United States)

    Keles, Hasan Onur; Barbour, Randall L; Omurtag, Ahmet

    2016-09-01

    The brains of awake, resting human subjects display spontaneously occurring neural activity patterns whose magnitude is typically many times greater than those triggered by cognitive or perceptual performance. Evoked and resting state activations affect local cerebral hemodynamic properties through processes collectively referred to as neurovascular coupling. Its investigation calls for an ability to track both the neural and vascular aspects of brain function. We used scalp electroencephalography (EEG), which provided a measure of the electrical potentials generated by cortical postsynaptic currents. Simultaneously we utilized functional near-infrared spectroscopy (NIRS) to continuously monitor hemoglobin concentration changes in superficial cortical layers. The multi-modal signal from 18 healthy adult subjects allowed us to investigate the association of neural activity in a range of frequencies over the whole-head to local changes in hemoglobin concentrations. Our results verified the delayed alpha (8-16Hz) modulation of hemodynamics in posterior areas known from the literature. They also indicated strong beta (16-32Hz) modulation of hemodynamics. Analysis revealed, however, that beta modulation was likely generated by the alpha-beta coupling in EEG. Signals from the inferior electrode sites were dominated by scalp muscle related activity. Our study aimed to characterize the phenomena related to neurovascular coupling observable by practical, cost-effective, and non-invasive multi-modal techniques. PMID:27236081

  3. Altered regional homogeneity in spontaneous cluster headache attacks: a resting-state functional magnetic resonance imaging study

    Institute of Scientific and Technical Information of China (English)

    QIU En-chao; YU Sheng-yuan; LIU Ruo-zhuo; WANG Yan; MA Lin; TIAN Li-xia

    2012-01-01

    Background Functional neuroimaging study has opened an avenue for exploring the pathophysiology of cluster headache (CH).The aim of our study was to assess the changes in brain activity in CH patients by the regional homogeneity method using resting-state functional magnetic resonance imaging technique.Methods The functional magnetic resonance imaging scans were obtained for 12 male CH patients with spontaneous right-sided headache attacks during “in attack” and “out of attack” periods and 12 age- and sex-matched normal controls.The data were analyzed to detect the altered brain activity by the regional homogeneity method using statistical parametric mapping software.Results Altered regional homogeneity was detected in the anterior cingulate cortex,the posterior cingulate cortex,the prefrontal cortex,insular cortex,and other brain regions involved in pain processing and modulation among different groups.Conclusion It is referred that these brain regions with altered regional homogeneity might be related to the pain processing and modulation of CH.

  4. A Quantitative Study of Network Robustness in Resting-State fMRI in Young and Elder Adults

    Science.gov (United States)

    Gomez-Ramirez, Jaime; Li, Yujie; Wu, Qiong; Wu, Jinglong

    2016-01-01

    Brain connectivity analysis has shown great promise in understanding how aging affects functional connectivity; however, an explanatory framework to study healthy aging in terms of network efficiency is still missing. Here, we study network robustness, i.e., resilience to perturbations, in resting-state functional connectivity networks (rs-fMRI) in young and elder subjects. We apply analytic measures of network communication efficiency in the human brain to investigate the compensatory mechanisms elicited in aging. Specifically, we quantify the effect of “lesioning” (node canceling) of either single regions of interest (ROI) or whole networks on global connectivity metrics (i.e., efficiency). We find that young individuals are more resilient than old ones to random “lesioning” of brain areas; global network efficiency is over 3 times lower in older subjects relative to younger subjects. On the other hand, the “lesioning” of central and limbic structures in young subjects yield a larger efficiency loss than in older individuals. Overall, our study shows a more idiosyncratic response to specific brain network “lesioning” in elder compared to young subjects, and that young adults are more resilient to random deletion of single nodes compared to old adults. PMID:26869917

  5. A novel model-free data analysis technique based on clustering in a mutual information space: application to resting-state fMRI

    Directory of Open Access Journals (Sweden)

    Simon Benjaminsson

    2010-08-01

    Full Text Available Non-parametric data-driven analysis techniques can be used to study datasets with few assumptions about the data and underlying experiment. Variations of Independent Component Analysis (ICA have been the methods mostly used on fMRI data, e.g. in finding resting-state networks thought to reflect the connectivity of the brain. Here we present a novel data analysis technique and demonstrate it on resting-state fMRI data. It is a generic method with few underlying assumptions about the data. The results are built from the statistical relations between all input voxels, resulting in a whole-brain analysis on a voxel level. It has good scalability properties and the parallel implementation is capable of handling large datasets and databases. From the mutual information between the activities of the voxels over time, a distance matrix is created for all voxels in the input space. Multidimensional scaling is used to put the voxels in a lower-dimensional space reflecting the dependency relations based on the distance matrix. By performing clustering in this space we can find the strong statistical regularities in the data, which for the resting-state data turns out to be the resting-state networks. The decomposition is performed in the last step of the algorithm and is computationally simple. This opens up for rapid analysis and visualization of the data on different spatial levels, as well as automatically finding a suitable number of decomposition components.

  6. Interhemispheric Functional and Structural Disconnection in Alzheimer's Disease: A Combined Resting-State fMRI and DTI Study.

    Directory of Open Access Journals (Sweden)

    Zhiqun Wang

    Full Text Available Neuroimaging studies have demonstrated that patients with Alzheimer's disease presented disconnection syndrome. However, little is known about the alterations of interhemispheric functional interactions and underlying structural connectivity in the AD patients. In this study, we combined resting-state functional MRI and diffusion tensor imaging (DTI to investigate interhemispheric functional and structural connectivity in 16 AD, 16 mild cognitive impairment (MCI, as well as 16 cognitive normal healthy subjects (CN. The pattern of the resting state interhemispheric functional connectivity was measured with a voxel-mirrored homotopic connectivity (VMHC method. Decreased VMHC was observed in AD and MCI subjects in anterior brain regions including the prefrontal cortices and subcortical regions with a pattern of ADbrain regions with patterns of AD/CN < MCI (sensorimotor cortex and AD < CN/MCI (occipital gyrus. DTI analysis showed the most significant difference among the three cohorts was the fractional anisotropy in the genu of corpus callosum, which was positively associated with the VMHC of prefrontal and subcortical regions. Across all the three cohorts, the diffusion parameters in the genu of corpus callosum and VMHC in the above brain regions had significant correlation with the cognitive performance. These results demonstrate that there are specific patterns of interhemispheric functional connectivity changes in the AD and MCI, which can be significantly correlated with the integrity changes in the midline white matter structures. These results suggest that VMHC can be used as a biomarker for the degeneration of the interhemispheric connectivity in AD.

  7. Relationship between functional connectivity and motor function assessment in stroke patients with hemiplegia: a resting-state functional MRI study

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Ye; Wang, Li; Zhang, Jingna; Sang, Linqiong; Li, Pengyue; Qiu, Mingguo [Third Military Medical University, Department of Medical Imaging, College of Biomedical Engineering, Chongqing (China); Liu, Hongliang; Yan, Rubing [Third Military Medical University, Department of Rehabilitation, Southwest Hospital, Chongqing (China); Yang, Jun; Wang, Jian [Third Military Medical University, Department of Radiology, Southwest Hospital, Chongqing (China)

    2016-05-15

    Resting-state functional magnetic resonance imaging (fMRI) has been used to examine the brain mechanisms of stroke patients with hemiplegia, but the relationship between functional connectivity (FC) and treatment-induced motor function recovery has not yet been fully investigated. This study aimed to identify the brain FC changes in stroke patients and study the relationship between FC and motor function assessment using the resting-state fMRI. Seventeen stroke patients with hemiplegia and fifteen healthy control subjects (HCSs) were recruited in this study. We compared the FC between the ipsilesional primary motor cortex (M1) and the whole brain of the patients with the FC of the HCSs and studied the FC changes in the patients before and after conventional rehabilitation and motor imagery therapy. Additionally, correlations between the FC change and motor function of the patients were studied. Compared to the HCSs, the FC in the patient group was significantly increased between the ipsilesional M1 and the ipsilesional inferior parietal cortex, frontal gyrus, supplementary motor area (SMA), and contralesional angular and decreased between the ipsilesional M1 and bilateral M1. After the treatment, the FC between the ipsilesional M1 and contralesional M1 increased while the FC between the ipsilesional M1 and ipsilesional SMA and paracentral lobule decreased. A statistically significant correlation was found between the FC change in the bilateral M1 and the Fugl-Meyer assessment (FMA) score change. Our results revealed an abnormal motor network after stroke and suggested that the FC could serve as a biomarker of motor function recovery in stroke patients with hemiplegia. (orig.)

  8. Relationship between functional connectivity and motor function assessment in stroke patients with hemiplegia: a resting-state functional MRI study

    International Nuclear Information System (INIS)

    Resting-state functional magnetic resonance imaging (fMRI) has been used to examine the brain mechanisms of stroke patients with hemiplegia, but the relationship between functional connectivity (FC) and treatment-induced motor function recovery has not yet been fully investigated. This study aimed to identify the brain FC changes in stroke patients and study the relationship between FC and motor function assessment using the resting-state fMRI. Seventeen stroke patients with hemiplegia and fifteen healthy control subjects (HCSs) were recruited in this study. We compared the FC between the ipsilesional primary motor cortex (M1) and the whole brain of the patients with the FC of the HCSs and studied the FC changes in the patients before and after conventional rehabilitation and motor imagery therapy. Additionally, correlations between the FC change and motor function of the patients were studied. Compared to the HCSs, the FC in the patient group was significantly increased between the ipsilesional M1 and the ipsilesional inferior parietal cortex, frontal gyrus, supplementary motor area (SMA), and contralesional angular and decreased between the ipsilesional M1 and bilateral M1. After the treatment, the FC between the ipsilesional M1 and contralesional M1 increased while the FC between the ipsilesional M1 and ipsilesional SMA and paracentral lobule decreased. A statistically significant correlation was found between the FC change in the bilateral M1 and the Fugl-Meyer assessment (FMA) score change. Our results revealed an abnormal motor network after stroke and suggested that the FC could serve as a biomarker of motor function recovery in stroke patients with hemiplegia. (orig.)

  9. Sex Differences in the Default Mode Network with Regard to Autism Spectrum Traits: A Resting State fMRI Study.

    Directory of Open Access Journals (Sweden)

    Minyoung Jung

    Full Text Available Autism spectrum traits exist on a continuum and are more common in males than in females, but the basis for this sex difference is unclear. To this end, the present study draws on the extreme male brain theory, investigating the relationship between sex difference and the default mode network (DMN, both known to be associated with autism spectrum traits. Resting-state functional magnetic resonance imaging (MRI was carried out in 42 females (mean age ± standard deviation, 22.4 ± 4.2 years and 43 males (mean age ± standard deviation, 23.8 ± 3.9 years with typical development. Using a combination of different analyses (viz., independent component analysis (ICA, fractional amplitude of low-frequency fluctuation (fALFF, regional homogeneity (ReHo, and seed-based analyses, we examined sex differences in the DMN and the relationship to autism spectrum traits as measured by autism-spectrum quotient (AQ scores. We found significant differences between female and male subjects in DMN brain regions, with seed-based analysis revealing a significant negative correlation between default-mode resting state functional connectivity of the anterior medial prefrontal cortex seed (aMPFC and AQ scores in males. However, there were no relationships between DMN sex differences and autism spectrum traits in females. Our findings may provide important insight into the skewed balance of functional connectivity in males compared to females that could serve as a potential biomarker of the degree of autism spectrum traits in line with the extreme male brain theory.

  10. Altered functional connectivity of fusiform gyrus in subjects with amnestic mild cognitive impairment: a resting state fMRI study

    Directory of Open Access Journals (Sweden)

    SuPing eCai

    2015-08-01

    Full Text Available Visual cognition such as face recognition requires a high level of functional interaction between distributed regions of a network. It has been reported that the fusiform gyrus (FG is an important brain area involved in facial cognition; altered connectivity of FG to some other regions may lead to a deficit in visual cognition especially face recognition. However, whether functional connectivity between the FG and other brain regions changes remains unclear during the resting state in amnestic mild cognitive impairment (aMCI subjects. Here, we employed a resting state functional MRI (fMRI to examine changes in functional connectivity of left/right FG comparing aMCI patients with age-matched control subjects. Forty-eight aMCI and thirty-eight control subjects from the Alzheimer’s disease Neuroimaging Initiative (ADNI were analyzed. We focused on the correlation between low frequency fMRI signal fluctuations in the FG and those in all other brain regions. Compared to the control group, we found some discrepant regions in the aMCI group which presented increased or decreased connectivity with the left/right FG including the left precuneus, left lingual gyrus, right thalamus, supramarginal gyrus, left supplementary motor area, left inferior temporal gyrus, and left parahippocampus. More importantly, we also obtained that both left and right FG have increased functional connections with the left middle occipital gyrus (MOG and right anterior cingulate gyrus (ACC in aMCI patients. That was not a coincidence and might imply that the MOG and ACC also play a critical role in visual cognition, especially face recognition. These findings in a large part supported our hypothesis and provided a new insight in understanding the important subtype of MCI.

  11. Abnormal Spontaneous Neural Activity in Obsessive-Compulsive Disorder: A Resting-State Functional Magnetic Resonance Imaging Study.

    Directory of Open Access Journals (Sweden)

    Li Ping

    Full Text Available Neuroimaging studies of obsessive-compulsive disorder have found abnormalities in orbitofronto-striato-thalamic circuitry, including the orbitofrontal cortex, anterior cingulate cortex, caudate, and thalamus, but few studies have explored abnormal intrinsic or spontaneous brain activity in the resting state. We investigated both intra- and inter-regional synchronized activity in twenty patients with obsessive-compulsive disorder and 20 healthy controls using resting-state functional magnetic resonance imaging. Regional homogeneity (ReHo and functional connectivity methods were used to analyze the intra- and inter-regional synchronized activity, respectively. Compared with healthy controls, patients with obsessive-compulsive disorder showed significantly increased ReHo in the orbitofrontal cortex, cerebellum, and insula, and decreased ReHo in the ventral anterior cingulate cortex, caudate, and inferior occipital cortex. Based on ReHo results, we determined functional connectivity differences between the orbitofrontal cortex and other brain regions in both patients with obsessive-compulsive disorder and controls. We found abnormal functional connectivity between the orbitofrontal cortex and ventral anterior cingulate cortex in patients with obsessive-compulsive disorder compared with healthy controls. Moreover, ReHo in the orbitofrontal cortex was correlated with the duration of obsessive-compulsive disorder. These findings suggest that increased intra- and inter-regional synchronized activity in the orbitofrontal cortex may have a key role in the pathology of obsessive-compulsive disorder. In addition to orbitofronto-striato-thalamic circuitry, brain regions such as the insula and cerebellum may also be involved in the pathophysiology of obsessive-compulsive disorder.

  12. Disrupted thalamic resting-state functional connectivity in patients with minimal hepatic encephalopathy

    International Nuclear Information System (INIS)

    Background and purpose: Little is known about the role of thalamus in the pathophysiology of minimal hepatic encephalopathy (MHE). The purpose of this study was to investigate whether the thalamic functional connectivity was disrupted in cirrhotic patients with MHE by using resting-state functional magnetic resonance imaging (rs-fMRI). Materials and Methods: Twenty seven MHE patients and twenty seven age- and gender- matched healthy controls participated in the rs-fMRI scans. The functional connectivity of 11 thalamic nuclei were characterized by using a standard seed-based whole-brain correlation method and compared between MHE patients and healthy controls. Pearson correlation analysis was performed between the thalamic functional connectivity and venous blood ammonia levels/neuropsychological tests scores of patients. Results: The ventral anterior nucleus (VAN) and the ventral posterior medial nucleus (VPMN) in each side of thalamus showed abnormal functional connectivities in MHE. Compared with healthy controls, MHE patients demonstrated significant decreased functional connectivity between the right/left VAN and the bilateral putamen/pallidum, inferior frontal gyri, insula, supplementary motor area, right middle frontal gyrus, medial frontal gyrus. In addition, MHE patients showed significantly decreased functional connectivity with the right/left VPMN in the bilateral middle temporal gyri (MTG), temporal lobe, and right superior temporal gyrus. The venous blood ammonia levels of MHE patients negatively correlated with the functional connectivity between the VAN and the insula. Number connecting test scores showed negative correlation with the functional connectivity between the VAN and the insula, and between the VPMN and the MTG. Conclusion: MHE patients had disrupted thalamic functional connectivity, which mainly located in the bilateral ventral anterior nuclei and ventral posterior medial nuclei. The decreased connectivity between thalamus and many

  13. Disrupted thalamic resting-state functional connectivity in patients with minimal hepatic encephalopathy

    Energy Technology Data Exchange (ETDEWEB)

    Qi, Rongfeng [Department of Medical Imaging, Jinling Hospital, Clinical School of Medical College, Nanjing University, Nanjing 210002 (China); Zhang, Long Jiang, E-mail: kevinzhanglongjiang@yahoo.com.cn [Department of Medical Imaging, Jinling Hospital, Clinical School of Medical College, Nanjing University, Nanjing 210002 (China); Zhong, Jianhui [Department of Biomedical Engineering, Zhejiang University, Hangzhou, Zhejiang 310027 (China); Zhang, Zhiqiang; Ni, Ling; Zheng, Gang [Department of Medical Imaging, Jinling Hospital, Clinical School of Medical College, Nanjing University, Nanjing 210002 (China); Lu, Guang Ming, E-mail: cjr.luguangming@vip.163.com [Department of Medical Imaging, Jinling Hospital, Clinical School of Medical College, Nanjing University, Nanjing 210002 (China)

    2013-05-15

    Background and purpose: Little is known about the role of thalamus in the pathophysiology of minimal hepatic encephalopathy (MHE). The purpose of this study was to investigate whether the thalamic functional connectivity was disrupted in cirrhotic patients with MHE by using resting-state functional magnetic resonance imaging (rs-fMRI). Materials and Methods: Twenty seven MHE patients and twenty seven age- and gender- matched healthy controls participated in the rs-fMRI scans. The functional connectivity of 11 thalamic nuclei were characterized by using a standard seed-based whole-brain correlation method and compared between MHE patients and healthy controls. Pearson correlation analysis was performed between the thalamic functional connectivity and venous blood ammonia levels/neuropsychological tests scores of patients. Results: The ventral anterior nucleus (VAN) and the ventral posterior medial nucleus (VPMN) in each side of thalamus showed abnormal functional connectivities in MHE. Compared with healthy controls, MHE patients demonstrated significant decreased functional connectivity between the right/left VAN and the bilateral putamen/pallidum, inferior frontal gyri, insula, supplementary motor area, right middle frontal gyrus, medial frontal gyrus. In addition, MHE patients showed significantly decreased functional connectivity with the right/left VPMN in the bilateral middle temporal gyri (MTG), temporal lobe, and right superior temporal gyrus. The venous blood ammonia levels of MHE patients negatively correlated with the functional connectivity between the VAN and the insula. Number connecting test scores showed negative correlation with the functional connectivity between the VAN and the insula, and between the VPMN and the MTG. Conclusion: MHE patients had disrupted thalamic functional connectivity, which mainly located in the bilateral ventral anterior nuclei and ventral posterior medial nuclei. The decreased connectivity between thalamus and many

  14. Increased power of resting-state gamma oscillations in autism spectrum disorder detected by routine electroencephalography

    NARCIS (Netherlands)

    van Diessen, Eric; Senders, Joeky; Jansen, Floor E.; Boersma, Maria; Bruining, Hilgo

    2015-01-01

    Experimental studies suggest that increased resting-state power of gamma oscillations is associated with autism spectrum disorder (ASD). To extend the clinical applicability of this finding, we retrospectively investigated routine electroencephalography (EEG) recordings of 19 patients with ASD and 1

  15. Resting-State Connectivity Predicts Levodopa-Induced Dyskinesias in Parkinson's Disease

    DEFF Research Database (Denmark)

    Herz, Damian M.; Haagensen, Brian N.; Nielsen, Silas H.;

    2016-01-01

    Background: Levodopa-induced dyskinesias are a common side effect of dopaminergic therapy in PD, but their neural correlates remain poorly understood. Objectives: This study examines whether dyskinesias are associated with abnormal dopaminergic modulation of resting-state cortico-striatal connect...

  16. Resting-State Retinotopic Organization in the Absence of Retinal Input and Visual Experience.

    Science.gov (United States)

    Bock, Andrew S; Binda, Paola; Benson, Noah C; Bridge, Holly; Watkins, Kate E; Fine, Ione

    2015-09-01

    Early visual areas have neuronal receptive fields that form a sampling mosaic of visual space, resulting in a series of retinotopic maps in which the same region of space is represented in multiple visual areas. It is not clear to what extent the development and maintenance of this retinotopic organization in humans depend on retinal waves and/or visual experience. We examined the corticocortical receptive field organization of resting-state BOLD data in normally sighted, early blind, and anophthalmic (in which both eyes fail to develop) individuals and found that resting-state correlations between V1 and V2/V3 were retinotopically organized for all subject groups. These results show that the gross retinotopic pattern of resting-state connectivity across V1-V3 requires neither retinal waves nor visual experience to develop and persist into adulthood. Significance statement: Evidence from resting-state BOLD data suggests that the connections between early visual areas develop and are maintained even in the absence of retinal waves and visual experience. PMID:26354906

  17. Graph analytic characterization of resting state networks in post-stroke aphasia

    Directory of Open Access Journals (Sweden)

    Swathi Kiran

    2014-04-01

    Relative to controls, these results indicate inefficiencies in the post-stroke resting-state network, with greater shifts in network hubs in PWA dependent on the site and size of lesion. Such graph analytic results may prove informative in advancing individual-specific therapies.

  18. Resting state functional MRI reveals abnormal network connectivity in orthostatic tremor.

    Science.gov (United States)

    Benito-León, Julián; Louis, Elan D; Manzanedo, Eva; Hernández-Tamames, Juan Antonio; Álvarez-Linera, Juan; Molina-Arjona, José Antonio; Matarazzo, Michele; Romero, Juan Pablo; Domínguez-González, Cristina; Domingo-Santos, Ángela; Sánchez-Ferro, Álvaro

    2016-07-01

    Very little is known about the pathogenesis of orthostatic tremor (OT). We have observed that OT patients might have deficits in specific aspects of neuropsychological function, particularly those thought to rely on the integrity of the prefrontal cortex, which suggests a possible involvement of frontocerebellar circuits. We examined whether resting-state functional magnetic resonance imaging (fMRI) might provide further insights into the pathogenesis on OT. Resting-state fMRI data in 13 OT patients (11 women and 2 men) and 13 matched healthy controls were analyzed using independent component analysis, in combination with a "dual-regression" technique, to identify group differences in several resting-state networks (RSNs). All participants also underwent neuropsychological testing during the same session. Relative to healthy controls, OT patients showed increased connectivity in RSNs involved in cognitive processes (default mode network [DMN] and frontoparietal networks), and decreased connectivity in the cerebellum and sensorimotor networks. Changes in network integrity were associated not only with duration (DMN and medial visual network), but also with cognitive function. Moreover, in at least 2 networks (DMN and medial visual network), increased connectivity was associated with worse performance on different cognitive domains (attention, executive function, visuospatial ability, visual memory, and language). In this exploratory study, we observed selective impairments of RSNs in OT patients. This and other future resting-state fMRI studies might provide a novel method to understand the pathophysiological mechanisms of motor and nonmotor features of OT. PMID:27442678

  19. Resting-state EEG theta activity and risk learning: sensitivity to reward or punishment?

    NARCIS (Netherlands)

    Massar, S.A.A.; Kenemans, J.L.; Schutter, D.J.L.G.

    2014-01-01

    Increased theta (4-7 Hz)-beta.(13-30 Hz) power ratio in resting state electroencephalography (EEG) has been associated with risky disadvantageous decision making and with impaired reinforcement learning. However, the specific contributions of theta and beta power in risky decision making remain uncl

  20. Developmental differences in higher-order resting-state networks in Autism Spectrum Disorder

    Directory of Open Access Journals (Sweden)

    Dienke J. Bos

    2014-01-01

    Conclusions: These results show subtle changes in between network connectivity in relatively young boys with ASD. However, the global architecture of resting-state networks appeared to be intact. This argues against recent suggestions that changes in connectivity in ASD may be the most prominent during development.

  1. Tracking dynamic resting-state networks at higher frequencies using MR-encephalography.

    Science.gov (United States)

    Lee, Hsu-Lei; Zahneisen, Benjamin; Hugger, Thimo; LeVan, Pierre; Hennig, Jürgen

    2013-01-15

    Current resting-state network analysis often looks for coherent spontaneous BOLD signal fluctuations at frequencies below 0.1 Hz in a multiple-minutes scan. However hemodynamic signal variation can occur at a faster rate, causing changes in functional connectivity at a smaller time scale. In this study we proposed to use MREG technique to increase the temporal resolution of resting-state fMRI. A three-dimensional single-shot concentric shells trajectory was used instead of conventional EPI, with a TR of 100 ms and a nominal spatial resolution of 4 × 4 × 4 mm(3). With this high sampling rate we were able to resolve frequency components up to 5 Hz, which prevents major physiological noises from aliasing with the BOLD signal of interest. We used a sliding-window method on signal components at different frequency bands, to look at the non-stationary connectivity maps over the course of each scan session. The aim of the study paradigm was to specifically observe visual and motor resting-state networks. Preliminary results have found corresponding networks at frequencies above 0.1 Hz. These networks at higher frequencies showed better stability in both spatial and temporal dimensions from the sliding-window analysis of the time series, which suggests the potential of using high temporal resolution MREG sequences to track dynamic resting-state networks at sub-minute time scale.

  2. EEG classification for motor imagery and resting state in BCI applications using multi-class Adaboost extreme learning machine

    Science.gov (United States)

    Gao, Lin; Cheng, Wei; Zhang, Jinhua; Wang, Jue

    2016-08-01

    Brain-computer interface (BCI) systems provide an alternative communication and control approach for people with limited motor function. Therefore, the feature extraction and classification approach should differentiate the relative unusual state of motion intention from a common resting state. In this paper, we sought a novel approach for multi-class classification in BCI applications. We collected electroencephalographic (EEG) signals registered by electrodes placed over the scalp during left hand motor imagery, right hand motor imagery, and resting state for ten healthy human subjects. We proposed using the Kolmogorov complexity (Kc) for feature extraction and a multi-class Adaboost classifier with extreme learning machine as base classifier for classification, in order to classify the three-class EEG samples. An average classification accuracy of 79.5% was obtained for ten subjects, which greatly outperformed commonly used approaches. Thus, it is concluded that the proposed method could improve the performance for classification of motor imagery tasks for multi-class samples. It could be applied in further studies to generate the control commands to initiate the movement of a robotic exoskeleton or orthosis, which finally facilitates the rehabilitation of disabled people.

  3. Challenges in Determining the Role of Rest and Exercise in the Management of Mild Traumatic Brain Injury.

    Science.gov (United States)

    Wells, Elizabeth M; Goodkin, Howard P; Griesbach, Grace S

    2016-01-01

    Current consensus guidelines recommending physical and cognitive rest until a patient is asymptomatic after a sports concussion (ie, a mild traumatic brain injury) are being called into question, particularly for patients who are slower to recover and in light of preclinical and clinical research demonstrating that exercise aids neurorehabilitation. The pathophysiological response to mild traumatic brain injury includes a complex neurometabolic cascade of events resulting in a neurologic energy deficit. It has been proposed that this energy deficit leads to a period of vulnerability during which the brain is at risk for additional injury, explains why early postconcussive symptoms are exacerbated by cognitive and physical exertion, and is used to rationalize absolute rest until all symptoms have resolved. However, at some point, rest might no longer be beneficial and exercise might need to be introduced. At both extremes, excessive exertion and prolonged avoidance of exercise (physical and mental) have negative consequences. Individuals who have experienced a concussion need guidance for avoidance of triggers of severe symptoms and a plan for graduated exercise to promote recovery as well as optimal functioning (physical, educational, and social) during the postconcussion period.

  4. Brain imaging studies in children with attention-deficit hyperactivity disorder revealed by resting-state fMRI degree centrality analysis%注意缺陷多动障碍儿童静息态功能磁共振度中心度的研究

    Institute of Scientific and Technical Information of China (English)

    江凯华; 沈惠娟; 李红新; 高敏; 易阳; 吴婷; 屠文娟; 张琴芬; 董选

    2014-01-01

    Objective To investigate the pathologic mechanisms of functional brain regions in attentiondeficit hyperactivity disorder (ADHD) patients through making comparisons of normal and ADHD children from the perspective of the network nodes with degree centrality(DC) analysis approach of resting-state functional magnetic resonance imaging(fMRI).Methods To carry out data analysis through DC approach on 30 school-age children and 30 ADHD children,both of whom had been examined by resting-state fMRI scans.Results It showed that ADHD children's scores were lower in the right posterior cingulate gyms,left medial superior frontal gyms,right inferior parietal gyrus,right middle frontal gyrus,left superior frontal gyrus and right superior frontal gyrus(t=-5.21,-3.53,-4.87,-4.21,-3.56,-4.06).There was statistically significant difference between the two groups (P<0.05).However,the ADHD group got higher DC scores in the cerebellar anterior lobe,right middle occipital,left middle cingulte gyrus and right middle cingulte gyrus than those of normal children (t =4.27,4.25,4.80,5.33).There was statistically significant difference between the two groups(P<0.05).Conclusion It is deemed that the decrease of DC in the default mode of network (DMN) and frontal gyrus results in the damage of central brain structure,which further leads to ADHD children' s difficulties in cognitive memory and executive control.Together with the influence of ADHD cerebral functional compensation,the increase of DC is believed to be connected with executive control disorders and aprosexia.DC is regarded as a new research method to study cognitive disorders of ADHD children.%目的 运用静息态功能磁共振(functional magnetic resonance imaging,fMRI)度中心度(degree centrality,DC)的分析技术,从网络节点的角度对注意缺陷多动障碍(attention-deficit hyperactivity disorder,ADHD)儿童与正常儿童进行比较研究,探讨ADHD功能脑区的病理机制.方法 学

  5. COHERENT STATES, FRACTALS AND BRAIN WAVES

    OpenAIRE

    Vitiello, Giuseppe

    2009-01-01

    I show that a functional representation of self-similarity (as the one occurring in fractals) is provided by squeezed coherent states. In this way, the dissipative model of brain is shown to account for the self-similarity in brain background activity suggested by power-law distributions of power spectral densities of electrocorticograms. I also briefly discuss the action-perception cycle in the dissipative model with reference to intentionality in terms of trajectories in the memory state sp...

  6. Drug polyconsumption is associated with increased synchronization of brain electrical-activity at rest and in a counting task.

    Science.gov (United States)

    Coullaut-Valera, R; Arbaiza, I; Bajo, R; Arrúe, R; López, M E; Coullaut-Valera, J; Correas, A; López-Sanz, D; Maestu, F; Papo, D

    2014-02-01

    Drug abusers typically consume not just one but several types of drugs, starting from alcohol and marijuana consumption, and then dramatically lapsing into addiction to harder drugs, such as cocaine, heroin, or amphetamine. The brain of drug abusers presents various structural and neurophysiological abnormalities, some of which may predate drug consumption onset. However, how these changes translate into modifications in functional brain connectivity is still poorly understood. To characterize functional connectivity patterns, we recorded Electroencephalogram (EEG) activity from 21 detoxified drug abusers and 20 age-matched control subjects performing a simple counting task and at rest activity. To evaluate the cortical brain connectivity network we applied the Synchronization Likelihood algorithm. The results showed that drug abusers had higher synchronization levels at low frequencies, mainly in the θ band (4-8 Hz) between frontal and posterior cortical regions. During the counting task, patients showed increased synchronization in the β (14-35 Hz), and γ (35-45 Hz) frequency bands, in fronto-posterior and interhemispheric temporal regions. Taken together 'slow-down' at rest and task-related 'over-exertion' could indicate that the brain of drug abusers is suffering from a premature form of ageing. Future studies will clarify whether this condition can be reversed following prolonged periods of abstinence.

  7. Insulin Resistance-Associated Interhemispheric Functional Connectivity Alterations in T2DM: A Resting-State fMRI Study

    Directory of Open Access Journals (Sweden)

    Wenqing Xia

    2015-01-01

    Full Text Available We aim to investigate whether decreased interhemispheric functional connectivity exists in patients with type 2 diabetes mellitus (T2DM by using resting-state functional magnetic resonance imaging (rs-fMRI. In addition, we sought to determine whether interhemispheric functional connectivity deficits associated with cognition and insulin resistance (IR among T2DM patients. We compared the interhemispheric resting state functional connectivity of 32 T2DM patients and 30 healthy controls using rs-fMRI. Partial correlation coefficients were used to detect the relationship between rs-fMRI information and cognitive or clinical data. Compared with healthy controls, T2DM patients showed bidirectional alteration of functional connectivity in several brain regions. Functional connectivity values in the middle temporal gyrus (MTG and in the superior frontal gyrus were inversely correlated with Trail Making Test-B score of patients. Notably, insulin resistance (log homeostasis model assessment-IR negatively correlated with functional connectivity in the MTG of patients. In conclusion, T2DM patients exhibit abnormal interhemispheric functional connectivity in several default mode network regions, particularly in the MTG, and such alteration is associated with IR. Alterations in interhemispheric functional connectivity might contribute to cognitive dysfunction in T2DM patients.

  8. Changes in low-frequency fluctuations in patients with antisocial personality disorder revealed by resting-state functional MRI.

    Directory of Open Access Journals (Sweden)

    Huasheng Liu

    Full Text Available Antisocial Personality Disorder (APD is a personality disorder that is most commonly associated with the legal and criminal justice systems. The study of the brain in APD has important implications in legal contexts and in helping ensure social stability. However, the neural contribution to the high prevalence of APD is still unclear. In this study, we used resting-state functional magnetic resonance imaging (fMRI to investigate the underlying neural mechanisms of APD. Thirty-two healthy individuals and thirty-five patients with APD were recruited. The amplitude of low-frequency fluctuations (ALFF was analyzed for the whole brain of all subjects. Our results showed that APD patients had a significant reduction in the ALFF in the right orbitofrontal cortex, the left temporal pole, the right inferior temporal gyrus, and the left cerebellum posterior lobe compared to normal controls. We observed that the right orbitofrontal cortex had a negative correlation between ALFF values and MMPI psychopathic deviate scores. Alterations in ALFF in these specific brain regions suggest that APD patients may be associated with abnormal activities in the fronto-temporal network. We propose that our results may contribute in a clinical and forensic context to a better understanding of APD.

  9. Evaluating the reliability of different preprocessing steps to estimate graph theoretical measures in resting state fMRI data.

    Science.gov (United States)

    Aurich, Nathassia K; Alves Filho, José O; Marques da Silva, Ana M; Franco, Alexandre R

    2015-01-01

    With resting-state functional MRI (rs-fMRI) there are a variety of post-processing methods that can be used to quantify the human brain connectome. However, there is also a choice of which preprocessing steps will be used prior to calculating the functional connectivity of the brain. In this manuscript, we have tested seven different preprocessing schemes and assessed the reliability between and reproducibility within the various strategies by means of graph theoretical measures. Different preprocessing schemes were tested on a publicly available dataset, which includes rs-fMRI data of healthy controls. The brain was parcellated into 190 nodes and four graph theoretical (GT) measures were calculated; global efficiency (GEFF), characteristic path length (CPL), average clustering coefficient (ACC), and average local efficiency (ALE). Our findings indicate that results can significantly differ based on which preprocessing steps are selected. We also found dependence between motion and GT measurements in most preprocessing strategies. We conclude that by using censoring based on outliers within the functional time-series as a processing, results indicate an increase in reliability of GT measurements with a reduction of the dependency of head motion.

  10. Effects of Methylphenidate on Resting-State Functional Connectivity of the Mesocorticolimbic Dopamine Pathways in Cocaine Addiction

    Science.gov (United States)

    Konova, Anna B.; Moeller, Scott J.; Tomasi, Dardo; Volkow, Nora D.; Goldstein, Rita Z.

    2015-01-01

    Importance Cocaine addiction is associated with altered resting-state functional connectivity among regions of the mesocorticolimbic dopamine pathways. Methylphenidate hydrochloride, an indirect dopamine agonist, normalizes task-related regional brain activity and associated behavior in cocaine users; however, the neural systems–level effects of methylphenidate in this population have not yet been described. Objective To use resting-state functional magnetic resonance imaging to examine changes in mesocorticolimbic connectivity with methylphenidate and how connectivity of affected pathways relates to severity of cocaine addiction. Design Randomized, placebo-controlled, before-after, crossover study. Setting Clinical research center. Participants Eighteen nonabstaining individuals with cocaine use disorders. Interventions Single doses of oral methylphenidate (20 mg) or placebo were administered at each of 2 study sessions. At each session, resting scans were acquired twice: immediately after drug administration (before the onset of effects [baseline]) and 120 minutes later (within the window of peak effects). Main outcomes and Measures Functional connectivity strength was evaluated using a seed voxel correlation approach. Changes in this measure were examined to characterize the neural systems–level effects of methylphenidate; severity of cocaine addiction was assessed by interview and questionnaire. Results Short-term methylphenidate administration reduced an abnormally strong connectivity of the ventral striatum with the dorsal striatum (putamen/globus pallidus), and lower connectivity between these regions during placebo administration uniquely correlated with less severe addiction. In contrast, methylphenidate strengthened several corticolimbic and corticocortical connections. Conclusions and Relevance These findings help elucidate the neural systems–level effects of methylphenidate and suggest that short-term methylphenidate can, at least transiently

  11. Interhemispheric functional connectivity and its relationships with clinical characteristics in major depressive disorder: a resting state fMRI study.

    Directory of Open Access Journals (Sweden)

    Li Wang

    Full Text Available BACKGROUND: Abnormalities in large-scale, structural and functional brain connectivity have been increasingly reported in patients with major depressive disorder (MDD. However, MDD-related alterations in functional interaction between the cerebral hemispheres are still not well understood. Resting state fMRI, which reveals spontaneous neural fluctuations in blood oxygen level dependent signals, provides a means to detect interhemispheric functional coherence. We examined the resting state functional connectivity (RSFC between the two hemispheres and its relationships with clinical characteristics in MDD patients using a recently proposed measurement named "voxel-mirrored homotopic connectivity (VMHC". METHODOLOGY/PRINCIPAL FINDINGS: We compared the interhemispheric RSFC, computed using the VMHC approach, of seventeen first-episode drug-naive patients with MDD and seventeen healthy controls. Compared to the controls, MDD patients showed significant VMHC decreases in the medial orbitofrontal gyrus, parahippocampal gyrus, fusiform gyrus, and occipital regions including the middle occipital gyrus and cuneus. In MDD patients, a negative correlation was found between VMHC of the fusiform gyrus and illness duration. Moreover, there were several regions whose VMHC showed significant negative correlations with the severity of cognitive disturbance, including the prefrontal regions, such as middle and inferior frontal gyri, and two regions in the cereballar crus. CONCLUSIONS/SIGNIFICANCE: These findings suggest that the functional coordination between homotopic brain regions is impaired in MDD patients, thereby providing new evidence supporting the interhemispheric connectivity deficits of MDD. The significant correlations between the VMHC and clinical characteristics in MDD patients suggest potential clinical implication of VMHC measures for MDD. Interhemispheric RSFC may serve as a useful screening method for evaluating MDD where neural connectivity is

  12. Resting-state qEEG predicts rate of second language learning in adults.

    Science.gov (United States)

    Prat, Chantel S; Yamasaki, Brianna L; Kluender, Reina A; Stocco, Andrea

    2016-01-01

    Understanding the neurobiological basis of individual differences in second language acquisition (SLA) is important for research on bilingualism, learning, and neural plasticity. The current study used quantitative electroencephalography (qEEG) to predict SLA in college-aged individuals. Baseline, eyes-closed resting-state qEEG was used to predict language learning rate during eight weeks of French exposure using an immersive, virtual scenario software. Individual qEEG indices predicted up to 60% of the variability in SLA, whereas behavioral indices of fluid intelligence, executive functioning, and working-memory capacity were not correlated with learning rate. Specifically, power in beta and low-gamma frequency ranges over right temporoparietal regions were strongly positively correlated with SLA. These results highlight the utility of resting-state EEG for studying the neurobiological basis of SLA in a relatively construct-free, paradigm-independent manner. PMID:27164483

  13. Abnormal cerebral functional connectivity in esophageal cancer patients with theory of mind deficits in resting state

    OpenAIRE

    Yin Cao; JianBo Xiang; Nong Qian; SuPing Sun; LiJun Hu; YongGui Yuan

    2015-01-01

    Objective: To explore the function of the default mode network (DMN) in the psychopathological mechanisms of theory of mind deficits in patients with an esophageal cancer concomitant with depression in resting the state. Subjects and Methods: Twenty-five cases of esophageal cancer with theory of mind deficits (test group) that meet the diagnostic criteria of esophageal cancer and neuropsychological tests, including Beck depression inventory, reading the mind in the eyes, and Faux pas, were...

  14. Resting-state subjective experience and EEG biomarkers are associated with sleep-onset latency

    OpenAIRE

    B. Alexander Diaz; Richard eHardstone; Mansvelder, Huibert D.; Van Someren, Eus J. W.; Klaus eLinkenkaer-Hansen

    2016-01-01

    Difficulties initiating sleep are common in several disorders, including insomnia and attention deficit hyperactivity disorder. These disorders are prevalent, bearing significant societal and financial costs which require the consideration of new treatment strategies and a better understanding of the physiological and cognitive processes surrounding the time of preparing for sleep or falling asleep. Here, we search for neuro-cognitive associations in the resting state and examine their releva...

  15. Considerations for resting state functional MRI and functional connectivity studies in rodents

    OpenAIRE

    Pan, Wen-Ju; Billings, Jacob C. W.; Grooms, Joshua K.; Shakil, Sadia; Keilholz, Shella D.

    2015-01-01

    Resting state functional MRI (rs-fMRI) and functional connectivity mapping have become w