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Sample records for brain resting state

  1. 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

    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

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

    NARCIS (Netherlands)

    Ferrarini, L.; Veer, I.M.; Baerends, E.; van Tol, M.J.; Renken, R.J.; van der Wee, N.J.A.; Veltman, D.J.; Aleman, A.; Zitman, F.G.; Penninx, B.W.J.H.; van Buchem, M.A.; Reiber, J.H.C.; Rombouts, S.A.R.B.; Milles, J.

    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

  3. Characterizing Resting-State Brain Function Using Arterial Spin Labeling

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    Jann, Kay; Wang, Danny J.J.

    2015-01-01

    Abstract Arterial spin labeling (ASL) is an increasingly established magnetic resonance imaging (MRI) technique that is finding broader applications in studying the healthy and diseased brain. This review addresses the use of ASL to assess brain function in the resting state. Following a brief technical description, we discuss the use of ASL in the following main categories: (1) resting-state functional connectivity (FC) measurement: the use of ASL-based cerebral blood flow (CBF) measurements as an alternative to the blood oxygen level-dependent (BOLD) technique to assess resting-state FC; (2) the link between network CBF and FC measurements: the use of network CBF as a surrogate of the metabolic activity within corresponding networks; and (3) the study of resting-state dynamic CBF-BOLD coupling and cerebral metabolism: the use of dynamic CBF information obtained using ASL to assess dynamic CBF-BOLD coupling and oxidative metabolism in the resting state. In addition, we summarize some future challenges and interesting research directions for ASL, including slice-accelerated (multiband) imaging as well as the effects of motion and other physiological confounds on perfusion-based FC measurement. In summary, this work reviews the state-of-the-art of ASL and establishes it as an increasingly viable MRI technique with high translational value in studying resting-state brain function. PMID:26106930

  4. Hierarchical functional modularity in the resting-state human brain.

    Science.gov (United States)

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

    2009-07-01

    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 more advanced topological property, has been hypothesized to be evolutionary advantageous, contributing to adaptive aspects of anatomical and functional brain connectivity. However, current definitions of modularity for complex networks focus on nonoverlapping clusters, and are seriously limited by disregarding inclusive relationships. Therefore, BFC's modularity has been mainly qualitatively investigated. Here, we introduce a new definition of modularity, based on a recently improved clustering measurement, which overcomes limitations of previous definitions, and apply it to the study of BFC in resting state fMRI of 53 healthy subjects. Results show hierarchical functional modularity in the brain. Copyright 2009 Wiley-Liss, Inc

  5. Resting state brain networks in the prairie vole.

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    Ortiz, Juan J; Portillo, Wendy; Paredes, Raul G; Young, Larry J; Alcauter, Sarael

    2018-01-19

    Resting state functional magnetic resonance imaging (rsfMRI) has shown the hierarchical organization of the human brain into large-scale complex networks, referred as resting state networks. This technique has turned into a promising translational research tool after the finding of similar resting state networks in non-human primates, rodents and other animal models of great value for neuroscience. Here, we demonstrate and characterize the presence of resting states networks in Microtus ochrogaster, the prairie vole, an extraordinary animal model to study complex human-like social behavior, with potential implications for the research of normal social development, addiction and neuropsychiatric disorders. Independent component analysis of rsfMRI data from isoflurane-anestethized prairie voles resulted in cortical and subcortical networks, including primary motor and sensory networks, but also included putative salience and default mode networks. We further discuss how future research could help to close the gap between the properties of the large scale functional organization and the underlying neurobiology of several aspects of social cognition. These results contribute to the evidence of preserved resting state brain networks across species and provide the foundations to explore the use of rsfMRI in the prairie vole for basic and translational research.

  6. 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.

  7. Resting-state brain activity in adult males who stutter.

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    Yun Xuan

    Full Text Available Although developmental stuttering has been extensively studied with structural and task-based functional magnetic resonance imaging (fMRI, few studies have focused on resting-state brain activity in this disorder. We investigated resting-state brain activity of stuttering subjects by analyzing the amplitude of low-frequency fluctuation (ALFF, region of interest (ROI-based functional connectivity (FC and independent component analysis (ICA-based FC. Forty-four adult males with developmental stuttering and 46 age-matched fluent male controls were scanned using resting-state fMRI. ALFF, ROI-based FCs and ICA-based FCs were compared between male stuttering subjects and fluent controls in a voxel-wise manner. Compared with fluent controls, stuttering subjects showed increased ALFF in left brain areas related to speech motor and auditory functions and bilateral prefrontal cortices related to cognitive control. However, stuttering subjects showed decreased ALFF in the left posterior language reception area and bilateral non-speech motor areas. ROI-based FC analysis revealed decreased FC between the posterior language area involved in the perception and decoding of sensory information and anterior brain area involved in the initiation of speech motor function, as well as increased FC within anterior or posterior speech- and language-associated areas and between the prefrontal areas and default-mode network (DMN in stuttering subjects. ICA showed that stuttering subjects had decreased FC in the DMN and increased FC in the sensorimotor network. Our findings support the concept that stuttering subjects have deficits in multiple functional systems (motor, language, auditory and DMN and in the connections between them.

  8. Resting-State Brain Activity in Adult Males Who Stutter

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    Zhu, Chaozhe; Wang, Liang; Yan, Qian; Lin, Chunlan; Yu, Chunshui

    2012-01-01

    Although developmental stuttering has been extensively studied with structural and task-based functional magnetic resonance imaging (fMRI), few studies have focused on resting-state brain activity in this disorder. We investigated resting-state brain activity of stuttering subjects by analyzing the amplitude of low-frequency fluctuation (ALFF), region of interest (ROI)-based functional connectivity (FC) and independent component analysis (ICA)-based FC. Forty-four adult males with developmental stuttering and 46 age-matched fluent male controls were scanned using resting-state fMRI. ALFF, ROI-based FCs and ICA-based FCs were compared between male stuttering subjects and fluent controls in a voxel-wise manner. Compared with fluent controls, stuttering subjects showed increased ALFF in left brain areas related to speech motor and auditory functions and bilateral prefrontal cortices related to cognitive control. However, stuttering subjects showed decreased ALFF in the left posterior language reception area and bilateral non-speech motor areas. ROI-based FC analysis revealed decreased FC between the posterior language area involved in the perception and decoding of sensory information and anterior brain area involved in the initiation of speech motor function, as well as increased FC within anterior or posterior speech- and language-associated areas and between the prefrontal areas and default-mode network (DMN) in stuttering subjects. ICA showed that stuttering subjects had decreased FC in the DMN and increased FC in the sensorimotor network. Our findings support the concept that stuttering subjects have deficits in multiple functional systems (motor, language, auditory and DMN) and in the connections between them. PMID:22276215

  9. Detecting Mild Traumatic Brain Injury Using Resting State Magnetoencephalographic Connectivity.

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    Vasily A Vakorin

    2016-12-01

    Full Text Available Accurate means to detect mild traumatic brain injury (mTBI using objective and quantitative measures remain elusive. Conventional imaging typically detects no abnormalities despite post-concussive symptoms. In the present study, we recorded resting state magnetoencephalograms (MEG from adults with mTBI and controls. Atlas-guided reconstruction of resting state activity was performed for 90 cortical and subcortical regions, and calculation of inter-regional oscillatory phase synchrony at various frequencies was performed. We demonstrate that mTBI is associated with reduced network connectivity in the delta and gamma frequency range (>30 Hz, together with increased connectivity in the slower alpha band (8-12 Hz. A similar temporal pattern was associated with correlations between network connectivity and the length of time between the injury and the MEG scan. Using such resting state MEG network synchrony we were able to detect mTBI with 88% accuracy. Classification confidence was also correlated with clinical symptom severity scores. These results provide the first evidence that imaging of MEG network connectivity, in combination with machine learning, has the potential to accurately detect and determine the severity of mTBI.

  10. Cognitive and default-mode resting state networks: do male and female brains "rest" differently?

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    Weissman-Fogel, Irit; Moayedi, Massieh; Taylor, Keri S; Pope, Geoff; Davis, Karen D

    2010-11-01

    Variability in human behavior related to sex is supported by neuroimaging studies showing differences in brain activation patterns during cognitive task performance. An emerging field is examining the human connectome, including networks of brain regions that are not only temporally-correlated during different task conditions, 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 task performance and behavior under certain conditions. Therefore, our aim was to determine whether sex differences exist during a task-free resting state for two networks associated with cognitive task performance (executive control network (ECN), salience network (SN)) and the default mode network (DMN). Forty-nine healthy subjects (26 females, 23 males) underwent a 5-min task-free fMRI scan in a 3T MRI. An independent components analysis (ICA) was performed to identify the best-fit IC for each network based on specific spatial nodes defined in previous studies. To determine the consistency of these networks across subjects we performed self-organizing group-level ICA analyses. There were no significant differences between sexes in the functional connectivity of the brain areas within the ECN, SN, or the DMN. These important findings highlight the robustness of intrinsic connectivity of these resting state networks and their similarity between sexes. Furthermore, our findings suggest that resting state fMRI studies do not need to be controlled for sex. © 2010 Wiley-Liss, Inc.

  11. Task vs. rest-different network configurations between the coactivation and the resting-state brain networks.

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    Di, Xin; Gohel, Suril; Kim, Eun H; Biswal, Bharat B

    2013-01-01

    There is a growing interest in studies of human brain networks using resting-state functional magnetic resonance imaging (fMRI). However, it is unclear whether and how brain networks measured during the resting-state exhibit comparable properties to brain networks during task performance. In the present study, we investigated meta-analytic coactivation patterns among brain regions based upon published neuroimaging studies, and compared the coactivation network configurations with those in the resting-state network. The strength of resting-state functional connectivity between two regions were strongly correlated with the coactivation strength. However, the coactivation network showed greater global efficiency, smaller mean clustering coefficient, and lower modularity compared with the resting-state network, which suggest a more efficient global information transmission and between system integrations during task performing. Hub shifts were also observed within the thalamus and the left inferior temporal cortex. The thalamus and the left inferior temporal cortex exhibited higher and lower degrees, respectively in the coactivation network compared with the resting-state network. These results shed light regarding the reconfiguration of the brain networks between task and resting-state conditions, and highlight the role of the thalamus in change of network configurations in task vs. rest.

  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

  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

    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 activity

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

    International Nuclear Information System (INIS)

    Long Miaomiao; Ni Hongyan

    2013-01-01

    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. Spatiotemporal psychopathology I: No rest for the brain's resting state activity in depression? Spatiotemporal psychopathology of depressive symptoms.

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    Northoff, Georg

    2016-01-15

    Despite intense neurobiological investigation in psychiatric disorders like major depressive disorder (MDD), the basic disturbance that underlies the psychopathological symptoms of MDD remains, nevertheless, unclear. Neuroimaging has focused mainly on the brain's extrinsic activity, specifically task-evoked or stimulus-induced activity, as related to the various sensorimotor, affective, cognitive, and social functions. Recently, the focus has shifted to the brain's intrinsic activity, otherwise known as its resting state activity. While various abnormalities have been observed during this activity, their meaning and significance for depression, along with its various psychopathological symptoms, are yet to be defined. Based on findings in healthy brain resting state activity and its particular spatial and temporal structure - defined in a functional and physiological sense rather than anatomical and structural - I claim that the various depressive symptoms are spatiotemporal disturbances of the resting state activity and its spatiotemporal structure. This is supported by recent findings that link ruminations and increased self-focus in depression to abnormal spatial organization of resting state activity. Analogously, affective and cognitive symptoms like anhedonia, suicidal ideation, and thought disorder can be traced to an increased focus on the past, increased past-focus as basic temporal disturbance o the resting state. Based on these findings, I conclude that the various depressive symptoms must be conceived as spatiotemporal disturbances of the brain's resting state's activity and its spatiotemporal structure. Importantly, this entails a new form of psychopathology, "Spatiotemporal Psychopathology" that directly links the brain and psyche, therefore having major diagnostic and therapeutic implications for clinical practice. Copyright © 2015 Elsevier B.V. All rights reserved.

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

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    Rzucidlo, Justyna K; Roseman, Paige L; Laurienti, Paul J; Dagenbach, Dale

    2013-01-01

    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. 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. 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. 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.

  18. Complex network analysis of resting-state fMRI of the brain.

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    Anwar, Abdul Rauf; Hashmy, Muhammad Yousaf; Imran, Bilal; Riaz, Muhammad Hussnain; Mehdi, Sabtain Muhammad Muntazir; Muthalib, Makii; Perrey, Stephane; Deuschl, Gunther; Groppa, Sergiu; Muthuraman, Muthuraman

    2016-08-01

    Due to the fact that the brain activity hardly ever diminishes in healthy individuals, analysis of resting state functionality of the brain seems pertinent. Various resting state networks are active inside the idle brain at any time. Based on various neuro-imaging studies, it is understood that various structurally distant regions of the brain could be functionally connected. Regions of the brain, that are functionally connected, during rest constitutes to the resting state network. In the present study, we employed the complex network measures to estimate the presence of community structures within a network. Such estimate is named as modularity. Instead of using a traditional correlation matrix, we used a coherence matrix taken from the causality measure between different nodes. Our results show that in prolonged resting state the modularity starts to decrease. This decrease was observed in all the resting state networks and on both sides of the brain. Our study highlights the usage of coherence matrix instead of correlation matrix for complex network analysis.

  19. Resting state cerebral blood flow with arterial spin labeling MRI in developing human brains.

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    Liu, Feng; Duan, Yunsuo; Peterson, Bradley S; Asllani, Iris; Zelaya, Fernando; Lythgoe, David; Kangarlu, Alayar

    2018-07-01

    The development of brain circuits is coupled with changes in neurovascular coupling, which refers to the close relationship between neural activity and cerebral blood flow (CBF). Studying the characteristics of CBF during resting state in developing brain can be a complementary way to understand the functional connectivity of the developing brain. Arterial spin labeling (ASL), as a noninvasive MR technique, is particularly attractive for studying cerebral perfusion in children and even newborns. We have collected pulsed ASL data in resting state for 47 healthy subjects from young children to adolescence (aged from 6 to 20 years old). In addition to studying the developmental change of static CBF maps during resting state, we also analyzed the CBF time series to reveal the dynamic characteristics of CBF in differing age groups. We used the seed-based correlation analysis to examine the temporal relationship of CBF time series between the selected ROIs and other brain regions. We have shown the developmental patterns in both static CBF maps and dynamic characteristics of CBF. While higher CBF of default mode network (DMN) in all age groups supports that DMN is the prominent active network during the resting state, the CBF connectivity patterns of some typical resting state networks show distinct patterns of metabolic activity during the resting state in the developing brains. Copyright © 2018 European Paediatric Neurology Society. All rights reserved.

  20. Detecting brain dynamics during resting state: a tensor based evolutionary clustering approach

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    Al-sharoa, Esraa; Al-khassaweneh, Mahmood; Aviyente, Selin

    2017-08-01

    Human brain is a complex network with connections across different regions. Understanding the functional connectivity (FC) of the brain is important both during resting state and task; as disruptions in connectivity patterns are indicators of different psychopathological and neurological diseases. In this work, we study the resting state functional connectivity networks (FCNs) of the brain from fMRI BOLD signals. Recent studies have shown that FCNs are dynamic even during resting state and understanding the temporal dynamics of FCNs is important for differentiating between different conditions. Therefore, it is important to develop algorithms to track the dynamic formation and dissociation of FCNs of the brain during resting state. In this paper, we propose a two step tensor based community detection algorithm to identify and track the brain network community structure across time. First, we introduce an information-theoretic function to reduce the dynamic FCN and identify the time points that are similar topologically to combine them into a tensor. These time points will be used to identify the different FC states. Second, a tensor based spectral clustering approach is developed to identify the community structure of the constructed tensors. The proposed algorithm applies Tucker decomposition to the constructed tensors and extract the orthogonal factor matrices along the connectivity mode to determine the common subspace within each FC state. The detected community structure is summarized and described as FC states. The results illustrate the dynamic structure of resting state networks (RSNs), including the default mode network, somatomotor network, subcortical network and visual network.

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

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    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.

  2. Intrinsic resting-state activity predicts working memory brain activation and behavioral performance.

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    Zou, Qihong; Ross, Thomas J; Gu, Hong; Geng, Xiujuan; Zuo, Xi-Nian; Hong, L Elliot; Gao, Jia-Hong; Stein, Elliot A; Zang, Yu-Feng; Yang, Yihong

    2013-12-01

    Although resting-state brain activity has been demonstrated to correspond with task-evoked brain activation, the relationship between intrinsic and evoked brain activity has not been fully characterized. For example, it is unclear whether intrinsic activity can also predict task-evoked deactivation and whether the rest-task relationship is dependent on task load. In this study, we addressed these issues on 40 healthy control subjects using resting-state and task-driven [N-back working memory (WM) task] functional magnetic resonance imaging data collected in the same session. Using amplitude of low-frequency fluctuation (ALFF) as an index of intrinsic resting-state activity, we found that ALFF in the middle frontal gyrus and inferior/superior parietal lobules was positively correlated with WM task-evoked activation, while ALFF in the medial prefrontal cortex, posterior cingulate cortex, superior frontal gyrus, superior temporal gyrus, and fusiform gyrus was negatively correlated with WM task-evoked deactivation. Further, the relationship between the intrinsic resting-state activity and task-evoked activation in lateral/superior frontal gyri, inferior/superior parietal lobules, superior temporal gyrus, and midline regions was stronger at higher WM task loads. In addition, both resting-state activity and the task-evoked activation in the superior parietal lobule/precuneus were significantly correlated with the WM task behavioral performance, explaining similar portions of intersubject performance variance. Together, these findings suggest that intrinsic resting-state activity facilitates or is permissive of specific brain circuit engagement to perform a cognitive task, and that resting activity can predict subsequent task-evoked brain responses and behavioral performance. Copyright © 2012 Wiley Periodicals, Inc.

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

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    Hongwen eSong; Zhiling eZou; Juan eKou; Yang eLiu; LiZhuang eYang; Anna ezilverstand; Federicod’Oleire eUquillas; Xiaochu eZhang; Xiaochu eZhang; Xiaochu eZhang

    2015-01-01

    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...

  4. 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

  5. Role of mitochondrial calcium uptake homeostasis in resting state fMRI brain networks.

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    Kannurpatti, Sridhar S; Sanganahalli, Basavaraju G; Herman, Peter; Hyder, Fahmeed

    2015-11-01

    Mitochondrial Ca(2+) uptake influences both brain energy metabolism and neural signaling. Given that brain mitochondrial organelles are distributed in relation to vascular density, which varies considerably across brain regions, we hypothesized different physiological impacts of mitochondrial Ca(2+) uptake across brain regions. We tested the hypothesis by monitoring brain "intrinsic activity" derived from the resting state functional MRI (fMRI) blood oxygen level dependent (BOLD) fluctuations in different functional networks spanning the somatosensory cortex, caudate putamen, hippocampus and thalamus, in normal and perturbed mitochondrial Ca(2+) uptake states. In anesthetized rats at 11.7 T, mitochondrial Ca(2+) uptake was inhibited or enhanced respectively by treatments with Ru360 or kaempferol. Surprisingly, mitochondrial Ca(2+) uptake inhibition by Ru360 and enhancement by kaempferol led to similar dose-dependent decreases in brain-wide intrinsic activities in both the frequency domain (spectral amplitude) and temporal domain (resting state functional connectivity; RSFC). The fact that there were similar dose-dependent decreases in the frequency and temporal domains of the resting state fMRI-BOLD fluctuations during mitochondrial Ca(2+) uptake inhibition or enhancement indicated that mitochondrial Ca(2+) uptake and its homeostasis may strongly influence the brain's functional organization at rest. Interestingly, the resting state fMRI-derived intrinsic activities in the caudate putamen and thalamic regions saturated much faster with increasing dosage of either drug treatment than the drug-induced trends observed in cortical and hippocampal regions. Regional differences in how the spectral amplitude and RSFC changed with treatment indicate distinct mitochondrion-mediated spontaneous neuronal activity coupling within the various RSFC networks determined by resting state fMRI. Copyright © 2015 John Wiley & Sons, Ltd.

  6. Brain entropy and human intelligence: A resting-state fMRI study.

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    Saxe, Glenn N; Calderone, Daniel; Morales, Leah J

    2018-01-01

    Human intelligence comprises comprehension of and reasoning about an infinitely variable external environment. A brain capable of large variability in neural configurations, or states, will more easily understand and predict variable external events. Entropy measures the variety of configurations possible within a system, and recently the concept of brain entropy has been defined as the number of neural states a given brain can access. This study investigates the relationship between human intelligence and brain entropy, to determine whether neural variability as reflected in neuroimaging signals carries information about intellectual ability. We hypothesize that intelligence will be positively associated with entropy in a sample of 892 healthy adults, using resting-state fMRI. Intelligence is measured with the Shipley Vocabulary and WASI Matrix Reasoning tests. Brain entropy was positively associated with intelligence. This relation was most strongly observed in the prefrontal cortex, inferior temporal lobes, and cerebellum. This relationship between high brain entropy and high intelligence indicates an essential role for entropy in brain functioning. It demonstrates that access to variable neural states predicts complex behavioral performance, and specifically shows that entropy derived from neuroimaging signals at rest carries information about intellectual capacity. Future work in this area may elucidate the links between brain entropy in both resting and active states and various forms of intelligence. This insight has the potential to provide predictive information about adaptive behavior and to delineate the subdivisions and nature of intelligence based on entropic patterns.

  7. Brain entropy and human intelligence: A resting-state fMRI study

    Science.gov (United States)

    Calderone, Daniel; Morales, Leah J.

    2018-01-01

    Human intelligence comprises comprehension of and reasoning about an infinitely variable external environment. A brain capable of large variability in neural configurations, or states, will more easily understand and predict variable external events. Entropy measures the variety of configurations possible within a system, and recently the concept of brain entropy has been defined as the number of neural states a given brain can access. This study investigates the relationship between human intelligence and brain entropy, to determine whether neural variability as reflected in neuroimaging signals carries information about intellectual ability. We hypothesize that intelligence will be positively associated with entropy in a sample of 892 healthy adults, using resting-state fMRI. Intelligence is measured with the Shipley Vocabulary and WASI Matrix Reasoning tests. Brain entropy was positively associated with intelligence. This relation was most strongly observed in the prefrontal cortex, inferior temporal lobes, and cerebellum. This relationship between high brain entropy and high intelligence indicates an essential role for entropy in brain functioning. It demonstrates that access to variable neural states predicts complex behavioral performance, and specifically shows that entropy derived from neuroimaging signals at rest carries information about intellectual capacity. Future work in this area may elucidate the links between brain entropy in both resting and active states and various forms of intelligence. This insight has the potential to provide predictive information about adaptive behavior and to delineate the subdivisions and nature of intelligence based on entropic patterns. PMID:29432427

  8. Resting-state oscillatory brain dynamics in Alzheimer disease

    NARCIS (Netherlands)

    de Haan, W.; Stam, C.J.; Jones, B.F.; Zuiderwijk, I.M.; van Dijk, B.W.; Scheltens, P.

    2008-01-01

    Altered oscillatory brain activity in Alzheimer disease (AD) may reflect underlying neuropathological changes, and its characterization might lead to new diagnostic possibilities. The present study using quantitative magnetoencephalography was set up to examine power spectrum changes in AD patients,

  9. Soft drink effects on sensorimotor rhythm brain computer interface performance and resting-state spectral power.

    Science.gov (United States)

    Mundahl, John; Jianjun Meng; He, Jeffrey; Bin He

    2016-08-01

    Brain-computer interface (BCI) systems allow users to directly control computers and other machines by modulating their brain waves. In the present study, we investigated the effect of soft drinks on resting state (RS) EEG signals and BCI control. Eight healthy human volunteers each participated in three sessions of BCI cursor tasks and resting state EEG. During each session, the subjects drank an unlabeled soft drink with either sugar, caffeine, or neither ingredient. A comparison of resting state spectral power shows a substantial decrease in alpha and beta power after caffeine consumption relative to control. Despite attenuation of the frequency range used for the control signal, caffeine average BCI performance was the same as control. Our work provides a useful characterization of caffeine, the world's most popular stimulant, on brain signal frequencies and their effect on BCI performance.

  10. Altered resting state brain networks in Parkinson's disease.

    Directory of Open Access Journals (Sweden)

    Martin Göttlich

    Full Text Available Parkinson's disease (PD is a neurodegenerative disorder affecting dopaminergic neurons in the substantia nigra leading to dysfunctional cortico-striato-thalamic-cortical loops. In addition to the characteristic motor symptoms, PD patients often show cognitive impairments, affective changes and other non-motor symptoms, suggesting system-wide effects on brain function. Here, we used functional magnetic resonance imaging and graph-theory based analysis methods to investigate altered whole-brain intrinsic functional connectivity in PD patients (n = 37 compared to healthy controls (n = 20. Global network properties indicated less efficient processing in PD. Analysis of brain network modules pointed to increased connectivity within the sensorimotor network, but decreased interaction of the visual network with other brain modules. We found lower connectivity mainly between the cuneus and the ventral caudate, medial orbitofrontal cortex and the temporal lobe. To identify regions of altered connectivity, we mapped the degree of intrinsic functional connectivity both on ROI- and on voxel-level across the brain. Compared to healthy controls, PD patients showed lower connectedness in the medial and middle orbitofrontal cortex. The degree of connectivity was also decreased in the occipital lobe (cuneus and calcarine, but increased in the superior parietal cortex, posterior cingulate gyrus, supramarginal gyrus and supplementary motor area. Our results on global network and module properties indicated that PD manifests as a disconnection syndrome. This was most apparent in the visual network module. The higher connectedness within the sensorimotor module in PD patients may be related to compensation mechanism in order to overcome the functional deficit of the striato-cortical motor loops or to loss of mutual inhibition between brain networks. Abnormal connectivity in the visual network may be related to adaptation and compensation processes as a consequence

  11. Immanuel Kant's mind and the brain's resting state.

    Science.gov (United States)

    Northoff, Georg

    2012-07-01

    The early philosopher Immanuel Kant suggested that the mind’s intrinsic features are intimately linked to the extrinsic stimuli of the environment it processes. Currently, the field faces an analogous problem with regard to the brain. Kant’s ideas may provide novel insights into how the brain’s intrinsic features must be so that they can be linked to the neural processing of extrinsic stimuli to enable the latter’s association with consciousness and self.

  12. Estimating repetitive spatiotemporal patterns from resting-state brain activity data.

    Science.gov (United States)

    Takeda, Yusuke; Hiroe, Nobuo; Yamashita, Okito; Sato, Masa-Aki

    2016-06-01

    Repetitive spatiotemporal patterns in spontaneous brain activities have been widely examined in non-human studies. These studies have reported that such patterns reflect past experiences embedded in neural circuits. In human magnetoencephalography (MEG) and electroencephalography (EEG) studies, however, spatiotemporal patterns in resting-state brain activities have not been extensively examined. This is because estimating spatiotemporal patterns from resting-state MEG/EEG data is difficult due to their unknown onsets. Here, we propose a method to estimate repetitive spatiotemporal patterns from resting-state brain activity data, including MEG/EEG. Without the information of onsets, the proposed method can estimate several spatiotemporal patterns, even if they are overlapping. We verified the performance of the method by detailed simulation tests. Furthermore, we examined whether the proposed method could estimate the visual evoked magnetic fields (VEFs) without using stimulus onset information. The proposed method successfully detected the stimulus onsets and estimated the VEFs, implying the applicability of this method to real MEG data. The proposed method was applied to resting-state functional magnetic resonance imaging (fMRI) data and MEG data. The results revealed informative spatiotemporal patterns representing consecutive brain activities that dynamically change with time. Using this method, it is possible to reveal discrete events spontaneously occurring in our brains, such as memory retrieval. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

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

    International Nuclear Information System (INIS)

    Hayashi, Toshihiro

    2011-01-01

    Spatial patterns of spontaneous fluctuations in blood oxygenation level-dependent (BOLD) signals reflect the underlying neural architecture. The study of the brain network based on these self-organized patterns is termed resting-state functional MRI (fMRI). This review article aims at briefly reviewing a basic concept of this technology and discussing its implications for neuropsychological studies. First, the technical aspects of resting-state fMRI, including signal sources, physiological artifacts, image acquisition, and analytical methods such as seed-based correlation analysis and independent component analysis, are explained, followed by a discussion on the major resting-state networks, including the default mode network. In addition, the structure-function correlation studied using diffuse tensor imaging and resting-state fMRI is briefly discussed. Second, I have discussed the reservations and potential pitfalls of 2 major imaging methods: voxel-based lesion-symptom mapping and task fMRI. Problems encountered with voxel-based lesion-symptom mapping can be overcome by using resting-state fMRI and evaluating undamaged brain networks in patients. Regarding task fMRI in patients, I have also emphasized the importance of evaluating the baseline brain activity because the amplitude of activation in BOLD fMRI is hard to interpret as the same baseline cannot be assumed for both patient and normal groups. (author)

  14. Brain dynamics of post-task resting state are influenced by expertise: Insights from baseball players.

    Science.gov (United States)

    Muraskin, Jordan; Dodhia, Sonam; Lieberman, Gregory; Garcia, Javier O; Verstynen, Timothy; Vettel, Jean M; Sherwin, Jason; Sajda, Paul

    2016-12-01

    Post-task resting state dynamics can be viewed as a task-driven state where behavioral performance is improved through endogenous, non-explicit learning. Tasks that have intrinsic value for individuals are hypothesized to produce post-task resting state dynamics that promote learning. We measured simultaneous fMRI/EEG and DTI in Division-1 collegiate baseball players and compared to a group of controls, examining differences in both functional and structural connectivity. Participants performed a surrogate baseball pitch Go/No-Go task before a resting state scan, and we compared post-task resting state connectivity using a seed-based analysis from the supplementary motor area (SMA), an area whose activity discriminated players and controls in our previous results using this task. Although both groups were equally trained on the task, the experts showed differential activity in their post-task resting state consistent with motor learning. Specifically, we found (1) differences in bilateral SMA-L Insula functional connectivity between experts and controls that may reflect group differences in motor learning, (2) differences in BOLD-alpha oscillation correlations between groups suggests variability in modulatory attention in the post-task state, and (3) group differences between BOLD-beta oscillations that may indicate cognitive processing of motor inhibition. Structural connectivity analysis identified group differences in portions of the functionally derived network, suggesting that functional differences may also partially arise from variability in the underlying white matter pathways. Generally, we find that brain dynamics in the post-task resting state differ as a function of subject expertise and potentially result from differences in both functional and structural connectivity. Hum Brain Mapp 37:4454-4471, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals

  15. Reconfiguration of Brain Network Architectures between Resting-State and Complexity-Dependent Cognitive Reasoning.

    Science.gov (United States)

    Hearne, Luke J; Cocchi, Luca; Zalesky, Andrew; Mattingley, Jason B

    2017-08-30

    Our capacity for higher cognitive reasoning has a measurable limit. This limit is thought to arise from the brain's capacity to flexibly reconfigure interactions between spatially distributed networks. Recent work, however, has suggested that reconfigurations of task-related networks are modest when compared with intrinsic "resting-state" network architecture. Here we combined resting-state and task-driven functional magnetic resonance imaging to examine how flexible, task-specific reconfigurations associated with increasing reasoning demands are integrated within a stable intrinsic brain topology. Human participants (21 males and 28 females) underwent an initial resting-state scan, followed by a cognitive reasoning task involving different levels of complexity, followed by a second resting-state scan. The reasoning task required participants to deduce the identity of a missing element in a 4 × 4 matrix, and item difficulty was scaled parametrically as determined by relational complexity theory. Analyses revealed that external task engagement was characterized by a significant change in functional brain modules. Specifically, resting-state and null-task demand conditions were associated with more segregated brain-network topology, whereas increases in reasoning complexity resulted in merging of resting-state modules. Further increments in task complexity did not change the established modular architecture, but affected selective patterns of connectivity between frontoparietal, subcortical, cingulo-opercular, and default-mode networks. Larger increases in network efficiency within the newly established task modules were associated with higher reasoning accuracy. Our results shed light on the network architectures that underlie external task engagement, and highlight selective changes in brain connectivity supporting increases in task complexity. SIGNIFICANCE STATEMENT Humans have clear limits in their ability to solve complex reasoning problems. It is thought that

  16. Increased power spectral density in resting-state pain-related brain networks in fibromyalgia.

    Science.gov (United States)

    Kim, Ji-Young; Kim, Seong-Ho; Seo, Jeehye; Kim, Sang-Hyon; Han, Seung Woo; Nam, Eon Jeong; Kim, Seong-Kyu; Lee, Hui Joong; Lee, Seung-Jae; Kim, Yang-Tae; Chang, Yongmin

    2013-09-01

    Fibromyalgia (FM), characterized by chronic widespread pain, is known to be associated with heightened responses to painful stimuli and atypical resting-state functional connectivity among pain-related regions of the brain. Previous studies of FM using resting-state functional magnetic resonance imaging (rs-fMRI) have focused on intrinsic functional connectivity, which maps the spatial distribution of temporal correlations among spontaneous low-frequency fluctuation in functional MRI (fMRI) resting-state data. In the current study, using rs-fMRI data in the frequency domain, we investigated the possible alteration of power spectral density (PSD) of low-frequency fluctuation in brain regions associated with central pain processing in patients with FM. rsfMRI data were obtained from 19 patients with FM and 20 age-matched healthy female control subjects. For each subject, the PSDs for each brain region identified from functional connectivity maps were computed for the frequency band of 0.01 to 0.25 Hz. For each group, the average PSD was determined for each brain region and a 2-sample t test was performed to determine the difference in power between the 2 groups. According to the results, patients with FM exhibited significantly increased frequency power in the primary somatosensory cortex (S1), supplementary motor area (SMA), dorsolateral prefrontal cortex, and amygdala. In patients with FM, the increase in PSD did not show an association with depression or anxiety. Therefore, our findings of atypical increased frequency power during the resting state in pain-related brain regions may implicate the enhanced resting-state baseline neural activity in several brain regions associated with pain processing in FM. Copyright © 2013 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

  17. Resting state functional MRI in Parkinson's disease: the impact of deep brain stimulation on 'effective' connectivity.

    Science.gov (United States)

    Kahan, Joshua; Urner, Maren; Moran, Rosalyn; Flandin, Guillaume; Marreiros, Andre; Mancini, Laura; White, Mark; Thornton, John; Yousry, Tarek; Zrinzo, Ludvic; Hariz, Marwan; Limousin, Patricia; Friston, Karl; Foltynie, Tom

    2014-04-01

    Depleted of dopamine, the dynamics of the parkinsonian brain impact on both 'action' and 'resting' motor behaviour. Deep brain stimulation has become an established means of managing these symptoms, although its mechanisms of action remain unclear. Non-invasive characterizations of induced brain responses, and the effective connectivity underlying them, generally appeals to dynamic causal modelling of neuroimaging data. When the brain is at rest, however, this sort of characterization has been limited to correlations (functional connectivity). In this work, we model the 'effective' connectivity underlying low frequency blood oxygen level-dependent fluctuations in the resting Parkinsonian motor network-disclosing the distributed effects of deep brain stimulation on cortico-subcortical connections. Specifically, we show that subthalamic nucleus deep brain stimulation modulates all the major components of the motor cortico-striato-thalamo-cortical loop, including the cortico-striatal, thalamo-cortical, direct and indirect basal ganglia pathways, and the hyperdirect subthalamic nucleus projections. The strength of effective subthalamic nucleus afferents and efferents were reduced by stimulation, whereas cortico-striatal, thalamo-cortical and direct pathways were strengthened. Remarkably, regression analysis revealed that the hyperdirect, direct, and basal ganglia afferents to the subthalamic nucleus predicted clinical status and therapeutic response to deep brain stimulation; however, suppression of the sensitivity of the subthalamic nucleus to its hyperdirect afferents by deep brain stimulation may subvert the clinical efficacy of deep brain stimulation. Our findings highlight the distributed effects of stimulation on the resting motor network and provide a framework for analysing effective connectivity in resting state functional MRI with strong a priori hypotheses.

  18. High-resolution photoacoustic tomography of resting-state functional connectivity in the mouse brain

    OpenAIRE

    Nasiriavanaki, Mohammadreza; Xia, Jun; Wan, Hanlin; Bauer, Adam Quentin; Culver, Joseph P.; Wang, Lihong V.

    2013-01-01

    The increasing use of mouse models for human brain disease studies presents an emerging need for a new functional imaging modality. Using optical excitation and acoustic detection, we developed a functional connectivity photoacoustic tomography system, which allows noninvasive imaging of resting-state functional connectivity in the mouse brain, with a large field of view and a high spatial resolution. Bilateral correlations were observed in eight functional regions, including the olfactory bu...

  19. Resting-state brain networks revealed by granger causal connectivity in frogs.

    Science.gov (United States)

    Xue, Fei; Fang, Guangzhan; Yue, Xizi; Zhao, Ermi; Brauth, Steven E; Tang, Yezhong

    2016-10-15

    Resting-state networks (RSNs) refer to the spontaneous brain activity generated under resting conditions, which maintain the dynamic connectivity of functional brain networks for automatic perception or higher order cognitive functions. Here, Granger causal connectivity analysis (GCCA) was used to explore brain RSNs in the music frog (Babina daunchina) during different behavioral activity phases. The results reveal that a causal network in the frog brain can be identified during the resting state which reflects both brain lateralization and sexual dimorphism. Specifically (1) ascending causal connections from the left mesencephalon to both sides of the telencephalon are significantly higher than those from the right mesencephalon, while the right telencephalon gives rise to the strongest efferent projections among all brain regions; (2) causal connections from the left mesencephalon in females are significantly higher than those in males and (3) these connections are similar during both the high and low behavioral activity phases in this species although almost all electroencephalograph (EEG) spectral bands showed higher power in the high activity phase for all nodes. The functional features of this network match important characteristics of auditory perception in this species. Thus we propose that this causal network maintains auditory perception during the resting state for unexpected auditory inputs as resting-state networks do in other species. These results are also consistent with the idea that females are more sensitive to auditory stimuli than males during the reproductive season. In addition, these results imply that even when not behaviorally active, the frogs remain vigilant for detecting external stimuli. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

  20. Interaction Effects of BDNF and COMT Genes on Resting-State Brain Activity and Working Memory

    Science.gov (United States)

    Chen, Wen; Chen, Chunhui; Xia, Mingrui; Wu, Karen; Chen, Chuansheng; He, Qinghua; Xue, Gui; Wang, Wenjing; He, Yong; Dong, Qi

    2016-01-01

    Catechol-O-methyltransferase (COMT) and brain-derived neurotrophic factor (BDNF) genes have been found to interactively influence working memory (WM) as well as brain activation during WM tasks. However, whether the two genes have interactive effects on resting-state activities of the brain and whether these spontaneous activations correlate with WM are still unknown. This study included behavioral data from WM tasks and genetic data (COMT rs4680 and BDNF Val66Met) from 417 healthy Chinese adults and resting-state fMRI data from 298 of them. Significant interactive effects of BDNF and COMT were found for WM performance as well as for resting-state regional homogeneity (ReHo) in WM-related brain areas, including the left medial frontal gyrus (lMeFG), left superior frontal gyrus (lSFG), right superior and medial frontal gyrus (rSMFG), right medial orbitofrontal gyrus (rMOFG), right middle frontal gyrus (rMFG), precuneus, bilateral superior temporal gyrus, left superior occipital gyrus, right middle occipital gyrus, and right inferior parietal lobule. Simple effects analyses showed that compared to other genotypes, subjects with COMT-VV/BDNF-VV had higher WM and lower ReHo in all five frontal brain areas. The results supported the hypothesis that COMT and BDNF polymorphisms influence WM performance and spontaneous brain activity (i.e., ReHo). PMID:27853425

  1. Abnormal resting-state brain activities in patients with first-episode obsessive-compulsive disorder.

    Science.gov (United States)

    Niu, Qihui; Yang, Lei; Song, Xueqin; Chu, Congying; Liu, Hao; Zhang, Lifang; Li, Yan; Zhang, Xiang; Cheng, Jingliang; Li, Youhui

    2017-01-01

    This paper attempts to explore the brain activity of patients with obsessive-compulsive disorder (OCD) and its correlation with the disease at resting duration in patients with first-episode OCD, providing a forceful imaging basis for clinic diagnosis and pathogenesis of OCD. Twenty-six patients with first-episode OCD and 25 healthy controls (HC group; matched for age, sex, and education level) underwent functional magnetic resonance imaging (fMRI) scanning at resting state. Statistical parametric mapping 8, data processing assistant for resting-state fMRI analysis toolkit, and resting state fMRI data analysis toolkit packages were used to process the fMRI data on Matlab 2012a platform, and the difference of regional homogeneity (ReHo) values between the OCD group and HC group was detected with independent two-sample t -test. With age as a concomitant variable, the Pearson correlation analysis was adopted to study the correlation between the disease duration and ReHo value of whole brain. Compared with HC group, the ReHo values in OCD group were decreased in brain regions, including left thalamus, right thalamus, right paracentral lobule, right postcentral gyrus, and the ReHo value was increased in the left angular gyrus region. There was a negative correlation between disease duration and ReHo value in the bilateral orbitofrontal cortex (OFC). OCD is a multifactorial disease generally caused by abnormal activities of many brain regions at resting state. Worse brain activity of the OFC is related to the OCD duration, which provides a new insight to the pathogenesis of OCD.

  2. Stomach-brain synchrony reveals a novel, delayed-connectivity resting-state network in humans.

    Science.gov (United States)

    Rebollo, Ignacio; Devauchelle, Anne-Dominique; Béranger, Benoît; Tallon-Baudry, Catherine

    2018-03-21

    Resting-state networks offer a unique window into the brain's functional architecture, but their characterization remains limited to instantaneous connectivity thus far. Here, we describe a novel resting-state network based on the delayed connectivity between the brain and the slow electrical rhythm (0.05 Hz) generated in the stomach. The gastric network cuts across classical resting-state networks with partial overlap with autonomic regulation areas. This network is composed of regions with convergent functional properties involved in mapping bodily space through touch, action or vision, as well as mapping external space in bodily coordinates. The network is characterized by a precise temporal sequence of activations within a gastric cycle, beginning with somato-motor cortices and ending with the extrastriate body area and dorsal precuneus. Our results demonstrate that canonical resting-state networks based on instantaneous connectivity represent only one of the possible partitions of the brain into coherent networks based on temporal dynamics. © 2018, Rebollo et al.

  3. Spatiotemporal dynamics of the brain at rest--exploring EEG microstates as electrophysiological signatures of BOLD resting state networks.

    Science.gov (United States)

    Yuan, Han; Zotev, Vadim; Phillips, Raquel; Drevets, Wayne C; Bodurka, Jerzy

    2012-05-01

    Neuroimaging research suggests that the resting cerebral physiology is characterized by complex patterns of neuronal activity in widely distributed functional networks. As studied using functional magnetic resonance imaging (fMRI) of the blood-oxygenation-level dependent (BOLD) signal, the resting brain activity is associated with slowly fluctuating hemodynamic signals (~10s). More recently, multimodal functional imaging studies involving simultaneous acquisition of BOLD-fMRI and electroencephalography (EEG) data have suggested that the relatively slow hemodynamic fluctuations of some resting state networks (RSNs) evinced in the BOLD data are related to much faster (~100 ms) transient brain states reflected in EEG signals, that are referred to as "microstates". To further elucidate the relationship between microstates and RSNs, we developed a fully data-driven approach that combines information from simultaneously recorded, high-density EEG and BOLD-fMRI data. Using independent component analysis (ICA) of the combined EEG and fMRI data, we identified thirteen microstates and ten RSNs that are organized independently in their temporal and spatial characteristics, respectively. We hypothesized that the intrinsic brain networks that are active at rest would be reflected in both the EEG data and the fMRI data. To test this hypothesis, the rapid fluctuations associated with each microstate were correlated with the BOLD-fMRI signal associated with each RSN. We found that each RSN was characterized further by a specific electrophysiological signature involving from one to a combination of several microstates. Moreover, by comparing the time course of EEG microstates to that of the whole-brain BOLD signal, on a multi-subject group level, we unraveled for the first time a set of microstate-associated networks that correspond to a range of previously described RSNs, including visual, sensorimotor, auditory, attention, frontal, visceromotor and default mode networks. These

  4. Disrupted resting-state functional architecture of the brain after 45-day simulated microgravity

    Science.gov (United States)

    Zhou, Yuan; Wang, Yun; Rao, Li-Lin; Liang, Zhu-Yuan; Chen, Xiao-Ping; Zheng, Dang; Tan, Cheng; Tian, Zhi-Qiang; Wang, Chun-Hui; Bai, Yan-Qiang; Chen, Shan-Guang; Li, Shu

    2014-01-01

    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. PMID:24926242

  5. 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.

  6. Effects of Soft Drinks on Resting State EEG and Brain-Computer Interface Performance.

    Science.gov (United States)

    Meng, Jianjun; Mundahl, John; Streitz, Taylor; Maile, Kaitlin; Gulachek, Nicholas; He, Jeffrey; He, Bin

    2017-01-01

    Motor imagery-based (MI based) brain-computer interface (BCI) using electroencephalography (EEG) allows users to directly control a computer or external device by modulating and decoding the brain waves. A variety of factors could potentially affect the performance of BCI such as the health status of subjects or the environment. In this study, we investigated the effects of soft drinks and regular coffee on EEG signals under resting state and on the performance of MI based BCI. Twenty-six healthy human subjects participated in three or four BCI sessions with a resting period in each session. During each session, the subjects drank an unlabeled soft drink with either sugar (Caffeine Free Coca-Cola), caffeine (Diet Coke), neither ingredient (Caffeine Free Diet Coke), or a regular coffee if there was a fourth session. The resting state spectral power in each condition was compared; the analysis showed that power in alpha and beta band after caffeine consumption were decreased substantially compared to control and sugar condition. Although the attenuation of powers in the frequency range used for the online BCI control signal was shown, group averaged BCI online performance after consuming caffeine was similar to those of other conditions. This work, for the first time, shows the effect of caffeine, sugar intake on the online BCI performance and resting state brain signal.

  7. A computational study of whole-brain connectivity in resting state and task fMRI

    Science.gov (United States)

    Goparaju, Balaji; Rana, Kunjan D.; Calabro, Finnegan J.; Vaina, Lucia Maria

    2014-01-01

    Background We compared the functional brain connectivity produced during resting-state in which subjects were not actively engaged in a task with that produced while they actively performed a visual motion task (task-state). Material/Methods In this paper we employed graph-theoretical measures and network statistics in novel ways to compare, in the same group of human subjects, functional brain connectivity during resting-state fMRI with brain connectivity during performance of a high level visual task. We performed a whole-brain connectivity analysis to compare network statistics in resting and task states among anatomically defined Brodmann areas to investigate how brain networks spanning the cortex changed when subjects were engaged in task performance. Results In the resting state, we found strong connectivity among the posterior cingulate cortex (PCC), precuneus, medial prefrontal cortex (MPFC), lateral parietal cortex, and hippocampal formation, consistent with previous reports of the default mode network (DMN). The connections among these areas were strengthened while subjects actively performed an event-related visual motion task, indicating a continued and strong engagement of the DMN during task processing. Regional measures such as degree (number of connections) and betweenness centrality (number of shortest paths), showed that task performance induces stronger inter-regional connections, leading to a denser processing network, but that this does not imply a more efficient system as shown by the integration measures such as path length and global efficiency, and from global measures such as small-worldness. Conclusions In spite of the maintenance of connectivity and the “hub-like” behavior of areas, our results suggest that the network paths may be rerouted when performing the task condition. PMID:24947491

  8. Ketamine changes the local resting-state functional properties of anesthetized-monkey brain.

    Science.gov (United States)

    Rao, Jia-Sheng; Liu, Zuxiang; Zhao, Can; Wei, Rui-Han; Zhao, Wen; Tian, Peng-Yu; Zhou, Xia; Yang, Zhao-Yang; Li, Xiao-Guang

    2017-11-01

    Ketamine is a well-known anesthetic. 'Recreational' use of ketamine common induces psychosis-like symptoms and cognitive impairments. The acute and chronic effects of ketamine on relevant brain circuits have been studied, but the effects of single-dose ketamine administration on the local resting-state functional properties of the brain remain unknown. In this study, we aimed to assess the effects of single-dose ketamine administration on the brain local intrinsic properties. We used resting-state functional magnetic resonance imaging (rs-fMRI) to explore the ketamine-induced alterations of brain intrinsic properties. Seven adult rhesus monkeys were imaged with rs-fMRI to examine the fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo) in the brain before and after ketamine injection. Paired comparisons were used to detect the significantly altered regions. Results showed that the fALFF of the prefrontal cortex (p=0.046), caudate nucleus (left side, p=0.018; right side, p=0.025), and putamen (p=0.020) in post-injection stage significantly increased compared with those in pre-injection period. The ReHo of nucleus accumbens (p=0.049), caudate nucleus (p=0.037), and hippocampus (p=0.025) increased after ketamine injection, but that of prefrontal cortex decreased (pketamine administration can change the regional intensity and synchronism of brain activity, thereby providing evidence of ketamine-induced abnormal resting-state functional properties in primates. This evidence may help further elucidate the effects of ketamine on the cerebral resting status. Copyright © 2017. Published by Elsevier Inc.

  9. Differential structural and resting state connectivity between insular subdivisions and other pain-related brain regions.

    Science.gov (United States)

    Wiech, K; Jbabdi, S; Lin, C S; Andersson, J; Tracey, I

    2014-10-01

    Functional neuroimaging studies suggest that the anterior, mid, and posterior division of the insula subserve different functions in the perception of pain. The anterior insula (AI) has predominantly been associated with cognitive-affective aspects of pain, while the mid and posterior divisions have been implicated in sensory-discriminative processing. We examined whether this functional segregation is paralleled by differences in (1) structural and (2) resting state connectivity and (3) in correlations with pain-relevant psychological traits. Analyses were restricted to the 3 insular subdivisions and other pain-related brain regions. Both type of analyses revealed largely overlapping results. The AI division was predominantly connected to the ventrolateral prefrontal cortex (structural and resting state connectivity) and orbitofrontal cortex (structural connectivity). In contrast, the posterior insula showed strong connections to the primary somatosensory cortex (SI; structural connectivity) and secondary somatosensory cortex (SII; structural and resting state connectivity). The mid insula displayed a hybrid connectivity pattern with strong connections with the ventrolateral prefrontal cortex, SII (structural and resting state connectivity) and SI (structural connectivity). Moreover, resting state connectivity revealed strong connectivity of all 3 subdivisions with the thalamus. On the behavioural level, AI structural connectivity was related to the individual degree of pain vigilance and awareness that showed a positive correlation with AI-amygdala connectivity and a negative correlation with AI-rostral anterior cingulate cortex connectivity. In sum, our findings show a differential structural and resting state connectivity for the anterior, mid, and posterior insula with other pain-relevant brain regions, which might at least partly explain their different functional profiles in pain processing. Copyright © 2014 The Authors. Published by Elsevier B.V. All

  10. Decreased integration and information capacity in stroke measured by whole brain models of resting state activity.

    Science.gov (United States)

    Adhikari, Mohit H; Hacker, Carl D; Siegel, Josh S; Griffa, Alessandra; Hagmann, Patric; Deco, Gustavo; Corbetta, Maurizio

    2017-04-01

    While several studies have shown that focal lesions affect the communication between structurally normal regions of the brain, and that these changes may correlate with behavioural deficits, their impact on brain's information processing capacity is currently unknown. Here we test the hypothesis that focal lesions decrease the brain's information processing capacity, of which changes in functional connectivity may be a measurable correlate. To measure processing capacity, we turned to whole brain computational modelling to estimate the integration and segregation of information in brain networks. First, we measured functional connectivity between different brain areas with resting state functional magnetic resonance imaging in healthy subjects (n = 26), and subjects who had suffered a cortical stroke (n = 36). We then used a whole-brain network model that coupled average excitatory activities of local regions via anatomical connectivity. Model parameters were optimized in each healthy or stroke participant to maximize correlation between model and empirical functional connectivity, so that the model's effective connectivity was a veridical representation of healthy or lesioned brain networks. Subsequently, we calculated two model-based measures: 'integration', a graph theoretical measure obtained from functional connectivity, which measures the connectedness of brain networks, and 'information capacity', an information theoretical measure that cannot be obtained empirically, representative of the segregative ability of brain networks to encode distinct stimuli. We found that both measures were decreased in stroke patients, as compared to healthy controls, particularly at the level of resting-state networks. Furthermore, we found that these measures, especially information capacity, correlate with measures of behavioural impairment and the segregation of resting-state networks empirically measured. This study shows that focal lesions affect the brain's ability to

  11. Motor imagery learning modulates functional connectivity of multiple brain systems in resting state.

    Science.gov (United States)

    Zhang, Hang; Long, Zhiying; Ge, Ruiyang; Xu, Lele; Jin, Zhen; Yao, Li; Liu, Yijun

    2014-01-01

    Learning motor skills involves subsequent modulation of resting-state functional connectivity in the sensory-motor system. This idea was mostly derived from the investigations on motor execution learning which mainly recruits the processing of sensory-motor information. Behavioral evidences demonstrated that motor skills in our daily lives could be learned through imagery procedures. However, it remains unclear whether the modulation of resting-state functional connectivity also exists in the sensory-motor system after motor imagery learning. We performed a fMRI investigation on motor imagery learning from resting state. Based on previous studies, we identified eight sensory and cognitive resting-state networks (RSNs) corresponding to the brain systems and further explored the functional connectivity of these RSNs through the assessments, connectivity and network strengths before and after the two-week consecutive learning. Two intriguing results were revealed: (1) The sensory RSNs, specifically sensory-motor and lateral visual networks exhibited greater connectivity strengths in precuneus and fusiform gyrus after learning; (2) Decreased network strength induced by learning was proved in the default mode network, a cognitive RSN. These results indicated that resting-state functional connectivity could be modulated by motor imagery learning in multiple brain systems, and such modulation displayed in the sensory-motor, visual and default brain systems may be associated with the establishment of motor schema and the regulation of introspective thought. These findings further revealed the neural substrates underlying motor skill learning and potentially provided new insights into the therapeutic benefits of motor imagery learning.

  12. Motor Imagery Learning Modulates Functional Connectivity of Multiple Brain Systems in Resting State

    Science.gov (United States)

    Zhang, Hang; Long, Zhiying; Ge, Ruiyang; Xu, Lele; Jin, Zhen; Yao, Li; Liu, Yijun

    2014-01-01

    Background Learning motor skills involves subsequent modulation of resting-state functional connectivity in the sensory-motor system. This idea was mostly derived from the investigations on motor execution learning which mainly recruits the processing of sensory-motor information. Behavioral evidences demonstrated that motor skills in our daily lives could be learned through imagery procedures. However, it remains unclear whether the modulation of resting-state functional connectivity also exists in the sensory-motor system after motor imagery learning. Methodology/Principal Findings We performed a fMRI investigation on motor imagery learning from resting state. Based on previous studies, we identified eight sensory and cognitive resting-state networks (RSNs) corresponding to the brain systems and further explored the functional connectivity of these RSNs through the assessments, connectivity and network strengths before and after the two-week consecutive learning. Two intriguing results were revealed: (1) The sensory RSNs, specifically sensory-motor and lateral visual networks exhibited greater connectivity strengths in precuneus and fusiform gyrus after learning; (2) Decreased network strength induced by learning was proved in the default mode network, a cognitive RSN. Conclusions/Significance These results indicated that resting-state functional connectivity could be modulated by motor imagery learning in multiple brain systems, and such modulation displayed in the sensory-motor, visual and default brain systems may be associated with the establishment of motor schema and the regulation of introspective thought. These findings further revealed the neural substrates underlying motor skill learning and potentially provided new insights into the therapeutic benefits of motor imagery learning. PMID:24465577

  13. Relation of visual creative imagery manipulation to resting-state brain oscillations.

    Science.gov (United States)

    Cai, Yuxuan; Zhang, Delong; Liang, Bishan; Wang, Zengjian; Li, Junchao; Gao, Zhenni; Gao, Mengxia; Chang, Song; Jiao, Bingqing; Huang, Ruiwang; Liu, Ming

    2018-02-01

    Visual creative imagery (VCI) manipulation is the key component of visual creativity; however, it remains largely unclear how it occurs in the brain. The present study investigated the brain neural response to VCI manipulation and its relation to intrinsic brain activity. We collected functional magnetic resonance imaging (fMRI) datasets related to a VCI task and a control task as well as pre- and post-task resting states in sequential sessions. A general linear model (GLM) was subsequently used to assess the specific activation of the VCI task compared with the control task. The changes in brain oscillation amplitudes across the pre-, on-, and post-task states were measured to investigate the modulation of the VCI task. Furthermore, we applied a Granger causal analysis (GCA) to demonstrate the dynamic neural interactions that underlie the modulation effect. We determined that the VCI task specifically activated the left inferior frontal gyrus pars triangularis (IFGtriang) and the right superior frontal gyrus (SFG), as well as the temporoparietal areas, including the left inferior temporal gyrus, right precuneus, and bilateral superior parietal gyrus. Furthermore, the VCI task modulated the intrinsic brain activity of the right IFGtriang (0.01-0.08 Hz) and the left caudate nucleus (0.2-0.25 Hz). Importantly, an inhibitory effect (negative) may exist from the left SFG to the right IFGtriang in the on-VCI task state, in the frequency of 0.01-0.08 Hz, whereas this effect shifted to an excitatory effect (positive) in the subsequent post-task resting state. Taken together, the present findings provide experimental evidence for the existence of a common mechanism that governs the brain activity of many regions at resting state and whose neural activity may engage during the VCI manipulation task, which may facilitate an understanding of the neural substrate of visual creativity.

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

    OpenAIRE

    Song, Hongwen; Zou, Zhiling; Kou, Juan; Liu, Yang; Yang, Lizhuang; Zilverstand, Anna; d’Oleire Uquillas, Federico; Zhang, Xiaochu

    2015-01-01

    Romantic love is a motivational state associated with a desire to enter or maintain a close relationship with a specific other person. Functional magnetic resonance imaging (fMRI) studies have found activation increases in brain regions involved in the processing of reward, motivation and emotion regulation, when romantic lovers view photographs of their partners. However, not much is known about whether romantic love affects the brain’s functional architecture during rest. In the present stu...

  15. Directed connectivity of brain default networks in resting state using GCA and motif.

    Science.gov (United States)

    Jiao, Zhuqing; Wang, Huan; Ma, Kai; Zou, Ling; Xiang, Jianbo

    2017-06-01

    Nowadays, there is a lot of interest in assessing functional interactions between key brain regions. In this paper, Granger causality analysis (GCA) and motif structure are adopted to study directed connectivity of brain default mode networks (DMNs) in resting state. Firstly, the time series of functional magnetic resonance imaging (fMRI) data in resting state were extracted, and the causal relationship values of the nodes representing related brain regions are analyzed in time domain to construct a default network. Then, the network structures were searched from the default networks of controls and patients to determine the fixed connection mode in the networks. The important degree of motif structures in directed connectivity of default networks was judged according to p-value and Z-score. Both node degree and average distance were used to analyze the effect degree an information transfer rate of brain regions in motifs and default networks, and efficiency of the network. Finally, activity and functional connectivity strength of the default brain regions are researched according to the change of energy distributions between the normals and the patients' brain regions. Experimental results demonstrate that, both normal subjects and stroke patients have some corresponding fixed connection mode of three nodes, and the efficiency and power spectrum of the patient's default network is somewhat lower than that of the normal person. In particular, the Right Posterior Cingulate Gyrus (PCG.R) has a larger change in functional connectivity and its activity. The research results verify the feasibility of the application of GCA and motif structure to study the functional connectivity of default networks in resting state.

  16. Resting-state brain activity in the motor cortex reflects task-induced activity: A multi-voxel pattern analysis.

    Science.gov (United States)

    Kusano, Toshiki; Kurashige, Hiroki; Nambu, Isao; Moriguchi, Yoshiya; Hanakawa, Takashi; Wada, Yasuhiro; Osu, Rieko

    2015-08-01

    It has been suggested that resting-state brain activity reflects task-induced brain activity patterns. In this study, we examined whether neural representations of specific movements can be observed in the resting-state brain activity patterns of motor areas. First, we defined two regions of interest (ROIs) to examine brain activity associated with two different behavioral tasks. Using multi-voxel pattern analysis with regularized logistic regression, we designed a decoder to detect voxel-level neural representations corresponding to the tasks in each ROI. Next, we applied the decoder to resting-state brain activity. We found that the decoder discriminated resting-state neural activity with accuracy comparable to that associated with task-induced neural activity. The distribution of learned weighted parameters for each ROI was similar for resting-state and task-induced activities. Large weighted parameters were mainly located on conjunctive areas. Moreover, the accuracy of detection was higher than that for a decoder whose weights were randomly shuffled, indicating that the resting-state brain activity includes multi-voxel patterns similar to the neural representation for the tasks. Therefore, these results suggest that the neural representation of resting-state brain activity is more finely organized and more complex than conventionally considered.

  17. Dopamine precursor depletion impairs structure and efficiency of resting state brain functional networks.

    Science.gov (United States)

    Carbonell, Felix; Nagano-Saito, Atsuko; Leyton, Marco; Cisek, Paul; Benkelfat, Chawki; He, Yong; Dagher, Alain

    2014-09-01

    Spatial patterns of functional connectivity derived from resting brain activity may be used to elucidate the topological properties of brain networks. Such networks are amenable to study using graph theory, which shows that they possess small world properties and can be used to differentiate healthy subjects and patient populations. Of particular interest is the possibility that some of these differences are related to alterations in the dopamine system. To investigate the role of dopamine in the topological organization of brain networks at rest, we tested the effects of reducing dopamine synthesis in 13 healthy subjects undergoing functional magnetic resonance imaging. All subjects were scanned twice, in a resting state, following ingestion of one of two amino acid drinks in a randomized, double-blind manner. One drink was a nutritionally balanced amino acid mixture, and the other was tyrosine and phenylalanine deficient. Functional connectivity between 90 cortical and subcortical regions was estimated for each individual subject under each dopaminergic condition. The lowered dopamine state caused the following network changes: reduced global and local efficiency of the whole brain network, reduced regional efficiency in limbic areas, reduced modularity of brain networks, and greater connection between the normally anti-correlated task-positive and default-mode networks. We conclude that dopamine plays a role in maintaining the efficient small-world properties and high modularity of functional brain networks, and in segregating the task-positive and default-mode networks. This article is part of the Special Issue Section entitled 'Neuroimaging in Neuropharmacology'. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. High-resolution photoacoustic tomography of resting-state functional connectivity in the mouse brain

    Science.gov (United States)

    Nasiriavanaki, Mohammadreza; Xia, Jun; Wan, Hanlin; Bauer, Adam Quentin; Culver, Joseph P.; Wang, Lihong V.

    2014-01-01

    The increasing use of mouse models for human brain disease studies presents an emerging need for a new functional imaging modality. Using optical excitation and acoustic detection, we developed a functional connectivity photoacoustic tomography system, which allows noninvasive imaging of resting-state functional connectivity in the mouse brain, with a large field of view and a high spatial resolution. Bilateral correlations were observed in eight functional regions, including the olfactory bulb, limbic, parietal, somatosensory, retrosplenial, visual, motor, and temporal regions, as well as in several subregions. The borders and locations of these regions agreed well with the Paxinos mouse brain atlas. By subjecting the mouse to alternating hyperoxic and hypoxic conditions, strong and weak functional connectivities were observed, respectively. In addition to connectivity images, vascular images were simultaneously acquired. These studies show that functional connectivity photoacoustic tomography is a promising, noninvasive technique for functional imaging of the mouse brain. PMID:24367107

  19. Task vs. rest—different network configurations between the coactivation and the resting-state brain networks

    Science.gov (United States)

    Di, Xin; Gohel, Suril; Kim, Eun H.; Biswal, Bharat B.

    2013-01-01

    There is a growing interest in studies of human brain networks using resting-state functional magnetic resonance imaging (fMRI). However, it is unclear whether and how brain networks measured during the resting-state exhibit comparable properties to brain networks during task performance. In the present study, we investigated meta-analytic coactivation patterns among brain regions based upon published neuroimaging studies, and compared the coactivation network configurations with those in the resting-state network. The strength of resting-state functional connectivity between two regions were strongly correlated with the coactivation strength. However, the coactivation network showed greater global efficiency, smaller mean clustering coefficient, and lower modularity compared with the resting-state network, which suggest a more efficient global information transmission and between system integrations during task performing. Hub shifts were also observed within the thalamus and the left inferior temporal cortex. The thalamus and the left inferior temporal cortex exhibited higher and lower degrees, respectively in the coactivation network compared with the resting-state network. These results shed light regarding the reconfiguration of the brain networks between task and resting-state conditions, and highlight the role of the thalamus in change of network configurations in task vs. rest. PMID:24062654

  20. Altered spontaneous brain activity in patients with hemifacial spasm: a resting-state functional MRI study.

    Directory of Open Access Journals (Sweden)

    Ye Tu

    Full Text Available Resting-state functional magnetic resonance imaging (fMRI has been used to detect the alterations of spontaneous neuronal activity in various neurological and neuropsychiatric diseases, but rarely in hemifacial spasm (HFS, a nervous system disorder. We used resting-state fMRI with regional homogeneity (ReHo analysis to investigate changes in spontaneous brain activity of patients with HFS and to determine the relationship of these functional changes with clinical features. Thirty patients with HFS and 33 age-, sex-, and education-matched healthy controls were included in this study. Compared with controls, HFS patients had significantly decreased ReHo values in left middle frontal gyrus (MFG, left medial cingulate cortex (MCC, left lingual gyrus, right superior temporal gyrus (STG and right precuneus; and increased ReHo values in left precentral gyrus, anterior cingulate cortex (ACC, right brainstem, and right cerebellum. Furthermore, the mean ReHo value in brainstem showed a positive correlation with the spasm severity (r = 0.404, p = 0.027, and the mean ReHo value in MFG was inversely related with spasm severity in HFS group (r = -0.398, p = 0.028. This study reveals that HFS is associated with abnormal spontaneous brain activity in brain regions most involved in motor control and blinking movement. The disturbances of spontaneous brain activity reflected by ReHo measurements may provide insights into the neurological pathophysiology of HFS.

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

    Science.gov (United States)

    Wylie, Korey P; Rojas, Donald C; Ross, Randal G; Hunter, Sharon K; Maharajh, Keeran; Cornier, Marc-Andre; Tregellas, Jason R

    2014-01-01

    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. 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. 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. 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.

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

    International Nuclear Information System (INIS)

    Yang Shiqi; Wu Guangyao; Lin Fuchun; Kong Xiangquan; Zhou Guofeng; Pang Haopeng; Zhu Ling; Liu Guobing; Lei Hao

    2012-01-01

    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)

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

    NARCIS (Netherlands)

    Zhang, Delong; Liang, Bishan; Wu, Xia; Wang, Zengjian; Xu, Pengfei; Chang, Song; Liu, Bo; Liu, Ming; Huang, Ruiwang

    2015-01-01

    The present study examined directional connections in the brain among resting-state networks (RSNs) when the participant had their eyes open (E0) or had their eyes closed (EC). The resting state fMRI data were collected from 20 healthy participants (9 males, 20.17 +/- 2.74 years) under the EO and EC

  4. Resting-State Functional Connectivity in the Infant Brain: Methods, Pitfalls, and Potentiality

    Directory of Open Access Journals (Sweden)

    Chandler R. L. Mongerson

    2017-08-01

    Full Text Available Early brain development is characterized by rapid growth and perpetual reconfiguration, driven by a dynamic milieu of heterogeneous processes. Postnatal brain plasticity is associated with increased vulnerability to environmental stimuli. However, little is known regarding the ontogeny and temporal manifestations of inter- and intra-regional functional connectivity that comprise functional brain networks. Resting-state functional magnetic resonance imaging (rs-fMRI has emerged as a promising non-invasive neuroinvestigative tool, measuring spontaneous fluctuations in blood oxygen level dependent (BOLD signal at rest that reflect baseline neuronal activity. Over the past decade, its application has expanded to infant populations providing unprecedented insight into functional organization of the developing brain, as well as early biomarkers of abnormal states. However, many methodological issues of rs-fMRI analysis need to be resolved prior to standardization of the technique to infant populations. As a primary goal, this methodological manuscript will (1 present a robust methodological protocol to extract and assess resting-state networks in early infancy using independent component analysis (ICA, such that investigators without previous knowledge in the field can implement the analysis and reliably obtain viable results consistent with previous literature; (2 review the current methodological challenges and ethical considerations associated with emerging field of infant rs-fMRI analysis; and (3 discuss the significance of rs-fMRI application in infants for future investigations of neurodevelopment in the context of early life stressors and pathological processes. The overarching goal is to catalyze efforts toward development of robust, infant-specific acquisition, and preprocessing pipelines, as well as promote greater transparency by researchers regarding methods used.

  5. Resting-State Functional Connectivity in the Infant Brain: Methods, Pitfalls, and Potentiality.

    Science.gov (United States)

    Mongerson, Chandler R L; Jennings, Russell W; Borsook, David; Becerra, Lino; Bajic, Dusica

    2017-01-01

    Early brain development is characterized by rapid growth and perpetual reconfiguration, driven by a dynamic milieu of heterogeneous processes. Postnatal brain plasticity is associated with increased vulnerability to environmental stimuli. However, little is known regarding the ontogeny and temporal manifestations of inter- and intra-regional functional connectivity that comprise functional brain networks. Resting-state functional magnetic resonance imaging (rs-fMRI) has emerged as a promising non-invasive neuroinvestigative tool, measuring spontaneous fluctuations in blood oxygen level dependent (BOLD) signal at rest that reflect baseline neuronal activity. Over the past decade, its application has expanded to infant populations providing unprecedented insight into functional organization of the developing brain, as well as early biomarkers of abnormal states. However, many methodological issues of rs-fMRI analysis need to be resolved prior to standardization of the technique to infant populations. As a primary goal, this methodological manuscript will (1) present a robust methodological protocol to extract and assess resting-state networks in early infancy using independent component analysis (ICA), such that investigators without previous knowledge in the field can implement the analysis and reliably obtain viable results consistent with previous literature; (2) review the current methodological challenges and ethical considerations associated with emerging field of infant rs-fMRI analysis; and (3) discuss the significance of rs-fMRI application in infants for future investigations of neurodevelopment in the context of early life stressors and pathological processes. The overarching goal is to catalyze efforts toward development of robust, infant-specific acquisition, and preprocessing pipelines, as well as promote greater transparency by researchers regarding methods used.

  6. Discriminating between brain rest and attention states using fMRI connectivity graphs and subtree SVM

    Science.gov (United States)

    Mokhtari, Fatemeh; Bakhtiari, Shahab K.; Hossein-Zadeh, Gholam Ali; Soltanian-Zadeh, Hamid

    2012-02-01

    Decoding techniques have opened new windows to explore the brain function and information encoding in brain activity. In the current study, we design a recursive support vector machine which is enriched by a subtree graph kernel. We apply the classifier to discriminate between attentional cueing task and resting state from a block design fMRI dataset. The classifier is trained using weighted fMRI graphs constructed from activated regions during the two mentioned states. The proposed method leads to classification accuracy of 1. It is also able to elicit discriminative regions and connectivities between the two states using a backward edge elimination algorithm. This algorithm shows the importance of regions including cerebellum, insula, left middle superior frontal gyrus, post cingulate cortex, and connectivities between them to enhance the correct classification rate.

  7. Altered resting-state whole-brain functional networks of neonates with intrauterine growth restriction.

    Science.gov (United States)

    Batalle, Dafnis; Muñoz-Moreno, Emma; Tornador, Cristian; Bargallo, Nuria; Deco, Gustavo; Eixarch, Elisenda; Gratacos, Eduard

    2016-04-01

    The feasibility to use functional MRI (fMRI) during natural sleep to assess low-frequency basal brain activity fluctuations in human neonates has been demonstrated, although its potential to characterise pathologies of prenatal origin has not yet been exploited. In the present study, we used intrauterine growth restriction (IUGR) as a model of altered neurodevelopment due to prenatal condition to show the suitability of brain networks to characterise functional brain organisation at neonatal age. Particularly, we analysed resting-state fMRI signal of 20 neonates with IUGR and 13 controls, obtaining whole-brain functional networks based on correlations of blood oxygen level-dependent (BOLD) signal in 90 grey matter regions of an anatomical atlas (AAL). Characterisation of the networks obtained with graph theoretical features showed increased network infrastructure and raw efficiencies but reduced efficiency after normalisation, demonstrating hyper-connected but sub-optimally organised IUGR functional brain networks. Significant association of network features with neurobehavioral scores was also found. Further assessment of spatiotemporal dynamics displayed alterations into features associated to frontal, cingulate and lingual cortices. These findings show the capacity of functional brain networks to characterise brain reorganisation from an early age, and their potential to develop biomarkers of altered neurodevelopment. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. 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

  9. A Bayesian Double Fusion Model for Resting-State Brain Connectivity Using Joint Functional and Structural Data

    KAUST Repository

    Kang, Hakmook; Ombao, Hernando; Fonnesbeck, Christopher; Ding, Zhaohua; Morgan, Victoria L.

    2017-01-01

    DTI that could potentially enhance estimation of resting-state functional connectivity (FC) between brain regions. To overcome this limitation, we develop a Bayesian hierarchical spatiotemporal model that incorporates structural connectivity (SC

  10. Regional homogeneity of the resting-state brain activity correlates with individual intelligence.

    Science.gov (United States)

    Wang, Leiqiong; Song, Ming; Jiang, Tianzi; Zhang, Yunting; Yu, Chunshui

    2011-01-25

    Resting-state functional magnetic resonance imaging has confirmed that the strengths of the long distance functional connectivity between different brain areas are correlated with individual differences in intelligence. However, the association between the local connectivity within a specific brain region and intelligence during rest remains largely unknown. The aim of this study is to investigate the relationship between local connectivity and intelligence. Fifty-nine right-handed healthy adults participated in the study. The regional homogeneity (ReHo) was used to assess the strength of local connectivity. The associations between ReHo and full-scale intelligence quotient (FSIQ) scores were studied in a voxel-wise manner using partial correlation analysis controlling for age and sex. We found that the FSIQ scores were positively correlated with the ReHo values of the bilateral inferior parietal lobules, middle frontal, parahippocampal and inferior temporal gyri, the right thalamus, superior frontal and fusiform gyri, and the left superior parietal lobule. The main findings are consistent with the parieto-frontal integration theory (P-FIT) of intelligence, supporting the view that general intelligence involves multiple brain regions throughout the brain. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

  11. Spinal Cord Injury Disrupts Resting-State Networks in the Human Brain.

    Science.gov (United States)

    Hawasli, Ammar H; Rutlin, Jerrel; Roland, Jarod L; Murphy, Rory K J; Song, Sheng-Kwei; Leuthardt, Eric C; Shimony, Joshua S; Ray, Wilson Z

    2018-03-15

    Despite 253,000 spinal cord injury (SCI) patients in the United States, little is known about how SCI affects brain networks. Spinal MRI provides only structural information with no insight into functional connectivity. Resting-state functional MRI (RS-fMRI) quantifies network connectivity through the identification of resting-state networks (RSNs) and allows detection of functionally relevant changes during disease. Given the robust network of spinal cord afferents to the brain, we hypothesized that SCI produces meaningful changes in brain RSNs. RS-fMRIs and functional assessments were performed on 10 SCI subjects. Blood oxygen-dependent RS-fMRI sequences were acquired. Seed-based correlation mapping was performed using five RSNs: default-mode (DMN), dorsal-attention (DAN), salience (SAL), control (CON), and somatomotor (SMN). RSNs were compared with normal control subjects using false-discovery rate-corrected two way t tests. SCI reduced brain network connectivity within the SAL, SMN, and DMN and disrupted anti-correlated connectivity between CON and SMN. When divided into separate cohorts, complete but not incomplete SCI disrupted connectivity within SAL, DAN, SMN and DMN and between CON and SMN. Finally, connectivity changed over time after SCI: the primary motor cortex decreased connectivity with the primary somatosensory cortex, the visual cortex decreased connectivity with the primary motor cortex, and the visual cortex decreased connectivity with the sensory parietal cortex. These unique findings demonstrate the functional network plasticity that occurs in the brain as a result of injury to the spinal cord. Connectivity changes after SCI may serve as biomarkers to predict functional recovery following an SCI and guide future therapy.

  12. [Brain activitivation of euthymic patients with Type I bipolar disorder in resting state Default Mode Network].

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    Vargas, Cristian; Pineda, Julián; Calvo, Víctor; López-Jaramillo, Carlos

    2014-01-01

    As there are still doubts about brain connectivity in type I bipolar disorder (BID), resting-state functional magnetic resonance imaging (RS-fMRI) studies are necessary during euthymia for a better control of confounding factors. To evaluate the differences in brain activation between euthymic BID patients and control subjects using resting state- functional-magnetic resonance imaging (RS-fMRI), and to identify the lithium effect in these activations. A cross-sectional study was conducted on 21 BID patients (10 receiving lithium only, and 11 non-medicated) and 12 healthy control subjects, using RS fMRI and independent component analysis (ICA). Increased activation was found in the right hippocampus (P=.049) and posterior cingulate (P=.040) within the Default Mode Network (DMN) when BID and control group were compared. No statistically significant differences were identified between BID on lithium only therapy and non-medicated BID patients. The results suggest that there are changes in brain activation and connectivity in BID even during euthymic phase and mainly within the DMN network, which could be relevant in affect regulation. Copyright © 2013 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

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

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    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.

  14. The spectral diversity of resting-state fluctuations in the human brain.

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    Klaudius Kalcher

    Full Text Available In order to assess whole-brain resting-state fluctuations at a wide range of frequencies, resting-state fMRI data of 20 healthy subjects were acquired using a multiband EPI sequence with a low TR (354 ms and compared to 20 resting-state datasets from standard, high-TR (1800 ms EPI scans. The spatial distribution of fluctuations in various frequency ranges are analyzed along with the spectra of the time-series in voxels from different regions of interest. Functional connectivity specific to different frequency ranges (<0.1 Hz; 0.1-0.25 Hz; 0.25-0.75 Hz; 0.75-1.4 Hz was computed for both the low-TR and (for the two lower-frequency ranges the high-TR datasets using bandpass filters. In the low-TR data, cortical regions exhibited highest contribution of low-frequency fluctuations and the most marked low-frequency peak in the spectrum, while the time courses in subcortical grey matter regions as well as the insula were strongly contaminated by high-frequency signals. White matter and CSF regions had highest contribution of high-frequency fluctuations and a mostly flat power spectrum. In the high-TR data, the basic patterns of the low-TR data can be recognized, but the high-frequency proportions of the signal fluctuations are folded into the low frequency range, thus obfuscating the low-frequency dynamics. Regions with higher proportion of high-frequency oscillations in the low-TR data showed flatter power spectra in the high-TR data due to aliasing of the high-frequency signal components, leading to loss of specificity in the signal from these regions in high-TR data. Functional connectivity analyses showed that there are correlations between resting-state signal fluctuations of distant brain regions even at high frequencies, which can be measured using low-TR fMRI. On the other hand, in the high-TR data, loss of specificity of measured fluctuations leads to lower sensitivity in detecting functional connectivity. This underlines the advantages of low

  15. Resting State Brain Network Disturbances Related to Hypomania and Depression in Medication-Free Bipolar Disorder.

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    Spielberg, Jeffrey M; Beall, Erik B; Hulvershorn, Leslie A; Altinay, Murat; Karne, Harish; Anand, Amit

    2016-12-01

    Research on resting functional brain networks in bipolar disorder (BP) has been unable to differentiate between disturbances related to mania or depression, which is necessary to understand the mechanisms leading to each state. Past research has also been unable to elucidate the impact of BP-related network disturbances on the organizational properties of the brain (eg, communication efficiency). Thus, the present work sought to isolate network disturbances related to BP, fractionate these into components associated with manic and depressive symptoms, and characterize the impact of disturbances on network function. Graph theory was used to analyze resting functional magnetic resonance imaging data from 60 medication-free patients meeting the criteria for BP and either a current hypomanic (n=30) or depressed (n=30) episode and 30 closely age/sex-matched healthy controls. Correction for multiple comparisons was carried out. Compared with controls, BP patients evidenced hyperconnectivity in a network involving right amygdala. Fractionation revealed that (hypo)manic symptoms were associated with hyperconnectivity in an overlapping network and disruptions in the brain's 'small-world' network organization. Depressive symptoms predicted hyperconnectivity in a network involving orbitofrontal cortex along with a less resilient global network organization. Findings provide deeper insight into the differential pathophysiological processes associated with hypomania and depression, along with the particular impact these differential processes have on network function.

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

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    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.

  17. Resting state fMRI entropy probes complexity of brain activity in adults with ADHD.

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    Sokunbi, Moses O; Fung, Wilson; Sawlani, Vijay; Choppin, Sabine; Linden, David E J; Thome, Johannes

    2013-12-30

    In patients with attention deficit hyperactivity disorder (ADHD), quantitative neuroimaging techniques have revealed abnormalities in various brain regions, including the frontal cortex, striatum, cerebellum, and occipital cortex. Nonlinear signal processing techniques such as sample entropy have been used to probe the regularity of brain magnetoencephalography signals in patients with ADHD. In the present study, we extend this technique to analyse the complex output patterns of the 4 dimensional resting state functional magnetic resonance imaging signals in adult patients with ADHD. After adjusting for the effect of age, we found whole brain entropy differences (P=0.002) between groups and negative correlation (r=-0.45) between symptom scores and mean whole brain entropy values, indicating lower complexity in patients. In the regional analysis, patients showed reduced entropy in frontal and occipital regions bilaterally and a significant negative correlation between the symptom scores and the entropy maps at a family-wise error corrected cluster level of Pentropy is a useful tool in revealing abnormalities in the brain dynamics of patients with psychiatric disorders. © 2013 Elsevier Ireland Ltd. All rights reserved.

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

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    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.

  19. Disrupted topological organization of resting-state functional brain network in subcortical vascular mild cognitive impairment.

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    Yi, Li-Ye; Liang, Xia; Liu, Da-Ming; Sun, Bo; Ying, Sun; Yang, Dong-Bo; Li, Qing-Bin; Jiang, Chuan-Lu; Han, Ying

    2015-10-01

    Neuroimaging studies have demonstrated both structural and functional abnormalities in widespread brain regions in patients with subcortical vascular mild cognitive impairment (svMCI). However, whether and how these changes alter functional brain network organization remains largely unknown. We recruited 21 patients with svMCI and 26 healthy control (HC) subjects who underwent resting-state functional magnetic resonance imaging scans. Graph theory-based network analyses were used to investigate alterations in the topological organization of functional brain networks. Compared with the HC individuals, the patients with svMCI showed disrupted global network topology with significantly increased path length and modularity. Modular structure was also impaired in the svMCI patients with a notable rearrangement of the executive control module, where the parietal regions were split out and grouped as a separate module. The svMCI patients also revealed deficits in the intra- and/or intermodule connectivity of several brain regions. Specifically, the within-module degree was decreased in the middle cingulate gyrus while it was increased in the left anterior insula, medial prefrontal cortex and cuneus. Additionally, increased intermodule connectivity was observed in the inferior and superior parietal gyrus, which was associated with worse cognitive performance in the svMCI patients. Together, our results indicate that svMCI patients exhibit dysregulation of the topological organization of functional brain networks, which has important implications for understanding the pathophysiological mechanism of svMCI. © 2015 John Wiley & Sons Ltd.

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

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    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.

  1. Principal States of Dynamic Functional Connectivity Reveal the Link Between Resting-State and Task-State Brain: An fMRI Study.

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    Cheng, Lin; Zhu, Yang; Sun, Junfeng; Deng, Lifu; He, Naying; Yang, Yang; Ling, Huawei; Ayaz, Hasan; Fu, Yi; Tong, Shanbao

    2018-01-25

    Task-related reorganization of functional connectivity (FC) has been widely investigated. Under classic static FC analysis, brain networks under task and rest have been demonstrated a general similarity. However, brain activity and cognitive process are believed to be dynamic and adaptive. Since static FC inherently ignores the distinct temporal patterns between rest and task, dynamic FC may be more a suitable technique to characterize the brain's dynamic and adaptive activities. In this study, we adopted [Formula: see text]-means clustering to investigate task-related spatiotemporal reorganization of dynamic brain networks and hypothesized that dynamic FC would be able to reveal the link between resting-state and task-state brain organization, including broadly similar spatial patterns but distinct temporal patterns. In order to test this hypothesis, this study examined the dynamic FC in default-mode network (DMN) and motor-related network (MN) using Blood-Oxygenation-Level-Dependent (BOLD)-fMRI data from 26 healthy subjects during rest (REST) and a hand closing-and-opening (HCO) task. Two principal FC states in REST and one principal FC state in HCO were identified. The first principal FC state in REST was found similar to that in HCO, which appeared to represent intrinsic network architecture and validated the broadly similar spatial patterns between REST and HCO. However, the second FC principal state in REST with much shorter "dwell time" implied the transient functional relationship between DMN and MN during REST. In addition, a more frequent shifting between two principal FC states indicated that brain network dynamically maintained a "default mode" in the motor system during REST, whereas the presence of a single principal FC state and reduced FC variability implied a more temporally stable connectivity during HCO, validating the distinct temporal patterns between REST and HCO. Our results further demonstrated that dynamic FC analysis could offer unique

  2. Regional homogeneity of resting-state brain abnormalities in bipolar and unipolar depression.

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    Liu, Chun-Hong; Ma, Xin; Wu, Xia; Zhang, Yu; Zhou, Fu-Chun; Li, Feng; Tie, Chang-Le; Dong, Jie; Wang, Yong-Jun; Yang, Zhi; Wang, Chuan-Yue

    2013-03-05

    Bipolar disorder patients experiencing a depressive episode (BD-dep) without an observed history of mania are often misdiagnosed and are consequently treated as having unipolar depression (UD), leading to inadequate treatment and poor outcomes. An essential solution to this problem is to identify objective biological markers that distinguish BD-dep and UD patients at an early stage. However, studies directly comparing the brain dysfunctions associated with BD-dep and UD are rare. More importantly, the specificity of the differences in brain activity between these mental disorders has not been examined. With whole-brain regional homogeneity analysis and region-of-interest (ROI) based receiver operating characteristic (ROC) analysis, we aimed to compare the resting-state brain activity of BD-dep and UD patients. Furthermore, we examined the specific differences and whether these differences were attributed to the brain abnormality caused by BD-dep, UD, or both. Twenty-one bipolar and 21 unipolar depressed patients, as well as 26 healthy subjects matched for gender, age, and educational levels, participated in the study. We compared the differences in the regional homogeneity (ReHo) of the BD-dep and UD groups and further identified their pathophysiological abnormality. In the brain regions showing a difference between the BD-dep and UD groups, we further conducted receptive operation characteristic (ROC) analyses to confirm the effectiveness of the identified difference in classifying the patients. We observed ReHo differences between the BD-dep and UD groups in the right ventrolateral middle frontal gyrus, right dorsal anterior insular, right ventral anterior insular, right cerebellum posterior gyrus, right posterior cingulate cortex, right parahippocampal gyrus, and left cerebellum anterior gyrus. Further ROI comparisons and ROC analysis on these ROIs showed that the right parahippocampal gyrus reflected abnormality specific to the BD-dep group, while the right

  3. Revealing topological organization of human brain functional networks with resting-state functional near infrared spectroscopy.

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    Niu, Haijing; Wang, Jinhui; Zhao, Tengda; Shu, Ni; He, Yong

    2012-01-01

    The human brain is a highly complex system that can be represented as a structurally interconnected and functionally synchronized network, which assures both the segregation and integration of information processing. Recent studies have demonstrated that a variety of neuroimaging and neurophysiological techniques such as functional magnetic resonance imaging (MRI), diffusion MRI and electroencephalography/magnetoencephalography can be employed to explore the topological organization of human brain networks. However, little is known about whether functional near infrared spectroscopy (fNIRS), a relatively new optical imaging technology, can be used to map functional connectome of the human brain and reveal meaningful and reproducible topological characteristics. We utilized resting-state fNIRS (R-fNIRS) to investigate the topological organization of human brain functional networks in 15 healthy adults. Brain networks were constructed by thresholding the temporal correlation matrices of 46 channels and analyzed using graph-theory approaches. We found that the functional brain network derived from R-fNIRS data had efficient small-world properties, significant hierarchical modular structure and highly connected hubs. These results were highly reproducible both across participants and over time and were consistent with previous findings based on other functional imaging techniques. Our results confirmed the feasibility and validity of using graph-theory approaches in conjunction with optical imaging techniques to explore the topological organization of human brain networks. These results may expand a methodological framework for utilizing fNIRS to study functional network changes that occur in association with development, aging and neurological and psychiatric disorders.

  4. Alcohol affects the brain's resting-state network in social drinkers.

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    Chrysa Lithari

    Full Text Available Acute alcohol intake is known to enhance inhibition through facilitation of GABA(A receptors, which are present in 40% of the synapses all over the brain. Evidence suggests that enhanced GABAergic transmission leads to increased large-scale brain connectivity. Our hypothesis is that acute alcohol intake would increase the functional connectivity of the human brain resting-state network (RSN. To test our hypothesis, electroencephalographic (EEG measurements were recorded from healthy social drinkers at rest, during eyes-open and eyes-closed sessions, after administering to them an alcoholic beverage or placebo respectively. Salivary alcohol and cortisol served to measure the inebriation and stress levels. By calculating Magnitude Square Coherence (MSC on standardized Low Resolution Electromagnetic Tomography (sLORETA solutions, we formed cortical networks over several frequency bands, which were then analyzed in the context of functional connectivity and graph theory. MSC was increased (p<0.05, corrected with False Discovery Rate, FDR corrected in alpha, beta (eyes-open and theta bands (eyes-closed following acute alcohol intake. Graph parameters were accordingly altered in these bands quantifying the effect of alcohol on the structure of brain networks; global efficiency and density were higher and path length was lower during alcohol (vs. placebo, p<0.05. Salivary alcohol concentration was positively correlated with the density of the network in beta band. The degree of specific nodes was elevated following alcohol (vs. placebo. Our findings support the hypothesis that short-term inebriation considerably increases large-scale connectivity in the RSN. The increased baseline functional connectivity can -at least partially- be attributed to the alcohol-induced disruption of the delicate balance between inhibitory and excitatory neurotransmission in favor of inhibitory influences. Thus, it is suggested that short-term inebriation is associated, as

  5. The Impact of Age and Cognitive Reserve on Resting-State Brain Connectivity

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    Jessica I. Fleck

    2017-12-01

    Full Text Available Cognitive reserve (CR is a protective mechanism that supports sustained cognitive function following damage to the physical brain associated with age, injury, or disease. The goal of the research was to identify relationships between age, CR, and brain connectivity. A sample of 90 cognitively normal adults, ages 45–64 years, had their resting-state brain activity recorded with electroencephalography (EEG and completed a series of memory and executive function assessments. CR was estimated using years of education and verbal IQ scores. Participants were divided into younger and older age groups and low- and high-CR groups. We observed greater left- than right-hemisphere coherence in younger participants, and greater right- than left-hemisphere coherence in older participants. In addition, greater coherence was observed under eyes-closed than eyes-open recording conditions for both low-CR and high-CR participants, with a more substantial difference between recording conditions in individuals high in CR regardless of age. Finally, younger participants low in CR exhibited greater mean coherence than younger participants high in CR, whereas the opposite pattern was observed in older participants, with greater coherence in older participants high in CR. Together, these findings suggest the possibility of a shift in the relationship between CR and brain connectivity during aging.

  6. Assessing the mean strength and variations of the time-to-time fluctuations of resting-state brain activity.

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    Li, Zhengjun; Zang, Yu-Feng; Ding, Jianping; Wang, Ze

    2017-04-01

    The time-to-time fluctuations (TTFs) of resting-state brain activity as captured by resting-state fMRI (rsfMRI) have been repeatedly shown to be informative of functional brain structures and disease-related alterations. TTFs can be characterized by the mean and the range of successive difference. The former can be measured with the mean squared successive difference (MSSD), which is mathematically similar to standard deviation; the latter can be calculated by the variability of the successive difference (VSD). The purpose of this study was to evaluate both the resting state-MSSD and VSD of rsfMRI regarding their test-retest stability, sensitivity to brain state change, as well as their biological meanings. We hypothesized that MSSD and VSD are reliable in resting brain; both measures are sensitive to brain state changes such as eyes-open compared to eyes-closed condition; both are predictive of age. These hypotheses were tested with three rsfMRI datasets and proven true, suggesting both MSSD and VSD as reliable and useful tools for resting-state studies.

  7. Neural markers of loss aversion in resting-state brain activity.

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    Canessa, Nicola; Crespi, Chiara; Baud-Bovy, Gabriel; Dodich, Alessandra; Falini, Andrea; Antonellis, Giulia; Cappa, Stefano F

    2017-02-01

    Neural responses in striatal, limbic and somatosensory brain regions track individual differences in loss aversion, i.e. the higher sensitivity to potential losses compared with equivalent gains in decision-making under risk. The engagement of structures involved in the processing of aversive stimuli and experiences raises a further question, i.e. whether the tendency to avoid losses rather than acquire gains represents a transient fearful overreaction elicited by choice-related information, or rather a stable component of one's own preference function, reflecting a specific pattern of neural activity. We tested the latter hypothesis by assessing in 57 healthy human subjects whether the relationship between behavioral and neural loss aversion holds at rest, i.e. when the BOLD signal is collected during 5minutes of cross-fixation in the absence of an explicit task. Within the resting-state networks highlighted by a spatial group Independent Component Analysis (gICA), we found a significant correlation between strength of activity and behavioral loss aversion in the left ventral striatum and right posterior insula/supramarginal gyrus, i.e. the very same regions displaying a pattern of neural loss aversion during explicit choices. Cross-study analyses confirmed that this correlation holds when voxels identified by gICA are used as regions of interest in task-related activity and vice versa. These results suggest that the individual degree of (neural) loss aversion represents a stable dimension of decision-making, which reflects in specific metrics of intrinsic brain activity at rest possibly modulating cortical excitability at choice. Copyright © 2016 Elsevier Inc. All rights reserved.

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

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    Gao, Qing; Xu, Qiang; Duan, Xujun; Liao, Wei; Ding, Jurong; Zhang, Zhiqiang; Li, Yuan; Lu, Guangming; Chen, Huafu

    2013-01-01

    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 (PreCG), 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 (MTG), indicating that the relationship between extraversion and regional arousal is not as simple as proposed by Eysenck.

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

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    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.

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

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

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    Song, Hongwen; Zou, Zhiling; Kou, Juan; Liu, Yang; Yang, Lizhuang; Zilverstand, Anna; d'Oleire Uquillas, Federico; Zhang, Xiaochu

    2015-01-01

    Romantic love is a motivational state associated with a desire to enter or maintain a close relationship with a specific other person. Functional magnetic resonance imaging (fMRI) studies have found activation increases in brain regions involved in the processing of reward, motivation and emotion regulation, when romantic lovers view photographs of their partners. However, not much is known about 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 an "in-love" group (LG, N = 34, currently intensely in love), an "ended-love" group (ELG, N = 34, ended romantic relationship recently), and a "single" group (SG, N = 32, never fallen in love). Results show 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) FC within the reward, motivation, and emotion regulation network (dACC, insula, caudate, amygdala, and nucleus accumbens) as well as FC in 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 duration of love in the LG but negatively correlated with the lovelorn duration of time since breakup in the ELG. This study provides first empirical evidence of love-related alterations in brain functional architecture. Furthermore, the results shed light on the underlying neural mechanisms of romantic love, and demonstrate the

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

    Directory of Open Access Journals (Sweden)

    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.

  13. Changes in Brain Resting-state Functional Connectivity Associated with Peripheral Nerve Block: A Pilot Study.

    Science.gov (United States)

    Melton, M Stephen; Browndyke, Jeffrey N; Harshbarger, Todd B; Madden, David J; Nielsen, Karen C; Klein, Stephen M

    2016-08-01

    Limited information exists on the effects of temporary functional deafferentation (TFD) on brain activity after peripheral nerve block (PNB) in healthy humans. Increasingly, resting-state functional connectivity (RSFC) is being used to study brain activity and organization. The purpose of this study was to test the hypothesis that TFD through PNB will influence changes in RSFC plasticity in central sensorimotor functional brain networks in healthy human participants. The authors achieved TFD using a supraclavicular PNB model with 10 healthy human participants undergoing functional connectivity magnetic resonance imaging before PNB, during active PNB, and during PNB recovery. RSFC differences among study conditions were determined by multiple-comparison-corrected (false discovery rate-corrected P value less than 0.05) random-effects, between-condition, and seed-to-voxel analyses using the left and right manual motor regions. The results of this pilot study demonstrated disruption of interhemispheric left-to-right manual motor region RSFC (e.g., mean Fisher-transformed z [effect size] at pre-PNB 1.05 vs. 0.55 during PNB) but preservation of intrahemispheric RSFC of these regions during PNB. Additionally, there was increased RSFC between the left motor region of interest (PNB-affected area) and bilateral higher order visual cortex regions after clinical PNB resolution (e.g., Fisher z between left motor region of interest and right and left lingual gyrus regions during PNB, -0.1 and -0.6 vs. 0.22 and 0.18 after PNB resolution, respectively). This pilot study provides evidence that PNB has features consistent with other models of deafferentation, making it a potentially useful approach to investigate brain plasticity. The findings provide insight into RSFC of sensorimotor functional brain networks during PNB and PNB recovery and support modulation of the sensory-motor integration feedback loop as a mechanism for explaining the behavioral correlates of peripherally

  14. Extraversion modulates functional connectivity hubs of resting-state brain networks.

    Science.gov (United States)

    Pang, Yajing; Cui, Qian; Duan, Xujun; Chen, Heng; Zeng, Ling; Zhang, Zhiqiang; Lu, Guangming; Chen, Huafu

    2017-09-01

    Personality dimension extraversion describes individual differences in social behaviour and socio-emotional functioning. The intrinsic functional connectivity patterns of the brain are reportedly associated with extraversion. However, whether or not extraversion is associated with functional hubs warrants clarification. Functional hubs are involved in the rapid integration of neural processing, and their dysfunction contributes to the development of neuropsychiatric disorders. In this study, we employed the functional connectivity density (FCD) method for the first time to distinguish the energy-efficient hubs associated with extraversion. The resting-state functional magnetic resonance imaging data of 71 healthy subjects were used in the analysis. Short-range FCD was positively correlated with extraversion in the left cuneus, revealing a link between the local functional activity of this region and extraversion in risk-taking. Long-range FCD was negatively correlated with extraversion in the right superior frontal gyrus and the inferior frontal gyrus. Seed-based resting-state functional connectivity (RSFC) analyses revealed that a decreased long-range FCD in individuals with high extraversion scores showed a low long-range functional connectivity pattern between the medial and dorsolateral prefrontal cortex, middle temporal gyrus, and anterior cingulate cortex. This result suggests that decreased RSFC patterns are responsible for self-esteem, self-evaluation, and inhibitory behaviour system that account for the modulation and shaping of extraversion. Overall, our results emphasize specific brain hubs, and reveal long-range functional connections in relation to extraversion, thereby providing a neurobiological basis of extraversion. © 2015 The British Psychological Society.

  15. An evaluation of the left-brain vs. right-brain hypothesis with resting state functional connectivity magnetic resonance imaging.

    Directory of Open Access Journals (Sweden)

    Jared A Nielsen

    Full Text Available Lateralized brain regions subserve functions such as language and visuospatial processing. It has been conjectured that individuals may be left-brain dominant or right-brain dominant based on personality and cognitive style, but neuroimaging data has not provided clear evidence whether such phenotypic differences in the strength of left-dominant or right-dominant networks exist. We evaluated whether strongly lateralized connections covaried within the same individuals. Data were analyzed from publicly available resting state scans for 1011 individuals between the ages of 7 and 29. For each subject, functional lateralization was measured for each pair of 7266 regions covering the gray matter at 5-mm resolution as a difference in correlation before and after inverting images across the midsagittal plane. The difference in gray matter density between homotopic coordinates was used as a regressor to reduce the effect of structural asymmetries on functional lateralization. Nine left- and 11 right-lateralized hubs were identified as peaks in the degree map from the graph of significantly lateralized connections. The left-lateralized hubs included regions from the default mode network (medial prefrontal cortex, posterior cingulate cortex, and temporoparietal junction and language regions (e.g., Broca Area and Wernicke Area, whereas the right-lateralized hubs included regions from the attention control network (e.g., lateral intraparietal sulcus, anterior insula, area MT, and frontal eye fields. Left- and right-lateralized hubs formed two separable networks of mutually lateralized regions. Connections involving only left- or only right-lateralized hubs showed positive correlation across subjects, but only for connections sharing a node. Lateralization of brain connections appears to be a local rather than global property of brain networks, and our data are not consistent with a whole-brain phenotype of greater "left-brained" or greater "right-brained

  16. An evaluation of the left-brain vs. right-brain hypothesis with resting state functional connectivity magnetic resonance imaging.

    Science.gov (United States)

    Nielsen, Jared A; Zielinski, Brandon A; Ferguson, Michael A; Lainhart, Janet E; Anderson, Jeffrey S

    2013-01-01

    Lateralized brain regions subserve functions such as language and visuospatial processing. It has been conjectured that individuals may be left-brain dominant or right-brain dominant based on personality and cognitive style, but neuroimaging data has not provided clear evidence whether such phenotypic differences in the strength of left-dominant or right-dominant networks exist. We evaluated whether strongly lateralized connections covaried within the same individuals. Data were analyzed from publicly available resting state scans for 1011 individuals between the ages of 7 and 29. For each subject, functional lateralization was measured for each pair of 7266 regions covering the gray matter at 5-mm resolution as a difference in correlation before and after inverting images across the midsagittal plane. The difference in gray matter density between homotopic coordinates was used as a regressor to reduce the effect of structural asymmetries on functional lateralization. Nine left- and 11 right-lateralized hubs were identified as peaks in the degree map from the graph of significantly lateralized connections. The left-lateralized hubs included regions from the default mode network (medial prefrontal cortex, posterior cingulate cortex, and temporoparietal junction) and language regions (e.g., Broca Area and Wernicke Area), whereas the right-lateralized hubs included regions from the attention control network (e.g., lateral intraparietal sulcus, anterior insula, area MT, and frontal eye fields). Left- and right-lateralized hubs formed two separable networks of mutually lateralized regions. Connections involving only left- or only right-lateralized hubs showed positive correlation across subjects, but only for connections sharing a node. Lateralization of brain connections appears to be a local rather than global property of brain networks, and our data are not consistent with a whole-brain phenotype of greater "left-brained" or greater "right-brained" network strength

  17. Sex differences in associations of arginine vasopressin and oxytocin with resting-state functional brain connectivity.

    Science.gov (United States)

    Rubin, Leah H; Yao, Li; Keedy, Sarah K; Reilly, James L; Bishop, Jeffrey R; Carter, C Sue; Pournajafi-Nazarloo, Hossein; Drogos, Lauren L; Tamminga, Carol A; Pearlson, Godfrey D; Keshavan, Matcheri S; Clementz, Brett A; Hill, Scot K; Liao, Wei; Ji, Gong-Jun; Lui, Su; Sweeney, John A

    2017-01-02

    Oxytocin (OT) and arginine vasopressin (AVP) exert robust and sexually dimorphic influences on cognition and emotion. How these hormones regulate relevant functional brain systems is not well understood. OT and AVP serum concentrations were assayed in 60 healthy individuals (36 women). Brain functional networks assessed with resting-state functional magnetic resonance imaging (rs-fMRI) were constructed with graph theory-based approaches that characterize brain networks as connected nodes. Sex differences were demonstrated in rs-fMRI. Men showed higher nodal degree (connectedness) and efficiency (information propagation capacity) in left inferior frontal gyrus (IFG) and bilateral superior temporal gyrus (STG) and higher nodal degree in left rolandic operculum. Women showed higher nodal betweenness (being part of paths between nodes) in right putamen and left inferior parietal gyrus (IPG). Higher hormone levels were associated with less intrinsic connectivity. In men, higher AVP was associated with lower nodal degree and efficiency in left IFG (pars orbitalis) and left STG and less efficiency in left IFG (pars triangularis). In women, higher AVP was associated with lower betweenness in left IPG, and higher OT was associated with lower nodal degree in left IFG (pars orbitalis). Hormones differentially correlate with brain networks that are important for emotion processing and cognition in men and women. AVP in men and OT in women may regulate orbital frontal cortex connectivity, which is important in emotion processing. Hormone associations with STG and pars triangularis in men and parietal cortex in women may account for well-established sex differences in verbal and visuospatial abilities, respectively. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  18. Is Rest Really Rest? Resting State Functional Connectivity during Rest and Motor Task Paradigms.

    Science.gov (United States)

    Jurkiewicz, Michael T; Crawley, Adrian P; Mikulis, David J

    2018-04-18

    Numerous studies have identified the default mode network (DMN) within the brain of healthy individuals, which has been attributed to the ongoing mental activity of the brain during the wakeful resting-state. While engaged during specific resting-state fMRI paradigms, it remains unclear as to whether traditional block-design simple movement fMRI experiments significantly influence the default mode network or other areas. Using blood-oxygen level dependent (BOLD) fMRI we characterized the pattern of functional connectivity in healthy subjects during a resting-state paradigm and compared this to the same resting-state analysis performed on motor task data residual time courses after regressing out the task paradigm. Using seed-voxel analysis to define the DMN, the executive control network (ECN), and sensorimotor, auditory and visual networks, the resting-state analysis of the residual time courses demonstrated reduced functional connectivity in the motor network and reduced connectivity between the insula and the ECN compared to the standard resting-state datasets. Overall, performance of simple self-directed motor tasks does little to change the resting-state functional connectivity across the brain, especially in non-motor areas. This would suggest that previously acquired fMRI studies incorporating simple block-design motor tasks could be mined retrospectively for assessment of the resting-state connectivity.

  19. 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.

    2016-01-01

    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. PMID:27456537

  20. 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. Copyright © 2016 Elsevier Inc. All rights reserved.

  1. Decreased Complexity in Alzheimer's Disease: Resting-State fMRI Evidence of Brain Entropy Mapping

    Directory of Open Access Journals (Sweden)

    Bin Wang

    2017-11-01

    Full Text Available Alzheimer's disease (AD is a frequently observed, irreversible brain function disorder among elderly individuals. Resting-state functional magnetic resonance imaging (rs-fMRI has been introduced as an alternative approach to assessing brain functional abnormalities in AD patients. However, alterations in the brain rs-fMRI signal complexities in mild cognitive impairment (MCI and AD patients remain unclear. Here, we described the novel application of permutation entropy (PE to investigate the abnormal complexity of rs-fMRI signals in MCI and AD patients. The rs-fMRI signals of 30 normal controls (NCs, 33 early MCI (EMCI, 32 late MCI (LMCI, and 29 AD patients were obtained from the Alzheimer's disease Neuroimaging Initiative (ADNI database. After preprocessing, whole-brain entropy maps of the four groups were extracted and subjected to Gaussian smoothing. We performed a one-way analysis of variance (ANOVA on the brain entropy maps of the four groups. The results after adjusting for age and sex differences together revealed that the patients with AD exhibited lower complexity than did the MCI and NC controls. We found five clusters that exhibited significant differences and were distributed primarily in the occipital, frontal, and temporal lobes. The average PE of the five clusters exhibited a decreasing trend from MCI to AD. The AD group exhibited the least complexity. Additionally, the average PE of the five clusters was significantly positively correlated with the Mini-Mental State Examination (MMSE scores and significantly negatively correlated with Functional Assessment Questionnaire (FAQ scores and global Clinical Dementia Rating (CDR scores in the patient groups. Significant correlations were also found between the PE and regional homogeneity (ReHo in the patient groups. These results indicated that declines in PE might be related to changes in regional functional homogeneity in AD. These findings suggested that complexity analyses using PE

  2. Handedness- and Brain Size-Related Efficiency Differences in Small-World Brain Networks: A Resting-State Functional Magnetic Resonance Imaging Study

    OpenAIRE

    Li, Meiling; Wang, Junping; Liu, Feng; Chen, Heng; Lu, Fengmei; Wu, Guorong; Yu, Chunshui; Chen, Huafu

    2015-01-01

    The human brain has been described as a complex network, which integrates information with high efficiency. However, the relationships between the efficiency of human brain functional networks and handedness and brain size remain unclear. Twenty-one left-handed and 32 right-handed healthy subjects underwent a resting-state functional magnetic resonance imaging scan. The whole brain functional networks were constructed by thresholding Pearson correlation matrices of 90 cortical and subcortical...

  3. Whole brain, high resolution spin-echo resting state fMRI using PINS multiplexing at 7 T

    NARCIS (Netherlands)

    Koopmans, P.J.; Boyacioglu, R.; Barth, M.; Norris, David Gordon

    2012-01-01

    This article demonstrates the application of spin-echo EPI for resting state fMRI at 7 T. A short repetition time of 1860 ms was made possible by the use of slice multiplexing which permitted whole brain coverage at high spatial resolution (84 slices of 1.6 mm thickness). Radiofrequency power

  4. Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI

    OpenAIRE

    Tingting Xu; Kathryn R. Cullen; Bryon Mueller; Mindy W. Schreiner; Kelvin O. Lim; S. Charles Schulz; Keshab K. Parhi

    2016-01-01

    Borderline personality disorder (BPD) is associated with symptoms such as affect dysregulation, impaired sense of self, and self-harm behaviors. Neuroimaging research on BPD has revealed structural and functional abnormalities in specific brain regions and connections. However, little is known about the topological organizations of brain networks in BPD. We collected resting-state functional magnetic resonance imaging (fMRI) data from 20 patients with BPD and 10 healthy controls, and construc...

  5. Association between resting-state brain network topological organization and creative ability: Evidence from a multiple linear regression model.

    Science.gov (United States)

    Jiao, Bingqing; Zhang, Delong; Liang, Aiying; Liang, Bishan; Wang, Zengjian; Li, Junchao; Cai, Yuxuan; Gao, Mengxia; Gao, Zhenni; Chang, Song; Huang, Ruiwang; Liu, Ming

    2017-10-01

    Previous studies have indicated a tight linkage between resting-state functional connectivity of the human brain and creative ability. This study aimed to further investigate the association between the topological organization of resting-state brain networks and creativity. Therefore, we acquired resting-state fMRI data from 22 high-creativity participants and 22 low-creativity participants (as determined by their Torrance Tests of Creative Thinking scores). We then constructed functional brain networks for each participant and assessed group differences in network topological properties before exploring the relationships between respective network topological properties and creative ability. We identified an optimized organization of intrinsic brain networks in both groups. However, compared with low-creativity participants, high-creativity participants exhibited increased global efficiency and substantially decreased path length, suggesting increased efficiency of information transmission across brain networks in creative individuals. Using a multiple linear regression model, we further demonstrated that regional functional integration properties (i.e., the betweenness centrality and global efficiency) of brain networks, particularly the default mode network (DMN) and sensorimotor network (SMN), significantly predicted the individual differences in creative ability. Furthermore, the associations between network regional properties and creative performance were creativity-level dependent, where the difference in the resource control component may be important in explaining individual difference in creative performance. These findings provide novel insights into the neural substrate of creativity and may facilitate objective identification of creative ability. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. Resting-state brain networks in patients with Parkinson's disease and impulse control disorders.

    Science.gov (United States)

    Tessitore, Alessandro; Santangelo, Gabriella; De Micco, Rosa; Giordano, Alfonso; Raimo, Simona; Amboni, Marianna; Esposito, Fabrizio; Barone, Paolo; Tedeschi, Gioacchino; Vitale, Carmine

    2017-09-01

    To investigate intrinsic neural networks connectivity changes in Parkinson's disease (PD) patients with and without impulse control disorders (ICD). Fifteen patients with PD with ICD (ICD+), 15 patients with PD without ICD (ICD-) and 24 age and sex-matched healthy controls (HC) were enrolled in the study. To identify patients with and without ICD and/or punding, we used the Minnesota Impulsive Disorders Interview (MIDI) and a clinical interview based on diagnostic criteria for each symptom. All patients underwent a detailed neuropsychological evaluation. Whole brain structural and functional imaging was performed on a 3T GE MR scanner. Statistical analysis of functional data was completed using BrainVoyager QX software. Voxel-based morphometry (VBM) was used to test whether between-group differences in resting-state connectivity were related to structural abnormalities. The presence of ICD symptoms was associated with an increased connectivity within the salience and default-mode networks, as well as with a decreased connectivity within the central executive network (p < .05 corrected). ICD severity was correlated with both salience and default mode networks connectivity changes only in the ICD+ group. VBM analysis did not reveal any statistically significant differences in local grey matter volume between ICD+ and ICD- patients and between all patients and HC (p < .05. FWE). The presence of a disrupted connectivity within the three core neurocognitive networks may be considered as a potential neural correlate of ICD presence in patients with PD. Our findings provide additional insights into the mechanisms underlying ICD in PD, confirming the crucial role of an abnormal prefrontal-limbic-striatal homeostasis in their development. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. 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.

  8. 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.

  9. 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.

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

    International Nuclear Information System (INIS)

    Liu Yaou; Liang Peipeng; Duan Yunyun; Jia Xiuqin; Wang Fei; Yu Chunshui; Qin Wen; Dong Huiqing; Ye Jing; Li Kuncheng

    2011-01-01

    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.

  11. Brain resting-state networks in adolescents with high-functioning autism: Analysis of spatial connectivity and temporal neurodynamics.

    Science.gov (United States)

    Bernas, Antoine; Barendse, Evelien M; Aldenkamp, Albert P; Backes, Walter H; Hofman, Paul A M; Hendriks, Marc P H; Kessels, Roy P C; Willems, Frans M J; de With, Peter H N; Zinger, Svitlana; Jansen, Jacobus F A

    2018-02-01

    Autism spectrum disorder (ASD) is mainly characterized by functional and communication impairments as well as restrictive and repetitive behavior. The leading hypothesis for the neural basis of autism postulates globally abnormal brain connectivity, which can be assessed using functional magnetic resonance imaging (fMRI). Even in the absence of a task, the brain exhibits a high degree of functional connectivity, known as intrinsic, or resting-state, connectivity. Global default connectivity in individuals with autism versus controls is not well characterized, especially for a high-functioning young population. The aim of this study is to test whether high-functioning adolescents with ASD (HFA) have an abnormal resting-state functional connectivity. We performed spatial and temporal analyses on resting-state networks (RSNs) in 13 HFA adolescents and 13 IQ- and age-matched controls. For the spatial analysis, we used probabilistic independent component analysis (ICA) and a permutation statistical method to reveal the RSN differences between the groups. For the temporal analysis, we applied Granger causality to find differences in temporal neurodynamics. Controls and HFA display very similar patterns and strengths of resting-state connectivity. We do not find any significant differences between HFA adolescents and controls in the spatial resting-state connectivity. However, in the temporal dynamics of this connectivity, we did find differences in the causal effect properties of RSNs originating in temporal and prefrontal cortices. The results show a difference between HFA and controls in the temporal neurodynamics from the ventral attention network to the salience-executive network: a pathway involving cognitive, executive, and emotion-related cortices. We hypothesized that this weaker dynamic pathway is due to a subtle trigger challenging the cognitive state prior to the resting state.

  12. Effective brain network analysis with resting-state EEG data: a comparison between heroin abstinent and non-addicted subjects

    Science.gov (United States)

    Hu, Bin; Dong, Qunxi; Hao, Yanrong; Zhao, Qinglin; Shen, Jian; Zheng, Fang

    2017-08-01

    Objective. Neuro-electrophysiological tools have been widely used in heroin addiction studies. Previous studies indicated that chronic heroin abuse would result in abnormal functional organization of the brain, while few heroin addiction studies have applied the effective connectivity tool to analyze the brain functional system (BFS) alterations induced by heroin abuse. The present study aims to identify the abnormality of resting-state heroin abstinent BFS using source decomposition and effective connectivity tools. Approach. The resting-state electroencephalograph (EEG) signals were acquired from 15 male heroin abstinent (HA) subjects and 14 male non-addicted (NA) controls. Multivariate autoregressive models combined independent component analysis (MVARICA) was applied for blind source decomposition. Generalized partial directed coherence (GPDC) was applied for effective brain connectivity analysis. Effective brain networks of both HA and NA groups were constructed. The two groups of effective cortical networks were compared by the bootstrap method. Abnormal causal interactions between decomposed source regions were estimated in the 1-45 Hz frequency domain. Main results. This work suggested: (a) there were clear effective network alterations in heroin abstinent subject groups; (b) the parietal region was a dominant hub of the abnormally weaker causal pathways, and the left occipital region was a dominant hub of the abnormally stronger causal pathways. Significance. These findings provide direct evidence that chronic heroin abuse induces brain functional abnormalities. The potential value of combining effective connectivity analysis and brain source decomposition methods in exploring brain alterations of heroin addicts is also implied.

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

    NARCIS (Netherlands)

    Veer, I.M.; Beckmann, C.F.; van Tol, M.J.; Ferrarini, L.; Milles, J.; Veltman, D.J.; Aleman, A.; van Buchem, M.A.; van der Wee, N.J.; Rombouts, S.A.R.B.

    2010-01-01

    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

  14. Brain Structure and Resting-State Functional Connectivity in University Professors with High Academic Achievement

    Science.gov (United States)

    Li, Weiwei; Yang, Wenjing; Li, Wenfu; Li, Yadan; Wei, Dongtao; Li, Huimin; Qiu, Jiang; Zhang, Qinglin

    2015-01-01

    Creative persons play an important role in technical innovation and social progress. There is little research on the neural correlates with researchers with high academic achievement. We used a combined structural (regional gray matter volume, rGMV) and functional (resting-state functional connectivity analysis, rsFC) approach to examine the…

  15. ABERRANT RESTING-STATE BRAIN ACTIVITY IN POSTTRAUMATIC STRESS DISORDER: A META-ANALYSIS AND SYSTEMATIC REVIEW.

    Science.gov (United States)

    Koch, Saskia B J; van Zuiden, Mirjam; Nawijn, Laura; Frijling, Jessie L; Veltman, Dick J; Olff, Miranda

    2016-07-01

    About 10% of trauma-exposed individuals develop PTSD. Although a growing number of studies have investigated resting-state abnormalities in PTSD, inconsistent results suggest a need for a meta-analysis and a systematic review. We conducted a systematic literature search in four online databases using keywords for PTSD, functional neuroimaging, and resting-state. In total, 23 studies matched our eligibility criteria. For the meta-analysis, we included 14 whole-brain resting-state studies, reporting data on 663 participants (298 PTSD patients and 365 controls). We used the activation likelihood estimation approach to identify concurrence of whole-brain hypo- and hyperactivations in PTSD patients during rest. Seed-based studies could not be included in the quantitative meta-analysis. Therefore, a separate qualitative systematic review was conducted on nine seed-based functional connectivity studies. The meta-analysis showed consistent hyperactivity in the ventral anterior cingulate cortex and the parahippocampus/amygdala, but hypoactivity in the (posterior) insula, cerebellar pyramis and middle frontal gyrus in PTSD patients, compared to healthy controls. Partly concordant with these findings, the systematic review on seed-based functional connectivity studies showed enhanced salience network (SN) connectivity, but decreased default mode network (DMN) connectivity in PTSD. Combined, these altered resting-state connectivity and activity patterns could represent neurobiological correlates of increased salience processing and hypervigilance (SN), at the cost of awareness of internal thoughts and autobiographical memory (DMN) in PTSD. However, several discrepancies between findings of the meta-analysis and systematic review were observed, stressing the need for future studies on resting-state abnormalities in PTSD patients. © 2016 Wiley Periodicals, Inc.

  16. Superiority illusion arises from resting-state brain networks modulated by dopamine.

    Science.gov (United States)

    Yamada, Makiko; Uddin, Lucina Q; Takahashi, Hidehiko; Kimura, Yasuyuki; Takahata, Keisuke; Kousa, Ririko; Ikoma, Yoko; Eguchi, Yoko; Takano, Harumasa; Ito, Hiroshi; Higuchi, Makoto; Suhara, Tetsuya

    2013-03-12

    The majority of individuals evaluate themselves as superior to average. This is a cognitive bias known as the "superiority illusion." This illusion helps us to have hope for the future and is deep-rooted in the process of human evolution. In this study, we examined the default states of neural and molecular systems that generate this illusion, using resting-state functional MRI and PET. Resting-state functional connectivity between the frontal cortex and striatum regulated by inhibitory dopaminergic neurotransmission determines individual levels of the superiority illusion. Our findings help elucidate how this key aspect of the human mind is biologically determined, and identify potential molecular and neural targets for treatment for depressive realism.

  17. 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.

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

    International Nuclear Information System (INIS)

    Jeong, Bum Seok; Choi, Jee Wook; Kim, Ji Woong

    2012-01-01

    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.

  19. Resting State Functional Connectivity in Mild Traumatic Brain Injury at the Acute Stage: Independent Component and Seed-Based Analyses

    Science.gov (United States)

    Iraji, Armin; Benson, Randall R.; Welch, Robert D.; O'Neil, Brian J.; Woodard, John L.; Imran Ayaz, Syed; Kulek, Andrew; Mika, Valerie; Medado, Patrick; Soltanian-Zadeh, Hamid; Liu, Tianming; Haacke, E. Mark

    2015-01-01

    Abstract Mild traumatic brain injury (mTBI) accounts for more than 1 million emergency visits each year. Most of the injured stay in the emergency department for a few hours and are discharged home without a specific follow-up plan because of their negative clinical structural imaging. Advanced magnetic resonance imaging (MRI), particularly functional MRI (fMRI), has been reported as being sensitive to functional disturbances after brain injury. In this study, a cohort of 12 patients with mTBI were prospectively recruited from the emergency department of our local Level-1 trauma center for an advanced MRI scan at the acute stage. Sixteen age- and sex-matched controls were also recruited for comparison. Both group-based and individual-based independent component analysis of resting-state fMRI (rsfMRI) demonstrated reduced functional connectivity in both posterior cingulate cortex (PCC) and precuneus regions in comparison with controls, which is part of the default mode network (DMN). Further seed-based analysis confirmed reduced functional connectivity in these two regions and also demonstrated increased connectivity between these regions and other regions of the brain in mTBI. Seed-based analysis using the thalamus, hippocampus, and amygdala regions further demonstrated increased functional connectivity between these regions and other regions of the brain, particularly in the frontal lobe, in mTBI. Our data demonstrate alterations of multiple brain networks at the resting state, particularly increased functional connectivity in the frontal lobe, in response to brain concussion at the acute stage. Resting-state functional connectivity of the DMN could serve as a potential biomarker for improved detection of mTBI in the acute setting. PMID:25285363

  20. Clustering of resting state networks.

    Directory of Open Access Journals (Sweden)

    Megan H Lee

    Full Text Available 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.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.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.

  1. Exploring resting-state EEG brain oscillatory activity in relation to cognitive functioning in multiple sclerosis.

    Science.gov (United States)

    Keune, Philipp M; Hansen, Sascha; Weber, Emily; Zapf, Franziska; Habich, Juliane; Muenssinger, Jana; Wolf, Sebastian; Schönenberg, Michael; Oschmann, Patrick

    2017-09-01

    Neurophysiologic monitoring parameters related to cognition in Multiple Sclerosis (MS) are sparse. Previous work reported an association between magnetoencephalographic (MEG) alpha-1 activity and information processing speed. While this remains to be replicated by more available electroencephalographic (EEG) methods, also other established EEG markers, e.g. the slow-wave/fast-wave ratio (theta/beta ratio), remain to be explored in this context. Performance on standard tests addressing information processing speed and attention (Symbol-Digit Modalities Test, SDMT; Test of Attention Performance, TAP) was examined in relation to resting-state EEG alpha-1 and alpha-2 activity and the theta/beta ratio in 25MS patients. Increased global alpha-1 and alpha-2 activity and an increased frontal theta/beta ratio (pronounced slow-wave relative to fast-wave activity) were associated with lower SDMT processing speed. In an exploratory analysis, clinically impaired attention was associated with a significantly increased frontal theta/beta ratio whereas alpha power did not show sensitivity to clinical impairment. EEG global alpha power and the frontal theta/beta ratio were both associated with attention. The theta/beta ratio involved potential clinical sensitivity. Resting-state EEG recordings can be obtained during the routine clinical process. The examined resting-state measures may represent feasible monitoring parameters in MS. This notion should be explored in future intervention studies. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

  2. 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.

  3. 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.

  4. A Bayesian Double Fusion Model for Resting-State Brain Connectivity Using Joint Functional and Structural Data

    KAUST Repository

    Kang, Hakmook

    2017-03-20

    Current approaches separately analyze concurrently acquired diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) data. The primary limitation of these approaches is that they do not take advantage of the information from DTI that could potentially enhance estimation of resting-state functional connectivity (FC) between brain regions. To overcome this limitation, we develop a Bayesian hierarchical spatiotemporal model that incorporates structural connectivity (SC) into estimating FC. In our proposed approach, SC based on DTI data is used to construct an informative prior for FC based on resting-state fMRI data through the Cholesky decomposition. Simulation studies showed that incorporating the two data produced significantly reduced mean squared errors compared to the standard approach of separately analyzing the two data from different modalities. We applied our model to analyze the resting state DTI and fMRI data collected to estimate FC between the brain regions that were hypothetically important in the origination and spread of temporal lobe epilepsy seizures. Our analysis concludes that the proposed model achieves smaller false positive rates and is much robust to data decimation compared to the conventional approach.

  5. Resting state fMRI: A review on methods in resting state connectivity analysis and resting state networks.

    Science.gov (United States)

    Smitha, K A; Akhil Raja, K; Arun, K M; Rajesh, P G; Thomas, Bejoy; Kapilamoorthy, T R; Kesavadas, Chandrasekharan

    2017-08-01

    The inquisitiveness about what happens in the brain has been there since the beginning of humankind. Functional magnetic resonance imaging is a prominent tool which helps in the non-invasive examination, localisation as well as lateralisation of brain functions such as language, memory, etc. In recent years, there is an apparent shift in the focus of neuroscience research to studies dealing with a brain at 'resting state'. Here the spotlight is on the intrinsic activity within the brain, in the absence of any sensory or cognitive stimulus. The analyses of functional brain connectivity in the state of rest have revealed different resting state networks, which depict specific functions and varied spatial topology. However, different statistical methods have been introduced to study resting state functional magnetic resonance imaging connectivity, yet producing consistent results. In this article, we introduce the concept of resting state functional magnetic resonance imaging in detail, then discuss three most widely used methods for analysis, describe a few of the resting state networks featuring the brain regions, associated cognitive functions and clinical applications of resting state functional magnetic resonance imaging. This review aims to highlight the utility and importance of studying resting state functional magnetic resonance imaging connectivity, underlining its complementary nature to the task-based functional magnetic resonance imaging.

  6. Measuring and manipulating brain connectivity with resting state functional connectivity magnetic resonance imaging (fcMRI) and transcranial magnetic stimulation (TMS).

    Science.gov (United States)

    Fox, Michael D; Halko, Mark A; Eldaief, Mark C; Pascual-Leone, Alvaro

    2012-10-01

    Both resting state functional magnetic resonance imaging (fcMRI) and transcranial magnetic stimulation (TMS) are increasingly popular techniques that can be used to non-invasively measure brain connectivity in human subjects. TMS shows additional promise as a method to manipulate brain connectivity. In this review we discuss how these two complimentary tools can be combined to optimally study brain connectivity and manipulate distributed brain networks. Important clinical applications include using resting state fcMRI to guide target selection for TMS and using TMS to modulate pathological network interactions identified with resting state fcMRI. The combination of TMS and resting state fcMRI has the potential to accelerate the translation of both techniques into the clinical realm and promises a new approach to the diagnosis and treatment of neurological and psychiatric diseases that demonstrate network pathology. Copyright © 2012 Elsevier Inc. All rights reserved.

  7. Altered functional connectivity architecture of the brain in medication overuse headache using resting state fMRI.

    Science.gov (United States)

    Chen, Zhiye; Chen, Xiaoyan; Liu, Mengqi; Dong, Zhao; Ma, Lin; Yu, Shengyuan

    2017-12-01

    Functional connectivity density (FCD) could identify the abnormal intrinsic and spontaneous activity over the whole brain, and a seed-based resting-state functional connectivity (RSFC) could further reveal the altered functional network with the identified brain regions. This may be an effective assessment strategy for headache research. This study is to investigate the RSFC architecture changes of the brain in the patients with medication overuse headache (MOH) using FCD and RSFC methods. 3D structure images and resting-state functional MRI data were obtained from 37 MOH patients, 18 episodic migraine (EM) patients and 32 normal controls (NCs). FCD was calculated to detect the brain regions with abnormal functional activity over the whole brain, and the seed-based RSFC was performed to explore the functional network changes in MOH and EM. The decreased FCD located in right parahippocampal gyrus, and the increased FCD located in left inferior parietal gyrus and right supramarginal gyrus in MOH compared with NC, and in right caudate and left insula in MOH compared with EM. RSFC revealed that decreased functional connectivity of the brain regions with decreased FCD anchored in the right dorsal-lateral prefrontal cortex, right frontopolar cortex in MOH, and in left temporopolar cortex and bilateral visual cortices in EM compared with NC, and in frontal-temporal-parietal pattern in MOH compared with EM. These results provided evidence that MOH and EM suffered from altered intrinsic functional connectivity architecture, and the current study presented a new perspective for understanding the neuromechanism of MOH and EM pathogenesis.

  8. A Resting-State Brain Functional Network Study in MDD Based on Minimum Spanning Tree Analysis and the Hierarchical Clustering

    Directory of Open Access Journals (Sweden)

    Xiaowei Li

    2017-01-01

    Full Text Available A large number of studies demonstrated that major depressive disorder (MDD is characterized by the alterations in brain functional connections which is also identifiable during the brain’s “resting-state.” But, in the present study, the approach of constructing functional connectivity is often biased by the choice of the threshold. Besides, more attention was paid to the number and length of links in brain networks, and the clustering partitioning of nodes was unclear. Therefore, minimum spanning tree (MST analysis and the hierarchical clustering were first used for the depression disease in this study. Resting-state electroencephalogram (EEG sources were assessed from 15 healthy and 23 major depressive subjects. Then the coherence, MST, and the hierarchical clustering were obtained. In the theta band, coherence analysis showed that the EEG coherence of the MDD patients was significantly higher than that of the healthy controls especially in the left temporal region. The MST results indicated the higher leaf fraction in the depressed group. Compared with the normal group, the major depressive patients lost clustering in frontal regions. Our findings suggested that there was a stronger brain interaction in the MDD group and a left-right functional imbalance in the frontal regions for MDD controls.

  9. Low-frequency hippocampal-cortical activity drives brain-wide resting-state functional MRI connectivity.

    Science.gov (United States)

    Chan, Russell W; Leong, Alex T L; Ho, Leon C; Gao, Patrick P; Wong, Eddie C; Dong, Celia M; Wang, Xunda; He, Jufang; Chan, Ying-Shing; Lim, Lee Wei; Wu, Ed X

    2017-08-15

    The hippocampus, including the dorsal dentate gyrus (dDG), and cortex engage in bidirectional communication. We propose that low-frequency activity in hippocampal-cortical pathways contributes to brain-wide resting-state connectivity to integrate sensory information. Using optogenetic stimulation and brain-wide fMRI and resting-state fMRI (rsfMRI), we determined the large-scale effects of spatiotemporal-specific downstream propagation of hippocampal activity. Low-frequency (1 Hz), but not high-frequency (40 Hz), stimulation of dDG excitatory neurons evoked robust cortical and subcortical brain-wide fMRI responses. More importantly, it enhanced interhemispheric rsfMRI connectivity in various cortices and hippocampus. Subsequent local field potential recordings revealed an increase in slow oscillations in dorsal hippocampus and visual cortex, interhemispheric visual cortical connectivity, and hippocampal-cortical connectivity. Meanwhile, pharmacological inactivation of dDG neurons decreased interhemispheric rsfMRI connectivity. Functionally, visually evoked fMRI responses in visual regions also increased during and after low-frequency dDG stimulation. Together, our results indicate that low-frequency activity robustly propagates in the dorsal hippocampal-cortical pathway, drives interhemispheric cortical rsfMRI connectivity, and mediates visual processing.

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

    Directory of Open Access Journals (Sweden)

    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

  11. Hemisphere- and gender-related differences in small-world brain networks: a resting-state functional MRI study.

    Science.gov (United States)

    Tian, Lixia; Wang, Jinhui; Yan, Chaogan; He, Yong

    2011-01-01

    We employed resting-state functional MRI (R-fMRI) to investigate hemisphere- and gender-related differences in the topological organization of human brain functional networks. Brain networks were first constructed by measuring inter-regional temporal correlations of R-fMRI data within each hemisphere in 86 young, healthy, right-handed adults (38 males and 48 females) followed by a graph-theory analysis. The hemispheric networks exhibit small-world attributes (high clustering and short paths) that are compatible with previous results in the whole-brain functional networks. Furthermore, we found that compared with females, males have a higher normalized clustering coefficient in the right hemispheric network but a lower clustering coefficient in the left hemispheric network, suggesting a gender-hemisphere interaction. Moreover, we observed significant hemisphere-related differences in the regional nodal characteristics in various brain regions, such as the frontal and occipital regions (leftward asymmetry) and the temporal regions (rightward asymmetry), findings that are consistent with previous studies of brain structural and functional asymmetries. Together, our results suggest that the topological organization of human brain functional networks is associated with gender and hemispheres, and they provide insights into the understanding of functional substrates underlying individual differences in behaviors and cognition. Copyright © 2010 Elsevier Inc. All rights reserved.

  12. Measuring alterations in oscillatory brain networks in schizophrenia with resting-state MEG: State-of-the-art and methodological challenges.

    Science.gov (United States)

    Alamian, Golnoush; Hincapié, Ana-Sofía; Pascarella, Annalisa; Thiery, Thomas; Combrisson, Etienne; Saive, Anne-Lise; Martel, Véronique; Althukov, Dmitrii; Haesebaert, Frédéric; Jerbi, Karim

    2017-09-01

    Neuroimaging studies provide evidence of disturbed resting-state brain networks in Schizophrenia (SZ). However, untangling the neuronal mechanisms that subserve these baseline alterations requires measurement of their electrophysiological underpinnings. This systematic review specifically investigates the contributions of resting-state Magnetoencephalography (MEG) in elucidating abnormal neural organization in SZ patients. A systematic literature review of resting-state MEG studies in SZ was conducted. This literature is discussed in relation to findings from resting-state fMRI and EEG, as well as to task-based MEG research in SZ population. Importantly, methodological limitations are considered and recommendations to overcome current limitations are proposed. Resting-state MEG literature in SZ points towards altered local and long-range oscillatory network dynamics in various frequency bands. Critical methodological challenges with respect to experiment design, and data collection and analysis need to be taken into consideration. Spontaneous MEG data show that local and global neural organization is altered in SZ patients. MEG is a highly promising tool to fill in knowledge gaps about the neurophysiology of SZ. However, to reach its fullest potential, basic methodological challenges need to be overcome. MEG-based resting-state power and connectivity findings could be great assets to clinical and translational research in psychiatry, and SZ in particular. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

  13. Altered brain function in new onset childhood acute lymphoblastic leukemia before chemotherapy: A resting-state fMRI study.

    Science.gov (United States)

    Hu, Zhanqi; Zou, Dongfang; Mai, Huirong; Yuan, Xiuli; Wang, Lihong; Li, Yue; Liao, Jianxiang; Liu, Liwei; Liu, Guosheng; Zeng, Hongwu; Wen, Feiqiu

    2017-10-01

    Cognitive impairments had been reported in childhood acute lymphoblastic leukemia, what caused the impairments needed to be demonstrated, chemotherapy-related or the disease itself. The primary aim of this exploratory investigation was to determine if there were changes in brain function of children with acute lymphoblastic leukemia before chemotherapy. In this study, we advanced a measure named regional homogeneity to evaluate the resting-state brain activities, intelligence quotient test was performed at same time. Using regional homogeneity, we first investigated the resting state brain function in patients with new onset childhood acute lymphoblastic leukemia before chemotherapy, healthy children as control. The decreased ReHo values were mainly founded in the default mode network and left frontal lobe, bilateral inferior parietal lobule, bilateral temporal lobe, bilateral occipital lobe, precentral gyrus, bilateral cerebellum in the newly diagnosed acute lymphoblastic leukemia patients compared with the healthy control. While in contrast, increased ReHo values were mainly shown in the right frontal lobe (language area), superior frontal gyrus-R, middle frontal gyrus-R and inferior parietal lobule-R for acute lymphoblastic leukemia patients group. There were no significant differences for intelligence quotient measurements between the acute lymphoblastic leukemia patient group and the healthy control in performance intelligence quotient, verbal intelligence quotient, total intelligence quotient. The altered brain functions are associated with cognitive change and language, it is suggested that there may be cognition impairment before the chemotherapy. Regional homogeneity by functional magnetic resonance image is a sensitive way for early detection on brain damage in childhood acute lymphoblastic leukemia. Copyright © 2017 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

  14. Default Mode Network Interference in Mild Traumatic Brain Injury – A Pilot Resting State Study

    Science.gov (United States)

    Sours, Chandler; Zhuo, Jiachen; Janowich, Jacqueline; Aarabi, Bizhan; Shanmuganathan, Kathirkamanthan; Gullapalli, Rao P

    2013-01-01

    In this study we investigated the functional connectivity in 23 Mild TBI (mTBI) patients with and without memory complaints using resting state fMRI in the sub-acute stage of injury as well as a group of control participants. Results indicate that mTBI patients with memory complaints performed significantly worse than patients without memory complaints on tests assessing memory from the Automated Neuropsychological Assessment Metrics (ANAM). Altered functional connectivity was observed between the three groups between the default mode network (DMN) and the nodes of the task positive network (TPN). Altered functional connectivity was also observed between both the TPN and DMN and nodes associated with the Salience Network (SN). Following mTBI there is a reduction in anti-correlated networks for both those with and without memory complaints for the DMN, but only a reduction in the anti-correlated network in mTBI patients with memory complaints for the TPN. Furthermore, an increased functional connectivity between the TPN and SN appears to be associated with reduced performance on memory assessments. Overall the results suggest that a disruption in the segregation of the DMN and the TPN at rest may be mediated through both a direct pathway of increased FC between various nodes of the TPN and DMN, and through an indirect pathway that links the TPN and DMN through nodes of the SN. This disruption between networks may cause a detrimental impact on memory functioning following mTBI, supporting the Default Mode Interference Hypothesis in the context of mTBI related memory deficits. PMID:23994210

  15. Default mode network interference in mild traumatic brain injury - a pilot resting state study.

    Science.gov (United States)

    Sours, Chandler; Zhuo, Jiachen; Janowich, Jacqueline; Aarabi, Bizhan; Shanmuganathan, Kathirkamanthan; Gullapalli, Rao P

    2013-11-06

    In this study we investigated the functional connectivity in 23 Mild TBI (mTBI) patients with and without memory complaints using resting state fMRI in the sub-acute stage of injury as well as a group of control participants. Results indicate that mTBI patients with memory complaints performed significantly worse than patients without memory complaints on tests assessing memory from the Automated Neuropsychological Assessment Metrics (ANAM). Altered functional connectivity was observed between the three groups between the default mode network (DMN) and the nodes of the task positive network (TPN). Altered functional connectivity was also observed between both the TPN and DMN and nodes associated with the Salience Network (SN). Following mTBI there is a reduction in anti-correlated networks for both those with and without memory complaints for the DMN, but only a reduction in the anti-correlated network in mTBI patients with memory complaints for the TPN. Furthermore, an increased functional connectivity between the TPN and SN appears to be associated with reduced performance on memory assessments. Overall the results suggest that a disruption in the segregation of the DMN and the TPN at rest may be mediated through both a direct pathway of increased FC between various nodes of the TPN and DMN, and through an indirect pathway that links the TPN and DMN through nodes of the SN. This disruption between networks may cause a detrimental impact on memory functioning following mTBI, supporting the Default Mode Interference Hypothesis in the context of mTBI related memory deficits. © 2013 Elsevier B.V. All rights reserved.

  16. How motor, cognitive and musical expertise shapes the brain: Focus on fMRI and EEG resting-state functional connectivity

    DEFF Research Database (Denmark)

    Cantou, Pauline; Platel, Hervé; Desgranges, Béatrice

    2017-01-01

    about functional cerebral reorganization due to expertise at the whole-brain level and might facilitate comparison across studies. Resting-state functional MRI and EEG makes it possible to explore the functional traces of expertise in the brain by measuring temporal correlations of blood oxygen level......, to determine whether there is a domain-specific neural signature of expertise. After highlighting expertise-related changes within resting-state networks for each domain, we discuss their specificity to the trained activity and the methodological considerations concerning different conditions and analyses used......-dependent (BOLD) and spontaneous neural activity fluctuations at rest. Since these correlations are thought to reflect a prior history co-activation of brain regions, we propose reviewing studies that focused on the effects of expertise in the motor, cognitive and musical domains on brain plasticity at rest...

  17. Abnormal brain functional connectivity leads to impaired mood and cognition in hyperthyroidism: a resting-state functional MRI study

    Science.gov (United States)

    Li, Ling; Zhi, Mengmeng; Hou, Zhenghua; Zhang, Yuqun; Yue, Yingying; Yuan, Yonggui

    2017-01-01

    Patients with hyperthyroidism frequently have neuropsychiatric complaints such as lack of concentration, poor memory, depression, anxiety, nervousness, and irritability, suggesting brain dysfunction. However, the underlying process of these symptoms remains unclear. Using resting-state functional magnetic resonance imaging (rs-fMRI), we depicted the altered graph theoretical metric degree centrality (DC) and seed-based resting-state functional connectivity (FC) in 33 hyperthyroid patients relative to 33 healthy controls. The peak points of significantly altered DC between the two groups were defined as the seed regions to calculate FC to the whole brain. Then, partial correlation analyses were performed between abnormal DC, FC and neuropsychological performances, as well as some clinical indexes. The decreased intrinsic functional connectivity in the posterior lobe of cerebellum (PLC) and medial frontal gyrus (MeFG), as well as the abnormal seed-based FC anchored in default mode network (DMN), attention network, visual network and cognitive network in this study, possibly constitutes the latent mechanism for emotional and cognitive changes in hyperthyroidism, including anxiety and impaired processing speed. PMID:28009983

  18. Abnormal brain functional connectivity leads to impaired mood and cognition in hyperthyroidism: a resting-state functional MRI study.

    Science.gov (United States)

    Li, Ling; Zhi, Mengmeng; Hou, Zhenghua; Zhang, Yuqun; Yue, Yingying; Yuan, Yonggui

    2017-01-24

    Patients with hyperthyroidism frequently have neuropsychiatric complaints such as lack of concentration, poor memory, depression, anxiety, nervousness, and irritability, suggesting brain dysfunction. However, the underlying process of these symptoms remains unclear. Using resting-state functional magnetic resonance imaging (rs-fMRI), we depicted the altered graph theoretical metric degree centrality (DC) and seed-based resting-state functional connectivity (FC) in 33 hyperthyroid patients relative to 33 healthy controls. The peak points of significantly altered DC between the two groups were defined as the seed regions to calculate FC to the whole brain. Then, partial correlation analyses were performed between abnormal DC, FC and neuropsychological performances, as well as some clinical indexes. The decreased intrinsic functional connectivity in the posterior lobe of cerebellum (PLC) and medial frontal gyrus (MeFG), as well as the abnormal seed-based FC anchored in default mode network (DMN), attention network, visual network and cognitive network in this study, possibly constitutes the latent mechanism for emotional and cognitive changes in hyperthyroidism, including anxiety and impaired processing speed.

  19. Effectiveness of cognitive-coping therapy and alteration of resting-state brain function in obsessive-compulsive disorder.

    Science.gov (United States)

    Zhao, Hong-Zeng; Wang, Chang-Hong; Gao, Zhong-Zhan; Ma, Jian-Dong; Huang, Ping; Li, Heng-Fen; Sang, De-En; Shan, Xiao-Wen; Kou, Shao-Jie; Li, Zhi-Rong; Ma, Li; Zhang, Zhao-Hui; Zhang, Jian-Hong; Ouyang, Hua; Lian, Hong-Kai; Zang, Yu-Feng; Hu, Xian-Zhang

    2017-01-15

    Cognitive-coping therapy (CCT), integrating cognitive theory with stress-coping theory, is an efficacious therapy for obsessive-compulsive disorder (OCD). However, the potential brain mediation for the effectiveness remains unclear. We sought to investigate differences of resting-state brain function between OCD and healthy controls and if such differences would be changed by a four-week CCT. Thirty-one OCD patients were recruited and randomized into CCT (n=15) and pharmacotherapy plus CCT (pCCT, n=16) groups, together with 25 age-, gender- and education-matched healthy controls. The Yale-Brown Obsessive Compulsive Scale (Y-BOCS) was scored to evaluate the severity in symptoms. Resting-state functional magnetic resonance imaging was scanned pre- and post-treatment. For patients, Y-BOCS scores were reduced during four-week treatment for CCT and pCCT (Pleft hippocampus, parahippocampus, and temporal lobes, but lower in the right orbitofrontal cortex, rectus, bilateral calcarine, cuneus, lingual, occipital, left parietal, postcentral, precentral, and parietal (corrected Pbrain function was different between OCD and controls; such differences disappeared after OCD symptoms were relieved. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. Measuring and manipulating brain connectivity with resting state functional connectivity magnetic resonance imaging (fcMRI) and transcranial magnetic stimulation (TMS)

    OpenAIRE

    Fox, Michael D.; Halko, Mark A.; Eldaief, Mark C.; Pascual-Leone, Alvaro

    2012-01-01

    Both resting state functional magnetic resonance imaging (fcMRI) and transcranial magnetic stimulation (TMS) are increasingly popular techniques that can be used to non-invasively measure brain connectivity in human subjects. TMS shows additional promise as a method to manipulate brain connectivity. In this review we discuss how these two complimentary tools can be combined to optimally study brain connectivity and manipulate distributed brain networks. Important clinical applications include...

  1. Handedness- and brain size-related efficiency differences in small-world brain networks: a resting-state functional magnetic resonance imaging study.

    Science.gov (United States)

    Li, Meiling; Wang, Junping; Liu, Feng; Chen, Heng; Lu, Fengmei; Wu, Guorong; Yu, Chunshui; Chen, Huafu

    2015-05-01

    The human brain has been described as a complex network, which integrates information with high efficiency. However, the relationships between the efficiency of human brain functional networks and handedness and brain size remain unclear. Twenty-one left-handed and 32 right-handed healthy subjects underwent a resting-state functional magnetic resonance imaging scan. The whole brain functional networks were constructed by thresholding Pearson correlation matrices of 90 cortical and subcortical regions. Graph theory-based methods were employed to further analyze their topological properties. As expected, all participants demonstrated small-world topology, suggesting a highly efficient topological structure. Furthermore, we found that smaller brains showed higher local efficiency, whereas larger brains showed higher global efficiency, reflecting a suitable efficiency balance between local specialization and global integration of brain functional activity. Compared with right-handers, significant alterations in nodal efficiency were revealed in left-handers, involving the anterior and median cingulate gyrus, middle temporal gyrus, angular gyrus, and amygdala. Our findings indicated that the functional network organization in the human brain was associated with handedness and brain size.

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

    Directory of Open Access Journals (Sweden)

    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.

  3. Network Analysis of Resting State EEG in the Developing Young Brain: Structure Comes With Maturation

    NARCIS (Netherlands)

    Boersma, M.; Smit, D.J.A.; de Bie, H.M.A.; van Baal, G.C.M.; Boomsma, D.I.; de Geus, E.J.C.; Delemarre-van de Waal, H.A.; Stam, C.J.

    2011-01-01

    During childhood, brain structure and function changes substantially. Recently, graph theory has been introduced to model connectivity in the brain. Small-world networks, such as the brain, combine optimal properties of both ordered and random networks, i.e., high clustering and short path lengths.

  4. Abnormal Baseline Brain Activity in Patients with Pulsatile Tinnitus: A Resting-State fMRI Study

    Directory of Open Access Journals (Sweden)

    Lv Han

    2014-01-01

    Full Text Available Numerous investigations studying the brain functional activity of the tinnitus patients have indicated that neurological changes are important findings of this kind of disease. However, the pulsatile tinnitus (PT patients were excluded in previous studies because of the totally different mechanisms of the two subtype tinnitus. The aim of this study is to investigate whether altered baseline brain activity presents in patients with PT using resting-state functional magnetic resonance imaging (rs-fMRI technique. The present study used unilateral PT patients (n=42 and age-, sex-, and education-matched normal control subjects (n=42 to investigate the changes in structural and amplitude of low-frequency (ALFF of the brain. Also, we analyzed the relationships between these changes with clinical data of the PT patients. Compared with normal controls, PT patients did not show any structural changes. PT patients showed significant increased ALFF in the bilateral precuneus, and bilateral inferior frontal gyrus (IFG and decreased ALFF in multiple occipital areas. Moreover, the increased THI score and PT duration was correlated with increased ALFF in precuneus and bilateral IFG. The abnormalities of spontaneous brain activity reflected by ALFF measurements in the absence of structural changes may provide insights into the neural reorganization in PT patients.

  5. Disrupted topological organization in whole-brain functional networks of heroin-dependent individuals: a resting-state FMRI study.

    Directory of Open Access Journals (Sweden)

    Guihua Jiang

    Full Text Available Neuroimaging studies have shown that heroin addiction is related to abnormalities in widespread local regions and in the functional connectivity of the brain. However, little is known about whether heroin addiction changes the topological organization of whole-brain functional networks. Seventeen heroin-dependent individuals (HDIs and 15 age-, gender-matched normal controls (NCs were enrolled, and the resting-state functional magnetic resonance images (RS-fMRI were acquired from these subjects. We constructed the brain functional networks of HDIs and NCs, and compared the between-group differences in network topological properties using graph theory method. We found that the HDIs showed decreases in the normalized clustering coefficient and in small-worldness compared to the NCs. Furthermore, the HDIs exhibited significantly decreased nodal centralities primarily in regions of cognitive control network, including the bilateral middle cingulate gyrus, left middle frontal gyrus, and right precuneus, but significantly increased nodal centralities primarily in the left hippocampus. The between-group differences in nodal centralities were not corrected by multiple comparisons suggesting these should be considered as an exploratory analysis. Moreover, nodal centralities in the left hippocampus were positively correlated with the duration of heroin addiction. Overall, our results indicated that disruptions occur in the whole-brain functional networks of HDIs, findings which may be helpful in further understanding the mechanisms underlying heroin addiction.

  6. Disrupted topological organization in whole-brain functional networks of heroin-dependent individuals: a resting-state FMRI study.

    Science.gov (United States)

    Jiang, Guihua; Wen, Xue; Qiu, Yingwei; Zhang, Ruibin; Wang, Junjing; Li, Meng; Ma, Xiaofen; Tian, Junzhang; Huang, Ruiwang

    2013-01-01

    Neuroimaging studies have shown that heroin addiction is related to abnormalities in widespread local regions and in the functional connectivity of the brain. However, little is known about whether heroin addiction changes the topological organization of whole-brain functional networks. Seventeen heroin-dependent individuals (HDIs) and 15 age-, gender-matched normal controls (NCs) were enrolled, and the resting-state functional magnetic resonance images (RS-fMRI) were acquired from these subjects. We constructed the brain functional networks of HDIs and NCs, and compared the between-group differences in network topological properties using graph theory method. We found that the HDIs showed decreases in the normalized clustering coefficient and in small-worldness compared to the NCs. Furthermore, the HDIs exhibited significantly decreased nodal centralities primarily in regions of cognitive control network, including the bilateral middle cingulate gyrus, left middle frontal gyrus, and right precuneus, but significantly increased nodal centralities primarily in the left hippocampus. The between-group differences in nodal centralities were not corrected by multiple comparisons suggesting these should be considered as an exploratory analysis. Moreover, nodal centralities in the left hippocampus were positively correlated with the duration of heroin addiction. Overall, our results indicated that disruptions occur in the whole-brain functional networks of HDIs, findings which may be helpful in further understanding the mechanisms underlying heroin addiction.

  7. Parcellating an individual subject's cortical and subcortical brain structures using snowball sampling of resting-state correlations.

    Science.gov (United States)

    Wig, Gagan S; Laumann, Timothy O; Cohen, Alexander L; Power, Jonathan D; Nelson, Steven M; Glasser, Matthew F; Miezin, Francis M; Snyder, Abraham Z; Schlaggar, Bradley L; Petersen, Steven E

    2014-08-01

    We describe methods for parcellating an individual subject's cortical and subcortical brain structures using resting-state functional correlations (RSFCs). Inspired by approaches from social network analysis, we first describe the application of snowball sampling on RSFC data (RSFC-Snowballing) to identify the centers of cortical areas, subdivisions of subcortical nuclei, and the cerebellum. RSFC-Snowballing parcellation is then compared with parcellation derived from identifying locations where RSFC maps exhibit abrupt transitions (RSFC-Boundary Mapping). RSFC-Snowballing and RSFC-Boundary Mapping largely complement one another, but also provide unique parcellation information; together, the methods identify independent entities with distinct functional correlations across many cortical and subcortical locations in the brain. RSFC parcellation is relatively reliable within a subject scanned across multiple days, and while the locations of many area centers and boundaries appear to exhibit considerable overlap across subjects, there is also cross-subject variability-reinforcing the motivation to parcellate brains at the level of individuals. Finally, examination of a large meta-analysis of task-evoked functional magnetic resonance imaging data reveals that area centers defined by task-evoked activity exhibit correspondence with area centers defined by RSFC-Snowballing. This observation provides important evidence for the ability of RSFC to parcellate broad expanses of an individual's brain into functionally meaningful units. © The Author 2013. Published by Oxford University Press.

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

    Directory of Open Access Journals (Sweden)

    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.

  9. The effects of a mid-task break on the brain connectome in healthy participants: A resting-state functional MRI study.

    Science.gov (United States)

    Sun, Yu; Lim, Julian; Dai, Zhongxiang; Wong, KianFoong; Taya, Fumihiko; Chen, Yu; Li, Junhua; Thakor, Nitish; Bezerianos, Anastasios

    2017-05-15

    Although rest breaks are commonly administered as a countermeasure to reduce mental fatigue and boost cognitive performance, the effects of taking a break on behavior are not consistent. Moreover, our understanding of the underlying neural mechanisms of rest breaks and how they modulate mental fatigue is still rudimentary. In this study, we investigated the effects of receiving a rest break on the topological properties of brain connectivity networks via a two-session experimental paradigm, in which one session comprised four successive blocks of a mentally demanding visual selective attention task (No-rest session), whereas the other contained a rest break between the second and third task blocks (Rest session). Functional brain networks were constructed using resting-state functional MRI data recorded from 20 healthy adults before and after the performance of the task blocks. Behaviorally, subjects displayed robust time-on-task (TOT) declines, as reflected by increasingly slower reaction time as the test progressed and lower post-task self-reported ratings of engagement. However, we did not find a significant effect on task performance due to administering a mid-task break. Compared to pre-task measurements, post-task functional brain networks demonstrated an overall decrease of optimal small-world properties together with lower global efficiency. Specifically, we found TOT-related reduced nodal efficiency in brain regions that mainly resided in the subcortical areas. More interestingly, a significant block-by-session interaction was revealed in local efficiency, attributing to a significant post-task decline in No-rest session and a preserved local efficiency when a mid-task break opportunity was introduced in the Rest session. Taken together, these findings augment our understanding of how the resting brain reorganizes following the accumulation of prolonged task, suggest dissociable processes between the neural mechanisms of fatigue and recovery, and provide

  10. Frequency-Dependent Modulation of Regional Synchrony in the Human Brain by Eyes Open and Eyes Closed Resting-States.

    Science.gov (United States)

    Song, Xiaopeng; Zhou, Shuqin; Zhang, Yi; Liu, Yijun; Zhu, Huaiqiu; Gao, Jia-Hong

    2015-01-01

    The eyes-open (EO) and eyes-closed (EC) states have differential effects on BOLD-fMRI signal dynamics, affecting both the BOLD oscillation frequency of a single voxel and the regional homogeneity (ReHo) of several neighboring voxels. To explore how the two resting-states modulate the local synchrony through different frequency bands, we decomposed the time series of each voxel into several components that fell into distinct frequency bands. The ReHo in each of the bands was calculated and compared between the EO and EC conditions. The cross-voxel correlations between the mean frequency and the overall ReHo of each voxel's original BOLD series in different brain areas were also calculated and compared between the two states. Compared with the EC state, ReHo decreased with EO in a wide frequency band of 0.01-0.25 Hz in the bilateral thalamus, sensorimotor network, and superior temporal gyrus, while ReHo increased significantly in the band of 0-0.01 Hz in the primary visual cortex, and in a higher frequency band of 0.02-0.1 Hz in the higher order visual areas. The cross-voxel correlations between the frequency and overall ReHo were negative in all the brain areas but varied from region to region. These correlations were stronger with EO in the visual network and the default mode network. Our results suggested that different frequency bands of ReHo showed different sensitivity to the modulation of EO-EC states. The better spatial consistency between the frequency and overall ReHo maps indicated that the brain might adopt a stricter frequency-dependent configuration with EO than with EC.

  11. 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.

  12. Effects of resting state condition on reliability, trait specificity, and network connectivity of brain function measured with arterial spin labeled perfusion MRI.

    Science.gov (United States)

    Li, Zhengjun; Vidorreta, Marta; Katchmar, Natalie; Alsop, David C; Wolf, Daniel H; Detre, John A

    2018-06-01

    Resting state fMRI (rs-fMRI) provides imaging biomarkers of task-independent brain function that can be associated with clinical variables or modulated by interventions such as behavioral training or pharmacological manipulations. These biomarkers include time-averaged regional brain function as manifested by regional cerebral blood flow (CBF) measured using arterial spin labeled (ASL) perfusion MRI and correlated temporal fluctuations of function across brain networks with either ASL or blood oxygenation level dependent (BOLD) fMRI. Resting-state studies are typically carried out using just one of several prescribed state conditions such as eyes closed (EC), eyes open (EO), or visual fixation on a cross-hair (FIX), which may affect the reliability and specificity of rs-fMRI. In this study, we collected test-retest ASL MRI data during 4 resting-state task conditions: EC, EO, FIX and PVT (low-frequency psychomotor vigilance task), and examined the effects of these task conditions on reliability and reproducibility as well as trait specificity of regional brain function. We also acquired resting-state BOLD fMRI under FIX and compared the network connectivity reliabilities between the four ASL conditions and the BOLD FIX condition. For resting-state ASL data, EC provided the highest CBF reliability, reproducibility, trait specificity, and network connectivity reliability, followed by EO, while FIX was lowest on all of these measures. PVT demonstrated lower CBF reliability, reproducibility and trait specificity than EO and EC. Overall network connectivity reliability was comparable between ASL and BOLD. Our findings confirm ASL CBF as a reliable, stable, and consistent measure of resting-state regional brain function and support the use of EC or EO over FIX and PVT as the resting-state condition. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  13. A Skew-t space-varying regression model for the spectral analysis of resting state brain activity.

    Science.gov (United States)

    Ismail, Salimah; Sun, Wenqi; Nathoo, Farouk S; Babul, Arif; Moiseev, Alexader; Beg, Mirza Faisal; Virji-Babul, Naznin

    2013-08-01

    It is known that in many neurological disorders such as Down syndrome, main brain rhythms shift their frequencies slightly, and characterizing the spatial distribution of these shifts is of interest. This article reports on the development of a Skew-t mixed model for the spatial analysis of resting state brain activity in healthy controls and individuals with Down syndrome. Time series of oscillatory brain activity are recorded using magnetoencephalography, and spectral summaries are examined at multiple sensor locations across the scalp. We focus on the mean frequency of the power spectral density, and use space-varying regression to examine associations with age, gender and Down syndrome across several scalp regions. Spatial smoothing priors are incorporated based on a multivariate Markov random field, and the markedly non-Gaussian nature of the spectral response variable is accommodated by the use of a Skew-t distribution. A range of models representing different assumptions on the association structure and response distribution are examined, and we conduct model selection using the deviance information criterion. (1) Our analysis suggests region-specific differences between healthy controls and individuals with Down syndrome, particularly in the left and right temporal regions, and produces smoothed maps indicating the scalp topography of the estimated differences.

  14. Altered brain network topology in left-behind children: A resting-state functional magnetic resonance imaging study.

    Science.gov (United States)

    Zhao, Youjin; Du, Meimei; Gao, Xin; Xiao, Yuan; Shah, Chandan; Sun, Huaiqiang; Chen, Fuqin; Yang, Lili; Yan, Zhihan; Fu, Yuchuan; Lui, Su

    2016-12-01

    Whether a lack of direct parental care affects brain function in children is an important question, particularly in developing countries where hundreds of millions of children are left behind when their parents migrate for economic or political reasons. In this study, we investigated changes in the topological architectures of brain functional networks in left-behind children (LBC). Resting-state functional magnetic resonance imaging data were obtained from 26 LBC and 21 children living within their nuclear family (non-LBC). LBC showed a significant increase in the normalized characteristic path length (λ), suggesting a decrease in efficiency in information access, and altered nodal centralities in the fronto-limbic regions and motor and sensory systems. Moreover, a decreased nodal degree and the nodal betweenness of the right rectus gyrus were positively correlated with annual family income. The present study provides the first empirical evidence that suggests that a lack of direct parental care could affect brain functional development in children, particularly involving emotional networks. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. Presurgery resting-state local graph-theory measures predict neurocognitive outcomes after brain surgery in temporal lobe epilepsy.

    Science.gov (United States)

    Doucet, Gaelle E; Rider, Robert; Taylor, Nathan; Skidmore, Christopher; Sharan, Ashwini; Sperling, Michael; Tracy, Joseph I

    2015-04-01

    This study determined the ability of resting-state functional connectivity (rsFC) graph-theory measures to predict neurocognitive status postsurgery in patients with temporal lobe epilepsy (TLE) who underwent anterior temporal lobectomy (ATL). A presurgical resting-state functional magnetic resonance imaging (fMRI) condition was collected in 16 left and 16 right TLE patients who underwent ATL. In addition, patients received neuropsychological testing pre- and postsurgery in verbal and nonverbal episodic memory, language, working memory, and attention domains. Regarding the functional data, we investigated three graph-theory properties (local efficiency, distance, and participation), measuring segregation, integration and centrality, respectively. These measures were only computed in regions of functional relevance to the ictal pathology, or the cognitive domain. Linear regression analyses were computed to predict the change in each neurocognitive domain. Our analyses revealed that cognitive outcome was successfully predicted with at least 68% of the variance explained in each model, for both TLE groups. The only model not significantly predictive involved nonverbal episodic memory outcome in right TLE. Measures involving the healthy hippocampus were the most common among the predictors, suggesting that enhanced integration of this structure with the rest of the brain may improve cognitive outcomes. Regardless of TLE group, left inferior frontal regions were the best predictors of language outcome. Working memory outcome was predicted mostly by right-sided regions, in both groups. Overall, the results indicated our integration measure was the most predictive of neurocognitive outcome. In contrast, our segregation measure was the least predictive. This study provides evidence that presurgery rsFC measures may help determine neurocognitive outcomes following ATL. The results have implications for refining our understanding of compensatory reorganization and predicting

  16. Exploring difference and overlap between schizophrenia, schizoaffective and bipolar disorders using resting-state brain functional networks.

    Science.gov (United States)

    Du, Yuhui; Liu, Jingyu; Sui, Jing; He, Hao; Pearlson, Godfrey D; Calhoun, Vince D

    2014-01-01

    Schizophrenia, schizoaffective and bipolar disorders share some common symptoms. However, the biomarkers underlying those disorders remain unclear. In fact, there is still controversy about the schizoaffective disorder with respect to its validity of independent category and its relationship with schizophrenia and bipolar disorders. In this paper, based on brain functional networks extracted from resting-state fMRI using a recently proposed group information guided ICA (GIG-ICA) method, we explore the biomarkers for discriminating healthy controls, schizophrenia patients, bipolar patients, and patients with two symptom defined subsets of schizoaffective disorder, and then investigate the relationship between different groups. The results demonstrate that the discriminating regions mainly including frontal, parietal, precuneus, cingulate, supplementary motor, cerebellar, insular and supramarginal cortices perform well in distinguishing the different diagnostic groups. The results also suggest that schizoaffective disorder may be an independent disorder, although its subtype characterized by depressive episodes shares more similarity with schizophrenia.

  17. 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 pRest atlas 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

  18. Analysis of Altered Baseline Brain Activity in Drug-Naive Adult Patients with Social Anxiety Disorder Using Resting-State Functional MRI

    OpenAIRE

    Qiu, Changjian; Feng, Yuan; Meng, Yajing; Liao, Wei; Huang, Xiaoqi; Lui, Su; Zhu, Chunyan; Chen, Huafu; Gong, Qiyong; Zhang, Wei

    2015-01-01

    Objective We hypothesize that the amplitude of low-frequency fluctuations (ALFF) is involved in the altered regional baseline brain function in social anxiety disorder (SAD). The aim of the study was to analyze the altered baseline brain activity in drug-naive adult patients with SAD. Methods We investigated spontaneous and baseline brain activities by obtaining the resting-state functional magnetic resonance imaging data of 20 drug-na?ve adult SAD patients and 19 healthy controls. Voxels wer...

  19. [Resting-state functional magnetic resonance study of brain function changes after TIPS operation in patients with liver cirrhosis].

    Science.gov (United States)

    Liu, C; Wang, H B; Yu, Y Q; Wang, M Q; Zhang, G B; Xu, L Y; Wu, J M

    2016-12-20

    Objective: To investigate the brain function changes in cirrhosis patients after transjugular intrahepatic portosystemic shunt (TIPS), resting-state functional MRI (rs-fMRI) performed and fractional amplitude of low frequency fluctuation (fALFF) was analyzed. Methods: From January 2014 to February 2016, a total of 96 cirrhotic patients from invasive technology department and infection department in the First Affiliated Hospital of Anhui Medical University were selected , the blood ammonia data of 96 cirrhotic patients with TIPS operation in four groups were collected after 1, 3, 6 and 12 month, and all subjects performed rs-fMRI scans. The rs-fMRI data processed with DPARSF and SPM12 softwares, whole-brain fALFF values were calculated, and One-Way analysis of variance , multiple comparison analysis and correlation analysis were performed. Results: There were brain regions with significant function changes in four groups patients with TIPS operation after 1, 3, 6 and 12 month, including bilateral superior temporal gyrus, right middle temportal gyrus , right hippocampus, right island of inferior frontal gyrus, left fusiform gyrus, left olfactory cortex, left orbital superior frontal gyrus (all P brain function areas increased in left olfactory cortex, left inferior temporal gyrus, left fusiform gyrus, left orbital middle frontal gyrus, left putamen, left cerebelum, and decreased in left lingual gyrus; patients in the 6-month follow-up showed that brain function areas increased in left middle temportal gyrus, right supramarginal gyrus, right temporal pole, right central operculum, and decreased in left top edge of angular gyrus, left postcentral gyrus; patients in the 12-month follow-up showed that brain function areas increased in right hippocampus, right middle cingulate gyrus, and decreased in right middle temportal gyrus.Compared with patients in the 3-month follow-up, patients in the 6-month follow-up showed that brain function areas increased in left superior

  20. Selective Changes of Resting-State Brain Oscillations in aMCI: An fMRI Study Using ALFF

    Directory of Open Access Journals (Sweden)

    Zhilian Zhao

    2014-01-01

    Full Text Available Mild cognitive impairment (MCI refers to a transitional state between normal aging and dementia and is a syndrome with cognitive decline greater than expected for an individual’s age and educational level. As a subtype of MCI, amnestic mild cognitive impairment (aMCI most often leads to Alzheimer’s disease. This study aims to elucidate the altered brain activation in patients with aMCI using resting-state functional magnetic resonance. We observed Frequency-dependent changes in the amplitude of low-frequency fluctuations in aMCI patients (n=20, and normal subjects (n=18. At the same time, we took gray matter volume as a covariate. We found that aMCI patients had decreased amplitude of low-frequency fluctuation signal in left superior temporal gyrus, right middle temporal gyrus, right inferior parietal lobe, and right postcentral gyrus compared to the control group. Specially, aMCI patients showed increased signal in left superior and middle frontal gyrus. Our results suggested that increased activation in frontal lobe of aMCI patients may indicate effective recruitment of compensatory brain resources. This finding and interpretation may lead to the better understanding of cognitive changes of aMCI.

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

    NARCIS (Netherlands)

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

    2016-01-01

    Oswal et al. characterise the effect of deep brain stimulation (DBS) on STN-cortical synchronisation in Parkinson-s disease. They propose that cortical driving of the STN in beta frequencies is subdivided anatomically and spectrally, corresponding to the hyperdirect and indirect pathways. DBS

  2. An EEG-Based Biometric System Using Eigenvector Centrality in Resting State Brain Networks

    NARCIS (Netherlands)

    Fraschini, M.; Hillebrand, A.; Demuru, M.; Didaci, L.; Marcialis, G.L.

    2015-01-01

    Recently, there has been a growing interest in the use of brain activity for biometric systems. However, so far these studies have focused mainly on basic features of the Electroencephalography. In this study we propose an approach based on phase synchronization, to investigate personal distinctive

  3. Altered Brain Functional Connectome in Migraine with and without Restless Legs Syndrome: A Resting-State Functional MRI Study

    Directory of Open Access Journals (Sweden)

    Fu-Chi Yang

    2018-01-01

    Full Text Available BackgroundMigraine is frequently comorbid with restless legs syndrome (RLS, both displaying functional connectivity (FC alterations in multiple brain networks, although the neurological basis of this association is unknown.MethodsWe performed resting-state functional magnetic resonance imaging and network-wise analysis of FC in migraine patients with and without RLS and healthy controls (CRL. Network-based statistics (NBS and composite FC matrix analyses were performed to identify the patterns of FC changes. Correlation analyses were performed to identify associations between alterations in FC and clinical profiles.ResultsNBS results revealed that both migraine patients with and without RLS exhibited lower FC than CRL in the dorsal attention, salience, default mode, cingulo-opercular, visual, frontoparietal, auditory, and sensory/somatomotor networks. Further composite FC matrix analyses revealed differences in FC of the salience, default mode to subcortical and frontoparietal, auditory to salience, and memory retrieval networks between migraine patients with and without RLS. There was a trend toward a negative association between RLS severity and cross-network abnormalities in the default mode to subcortical network.DiscussionMigraine patients with and without RLS exhibit disruptions of brain FC. Such findings suggest that these disorders are associated with differential neuropathological mechanisms and may aid in the future development of neuroimaging-driven biomarkers for these conditions.

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

    Directory of Open Access Journals (Sweden)

    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.

  5. Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI.

    Science.gov (United States)

    Xu, Tingting; Cullen, Kathryn R; Mueller, Bryon; Schreiner, Mindy W; Lim, Kelvin O; Schulz, S Charles; Parhi, Keshab K

    2016-01-01

    Borderline personality disorder (BPD) is associated with symptoms such as affect dysregulation, impaired sense of self, and self-harm behaviors. Neuroimaging research on BPD has revealed structural and functional abnormalities in specific brain regions and connections. However, little is known about the topological organizations of brain networks in BPD. We collected resting-state functional magnetic resonance imaging (fMRI) data from 20 patients with BPD and 10 healthy controls, and constructed frequency-specific functional brain networks by correlating wavelet-filtered fMRI signals from 82 cortical and subcortical regions. We employed graph-theory based complex network analysis to investigate the topological properties of the brain networks, and employed network-based statistic to identify functional dysconnections in patients. In the 0.03-0.06 Hz frequency band, compared to controls, patients with BPD showed significantly larger measures of global network topology, including the size of largest connected graph component, clustering coefficient, small-worldness, and local efficiency, indicating increased local cliquishness of the functional brain network. Compared to controls, patients showed lower nodal centrality at several hub nodes but greater centrality at several non-hub nodes in the network. Furthermore, an interconnected subnetwork in 0.03-0.06 Hz frequency band was identified that showed significantly lower connectivity in patients. The links in the subnetwork were mainly long-distance connections between regions located at different lobes; and the mean connectivity of this subnetwork was negatively correlated with the increased global topology measures. Lastly, the key network measures showed high correlations with several clinical symptom scores, and classified BPD patients against healthy controls with high accuracy based on linear discriminant analysis. The abnormal topological properties and connectivity found in this study may add new knowledge

  6. Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI

    Directory of Open Access Journals (Sweden)

    Tingting Xu

    2016-01-01

    Full Text Available Borderline personality disorder (BPD is associated with symptoms such as affect dysregulation, impaired sense of self, and self-harm behaviors. Neuroimaging research on BPD has revealed structural and functional abnormalities in specific brain regions and connections. However, little is known about the topological organizations of brain networks in BPD. We collected resting-state functional magnetic resonance imaging (fMRI data from 20 patients with BPD and 10 healthy controls, and constructed frequency-specific functional brain networks by correlating wavelet-filtered fMRI signals from 82 cortical and subcortical regions. We employed graph-theory based complex network analysis to investigate the topological properties of the brain networks, and employed network-based statistic to identify functional dysconnections in patients. In the 0.03–0.06 Hz frequency band, compared to controls, patients with BPD showed significantly larger measures of global network topology, including the size of largest connected graph component, clustering coefficient, small-worldness, and local efficiency, indicating increased local cliquishness of the functional brain network. Compared to controls, patients showed lower nodal centrality at several hub nodes but greater centrality at several non-hub nodes in the network. Furthermore, an interconnected subnetwork in 0.03–0.06 Hz frequency band was identified that showed significantly lower connectivity in patients. The links in the subnetwork were mainly long-distance connections between regions located at different lobes; and the mean connectivity of this subnetwork was negatively correlated with the increased global topology measures. Lastly, the key network measures showed high correlations with several clinical symptom scores, and classified BPD patients against healthy controls with high accuracy based on linear discriminant analysis. The abnormal topological properties and connectivity found in this study

  7. The temporal structure of resting-state brain activity in the medial prefrontal cortex predicts self-consciousness.

    Science.gov (United States)

    Huang, Zirui; Obara, Natsuho; Davis, Henry Hap; Pokorny, Johanna; Northoff, Georg

    2016-02-01

    Recent studies have demonstrated an overlap between the neural substrate of resting-state activity and self-related processing in the cortical midline structures (CMS). However, the neural and psychological mechanisms mediating this so-called "rest-self overlap" remain unclear. To investigate the neural mechanisms, we estimated the temporal structure of spontaneous/resting-state activity, e.g. its long-range temporal correlations or self-affinity across time as indexed by the power-law exponent (PLE). The PLE was obtained in resting-state activity in the medial prefrontal cortex (MPFC) and the posterior cingulate cortex (PCC) in 47 healthy subjects by functional magnetic resonance imaging (fMRI). We performed correlation analyses of the PLE and Revised Self-Consciousness Scale (SCSR) scores, which enabled us to access different dimensions of self-consciousness and specified rest-self overlap in a psychological regard. The PLE in the MPFC's resting-state activity correlated with private self-consciousness scores from the SCSR. Conversely, we found no correlation between the PLE and the other subscales of the SCSR (public, social) or between other resting-state measures, including functional connectivity, and the SCSR subscales. This is the first evidence for the association between the scale-free dynamics of resting-state activity in the CMS and the private dimension of self-consciousness. This finding implies the relationship of especially the private dimension of self with the temporal structure of resting-state activity. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. An Evaluation of the Left-Brain vs. Right-Brain Hypothesis with Resting State Functional Connectivity Magnetic Resonance Imaging

    OpenAIRE

    Nielsen, Jared A.; Zielinski, Brandon A.; Ferguson, Michael A.; Lainhart, Janet E.; Anderson, Jeffrey S.

    2013-01-01

    Lateralized brain regions subserve functions such as language and visuospatial processing. It has been conjectured that individuals may be left-brain dominant or right-brain dominant based on personality and cognitive style, but neuroimaging data has not provided clear evidence whether such phenotypic differences in the strength of left-dominant or right-dominant networks exist. We evaluated whether strongly lateralized connections covaried within the same individuals. Data were analyzed from...

  9. Clinical applications of resting state functional connectivity

    Directory of Open Access Journals (Sweden)

    Michael D Fox

    2010-06-01

    Full Text Available During resting conditions the brain remains functionally and metabolically active. One manifestation of this activity that has become an important research tool is spontaneous fluctuations in the blood oxygen level dependent (BOLD signal of fMRI. The identification of correlation patterns in these spontaneous fluctuations has been termed resting state functional connectivity (fcMRI and has the potential to greatly increase the translation of fMRI into clinical care. In this article we review the advantages of the resting state signal for clinical applications including detailed discussion of signal to noise considerations. We include guidelines for performing resting state research on clinical populations, outline the different areas for clinical application, and identify important barriers to be addressed to facilitate the translation of resting state fcMRI into the clinical realm.

  10. [Follow-up of resting-state brain function with magnetic resonance imaging in patients with type 2 diabetes mellitus].

    Science.gov (United States)

    Qi, N; Cui, Y; Liu, J C; Yu, M; Teng, G J

    2017-10-24

    Objective: To investigate the changes of resting brain function with time in patients with type 2 diabetes mellitus (T2DM) by using regional homogeneity (ReHo) with resting-state functional magnetic resonance imaging (rs-fMRI). Methods: Multidimensional cognitive function tests and rs-fMRI scans were performed in 21 T2DM patients and 12 healthy controls in 2012 and 2015 respectively.The differences in clinical variables and the ReHo values before and after were measured by paired sample t test, and the correlation between the change of ReHo value and the change of clinical variables was measured by Pearson correlation analysis based on voxel. Results: The delayed score (14±6) of the T2DM patients in 2015 was significantly lower than that in 2012 (18±6) ( t =-2.88, P =0.009); while the value of ReHo in the bilateral occipital lobe and right middle frontal gyrus was significantly lower than that in 2012 ( P left occipital lobe was significantly correlated with the change of complex figure test (CFT) delay score and the trail making test-B (TMT-B)( r =0.52, -0.46, both P function tests in the healthy control group was found between the two years, ReHo value in right cuneus decreased significantly ( P right cuneus and right superior frontal gyrus and the changes of cognitive function scores was found in the healthy controls. Conclusions: The visual memory is significantly declined in T2DM patients within 3 years.The reduced neural activity areas in T2DM patients are in the bilateral occipitai lobes and the right middle frontal lobe. Decreased neural activity in the left occipital area is related to visual impairment, information processing speed and attention drops.

  11. Spontaneous Brain Activity Did Not Show the Effect of Violent Video Games on Aggression: A Resting-State fMRI Study

    OpenAIRE

    Wei Pan; Wei Pan; Wei Pan; Xuemei Gao; Shuo Shi; Fuqu Liu; Chao Li

    2018-01-01

    A great many of empirical researches have proved that longtime exposure to violent video game can lead to a series of negative effects. Although research has focused on the neural basis of the correlation between violent video game and aggression, little is known whether the spontaneous brain activity is associated with violent video game exposure. To address this question, we measured the spontaneous brain activity using resting-state functional magnetic resonance imaging (fMRI). We used the...

  12. Disrupted Topological Organization in Whole-Brain Functional Networks of Heroin-Dependent Individuals: A Resting-State fMRI Study

    OpenAIRE

    Jiang, Guihua; Wen, Xue; Qiu, Yingwei; Zhang, Ruibin; Wang, Junjing; Li, Meng; Ma, Xiaofen; Tian, Junzhang; Huang, Ruiwang

    2013-01-01

    Neuroimaging studies have shown that heroin addiction is related to abnormalities in widespread local regions and in the functional connectivity of the brain. However, little is known about whether heroin addiction changes the topological organization of whole-brain functional networks. Seventeen heroin-dependent individuals (HDIs) and 15 age-, gender-matched normal controls (NCs) were enrolled, and the resting-state functional magnetic resonance images (RS-fMRI) were acquired from these subj...

  13. Mapping the brain correlates of borderline personality disorder: A functional neuroimaging meta-analysis of resting state studies.

    Science.gov (United States)

    Visintin, Eleonora; De Panfilis, Chiara; Amore, Mario; Balestrieri, Matteo; Wolf, Robert Christian; Sambataro, Fabio

    2016-11-01

    Altered intrinsic function of the brain has been implicated in Borderline Personality Disorder (BPD). Nonetheless, imaging studies have yielded inconsistent alterations of brain function. To investigate the neural activity at rest in BPD, we conducted a set of meta-analyses of brain imaging studies performed at rest. A total of seven functional imaging studies (152 patients with BPD and 147 control subjects) were combined using whole-brain Signed Differential Mapping meta-analyses. Furthermore, two conjunction meta-analyses of neural activity at rest were also performed: with neural activity changes during emotional processing, and with structural differences, respectively. We found altered neural activity in the regions of the default mode network (DMN) in BPD. Within the regions of the midline core DMN, patients with BPD showed greater activity in the anterior as well as in the posterior midline hubs relative to controls. Conversely, in the regions of the dorsal DMN they showed reduced activity compared to controls in the right lateral temporal complex and bilaterally in the orbitofrontal cortex. Increased activity in the precuneus was observed both at rest and during emotional processing. Reduced neural activity at rest in lateral temporal complex was associated with smaller volume of this area. Heterogeneity across imaging studies. Altered activity in the regions of the midline core as well as of the dorsal subsystem of the DMN may reflect difficulties with interpersonal and affective regulation in BPD. These findings suggest that changes in spontaneous neural activity could underlie core symptoms in BPD. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. Higher resting-state activity in reward-related brain circuits in obese versus normal-weight females independent of food intake

    OpenAIRE

    Hogenkamp, P S; Zhou, W; Dahlberg, L S; Stark, J; Larsen, A L; Olivo, G; Wiemerslage, L; Larsson, E-M; Sundbom, M; Benedict, C; Schi?th, H B

    2016-01-01

    BACKGROUND: In response to food cues, obese vs normal-weight individuals show greater activation in brain regions involved in the regulation of food intake under both fasted and sated conditions. Putative effects of obesity on task-independent low-frequency blood-oxygenation-level-dependent signals-that is, resting-state brain activity-in the context of food intake are, however, less well studied. OBJECTIVE: To compare eyes closed, whole-brain low-frequency BOLD signals between severely obese...

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

    Science.gov (United States)

    Diaz, B. Alexander; Van Der Sluis, Sophie; Moens, Sarah; Benjamins, Jeroen S.; Migliorati, Filippo; Stoffers, Diederick; Den Braber, Anouk; Poil, Simon-Shlomo; Hardstone, Richard; Van't Ent, Dennis; Boomsma, Dorret I.; De Geus, Eco; Mansvelder, Huibert D.; Van Someren, Eus J. W.; Linkenkaer-Hansen, Klaus

    2013-01-01

    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 5 min 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. PMID:23964225

  17. ABERRANT RESTING-STATE BRAIN ACTIVITY IN POSTTRAUMATIC STRESS DISORDER: A META-ANALYSIS AND SYSTEMATIC REVIEW

    NARCIS (Netherlands)

    Koch, Saskia B. J.; van Zuiden, Mirjam; Nawijn, Laura; Frijling, Jessie L.; Veltman, Dick J.; Olff, Miranda

    2016-01-01

    About 10% of trauma-exposed individuals develop PTSD. Although a growing number of studies have investigated resting-state abnormalities in PTSD, inconsistent results suggest a need for a meta-analysis and a systematic review. We conducted a systematic literature search in four online databases

  18. Resting-state fMRI revealed different brain activities responding to valproic acid and levetiracetam in benign epilepsy with central-temporal spikes

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    Zhang, Qirui; Zhang, Zhiqiang; Xu, Qiang; Wu, Han; Li, Zhipeng; Lu, Guangming [Nanjing University School of Medicine, Department of Medical Imaging, Jinling Hospital, Nanjing (China); Yang, Fang; Li, Qian [Nanjing University School of Medicine, Department of Neurology, Jinling Hospital, Nanjing (China); Hu, Zheng [Nanjing Children' s Hospital, Department of Neurology, Nanjing (China); Dante, Mantini [Faculty of Kinesiology and Rehabilitation Sciences, KU Leuven (Belgium); Li, Kai [Suzhou University, Laboratory of Molecular Medicine, Suzhou (China)

    2017-05-15

    Our aim was to investigate regional difference in brain activities in response to antiepileptic drug (AED) medications in benign epilepsy with central-temporal spikes (BECTS) using resting-state functional magnetic resonance imaging (fMRI). Fifty-seven patients with BECTS underwent resting-state fMRI scans after receiving either valproic acid (VPA) (n = 15), levetiracetam (LEV) (n = 21), or no medication (n = 21). fMRI regional homogeneity (ReHo) parameter among the three groups of patients were compared and were correlated with total doses of AED in the two medicated groups. Compared with patients on no-medication, patients receiving either VPA or LEV showed decreased ReHo in the central-temporal region, frontal cortex, and thalamus. In particular, the VPA group showed greater ReHo decrease in the thalamus and milder in cortices and caudate heads compared with the LEV group. In addition, the VPA group demonstrated a negative correlation between ReHo values in the central-temporal region and medication dose. Both VPA and LEV inhibit resting-state neural activity in the central-temporal region, which is the main epileptogenic focus of BECTS. VPA reduced brain activity in the cortical epileptogenic regions and thalamus evenly, whereas LEV reduced brain activity predominantly in the cortices. Interestingly, VPA showed a cumulative effect on inhibiting brain activity in the epileptogenic regions in BECTS. (orig.)

  19. Resting-state fMRI revealed different brain activities responding to valproic acid and levetiracetam in benign epilepsy with central-temporal spikes

    International Nuclear Information System (INIS)

    Zhang, Qirui; Zhang, Zhiqiang; Xu, Qiang; Wu, Han; Li, Zhipeng; Lu, Guangming; Yang, Fang; Li, Qian; Hu, Zheng; Dante, Mantini; Li, Kai

    2017-01-01

    Our aim was to investigate regional difference in brain activities in response to antiepileptic drug (AED) medications in benign epilepsy with central-temporal spikes (BECTS) using resting-state functional magnetic resonance imaging (fMRI). Fifty-seven patients with BECTS underwent resting-state fMRI scans after receiving either valproic acid (VPA) (n = 15), levetiracetam (LEV) (n = 21), or no medication (n = 21). fMRI regional homogeneity (ReHo) parameter among the three groups of patients were compared and were correlated with total doses of AED in the two medicated groups. Compared with patients on no-medication, patients receiving either VPA or LEV showed decreased ReHo in the central-temporal region, frontal cortex, and thalamus. In particular, the VPA group showed greater ReHo decrease in the thalamus and milder in cortices and caudate heads compared with the LEV group. In addition, the VPA group demonstrated a negative correlation between ReHo values in the central-temporal region and medication dose. Both VPA and LEV inhibit resting-state neural activity in the central-temporal region, which is the main epileptogenic focus of BECTS. VPA reduced brain activity in the cortical epileptogenic regions and thalamus evenly, whereas LEV reduced brain activity predominantly in the cortices. Interestingly, VPA showed a cumulative effect on inhibiting brain activity in the epileptogenic regions in BECTS. (orig.)

  20. Increased sensitivity to age-related differences in brain functional connectivity during continuous multiple object tracking compared to resting-state.

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    Dørum, Erlend S; Kaufmann, Tobias; Alnæs, Dag; Andreassen, Ole A; Richard, Geneviève; Kolskår, Knut K; Nordvik, Jan Egil; Westlye, Lars T

    2017-03-01

    Age-related differences in cognitive agility vary greatly between individuals and cognitive functions. This heterogeneity is partly mirrored in individual differences in brain network connectivity as revealed using resting-state functional magnetic resonance imaging (fMRI), suggesting potential imaging biomarkers for age-related cognitive decline. However, although convenient in its simplicity, the resting state is essentially an unconstrained paradigm with minimal experimental control. Here, based on the conception that the magnitude and characteristics of age-related differences in brain connectivity is dependent on cognitive context and effort, we tested the hypothesis that experimentally increasing cognitive load boosts the sensitivity to age and changes the discriminative network configurations. To this end, we obtained fMRI data from younger (n=25, mean age 24.16±5.11) and older (n=22, mean age 65.09±7.53) healthy adults during rest and two load levels of continuous multiple object tracking (MOT). Brain network nodes and their time-series were estimated using independent component analysis (ICA) and dual regression, and the edges in the brain networks were defined as the regularized partial temporal correlations between each of the node pairs at the individual level. Using machine learning based on a cross-validated regularized linear discriminant analysis (rLDA) we attempted to classify groups and cognitive load from the full set of edge-wise functional connectivity indices. While group classification using resting-state data was highly above chance (approx. 70% accuracy), functional connectivity (FC) obtained during MOT strongly increased classification performance, with 82% accuracy for the young and 95% accuracy for the old group at the highest load level. Further, machine learning revealed stronger differentiation between rest and task in young compared to older individuals, supporting the notion of network dedifferentiation in cognitive aging. Task

  1. Large-Scale Network Analysis of Whole-Brain Resting-State Functional Connectivity in Spinal Cord Injury: A Comparative Study.

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    Kaushal, Mayank; Oni-Orisan, Akinwunmi; Chen, Gang; Li, Wenjun; Leschke, Jack; Ward, Doug; Kalinosky, Benjamin; Budde, Matthew; Schmit, Brian; Li, Shi-Jiang; Muqeet, Vaishnavi; Kurpad, Shekar

    2017-09-01

    Network analysis based on graph theory depicts the brain as a complex network that allows inspection of overall brain connectivity pattern and calculation of quantifiable network metrics. To date, large-scale network analysis has not been applied to resting-state functional networks in complete spinal cord injury (SCI) patients. To characterize modular reorganization of whole brain into constituent nodes and compare network metrics between SCI and control subjects, fifteen subjects with chronic complete cervical SCI and 15 neurologically intact controls were scanned. The data were preprocessed followed by parcellation of the brain into 116 regions of interest (ROI). Correlation analysis was performed between every ROI pair to construct connectivity matrices and ROIs were categorized into distinct modules. Subsequently, local efficiency (LE) and global efficiency (GE) network metrics were calculated at incremental cost thresholds. The application of a modularity algorithm organized the whole-brain resting-state functional network of the SCI and the control subjects into nine and seven modules, respectively. The individual modules differed across groups in terms of the number and the composition of constituent nodes. LE demonstrated statistically significant decrease at multiple cost levels in SCI subjects. GE did not differ significantly between the two groups. The demonstration of modular architecture in both groups highlights the applicability of large-scale network analysis in studying complex brain networks. Comparing modules across groups revealed differences in number and membership of constituent nodes, indicating modular reorganization due to neural plasticity.

  2. Altered Coupling between Motion-Related Activation and Resting-State Brain Activity in the Ipsilesional Sensorimotor Cortex after Cerebral Stroke

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    Jianping Hu

    2017-07-01

    Full Text Available Functional connectivity maps using resting-state functional magnetic resonance imaging (rs-fMRI can closely resemble task fMRI activation patterns, suggesting that resting-state brain activity may predict task-evoked activation or behavioral performance. However, this conclusion was mostly drawn upon a healthy population. It remains unclear whether the predictive ability of resting-state brain activity for task-evoked activation would change under different pathological conditions. This study investigated dynamic changes of coupling between patterns of resting-state functional connectivity (RSFC and motion-related activation in different stages of cerebral stroke. Twenty stroke patients with hand motor function impairment were involved. rs-fMRI and hand motion-related fMRI data were acquired in the acute, subacute, and early chronic stages of cerebral stroke on a 3-T magnetic resonance (MR scanner. Sixteen healthy participants were enrolled as controls. For each subject, an activation map of the affected hand was first created using general linear model analysis on task fMRI data, and then an RSFC map was determined by seeding at the peak region of hand motion activation during the intact hand task. We then measured the extent of coupling between the RSFC maps and motion-related activation maps. Dynamic changes of the coupling between the two fMRI maps were estimated using one-way repeated measures analysis of variance across the three stages. Moreover, imaging parameters were correlated with motor performances. Data analysis showed that there were different coupling patterns between motion-related activation and RSFC maps associating with the affected motor regions during the acute, subacute, and early chronic stages of stroke. Coupling strengths increased as the recovery from stroke progressed. Coupling strengths were correlated with hand motion performance in the acute stage, while coupling recovery was negatively correlated with the recovery

  3. Alteration of functional connectivity within visuospatial working memory-related brain network in patients with right temporal lobe epilepsy: a resting-state fMRI study.

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    Lv, Zong-xia; Huang, Dong-Hong; Ye, Wei; Chen, Zi-rong; Huang, Wen-li; Zheng, Jin-ou

    2014-06-01

    This study aimed to investigate the resting-state brain network related to visuospatial working memory (VSWM) in patients with right temporal lobe epilepsy (rTLE). The functional mechanism underlying the cognitive impairment in VSWM was also determined. Fifteen patients with rTLE and 16 healthy controls matched for age, gender, and handedness underwent a 6-min resting-state functional MRI session and a neuropsychological test using VSWM_Nback. The VSWM-related brain network at rest was extracted using multiple independent component analysis; the spatial distribution and the functional connectivity (FC) parameters of the cerebral network were compared between groups. Behavioral data were subsequently correlated with the mean Z-value in voxels showing significant FC difference during intergroup comparison. The distribution of the VSWM-related resting-state network (RSN) in the group with rTLE was virtually consistent with that in the healthy controls. The distribution involved the dorsolateral prefrontal lobe and parietal lobe in the right hemisphere and the partial inferior parietal lobe and posterior lobe of the cerebellum in the left hemisphere (pright superior frontal lobe (BA8), right middle frontal lobe, and right ventromedial prefrontal lobe compared with the controls (pright superior frontal lobe (BA11), right superior parietal lobe, and left posterior lobe of the cerebellum (prights reserved.

  4. Resting-state FMRI confounds and cleanup

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    Murphy, Kevin; Birn, Rasmus M.; Bandettini, Peter A.

    2013-01-01

    The goal of resting-state functional magnetic resonance imaging (FMRI) is to investigate the brain’s functional connections by using the temporal similarity between blood oxygenation level dependent (BOLD) signals in different regions of the brain “at rest” as an indicator of synchronous neural activity. Since this measure relies on the temporal correlation of FMRI signal changes between different parts of the brain, any non-neural activity-related process that affects the signals will influence the measure of functional connectivity, yielding spurious results. To understand the sources of these resting-state FMRI confounds, this article describes the origins of the BOLD signal in terms of MR physics and cerebral physiology. Potential confounds arising from motion, cardiac and respiratory cycles, arterial CO2 concentration, blood pressure/cerebral autoregulation, and vasomotion are discussed. Two classes of techniques to remove confounds from resting-state BOLD time series are reviewed: 1) those utilising external recordings of physiology and 2) data-based cleanup methods that only use the resting-state FMRI data itself. Further methods that remove noise from functional connectivity measures at a group level are also discussed. For successful interpretation of resting-state FMRI comparisons and results, noise cleanup is an often over-looked but essential step in the analysis pipeline. PMID:23571418

  5. Generation of Individual Whole-Brain Atlases With Resting-State fMRI Data Using Simultaneous Graph Computation and Parcellation.

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    Wang, J; Hao, Z; Wang, H

    2018-01-01

    The human brain can be characterized as functional networks. Therefore, it is important to subdivide the brain appropriately in order to construct reliable networks. Resting-state functional connectivity-based parcellation is a commonly used technique to fulfill this goal. Here we propose a novel individual subject-level parcellation approach based on whole-brain resting-state functional magnetic resonance imaging (fMRI) data. We first used a supervoxel method known as simple linear iterative clustering directly on resting-state fMRI time series to generate supervoxels, and then combined similar supervoxels to generate clusters using a clustering method known as graph-without-cut (GWC). The GWC approach incorporates spatial information and multiple features of the supervoxels by energy minimization, simultaneously yielding an optimal graph and brain parcellation. Meanwhile, it theoretically guarantees that the actual cluster number is exactly equal to the initialized cluster number. By comparing the results of the GWC approach and those of the random GWC approach, we demonstrated that GWC does not rely heavily on spatial structures, thus avoiding the challenges encountered in some previous whole-brain parcellation approaches. In addition, by comparing the GWC approach to two competing approaches, we showed that GWC achieved better parcellation performances in terms of different evaluation metrics. The proposed approach can be used to generate individualized brain atlases for applications related to cognition, development, aging, disease, personalized medicine, etc. The major source codes of this study have been made publicly available at https://github.com/yuzhounh/GWC.

  6. Generation of Individual Whole-Brain Atlases With Resting-State fMRI Data Using Simultaneous Graph Computation and Parcellation

    Directory of Open Access Journals (Sweden)

    J. Wang

    2018-05-01

    Full Text Available The human brain can be characterized as functional networks. Therefore, it is important to subdivide the brain appropriately in order to construct reliable networks. Resting-state functional connectivity-based parcellation is a commonly used technique to fulfill this goal. Here we propose a novel individual subject-level parcellation approach based on whole-brain resting-state functional magnetic resonance imaging (fMRI data. We first used a supervoxel method known as simple linear iterative clustering directly on resting-state fMRI time series to generate supervoxels, and then combined similar supervoxels to generate clusters using a clustering method known as graph-without-cut (GWC. The GWC approach incorporates spatial information and multiple features of the supervoxels by energy minimization, simultaneously yielding an optimal graph and brain parcellation. Meanwhile, it theoretically guarantees that the actual cluster number is exactly equal to the initialized cluster number. By comparing the results of the GWC approach and those of the random GWC approach, we demonstrated that GWC does not rely heavily on spatial structures, thus avoiding the challenges encountered in some previous whole-brain parcellation approaches. In addition, by comparing the GWC approach to two competing approaches, we showed that GWC achieved better parcellation performances in terms of different evaluation metrics. The proposed approach can be used to generate individualized brain atlases for applications related to cognition, development, aging, disease, personalized medicine, etc. The major source codes of this study have been made publicly available at https://github.com/yuzhounh/GWC.

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

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    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.

  8. Changes in resting-state functional connectivity after stroke in a mouse brain lacking extracellular matrix components.

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    Quattromani, Miriana Jlenia; Hakon, Jakob; Rauch, Uwe; Bauer, Adam Q; Wieloch, Tadeusz

    2018-04-01

    In the brain, focal ischemia results in a local region of cell death and disruption of both local and remote functional neuronal networks. Tissue reorganization following stroke can be limited by factors such as extracellular matrix (ECM) molecules that prevent neuronal growth and synaptic plasticity. The brain's ECM plays a crucial role in network formation, development, and regeneration of the central nervous system. Further, the ECM is essential for proper white matter tract development and for the formation of structures called perineuronal nets (PNNs). PNNs mainly surround parvalbumin/GABA inhibitory interneurons, of importance for processing sensory information. Previous studies have shown that downregulating PNNs after stroke reduces the neurite-inhibitory environment, reactivates plasticity, and promotes functional recovery. Resting-state functional connectivity (RS-FC) within and across hemispheres has been shown to correlate with behavioral recovery after stroke. However, the relationship between PNNs and RS-FC has not been examined. Here we studied a quadruple knock-out mouse (Q4) that lacks four ECM components: brevican, neurocan, tenascin-C and tenascin-R. We applied functional connectivity optical intrinsic signal (fcOIS) imaging in Q4 mice and wild-type (129S1 mice) before and 14 days after photothrombotic stroke (PT) to understand how the lack of crucial ECM components affects neuronal networks and functional recovery after stroke. Limb-placement ability was evaluated at 2, 7 and 14 days of recovery through the paw-placement test. Q4 mice exhibited significantly impaired homotopic RS-FC compared to wild-type mice, especially in the sensory and parietal regions. Changes in RS-FC were significantly correlated with the number of interhemispheric callosal crossings in those same regions. PT caused unilateral damage to the sensorimotor cortex and deficits of tactile-proprioceptive placing ability in contralesional fore- and hindlimbs, but the two

  9. 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

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    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.

  10. Abnormal functional connectivity of brain network hubs associated with symptom severity in treatment-naive patients with obsessive-compulsive disorder: A resting-state functional MRI study.

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    Tian, Lin; Meng, Chun; Jiang, Ying; Tang, Qunfeng; Wang, Shuai; Xie, Xiyao; Fu, Xiangshuai; Jin, Chunhui; Zhang, Fuquan; Wang, Jidong

    2016-04-03

    Abnormal brain networks have been observed in patients with obsessive-compulsive disorder (OCD). However, detailed network hub and connectivity changes remained unclear in treatment-naive patients with OCD. Here, we sought to determine whether patients show hub-related connectivity changes in their whole-brain functional networks. We used resting-state functional magnetic resonance imaging data and voxel-based graph-theoretic analysis to investigate functional connectivity strength and hubs of whole-brain networks in 29 treatment-naive patients with OCD and 29 age- and gender-matched healthy controls. Correlation analysis was applied for potential associations with OCD symptom severity. OCD selectively targeted brain regions of higher functional connectivity strength than the average including brain network hubs, mainly distributed in the cortico-striato-thalamo-cortical (CSTC) circuits and additionally parietal, occipital, temporal and cerebellar regions. Moreover, affected functional connectivity strength in the cerebellum, the medial orbitofrontal cortex and superior occipital cortex was significantly associated with global OCD symptom severity. Our results provide the evidence about OCD-related brain network hub changes, not only in the CSTC circuits but more distributed in whole brain networks. Data suggest that whole brain network hub analysis is useful for understanding the pathophysiology of OCD. Copyright © 2015 Elsevier Inc. All rights reserved.

  11. Higher resting-state activity in reward-related brain circuits in obese versus normal-weight females independent of food intake.

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    Hogenkamp, P S; Zhou, W; Dahlberg, L S; Stark, J; Larsen, A L; Olivo, G; Wiemerslage, L; Larsson, E-M; Sundbom, M; Benedict, C; Schiöth, H B

    2016-11-01

    In response to food cues, obese vs normal-weight individuals show greater activation in brain regions involved in the regulation of food intake under both fasted and sated conditions. Putative effects of obesity on task-independent low-frequency blood-oxygenation-level-dependent signals-that is, resting-state brain activity-in the context of food intake are, however, less well studied. To compare eyes closed, whole-brain low-frequency BOLD signals between severely obese and normal-weight females, as assessed by functional magnetic resonance imaging (fMRI). Fractional amplitude of low-frequency fluctuations were measured in the morning following an overnight fast in 17 obese (age: 39±11 years, body mass index (BMI): 42.3±4.8 kg m - 2 ) and 12 normal-weight females (age: 36±12 years, BMI: 22.7±1.8 kg m - 2 ), both before and 30 min after consumption of a standardized meal (~260 kcal). Compared with normal-weight controls, obese females had increased low-frequency activity in clusters located in the putamen, claustrum and insula (Pfood intake. Self-reported hunger dropped and plasma glucose concentrations increased after food intake (Pfood intake under the experimental settings applied in the current study. Future studies involving males and females, as well as utilizing repeated post-prandial resting-state fMRI scans and various types of meals are needed to further investigate how food intake alters resting-state brain activity in obese humans.

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

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    Sair, Haris I; Yahyavi-Firouz-Abadi, Noushin; Calhoun, Vince D; Airan, Raag D; Agarwal, Shruti; Intrapiromkul, Jarunee; Choe, Ann S; Gujar, Sachin K; Caffo, Brian; Lindquist, Martin A; Pillai, Jay J

    2016-03-01

    To compare language networks derived from resting-state fMRI (rs-fMRI) with task-fMRI in patients with brain tumors and investigate variables that affect rs-fMRI vs task-fMRI concordance. Independent component analysis (ICA) of rs-fMRI was performed with 20, 30, 40, and 50 target components (ICA20 to ICA50) and language networks identified for patients presenting for presurgical fMRI mapping between 1/1/2009 and 7/1/2015. 49 patients were analyzed fulfilling criteria for presence of brain tumors, no prior brain surgery, and adequate task-fMRI performance. Rs-vs-task-fMRI concordance was measured using Dice coefficients across varying fMRI thresholds before and after noise removal. Multi-thresholded Dice coefficient volume under the surface (DiceVUS) and maximum Dice coefficient (MaxDice) were calculated. One-way Analysis of Variance (ANOVA) was performed to determine significance of DiceVUS and MaxDice between the four ICA order groups. Age, Sex, Handedness, Tumor Side, Tumor Size, WHO Grade, number of scrubbed volumes, image intensity root mean square (iRMS), and mean framewise displacement (FD) were used as predictors for VUS in a linear regression. Artificial elevation of rs-fMRI vs task-fMRI concordance is seen at low thresholds due to noise. Noise-removed group-mean DiceVUS and MaxDice improved as ICA order increased, however ANOVA demonstrated no statistically significant difference between the four groups. Linear regression demonstrated an association between iRMS and DiceVUS for ICA30-50, and iRMS and MaxDice for ICA50. Overall there is moderate group level rs-vs-task fMRI language network concordance, however substantial subject-level variability exists; iRMS may be used to determine reliability of rs-fMRI derived language networks. © 2015 Wiley Periodicals, Inc.

  13. Prediction of clinical depression scores and detection of changes in whole-brain using resting-state functional MRI data with partial least squares regression.

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    Kosuke Yoshida

    Full Text Available In diagnostic applications of statistical machine learning methods to brain imaging data, common problems include data high-dimensionality and co-linearity, which often cause over-fitting and instability. To overcome these problems, we applied partial least squares (PLS regression to resting-state functional magnetic resonance imaging (rs-fMRI data, creating a low-dimensional representation that relates symptoms to brain activity and that predicts clinical measures. Our experimental results, based upon data from clinically depressed patients and healthy controls, demonstrated that PLS and its kernel variants provided significantly better prediction of clinical measures than ordinary linear regression. Subsequent classification using predicted clinical scores distinguished depressed patients from healthy controls with 80% accuracy. Moreover, loading vectors for latent variables enabled us to identify brain regions relevant to depression, including the default mode network, the right superior frontal gyrus, and the superior motor area.

  14. Resting state cortical oscillations of patients with Parkinson disease and with and without subthalamic deep brain stimulation: a magnetoencephalography study.

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    Cao, Chunyan; Li, Dianyou; Jiang, Tianxiao; Ince, Nuri Firat; Zhan, Shikun; Zhang, Jing; Sha, Zhiyi; Sun, Bomin

    2015-04-01

    In this study, we investigate the modification to cortical oscillations of patients with Parkinson disease (PD) by subthalamic deep brain stimulation (STN-DBS). Spontaneous cortical oscillations of patients with PD were recorded with magnetoencephalography during on and off subthalamic nucleus deep brain stimulation states. Several features such as average frequency, average power, and relative subband power in regions of interest were extracted in the frequency domain, and these features were correlated with Unified Parkinson Disease Rating Scale III evaluation. The same features were also investigated in patients with PD without surgery and healthy controls. Patients with Parkinson disease without surgery compared with healthy controls had a significantly lower average frequency and an increased average power in 1 to 48 Hz range in whole cortex. Higher relative power in theta and simultaneous decrease in beta and gamma over temporal and occipital were also observed in patients with PD. The Unified Parkinson Disease Rating Scale III rigidity score correlated with the average frequency and with the relative power of beta and gamma in frontal areas. During subthalamic nucleus deep brain stimulation, the average frequency increased significantly when stimulation was on compared with off state. In addition, the relative power dropped in delta, whereas it rose in beta over the whole cortex. Through the course of stimulation, the Unified Parkinson Disease Rating Scale III rigidity and tremor scores correlated with the relative power of alpha over left parietal. Subthalamic nucleus deep brain stimulation improves the symptoms of PD by suppressing the synchronization of alpha rhythm in somatomotor region.

  15. Identifying differences in brain activities and an accurate detection of autism spectrum disorder using resting state functional-magnetic resonance imaging : A spatial filtering approach.

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    Subbaraju, Vigneshwaran; Suresh, Mahanand Belathur; Sundaram, Suresh; Narasimhan, Sundararajan

    2017-01-01

    This paper presents a new approach for detecting major differences in brain activities between Autism Spectrum Disorder (ASD) patients and neurotypical subjects using the resting state fMRI. Further the method also extracts discriminative features for an accurate diagnosis of ASD. The proposed approach determines a spatial filter that projects the covariance matrices of the Blood Oxygen Level Dependent (BOLD) time-series signals from both the ASD patients and neurotypical subjects in orthogonal directions such that they are highly separable. The inverse of this filter also provides a spatial pattern map within the brain that highlights those regions responsible for the distinguishable activities between the ASD patients and neurotypical subjects. For a better classification, highly discriminative log-variance features providing the maximum separation between the two classes are extracted from the projected BOLD time-series data. A detailed study has been carried out using the publicly available data from the Autism Brain Imaging Data Exchange (ABIDE) consortium for the different gender and age-groups. The study results indicate that for all the above categories, the regional differences in resting state activities are more commonly found in the right hemisphere compared to the left hemisphere of the brain. Among males, a clear shift in activities to the prefrontal cortex is observed for ASD patients while other parts of the brain show diminished activities compared to neurotypical subjects. Among females, such a clear shift is not evident; however, several regions, especially in the posterior and medial portions of the brain show diminished activities due to ASD. Finally, the classification performance obtained using the log-variance features is found to be better when compared to earlier studies in the literature. Copyright © 2016 Elsevier B.V. All rights reserved.

  16. Theory of Mind and the Whole Brain Functional Connectivity: Behavioral and Neural Evidences with the Amsterdam Resting State Questionnaire.

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    Marchetti, Antonella; Baglio, Francesca; Costantini, Isa; Dipasquale, Ottavia; Savazzi, Federica; Nemni, Raffaello; Sangiuliano Intra, Francesca; Tagliabue, Semira; Valle, Annalisa; Massaro, Davide; Castelli, Ilaria

    2015-01-01

    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 et al. (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.

  17. Abnormal Baseline Brain Activity in Drug-Naïve Patients with Tourette Syndrome: A Resting-state fMRI Study

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    Yonghua eCui

    2014-01-01

    Full Text Available Tourette Syndrome (TS is a childhood-onset chronic disorder characterized by the presence of multiple motor and vocal tics. This study investigated spontaneous low-frequency fluctuations in TS patients during resting-state functional magnetic resonance imaging (fMRI scans. We obtained resting-state fMRI scans from seventeen drug-naïve TS children and fifteen demographically matched healthy children. We computed the amplitude of low frequency fluctuation (ALFF and fractional ALFF (fALFF of resting-state fMRI data to measure spontaneous brain activity, and assessed the between-group differences in ALFF/fALFF and the relationship between ALFF/fALFF and tic severity scores. Our results showed that the children with TS exhibited significantly decreased ALFF in the posterior cingulate gyrus/precuneus and bilateral parietal gyrus. fALFF was decreased in TS children in the anterior cingulated cortex, bilateral middle and superior frontal cortices and superior parietal lobule, and increased in the left putamen and bilateral thalamus. Moreover, we found significantly positive correlations between fALFF and tic severity scores in the right thalamus. Our study provides empirical evidence for abnormal spontaneous neuronal activity in TS patients, which may implicate the underlying neurophysiological mechanism in TS and demonstrate the possibility of applying ALFF/fALFF for clinical TS studies.

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

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    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.

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

    Science.gov (United States)

    Liang, Xia; Wang, Jinhui; Yan, Chaogan; Shu, Ni; Xu, Ke; Gong, Gaolang; He, Yong

    2012-01-01

    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 and specific

  20. 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.

  1. Altered spontaneous brain activity pattern in patients with high myopia using amplitude of low-frequency fluctuation: a resting-state fMRI study

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    Huang X

    2016-11-01

    Full Text Available Xin Huang,1,2,* Fu-Qing Zhou,3,* Yu-Xiang Hu,1 Xiao-Xuan Xu,1 Xiong Zhou,4 Yu-Lin Zhong,1 Jun Wang,4 Xiao-Rong Wu1 1Department of Ophthalmology, The First Affiliated Hospital of Nanchang University, Nanchang, 2Department of Ophthalmology, The First People’s Hospital of Jiujiang City, Jiujiang, 3Department of Radiology, The First Affiliated Hospital of Nanchang University, Jiangxi Province Medical Imaging Research Institute, 4Second Department of Respiratory Disease, Jiangxi Provincial People’s Hospital, Nanchang, Jiangxi, People’s Republic of China *These authors contributed equally to this work Objective: Many previous reports have demonstrated significant neural anatomy changes in the brain of high myopic (HM patients, whereas the spontaneous brain activity changes in the HM patients at rest are not well studied. Our objective was to use amplitude of low-frequency fluctuation (ALFF method to investigate the changes in spontaneous brain activity in HM patients and their relationships with clinical features. Methods: A total of 38 patients with HM (17 males and 21 females and 38 healthy controls (HCs (17 males and 21 females closely matched in age, sex, and education underwent resting-state functional magnetic resonance imaging scans. The ALFF method was used to assess local features of spontaneous brain activity. The relationship between the mean ALFF signal values in many brain regions and the clinical features in HM patients was calculated by correlation analysis. Results: Compared with HCs, the HM patients had significantly lower ALFF in the right inferior and middle temporal gyrus, left middle temporal gyrus, left inferior frontal gyrus/putamen, right inferior frontal gyrus/putamen/insula, right middle frontal gyrus, and right inferior parietal lobule and higher ALFF values in the bilateral midcingulate cortex, left postcentral gyrus, and left precuneus/inferior parietal lobule. However, no relationship was found between the mean ALFF

  2. Tinnitus alters resting state functional connectivity (RSFC) in human auditory and non-auditory brain regions as measured by functional near-infrared spectroscopy (fNIRS).

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    San Juan, Juan; Hu, Xiao-Su; Issa, Mohamad; Bisconti, Silvia; Kovelman, Ioulia; Kileny, Paul; Basura, Gregory

    2017-01-01

    Tinnitus, or phantom sound perception, leads to increased spontaneous neural firing rates and enhanced synchrony in central auditory circuits in animal models. These putative physiologic correlates of tinnitus to date have not been well translated in the brain of the human tinnitus sufferer. Using functional near-infrared spectroscopy (fNIRS) we recently showed that tinnitus in humans leads to maintained hemodynamic activity in auditory and adjacent, non-auditory cortices. Here we used fNIRS technology to investigate changes in resting state functional connectivity between human auditory and non-auditory brain regions in normal-hearing, bilateral subjective tinnitus and controls before and after auditory stimulation. Hemodynamic activity was monitored over the region of interest (primary auditory cortex) and non-region of interest (adjacent non-auditory cortices) and functional brain connectivity was measured during a 60-second baseline/period of silence before and after a passive auditory challenge consisting of alternating pure tones (750 and 8000Hz), broadband noise and silence. Functional connectivity was measured between all channel-pairs. Prior to stimulation, connectivity of the region of interest to the temporal and fronto-temporal region was decreased in tinnitus participants compared to controls. Overall, connectivity in tinnitus was differentially altered as compared to controls following sound stimulation. Enhanced connectivity was seen in both auditory and non-auditory regions in the tinnitus brain, while controls showed a decrease in connectivity following sound stimulation. In tinnitus, the strength of connectivity was increased between auditory cortex and fronto-temporal, fronto-parietal, temporal, occipito-temporal and occipital cortices. Together these data suggest that central auditory and non-auditory brain regions are modified in tinnitus and that resting functional connectivity measured by fNIRS technology may contribute to conscious phantom

  3. Tinnitus alters resting state functional connectivity (RSFC in human auditory and non-auditory brain regions as measured by functional near-infrared spectroscopy (fNIRS.

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    Juan San Juan

    Full Text Available Tinnitus, or phantom sound perception, leads to increased spontaneous neural firing rates and enhanced synchrony in central auditory circuits in animal models. These putative physiologic correlates of tinnitus to date have not been well translated in the brain of the human tinnitus sufferer. Using functional near-infrared spectroscopy (fNIRS we recently showed that tinnitus in humans leads to maintained hemodynamic activity in auditory and adjacent, non-auditory cortices. Here we used fNIRS technology to investigate changes in resting state functional connectivity between human auditory and non-auditory brain regions in normal-hearing, bilateral subjective tinnitus and controls before and after auditory stimulation. Hemodynamic activity was monitored over the region of interest (primary auditory cortex and non-region of interest (adjacent non-auditory cortices and functional brain connectivity was measured during a 60-second baseline/period of silence before and after a passive auditory challenge consisting of alternating pure tones (750 and 8000Hz, broadband noise and silence. Functional connectivity was measured between all channel-pairs. Prior to stimulation, connectivity of the region of interest to the temporal and fronto-temporal region was decreased in tinnitus participants compared to controls. Overall, connectivity in tinnitus was differentially altered as compared to controls following sound stimulation. Enhanced connectivity was seen in both auditory and non-auditory regions in the tinnitus brain, while controls showed a decrease in connectivity following sound stimulation. In tinnitus, the strength of connectivity was increased between auditory cortex and fronto-temporal, fronto-parietal, temporal, occipito-temporal and occipital cortices. Together these data suggest that central auditory and non-auditory brain regions are modified in tinnitus and that resting functional connectivity measured by fNIRS technology may contribute to

  4. Connectomic markers of symptom severity in sport-related concussion: Whole-brain analysis of resting-state fMRI

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    Nathan W. Churchill

    Full Text Available Concussion is associated with significant adverse effects within the first week post-injury, including physical complaints and altered cognition, sleep and mood. It is currently unknown whether these subjective disturbances have reliable functional brain correlates. Resting-state functional magnetic resonance imaging (rs-fMRI has been used to measure functional connectivity of individuals after traumatic brain injury, but less is known about the relationship between functional connectivity and symptom assessments after a sport concussion. In this study, rs-fMRI was used to evaluate whole-brain functional connectivity for seventy (70 university-level athletes, including 35 with acute concussion and 35 healthy matched controls. Univariate analyses showed that greater symptom severity was mainly associated with lower pairwise connectivity in frontal, temporal and insular regions, along with higher connectivity in a sparser set of cerebellar regions. A novel multivariate approach also extracted two components that showed reliable covariation with symptom severity: (1 a network of frontal, temporal and insular regions where connectivity was negatively correlated with symptom severity (replicating the univariate findings; and (2 a network with anti-correlated elements of the default-mode network and sensorimotor system, where connectivity was positively correlated with symptom severity. These findings support the presence of connectomic signatures of symptom complaints following a sport-related concussion, including both increased and decreased functional connectivity within distinct functional brain networks. Keywords: fMRI, Functional connectivity, Concussion, Brain injury, Symptoms

  5. Spontaneous Brain Activity Did Not Show the Effect of Violent Video Games on Aggression: A Resting-State fMRI Study.

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    Pan, Wei; Gao, Xuemei; Shi, Shuo; Liu, Fuqu; Li, Chao

    2017-01-01

    A great many of empirical researches have proved that longtime exposure to violent video game can lead to a series of negative effects. Although research has focused on the neural basis of the correlation between violent video game and aggression, little is known whether the spontaneous brain activity is associated with violent video game exposure. To address this question, we measured the spontaneous brain activity using resting-state functional magnetic resonance imaging (fMRI). We used the amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF) to quantify spontaneous brain activity. The results showed there is no significant difference in ALFF, or fALFF, between violent video game group and the control part, indicating that long time exposure to violent video games won't significantly influence spontaneous brain activity, especially the core brain regions such as execution control, moral judgment and short-term memory. This implies the adverse impact of violent video games is exaggerated.

  6. Spontaneous Brain Activity Did Not Show the Effect of Violent Video Games on Aggression: A Resting-State fMRI Study

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    Wei Pan

    2018-01-01

    Full Text Available A great many of empirical researches have proved that longtime exposure to violent video game can lead to a series of negative effects. Although research has focused on the neural basis of the correlation between violent video game and aggression, little is known whether the spontaneous brain activity is associated with violent video game exposure. To address this question, we measured the spontaneous brain activity using resting-state functional magnetic resonance imaging (fMRI. We used the amplitude of low-frequency fluctuations (ALFF and fractional ALFF (fALFF to quantify spontaneous brain activity. The results showed there is no significant difference in ALFF, or fALFF, between violent video game group and the control part, indicating that long time exposure to violent video games won’t significantly influence spontaneous brain activity, especially the core brain regions such as execution control, moral judgment and short-term memory. This implies the adverse impact of violent video games is exaggerated.

  7. Spontaneous Brain Activity Did Not Show the Effect of Violent Video Games on Aggression: A Resting-State fMRI Study

    Science.gov (United States)

    Pan, Wei; Gao, Xuemei; Shi, Shuo; Liu, Fuqu; Li, Chao

    2018-01-01

    A great many of empirical researches have proved that longtime exposure to violent video game can lead to a series of negative effects. Although research has focused on the neural basis of the correlation between violent video game and aggression, little is known whether the spontaneous brain activity is associated with violent video game exposure. To address this question, we measured the spontaneous brain activity using resting-state functional magnetic resonance imaging (fMRI). We used the amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF) to quantify spontaneous brain activity. The results showed there is no significant difference in ALFF, or fALFF, between violent video game group and the control part, indicating that long time exposure to violent video games won’t significantly influence spontaneous brain activity, especially the core brain regions such as execution control, moral judgment and short-term memory. This implies the adverse impact of violent video games is exaggerated. PMID:29375416

  8. Liver transplantation nearly normalizes brain spontaneous activity and cognitive function at 1 month: a resting-state functional MRI study.

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    Cheng, Yue; Huang, Lixiang; Zhang, Xiaodong; Zhong, Jianhui; Ji, Qian; Xie, Shuangshuang; Chen, Lihua; Zuo, Panli; Zhang, Long Jiang; Shen, Wen

    2015-08-01

    To investigate the short-term brain activity changes in cirrhotic patients with Liver transplantation (LT) using resting-state functional MRI (fMRI) with regional homogeneity (ReHo) method. Twenty-six cirrhotic patients as transplant candidates and 26 healthy controls were included in this study. The assessment was repeated for a sub-group of 12 patients 1 month after LT. ReHo values were calculated to evaluate spontaneous brain activity and whole brain voxel-wise analysis was carried to detect differences between groups. Correlation analyses were performed to explore the relationship between the change of ReHo with the change of clinical indexes pre- and post-LT. Compared to pre-LT, ReHo values increased in the bilateral inferior frontal gyrus (IFG), right inferior parietal lobule (IPL), right supplementary motor area (SMA), right STG and left middle frontal gyrus (MFG) in patients post-LT. Compared to controls, ReHo values of post-LT patients decreased in the right precuneus, right SMA and increased in bilateral temporal pole, left caudate, left MFG, and right STG. The changes of ReHo in the right SMA, STG and IFG were correlated with change of digit symbol test (DST) scores (P brain activity of most brain regions with decreased ReHo in pre-LT was substantially improved and nearly normalized, while spontaneous brain activity of some brain regions with increased ReHo in pre-LT continuously increased. ReHo may provide information on the neural mechanisms of LT' effects on brain function.

  9. Aberrant brain regional homogeneity and functional connectivity in middle-aged T2DM patients: a resting-state functional MRI study

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    Daihong Liu

    2016-09-01

    Full Text Available 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 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 and lower ReHo in right fusiform gyrus, right precentral gyrus and right medial orbit of the superior frontal gyrus. 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 forward scores revealed significant correlations with the ReHo values of the right precentral gyrus (ρ = 0.527, p = 0.014 and FC between the right fusiform gyrus and middle temporal gyrus (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-associated brain

  10. MEG source imaging method using fast L1 minimum-norm and its applications to signals with brain noise and human resting-state source amplitude images.

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    Huang, Ming-Xiong; Huang, Charles W; Robb, Ashley; Angeles, AnneMarie; Nichols, Sharon L; Baker, Dewleen G; Song, Tao; Harrington, Deborah L; Theilmann, Rebecca J; Srinivasan, Ramesh; Heister, David; Diwakar, Mithun; Canive, Jose M; Edgar, J Christopher; Chen, Yu-Han; Ji, Zhengwei; Shen, Max; El-Gabalawy, Fady; Levy, Michael; McLay, Robert; Webb-Murphy, Jennifer; Liu, Thomas T; Drake, Angela; Lee, Roland R

    2014-01-01

    The present study developed a fast MEG source imaging technique based on Fast Vector-based Spatio-Temporal Analysis using a L1-minimum-norm (Fast-VESTAL) and then used the method to obtain the source amplitude images of resting-state magnetoencephalography (MEG) signals for different frequency bands. The Fast-VESTAL technique consists of two steps. First, L1-minimum-norm MEG source images were obtained for the dominant spatial modes of sensor-waveform covariance matrix. Next, accurate source time-courses with millisecond temporal resolution were obtained using an inverse operator constructed from the spatial source images of Step 1. Using simulations, Fast-VESTAL's performance was assessed for its 1) ability to localize multiple correlated sources; 2) ability to faithfully recover source time-courses; 3) robustness to different SNR conditions including SNR with negative dB levels; 4) capability to handle correlated brain noise; and 5) statistical maps of MEG source images. An objective pre-whitening method was also developed and integrated with Fast-VESTAL to remove correlated brain noise. Fast-VESTAL's performance was then examined in the analysis of human median-nerve MEG responses. The results demonstrated that this method easily distinguished sources in the entire somatosensory network. Next, Fast-VESTAL was applied to obtain the first whole-head MEG source-amplitude images from resting-state signals in 41 healthy control subjects, for all standard frequency bands. Comparisons between resting-state MEG sources images and known neurophysiology were provided. Additionally, in simulations and cases with MEG human responses, the results obtained from using conventional beamformer technique were compared with those from Fast-VESTAL, which highlighted the beamformer's problems of signal leaking and distorted source time-courses. © 2013.

  11. Large-scale brain network associated with creative insight: combined voxel-based morphometry and resting-state functional connectivity analyses.

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    Ogawa, Takeshi; Aihara, Takatsugu; Shimokawa, Takeaki; Yamashita, Okito

    2018-04-24

    Creative insight occurs with an "Aha!" experience when solving a difficult problem. Here, we investigated large-scale networks associated with insight problem solving. We recruited 232 healthy participants aged 21-69 years old. Participants completed a magnetic resonance imaging study (MRI; structural imaging and a 10 min resting-state functional MRI) and an insight test battery (ITB) consisting of written questionnaires (matchstick arithmetic task, remote associates test, and insight problem solving task). To identify the resting-state functional connectivity (RSFC) associated with individual creative insight, we conducted an exploratory voxel-based morphometry (VBM)-constrained RSFC analysis. We identified positive correlations between ITB score and grey matter volume (GMV) in the right insula and middle cingulate cortex/precuneus, and a negative correlation between ITB score and GMV in the left cerebellum crus 1 and right supplementary motor area. We applied seed-based RSFC analysis to whole brain voxels using the seeds obtained from the VBM and identified insight-positive/negative connections, i.e. a positive/negative correlation between the ITB score and individual RSFCs between two brain regions. Insight-specific connections included motor-related regions whereas creative-common connections included a default mode network. Our results indicate that creative insight requires a coupling of multiple networks, such as the default mode, semantic and cerebral-cerebellum networks.

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

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    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

  13. Elevated Body Mass Index is Associated with Increased Integration and Reduced Cohesion of Sensory-Driven and Internally Guided Resting-State Functional Brain Networks.

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    Doucet, Gaelle E; Rasgon, Natalie; McEwen, Bruce S; Micali, Nadia; Frangou, Sophia

    2018-03-01

    Elevated body mass index (BMI) is associated with increased multi-morbidity and mortality. The investigation of the relationship between BMI and brain organization has the potential to provide new insights relevant to clinical and policy strategies for weight control. Here, we quantified the association between increasing BMI and the functional organization of resting-state brain networks in a sample of 496 healthy individuals that were studied as part of the Human Connectome Project. We demonstrated that higher BMI was associated with changes in the functional connectivity of the default-mode network (DMN), central executive network (CEN), sensorimotor network (SMN), visual network (VN), and their constituent modules. In siblings discordant for obesity, we showed that person-specific factors contributing to obesity are linked to reduced cohesiveness of the sensory networks (SMN and VN). We conclude that higher BMI is associated with widespread alterations in brain networks that balance sensory-driven (SMN, VN) and internally guided (DMN, CEN) states which may augment sensory-driven behavior leading to overeating and subsequent weight gain. Our results provide a neurobiological context for understanding the association between BMI and brain functional organization while accounting for familial and person-specific influences. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  14. Resting State Network Estimation in Individual Subjects

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    Hacker, Carl D.; Laumann, Timothy O.; Szrama, Nicholas P.; Baldassarre, Antonello; Snyder, Abraham Z.

    2014-01-01

    Resting-state functional magnetic resonance imaging (fMRI) has been used to study brain networks associated with both normal and pathological cognitive function. The objective of this work is to reliably compute resting state network (RSN) topography in single participants. We trained a supervised classifier (multi-layer perceptron; MLP) to associate blood oxygen level dependent (BOLD) correlation maps corresponding to pre-defined seeds with specific RSN identities. Hard classification of maps obtained from a priori seeds was highly reliable across new participants. Interestingly, continuous estimates of RSN membership retained substantial residual error. This result is consistent with the view that RSNs are hierarchically organized, and therefore not fully separable into spatially independent components. After training on a priori seed-based maps, we propagated voxel-wise correlation maps through the MLP to produce estimates of RSN membership throughout the brain. The MLP generated RSN topography estimates in individuals consistent with previous studies, even in brain regions not represented in the training data. This method could be used in future studies to relate RSN topography to other measures of functional brain organization (e.g., task-evoked responses, stimulation mapping, and deficits associated with lesions) in individuals. The multi-layer perceptron was directly compared to two alternative voxel classification procedures, specifically, dual regression and linear discriminant analysis; the perceptron generated more spatially specific RSN maps than either alternative. PMID:23735260

  15. Mapping brain functional alterations in betel-quid chewers using resting-state fMRI and network analysis.

    Science.gov (United States)

    Weng, Jun-Cheng; Chou, Yu-Syuan; Huang, Guo-Joe; Tyan, Yeu-Sheng; Ho, Ming-Chou

    2018-04-01

    The World Health Organization regards betel quid (BQ) as a human carcinogen, and DSM-IV and ICD-10 dependence symptoms may develop with its heavy use. BQ's possible effects of an enhanced reward system and disrupted inhibitory control may increase the likelihood of habitual substance use. The current study aimed to employ resting-state fMRI to examine the hypothesized enhanced reward system (e.g., the basal forebrain system) and disrupted inhibitory control (e.g., the prefrontal system) in BQ chewers. The current study recruited three groups of 48 male participants: 16 BQ chewers, 15 tobacco- and alcohol-user controls, and 17 healthy controls. We used functional connectivity (FC), mean fractional amplitude of low-frequency fluctuations (mfALFF), and mean regional homogeneity (mReHo) to evaluate functional alternations in BQ chewers. Graph theoretical analysis (GTA) and network-based statistical (NBS) analysis were also performed to identify the functional network differences among the three groups. Our hypothesis was partially supported: the enhanced reward system for the BQ chewers (e.g., habitual drug-seeking behavior) was supported; however, their inhibitory control was relatively preserved. In addition, we reported that the BQ chewers may have enhanced visuospatial processing and decreased local segregation. The current results (showing an enhanced reward system in the chewers) provided the clinicians with important insight for the future development of an effective abstinence treatment.

  16. A whole-brain computational modeling approach to explain the alterations in resting-state functional connectivity during progression of Alzheimer's disease

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    Murat Demirtaş

    2017-01-01

    Full Text Available Alzheimer's disease (AD is the most common dementia with dramatic consequences. The research in structural and functional neuroimaging showed altered brain connectivity in AD. In this study, we investigated the whole-brain resting state functional connectivity (FC of the subjects with preclinical Alzheimer's disease (PAD, mild cognitive impairment due to AD (MCI and mild dementia due to Alzheimer's disease (AD, the impact of APOE4 carriership, as well as in relation to variations in core AD CSF biomarkers. The synchronization in the whole-brain was monotonously decreasing during the course of the disease progression. Furthermore, in AD patients we found widespread significant decreases in functional connectivity (FC strengths particularly in the brain regions with high global connectivity. We employed a whole-brain computational modeling approach to study the mechanisms underlying these alterations. To characterize the causal interactions between brain regions, we estimated the effective connectivity (EC in the model. We found that the significant EC differences in AD were primarily located in left temporal lobe. Then, we systematically manipulated the underlying dynamics of the model to investigate simulated changes in FC based on the healthy control subjects. Furthermore, we found distinct patterns involving CSF biomarkers of amyloid-beta (Aβ1−42 total tau (t-tau and phosphorylated tau (p-tau. CSF Aβ1−42 was associated to the contrast between healthy control subjects and clinical groups. Nevertheless, tau CSF biomarkers were associated to the variability in whole-brain synchronization and sensory integration regions. These associations were robust across clinical groups, unlike the associations that were found for CSF Aβ1−42. APOE4 carriership showed no significant correlations with the connectivity measures.

  17. Connectomic markers of symptom severity in sport-related concussion: Whole-brain analysis of resting-state fMRI.

    Science.gov (United States)

    Churchill, Nathan W; Hutchison, Michael G; Graham, Simon J; Schweizer, Tom A

    2018-01-01

    Concussion is associated with significant adverse effects within the first week post-injury, including physical complaints and altered cognition, sleep and mood. It is currently unknown whether these subjective disturbances have reliable functional brain correlates. Resting-state functional magnetic resonance imaging (rs-fMRI) has been used to measure functional connectivity of individuals after traumatic brain injury, but less is known about the relationship between functional connectivity and symptom assessments after a sport concussion. In this study, rs-fMRI was used to evaluate whole-brain functional connectivity for seventy (70) university-level athletes, including 35 with acute concussion and 35 healthy matched controls. Univariate analyses showed that greater symptom severity was mainly associated with lower pairwise connectivity in frontal, temporal and insular regions, along with higher connectivity in a sparser set of cerebellar regions. A novel multivariate approach also extracted two components that showed reliable covariation with symptom severity: (1) a network of frontal, temporal and insular regions where connectivity was negatively correlated with symptom severity (replicating the univariate findings); and (2) a network with anti-correlated elements of the default-mode network and sensorimotor system, where connectivity was positively correlated with symptom severity. These findings support the presence of connectomic signatures of symptom complaints following a sport-related concussion, including both increased and decreased functional connectivity within distinct functional brain networks.

  18. [Aberrant topological properties of whole-brain functional network in chronic right-sided sensorineural hearing loss: a resting-state functional MRI study].

    Science.gov (United States)

    Zhang, Lingling; Liu, Bin; Xu, Yangwen; Yang, Ming; Feng, Yuan; Huang, Yaqing; Huan, Zhichun; Hou, Zhaorui

    2015-02-03

    To investigate the topological properties of the functional brain network in unilateral sensorineural hearing loss patients. In this study, we acquired resting-state BOLD- fMRI data from 19 right-sided SNHL patients and 31 healthy controls with normal hearing and constructed their whole brain functional networks. Two-sample two-tailed t-tests were performed to investigate group differences in topological parameters between the USNHL patients and the controls. Partial correlation analysis was conducted to determine the relationships between the network metrics and USNHL-related variables. Both USNHL patients and controls exhibited small-word architecture in their brain functional networks within the range 0. 1 - 0. 2 of sparsity. Compared to the controls, USNHL patients showed significant increase in characteristic path length and normalized characteristic path length, but significant decrease in global efficiency. Clustering coefficient, local efficiency and normalized clustering coefficient demonstrated no significant difference. Furthermore, USNHL patients exhibited no significant association between the altered network metrics and the duration of USNHL or the severity of hearing loss. Our results indicated the altered topological properties of whole brain functional networks in USNHL patients, which may help us to understand pathophysiologic mechanism of USNHL patients.

  19. Diagnosing Autism Spectrum Disorder from Brain Resting-State Functional Connectivity Patterns Using a Deep Neural Network with a Novel Feature Selection Method.

    Science.gov (United States)

    Guo, Xinyu; Dominick, Kelli C; Minai, Ali A; Li, Hailong; Erickson, Craig A; Lu, Long J

    2017-01-01

    The whole-brain functional connectivity (FC) pattern obtained from resting-state functional magnetic resonance imaging data are commonly applied to study neuropsychiatric conditions such as autism spectrum disorder (ASD) by using different machine learning models. Recent studies indicate that both hyper- and hypo- aberrant ASD-associated FCs were widely distributed throughout the entire brain rather than only in some specific brain regions. Deep neural networks (DNN) with multiple hidden layers have shown the ability to systematically extract lower-to-higher level information from high dimensional data across a series of neural hidden layers, significantly improving classification accuracy for such data. In this study, a DNN with a novel feature selection method (DNN-FS) is developed for the high dimensional whole-brain resting-state FC pattern classification of ASD patients vs. typical development (TD) controls. The feature selection method is able to help the DNN generate low dimensional high-quality representations of the whole-brain FC patterns by selecting features with high discriminating power from multiple trained sparse auto-encoders. For the comparison, a DNN without the feature selection method (DNN-woFS) is developed, and both of them are tested with different architectures (i.e., with different numbers of hidden layers/nodes). Results show that the best classification accuracy of 86.36% is generated by the DNN-FS approach with 3 hidden layers and 150 hidden nodes (3/150). Remarkably, DNN-FS outperforms DNN-woFS for all architectures studied. The most significant accuracy improvement was 9.09% with the 3/150 architecture. The method also outperforms other feature selection methods, e.g., two sample t -test and elastic net. In addition to improving the classification accuracy, a Fisher's score-based biomarker identification method based on the DNN is also developed, and used to identify 32 FCs related to ASD. These FCs come from or cross different pre

  20. Altered intrinsic brain activities in patients with acute eye pain using amplitude of low-frequency fluctuation: a resting-state fMRI study

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    Pan Z

    2018-01-01

    Full Text Available Zhi-Ming Pan,1 Hai-Jun Li,1 Jing Bao,1 Nan Jiang,1 Qing Yuan,1 Shelby Freeberg,2 Pei-Wen Zhu,1 Lei Ye,1 Ming-Yang Ma,1 Xin Huang,1 Yi Shao1 1Department of Ophthalmology and Radiology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, People’s Republic of China; 2Department of Ophthalmology, University of Florida, Gainesville, FL, USA Objective: Many previous studies have reported that pain symptoms can lead to significant brain function and anatomical changes, whereas the intrinsic brain activity changes in acute eye pain (EP patients remain unknown. Using the amplitude of low-frequency fluctuation (ALFF method, this study aimed to evaluate the spontaneous brain activity alterations and their relationships with clinical features in acute EP patients.Participants and methods: A total of 20 patients with EP (15 males and 5 females and 20 healthy controls (HCs; 15 males and 5 females closely matched in age, sex, and education underwent resting-state functional magnetic resonance imaging scans. The ALFF method was applied to assess spontaneous brain activity changes. The ALFF values of the EP patients were distinguished from those of the HCs using a receiver operating characteristic curve. Pearson’s correlation analysis was used to investigate the relationships between the mean ALFF signal values from many brain regions and the clinical features in EP patients.Results: Compared with the HCs, acute EP patients had significantly lower ALFF in the left and right precentral/postcentral gyrus and left precuneus. In contrast, acute EP patients showed higher ALFF values in the right and left parahippocampal gyri and left caudate. However, no relationship was observed between the mean ALFF signal values from the different areas and clinical manifestations in the acute EP patients.Conclusion: We demonstrated that acute EP patients showed abnormal intrinsic brain activities in the precentral/postcentral gyrus and limbic system

  1. Diagnosing Autism Spectrum Disorder from Brain Resting-State Functional Connectivity Patterns Using a Deep Neural Network with a Novel Feature Selection Method

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    Xinyu Guo

    2017-08-01

    Full Text Available The whole-brain functional connectivity (FC pattern obtained from resting-state functional magnetic resonance imaging data are commonly applied to study neuropsychiatric conditions such as autism spectrum disorder (ASD by using different machine learning models. Recent studies indicate that both hyper- and hypo- aberrant ASD-associated FCs were widely distributed throughout the entire brain rather than only in some specific brain regions. Deep neural networks (DNN with multiple hidden layers have shown the ability to systematically extract lower-to-higher level information from high dimensional data across a series of neural hidden layers, significantly improving classification accuracy for such data. In this study, a DNN with a novel feature selection method (DNN-FS is developed for the high dimensional whole-brain resting-state FC pattern classification of ASD patients vs. typical development (TD controls. The feature selection method is able to help the DNN generate low dimensional high-quality representations of the whole-brain FC patterns by selecting features with high discriminating power from multiple trained sparse auto-encoders. For the comparison, a DNN without the feature selection method (DNN-woFS is developed, and both of them are tested with different architectures (i.e., with different numbers of hidden layers/nodes. Results show that the best classification accuracy of 86.36% is generated by the DNN-FS approach with 3 hidden layers and 150 hidden nodes (3/150. Remarkably, DNN-FS outperforms DNN-woFS for all architectures studied. The most significant accuracy improvement was 9.09% with the 3/150 architecture. The method also outperforms other feature selection methods, e.g., two sample t-test and elastic net. In addition to improving the classification accuracy, a Fisher's score-based biomarker identification method based on the DNN is also developed, and used to identify 32 FCs related to ASD. These FCs come from or cross

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

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    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.

  3. Gender differences in brain regional homogeneity of healthy subjects after normal sleep and after sleep deprivation: a resting-state fMRI study.

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    Dai, Xi-Jian; Gong, Hong-Han; Wang, Yi-Xiang; Zhou, Fu-Qing; Min, You-Jiang; Zhao, Feng; Wang, Si-Yong; Liu, Bi-Xia; Xiao, Xiang-Zuo

    2012-06-01

    To explore the gender differences of brain regional homogeneity (ReHo) in healthy subjects during the resting-state, after normal sleep, and after sleep deprivation (SD) using functional magnetic resonance imaging (fMRI) and the ReHo method. Sixteen healthy subjects (eight males and eight females) each underwent the resting-state fMRI exams twice, i.e., once after normal sleep and again after 24h's SD. According to the gender and sleep, 16 subjects were all measured twice and divided into four groups: the male control group (MC), female control group (FC), male SD group (MSD), and female SD group (FSD). The ReHo method was used to calculate and analyze the data, SPM5 software was used to perform a two-sample T-test and a two-pair T-test with a P value right paracentral lobule (BA3/6), but in no obviously lower regions. Compared with the FC, the FSD showed significantly higher ReHo in bilateral parietal lobes (BA2/3), bilateral vision-related regions of occipital lobes (BA17/18/19), right frontal lobe (BA4/6), and lower ReHo in the right frontal lobe. Compared with the FC, the MC showed significantly higher ReHo in the left occipital lobe (BA18/19), and left temporal lobe (BA21), left frontal lobe, and lower ReHo in the right insula and in the left parietal lobe. Compared with the FSD, the MSD showed significantly higher ReHo in the left cerebellum posterior lobe (uvula/declive of vermis), left parietal lobe, and bilateral frontal lobes, and lower ReHo in the right occipital lobe (BA17) and right frontal lobe (BA4). The differences of brain activity in the resting state can be widely found not only between the control and SD group in a same gender group, but also between the male group and female group. Thus, we should take the gender differences into consideration in future fMRI studies, especially the treatment of brain-related diseases (e.g., depression). Copyright © 2012 Elsevier B.V. All rights reserved.

  4. 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.

  5. Cortical sources of resting state EEG rhythms are related to brain hypometabolism in subjects with Alzheimer's disease: an EEG-PET study.

    Science.gov (United States)

    Babiloni, Claudio; Del Percio, Claudio; Caroli, Anna; Salvatore, Elena; Nicolai, Emanuele; Marzano, Nicola; Lizio, Roberta; Cavedo, Enrica; Landau, Susan; Chen, Kewei; Jagust, William; Reiman, Eric; Tedeschi, Gioacchino; Montella, Patrizia; De Stefano, Manuela; Gesualdo, Loreto; Frisoni, Giovanni B; Soricelli, Andrea

    2016-12-01

    Cortical sources of resting state electroencephalographic (EEG) delta (2-4 Hz) and low-frequency alpha (8-10.5 Hz) rhythms show abnormal activity (i.e., current density) in patients with dementia due to Alzheimer's disease (AD). Here, we hypothesized that abnormality of this activity is related to relevant disease processes as revealed by cortical hypometabolism typically observed in AD patients by fluorodeoxyglucose positron emission tomography. Resting state eyes-closed EEG data were recorded in 19 AD patients with dementia and 40 healthy elderly (Nold) subjects. EEG frequency bands of interest were delta and low-frequency alpha. EEG sources were estimated in these bands by low-resolution brain electromagnetic tomography (LORETA). Fluorodeoxyglucose positron emission tomography images were recorded only in the AD patients, and cortical hypometabolism was indexed by the so-called Alzheimer's discrimination analysis tool (PALZ) in the frontal association, ventromedial frontal, temporoparietal association, posterior cingulate, and precuneus areas. Results showed that compared with the Nold group, the AD group pointed to higher activity of delta sources and lower activity of low-frequency alpha sources in a cortical region of interest formed by all cortical areas of the PALZ score. In the AD patients, there was a positive correlation between the PALZ score and the activity of delta sources in the cortical region of interest (p < 0.05). These results suggest a relationship between resting state cortical hypometabolism and synchronization of cortical neurons at delta rhythms in AD patients with dementia. Copyright © 2016 Elsevier Inc. All rights reserved.

  6. Information Flow Between Resting-State Networks.

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    Diez, Ibai; Erramuzpe, Asier; Escudero, Iñaki; Mateos, Beatriz; Cabrera, Alberto; Marinazzo, Daniele; Sanz-Arigita, Ernesto J; Stramaglia, Sebastiano; Cortes Diaz, Jesus M

    2015-11-01

    The resting brain dynamics self-organize into a finite number of correlated patterns known as resting-state networks (RSNs). It is well known that techniques such as independent component analysis can separate the brain activity at rest to provide such RSNs, but the specific pattern of interaction between RSNs is not yet fully understood. To this aim, we propose here a novel method to compute the information flow (IF) between different RSNs from resting-state magnetic resonance imaging. After hemodynamic response function blind deconvolution of all voxel signals, and under the hypothesis that RSNs define regions of interest, our method first uses principal component analysis to reduce dimensionality in each RSN to next compute IF (estimated here in terms of transfer entropy) between the different RSNs by systematically increasing k (the number of principal components used in the calculation). When k=1, this method is equivalent to computing IF using the average of all voxel activities in each RSN. For k≥1, our method calculates the k multivariate IF between the different RSNs. We find that the average IF among RSNs is dimension dependent, increasing from k=1 (i.e., the average voxel activity) up to a maximum occurring at k=5 and to finally decay to zero for k≥10. This suggests that a small number of components (close to five) is sufficient to describe the IF pattern between RSNs. Our method--addressing differences in IF between RSNs for any generic data--can be used for group comparison in health or disease. To illustrate this, we have calculated the inter-RSN IF in a data set of Alzheimer's disease (AD) to find that the most significant differences between AD and controls occurred for k=2, in addition to AD showing increased IF w.r.t. The spatial localization of the k=2 component, within RSNs, allows the characterization of IF differences between AD and controls.

  7. 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...

  8. 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

  9. Spatial distribution of resting-state BOLD regional homogeneity as a predictor of brain glucose uptake: A study in healthy aging.

    Science.gov (United States)

    Bernier, Michaël; Croteau, Etienne; Castellano, Christian-Alexandre; Cunnane, Stephen C; Whittingstall, Kevin

    2017-04-15

    Positron emission tomography using [18F]-fluorodeoxyglucose (PET-FDG) is the primary imaging modality used to measure glucose metabolism in the brain (CMRGlu). CMRGlu has been used as a biomarker of brain aging and neurodegenerative diseases, but the complexity and invasive nature of PET often limits its use in research. There is therefore great interest in developing non-invasive metrics for estimating brain CMRGlu. We therefore investigated resting state fMRI metrics such as regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF) and regional global connectivity (Closeness) with multiple analytical approaches to determine their relationship to CMRGlu. We investigated this relation in two distinct cognitively healthy populations separated by age (27 young adults and 35 older adults). Overall, we found that both regionally and across participants, ReHo strongly correlated with CMRGlu in healthy young and older adults. Moreover, ReHo demonstrated the same age-related differences as CMRGlu throughout all cortical regions, particularly in the default network and frontal areas. Copyright © 2017 Elsevier Inc. All rights reserved.

  10. Alterations in Spontaneous Brain Activity and Functional Network Reorganization following Surgery in Children with Medically Refractory Epilepsy: A Resting-State Functional Magnetic Resonance Imaging Study

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    Yongxin Li

    2017-08-01

    Full Text Available For some patients with medically refractory epilepsy (MRE, surgery is a safe and effective treatment for controlling epilepsy. However, the functional consequences of such surgery on brain activity and connectivity in children remain unknown. In the present study, we carried out a longitudinal study using resting-state functional magnetic resonance imaging in 10 children with MRE before and again at a mean of 79 days after surgery, as well as in a group of 28 healthy controls. Compared with the controls, children with epilepsy exhibited abnormalities in intrinsic activity in the thalamus, putamen, pallidum, insula, hippocampus, cerebellum, and cingulate gyrus both before and after surgery. Longitudinal analyses showed that the amplitude of low frequency fluctuations (ALFF increased in the parietal–frontal cortex and decreased in the deep nuclei from pre- to post-surgery. The percentage changes in ALFF values in the deep nuclei were positively correlated with the age of epilepsy onset. Functional connectivity (FC analyses demonstrated a reorganization of FC architecture after surgery. These changes in brain activity and FC after surgery might indicate that the previously disrupted functional interactions were reorganized after surgery. All these results provide preliminary evidence that the age of epilepsy onset may have some potential to predict the outcome of brain functional reorganization after surgery in children with MRE.

  11. Bilingual experience and resting-state brain connectivity: Impacts of L2 age of acquisition and social diversity of language use on control networks.

    Science.gov (United States)

    Gullifer, Jason W; Chai, Xiaoqian J; Whitford, Veronica; Pivneva, Irina; Baum, Shari; Klein, Denise; Titone, Debra

    2018-05-01

    We investigated the independent contributions of second language (L2) age of acquisition (AoA) and social diversity of language use on intrinsic brain organization using seed-based resting-state functional connectivity among highly proficient French-English bilinguals. There were two key findings. First, earlier L2 AoA related to greater interhemispheric functional connectivity between homologous frontal brain regions, and to decreased reliance on proactive executive control in an AX-Continuous Performance Task completed outside the scanner. Second, greater diversity in social language use in daily life related to greater connectivity between the anterior cingulate cortex and the putamen bilaterally, and to increased reliance on proactive control in the same task. These findings suggest that early vs. late L2 AoA links to a specialized neural framework for processing two languages that may engage a specific type of executive control (e.g., reactive control). In contrast, higher vs. lower degrees of diversity in social language use link to a broadly distributed set of brain networks implicated in proactive control and context monitoring. Copyright © 2018 Elsevier Ltd. All rights reserved.

  12. Mechanism of Cerebralcare Granule® for Improving Cognitive Function in Resting-State Brain Functional Networks of Sub-healthy Subjects

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    Jing Li

    2017-07-01

    Full Text Available Cerebralcare Granule® (CG, a Chinese herbal medicine, has been used to ameliorate cognitive impairment induced by ischemia or mental disorders. The ability of CG to improve health status and cognitive function has drawn researchers' attention, but the relevant brain circuits that underlie the ameliorative effects of CG remain unclear. The present study aimed to explore the underlying neurobiological mechanisms of CG in ameliorating cognitive function in sub-healthy subjects using resting-state functional magnetic resonance imaging (fMRI. Thirty sub-healthy participants were instructed to take one 2.5-g package of CG three times a day for 3 months. Clinical cognitive functions were assessed with the Chinese Revised Wechsler Adult Intelligence Scale (WAIS-RC and Wechsler Memory Scale (WMS, and fMRI scans were performed at baseline and the end of intervention. Functional brain network data were analyzed by conventional network metrics (CNM and frequent subgraph mining (FSM. Then 21 other sub-healthy participants were enrolled as a blank control group of cognitive functional. We found that administrating CG can improve the full scale of intelligence quotient (FIQ and Memory Quotient (MQ scores. At the same time, following CG treatment, in CG group, the topological properties of functional brain networks were altered in various frontal, temporal, occipital cortex regions, and several subcortical brain regions, including essential components of the executive attention network, the salience network, and the sensory-motor network. The nodes involved in the FSM results were largely consistent with the CNM findings, and the changes in nodal metrics correlated with improved cognitive function. These findings indicate that CG can improve sub-healthy subjects' cognitive function through altering brain functional networks. These results provide a foundation for future studies of the potential physiological mechanism of CG.

  13. Characterizing Signals within Lesions and Mapping Brain Network Connectivity After Traumatic Axonal Injury: A 7 Tesla Resting-State FMRI Study.

    Science.gov (United States)

    Lee, Seul; Polimeni, Jonathan R; Price, Collin M; Edlow, Brian L; McNab, Jennifer A

    2018-04-18

    Resting-state functional magnetic resonance imaging (RS-FMRI) has been widely used to map brain functional connectivity, but it is unclear how to probe connectivity within and around lesions. Here we characterize RS-FMRI signal time-course properties and evaluate different seed placements within and around hemorrhagic traumatic axonal injury lesions. RS-FMRI was performed on a 7 Tesla scanner in a patient who recovered consciousness after traumatic coma and in three healthy controls. Eleven lesions in the patient were characterized in terms of: 1) temporal signal-to-noise ratio (tSNR); 2) physiological noise, through comparison of noise regressors derived from the white matter (WM), cerebrospinal fluid (CSF) and gray matter (GM); and 3) seed-based functional connectivity. Temporal SNR at the center of the lesions was 38.3% and 74.1% lower compared to the same region in the contralesional hemisphere of the patient and in the ipsilesional hemispheres of the controls, respectively. Within the lesions, WM noise was more prominent than CSF and GM noise. Lesional seeds did not produce discernable networks, but seeds in the contralesional hemisphere revealed networks whose nodes appeared to be shifted or obscured due to overlapping or nearby lesions. Single-voxel seed analysis demonstrated that placing a seed within a lesion's periphery was necessary to identify networks associated with the lesion region. These findings provide evidence of resting-state network changes in the human brain after recovery from traumatic coma. Further, we show that seed placement within a lesion's periphery or in the contralesional hemisphere may be necessary for network identification in patients with hemorrhagic traumatic axonal injury.

  14. Brain sexual differentiation and effects of cross-sex hormone therapy in transpeople: A resting-state functional magnetic resonance study.

    Science.gov (United States)

    Nota, Nienke M; Burke, Sarah M; den Heijer, Martin; Soleman, Remi S; Lambalk, Cornelis B; Cohen-Kettenis, Peggy T; Veltman, Dick J; Kreukels, Baudewijntje P

    2017-12-01

    It is hypothesized that transpeople show sex-atypical differentiation of the brain. Various structural neuroimaging studies provide support for this notion, but little is known about the sexual differentiation of functional resting-state networks in transpeople. In this study we therefore aimed to determine whether brain functional connectivity (FC) patterns in transpeople are sex-typical or sex-atypical, before and after the start of cross-sex hormone therapy (CHT). We acquired resting-state functional magnetic resonance data in 36 transpeople (22 with female sex assigned at birth), first during gonadal suppression, and again four months after start of CHT, and in 37 cisgender people (20 females), both sessions without any hormonal intervention. We used independent component analysis to identify the default mode network (DMN), salience network (SN), and left and right working memory network (WMN). These spatial maps were used for group comparisons. Within the DMN, SN, and left WMN similar FC patterns were found across groups. However, within the right WMN, cisgender males showed significantly greater FC in the right caudate nucleus than cisgender females. There was no such sex difference in FC among the transgender groups and they did not differ significantly from either of the cisgender groups. CHT (in transgender participants) and circulating sex steroids (in cisgender participants) did not affect FC. Our findings may suggest that cisgender males and females experience a dissimilar (early) differentiation of the right WMN and that such differentiation is less pronounced in transpeople. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

  15. Brain resting-state networks in adolescents with high-functioning autism: Analysis of spatial connectivity and temporal neurodynamics

    NARCIS (Netherlands)

    Bernas, A.; Barendse, E.M.; Aldenkamp, A.P.; Backes, W.H.; Hofman, P.A.M.; Hendriks, M.P.H.; Kessels, R.P.C.; Willems, F.M.J.; With, P.H.N. de; Zinger, S.; Jansen, J.F.A.

    2018-01-01

    Introduction: Autism spectrum disorder (ASD) is mainly characterized by functional and communication impairments as well as restrictive and repetitive behavior. The leading hypothesis for the neural basis of autism postulates globally abnormal brain connectivity, which can be assessed using

  16. Subjective Cognitive Decline: Mapping Functional and Structural Brain Changes-A Combined Resting-State Functional and Structural MR Imaging Study.

    Science.gov (United States)

    Sun, Yu; Dai, Zhengjia; Li, Yuxia; Sheng, Can; Li, Hongyan; Wang, Xiaoni; Chen, Xiaodan; He, Yong; Han, Ying

    2016-10-01

    Purpose To determine whether individuals with subjective cognitive decline (SCD) exhibit functional and structural brain alterations by using resting-state functional and structural magnetic resonance (MR) imaging. Materials and Methods This study received institutional review board approval, and all participants gave informed consent. Resting-state functional MR imaging and structural MR imaging techniques were used to measure amplitude of low-frequency fluctuations (ALFF) and regional gray matter volume in 25 subjects with SCD (mean age, 65.52 years ± 6.12) and 61 control subjects (mean age, 64.11 years ± 8.59). Voxel-wise general linear model analyses were used to examine between-group differences in ALFF or in gray matter volume and to further determine the brain-behavioral relationship. Results Subjects with SCD exhibited higher ALFF values than did control subjects in the bilateral inferior parietal lobule (left: 0.44 ± 0.25 vs 0.27 ± 0.18, respectively; P = .0003; right: 1.46 ± 0.45 vs 1.10 ± 0.37, respectively; P = .0015), right inferior (0.45 ± 0.15 vs 0.37 ± 0.08, repectively; P = .0106) and middle (1.03 ± 0.32 vs 0.83 ± 0.20, respectively; P = .0008) occipital gyrus, right superior temporal gyrus (0.11 ± 0.07 vs 0.07 ± 0.04, respectively; P = .0016), and right cerebellum posterior lobe (0.51 ± 0.27 vs 0.39 ± 0.15, respectively; P = .0010). In the SCD group, significant correlations were found between Auditory Verbal Learning Test recognition scores and ALFF in the left inferior parietal lobe (r = -0.79, P Learning Test immediate recall scores and ALFF values in the right middle occipital gyrus (r = -0.64, P = .002). Nonsignificant group differences were found in gray matter volume (P > .05, corrected). Conclusion Individuals with SCD had altered spontaneous functional activity, suggesting that resting-state functional MR imaging may be a noninvasive method for characterizing SCD. (©) RSNA, 2016 Online supplemental material is available for

  17. 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.

  18. 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.

  19. Resting State Functional Connectivity in Mild Traumatic Brain Injury at the Acute Stage: Independent Component and Seed-Based Analyses

    OpenAIRE

    Iraji, Armin; Benson, Randall R.; Welch, Robert D.; O'Neil, Brian J.; Woodard, John L.; Imran Ayaz, Syed; Kulek, Andrew; Mika, Valerie; Medado, Patrick; Soltanian-Zadeh, Hamid; Liu, Tianming; Haacke, E. Mark; Kou, Zhifeng

    2015-01-01

    Mild traumatic brain injury (mTBI) accounts for more than 1 million emergency visits each year. Most of the injured stay in the emergency department for a few hours and are discharged home without a specific follow-up plan because of their negative clinical structural imaging. Advanced magnetic resonance imaging (MRI), particularly functional MRI (fMRI), has been reported as being sensitive to functional disturbances after brain injury. In this study, a cohort of 12 patients with mTBI were pr...

  20. The Role of Nonlinearity in Computing Graph-Theoretical Properties of Resting-State Functional Magnetic Resonance Imaging Brain Networks

    Czech Academy of Sciences Publication Activity Database

    Hartman, David; Hlinka, Jaroslav; Paluš, Milan; Mantini, D.; Corbetta, M.

    2011-01-01

    Roč. 21, č. 1 (2011), art.no 013119 ISSN 1054-1500 R&D Projects: GA MŠk 7E08027 Institutional research plan: CEZ:AV0Z10300504 Keywords : complex network * fMRI * brain connectivity * nonlinear * mutual information * correlation Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.076, year: 2011

  1. 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. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

  2. 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. Copyright © 2016 Elsevier Inc. All rights reserved.

  3. Altered Rich-Club and Frequency-Dependent Subnetwork Organization in Mild Traumatic Brain Injury: A MEG Resting-State Study

    Directory of Open Access Journals (Sweden)

    Marios Antonakakis

    2017-08-01

    Full Text Available Functional brain connectivity networks exhibit “small-world” characteristics and some of these networks follow a “rich-club” organization, whereby a few nodes of high connectivity (hubs tend to connect more densely among themselves than to nodes of lower connectivity. The Current study followed an “attack strategy” to compare the rich-club and small-world network organization models using Magnetoencephalographic (MEG recordings from mild traumatic brain injury (mTBI patients and neurologically healthy controls to identify the topology that describes the underlying intrinsic brain network organization. We hypothesized that the reduction in global efficiency caused by an attack targeting a model's hubs would reveal the “true” underlying topological organization. Connectivity networks were estimated using mutual information as the basis for cross-frequency coupling. Our results revealed a prominent rich-club network organization for both groups. In particular, mTBI patients demonstrated hyper-synchronization among rich-club hubs compared to controls in the δ band and the δ-γ1, θ-γ1, and β-γ2 frequency pairs. Moreover, rich-club hubs in mTBI patients were overrepresented in right frontal brain areas, from θ to γ1 frequencies, and underrepresented in left occipital regions in the δ-β, δ-γ1, θ-β, and β-γ2 frequency pairs. These findings indicate that the rich-club organization of resting-state MEG, considering its role in information integration and its vulnerability to various disorders like mTBI, may have a significant predictive value in the development of reliable biomarkers to help the validation of the recovery from mTBI. Furthermore, the proposed approach might be used as a validation tool to assess patient recovery.

  4. Resting state FMRI research in child psychiatric disorders

    NARCIS (Netherlands)

    Oldehinkel, Marianne; Francx, Winke; Beckmann, Christian; Buitelaar, Jan K.; Mennes, Maarten

    2013-01-01

    Concurring with the shift from linking functions to specific brain areas towards studying network integration, resting state FMRI (R-FMRI) has become an important tool for delineating the functional network architecture of the brain. Fueled by straightforward data collection, R-FMRI analysis methods

  5. Abnormal baseline brain activity in Parkinson's disease with and without REM sleep behavior disorder: A resting-state functional MRI study.

    Science.gov (United States)

    Li, Dan; Huang, Peiyu; Zang, Yufeng; Lou, Yuting; Cen, Zhidong; Gu, Quanquan; Xuan, Min; Xie, Fei; Ouyang, Zhiyuan; Wang, Bo; Zhang, Minming; Luo, Wei

    2017-09-01

    To investigate the differences in spontaneous brain activity between Parkinson's disease (PD) patients with rapid eye movement sleep behavior disorder (RBD), PD patients without RBD, and normal controls, which may shed new light on the neural mechanism of RBD. Eighteen PD patients with RBD, 16 patients without RBD, and 19 age- and gender-matched normal controls underwent clinical assessment and functional magnetic resonance imaging (fMRI) with a 3.0T scanner. Resting-state fMRI scans were collected using an echo planar imaging sequence. Amplitude of low-frequency fluctuations (ALFF) were calculated to measure spontaneous brain activity in each subject. Compared with PD patients without RBD, patients with RBD exhibited significantly decreased ALFF values (P abnormalities. Our findings provide additional insight into the neural mechanism of RBD and may drive future research to develop better treatment. 3 Technical Efficacy: Stage 3 J. MAGN. RESON. IMAGING 2017;46:697-703. © 2016 International Society for Magnetic Resonance in Medicine.

  6. Associations Between Daily Mood States and Brain Gray Matter Volume, Resting-State Functional Connectivity and Task-Based Activity in Healthy Adults

    Directory of Open Access Journals (Sweden)

    Elmira Ismaylova

    2018-05-01

    Full Text Available Numerous studies have shown differences in the functioning in the areas of the frontal-limbic circuitry between depressed patients and controls. However, current knowledge on frontal-limbic neural substrates of individual differences in mood states in everyday life in healthy individuals is scarce. The present study investigates anatomical, resting-state, and functional neural correlates of daily mood states in healthy individuals. We expected to observe associations between mood and the frontal-limbic circuitry and the default-mode network (DMN. A total of 42 healthy adults (19 men, 23 women; 34 ± 1.2 years regularly followed for behavior and psychosocial functioning since age of 6, underwent a functional magnetic resonance imaging scan, and completed a daily diary of mood states and related cognitions for 5 consecutive days. Results showed that individuals with smaller left hippocampal gray matter volumes experienced more negative mood and rumination in their daily life. Greater resting-state functional connectivity (rsFC within the DMN, namely between posterior cingulate cortex (PCC and medial prefrontal cortex regions as well as between PCC and precuneus, was associated with both greater negative and positive mood states in daily life. These rsFC results could be indicative of the role of the DMN regional functioning in emotional arousal, irrespective of valence. Lastly, greater daily positive mood was associated with greater activation in response to negative emotional stimuli in the precentral gyri, previously linked to emotional interference on cognitive control. Altogether, present findings might reflect neural mechanisms underlying daily affect and cognition among healthy individuals.

  7. Associations Between Daily Mood States and Brain Gray Matter Volume, Resting-State Functional Connectivity and Task-Based Activity in Healthy Adults.

    Science.gov (United States)

    Ismaylova, Elmira; Di Sante, Jessica; Gouin, Jean-Philippe; Pomares, Florence B; Vitaro, Frank; Tremblay, Richard E; Booij, Linda

    2018-01-01

    Numerous studies have shown differences in the functioning in the areas of the frontal-limbic circuitry between depressed patients and controls. However, current knowledge on frontal-limbic neural substrates of individual differences in mood states in everyday life in healthy individuals is scarce. The present study investigates anatomical, resting-state, and functional neural correlates of daily mood states in healthy individuals. We expected to observe associations between mood and the frontal-limbic circuitry and the default-mode network (DMN). A total of 42 healthy adults (19 men, 23 women; 34 ± 1.2 years) regularly followed for behavior and psychosocial functioning since age of 6, underwent a functional magnetic resonance imaging scan, and completed a daily diary of mood states and related cognitions for 5 consecutive days. Results showed that individuals with smaller left hippocampal gray matter volumes experienced more negative mood and rumination in their daily life. Greater resting-state functional connectivity (rsFC) within the DMN, namely between posterior cingulate cortex (PCC) and medial prefrontal cortex regions as well as between PCC and precuneus, was associated with both greater negative and positive mood states in daily life. These rsFC results could be indicative of the role of the DMN regional functioning in emotional arousal, irrespective of valence. Lastly, greater daily positive mood was associated with greater activation in response to negative emotional stimuli in the precentral gyri, previously linked to emotional interference on cognitive control. Altogether, present findings might reflect neural mechanisms underlying daily affect and cognition among healthy individuals.

  8. [Brain plastic alterations in subjects with chronic right-sided sensorineural hearing loss: a resting-state MRI study].

    Science.gov (United States)

    Zhang, L L; Gong, J P; Xu, Y W; Liu, B

    2016-06-21

    To investigate the nodal properties and reorganization of whole-brain functional network in subjects with severe right-sided SNHL. From June 2012 to June 2013, a total of 19 patients with severe right-sided SNHL were collected from Zhongda Hospital or the recruitment advertising along with 31 healthy controls.Based on the graph-theoretical analysis, the whole-brain functional networks were constructed using the BOLD-fMRI data of all subjects.Two sample two-tailed t-tests were used to investigate the differences between two groups in nodal metrics, such as node degree, node betweenness, node global efficiency and node local efficiency.All metrics were corrected by multiple comparisons.Partial correlation analysis was used to estimate the relationship between the significant metrics and the duration or severity of hearing loss. The right-sided SNHL showed significantly increased betweenness centrality in left supramarginal gyrus and right fusiform.However, other nodal parameters showed no statistical difference.Besides, patients exhibited no significant association between the altered metrics and clinical variables. Alterations of local topological properties may underlie cerebral cross-modal plastic reorganization in visual or speech-related regions in severe right-sided SNHL patients.

  9. 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.

  10. Effects of Long-Term Acupuncture Treatment on Resting-State Brain Activity in Migraine Patients: A Randomized Controlled Trial on Active Acupoints and Inactive Acupoints

    Science.gov (United States)

    Zhao, Ling; Liu, Jixin; Zhang, Fuwen; Dong, Xilin; Peng, Yulin; Qin, Wei; Wu, Fumei; Li, Ying; Yuan, Kai; von Deneen, Karen M.; Gong, Qiyong; Tang, Zili; Liang, Fanrong

    2014-01-01

    Background Acupuncture has been commonly used for preventing migraine attacks and relieving pain during a migraine, although there is limited knowledge on the physiological mechanism behind this method. The objectives of this study were to compare the differences in brain activities evoked by active acupoints and inactive acupoints and to investigate the possible correlation between clinical variables and brain responses. Methods and Results A randomized controlled trial and resting-state functional magnetic resonance imaging (fMRI) were conducted. A total of eighty migraineurs without aura were enrolled to receive either active acupoint acupuncture or inactive acupoint acupuncture treatment for 8 weeks, and twenty patients in each group were randomly selected for the fMRI scan at the end of baseline and at the end of treatment. The neuroimaging data indicated that long-term active acupoint therapy elicited a more extensive and remarkable cerebral response compared with acupuncture at inactive acupoints. Most of the regions were involved in the pain matrix, lateral pain system, medial pain system, default mode network, and cognitive components of pain processing. Correlation analysis showed that the decrease in the visual analogue scale (VAS) was significantly related to the increased average Regional homogeneity (ReHo) values in the anterior cingulate cortex in the two groups. Moreover, the decrease in the VAS was associated with increased average ReHo values in the insula which could be detected in the active acupoint group. Conclusions Long-term active acupoint therapy and inactive acupoint therapy have different brain activities. We postulate that acupuncture at the active acupoint might have the potential effect of regulating some disease-affected key regions and the pain circuitry for migraine, and promote establishing psychophysical pain homeostasis. Trial Registration Chinese Clinical Trial Registry ChiCTR-TRC-13003635 PMID:24915066

  11. Altered intrinsic regional brain activity in male patients with severe obstructive sleep apnea: a resting-state functional magnetic resonance imaging study

    Directory of Open Access Journals (Sweden)

    Peng DC

    2014-09-01

    Full Text Available De-Chang Peng,1 Xi-Jian Dai,1,2 Hong-Han Gong,1 Hai-Jun Li,1 Xiao Nie,1 Wei Zhang3 1Department of Radiology, The First Affiliated Hospital of Nanchang University, Jiangxi, 2Department of Imaging and Interventional Radiology, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong, Special Administrative Region, 3Department of Pneumology, The First Affiliated Hospital of Nanchang University, Jiangxi, People’s Republic of China Background: Previous studies have demonstrated that obstructive sleep apnea (OSA is associated with abnormal brain structural deficits. However, little is known about the changes in local synchronization of spontaneous activity in patients with OSA. The primary aim of the present study was to investigate spontaneous brain activity in patients with OSA compared with good sleepers (GSs using regional homogeneity (ReHo analysis based on resting-state ­functional magnetic resonance imaging (MRI. Methods: Twenty-five untreated male patients with severe OSA and 25 male GSs matched for age and years of education were included in this study. The ReHo method was calculated to assess the strength of local signal synchrony and was compared between the two groups. The observed mean ReHo values were entered into Statistical Package for the Social Sciences software to assess their correlation with behavioral performance. Results: Compared with GSs, patients with OSA showed significantly lower ReHo in the right medial frontal gyrus (BA11, right superior frontal gyrus (BA10, right cluster of the precuneus and angular gyrus (BA39, and left superior parietal lobule (BA7, and higher ReHo in the right posterior lobe of the cerebellum, right cingulate gyrus (BA23, and bilateral cluster covering the lentiform nucleus, putamen, and insula (BA13. The lower mean ReHo value in the right cluster of the precuneus and angular gyrus had a significant negative correlation with sleep time (r=-0.430, P=0.032, and higher ReHo in

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

    Science.gov (United States)

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

    2014-01-01

    To what degree resting state fMRI is stable or susceptible to internal mind states of the individual is currently an issue of debate. To address this issue, the present study focuses on sex differences and investigates whether resting state fMRI is stable in men and women or changes within relative short-term periods (i.e., across the menstrual cycle). Due to the fact that we recently reported menstrual cycle effects on cognitive control based on data collected during the same sessions, the current study is particularly interested in fronto-parietal resting state networks. Resting state fMRI was measured in sixteen women during three different cycle phases (menstrual, follicular, and luteal). Fifteen men underwent three sessions in corresponding time intervals. We used independent component analysis to identify four fronto-parietal networks. The results showed sex differences in two of these networks with women exhibiting higher functional connectivity in general, including the prefrontal cortex. Menstrual cycle effects on resting states were non-existent. It is concluded that sex differences in resting state fMRI might reflect sexual dimorphisms in the brain rather than transitory activating effects of sex hormones on the functional connectivity in the resting brain.

  13. Functional Clustering of the Human Inferior Parietal Lobule by Whole-Brain Connectivity Mapping of Resting-State Functional Magnetic Resonance Imaging Signals

    Science.gov (United States)

    Li, Chiang-Shan R.

    2014-01-01

    Abstract The human inferior parietal lobule (IPL) comprised the lateral bank of the intraparietal sulcus, angular gyrus, and supramarginal gyrus, defined on the basis of anatomical landmarks and cytoarchitectural organization of neurons. However, it is not clear as to whether the three areas represent functional subregions within the IPL. For instance, imaging studies frequently identified clusters of activities that cut across areal boundaries. Here, we used resting-state functional magnetic resonance imaging (fMRI) data to examine how individual voxels within the IPL are best clustered according to their connectivity to the whole brain. The results identified a best estimate of seven clusters that are hierarchically arranged as the anterior, middle, and posterior subregions. The anterior, middle, and posterior IPL are each significantly connected to the somatomotor areas, superior/middle/inferior frontal gyri, and regions of the default mode network. This functional segregation is supported by recent cytoarchitechtonics and tractography studies. IPL showed hemispheric differences in connectivity that accord with a predominantly left parietal role in tool use and language processing and a right parietal role in spatial attention and mathematical cognition. The functional clusters may also provide a more parsimonious and perhaps even accurate account of regional activations of the IPL during a variety of cognitive challenges, as reported in earlier fMRI studies. PMID:24308753

  14. Graph Theoretical Analysis of Functional Brain Networks: Test-Retest Evaluation on Short- and Long-Term Resting-State Functional MRI Data

    Science.gov (United States)

    Wang, Jin-Hui; Zuo, Xi-Nian; Gohel, Suril; Milham, Michael P.; Biswal, Bharat B.; He, Yong

    2011-01-01

    Graph-based computational network analysis has proven a powerful tool to quantitatively characterize functional architectures of the brain. However, the test-retest (TRT) reliability of graph metrics of functional networks has not been systematically examined. Here, we investigated TRT reliability of topological metrics of functional brain networks derived from resting-state functional magnetic resonance imaging data. Specifically, we evaluated both short-term (5 months apart) TRT reliability for 12 global and 6 local nodal network metrics. We found that reliability of global network metrics was overall low, threshold-sensitive and dependent on several factors of scanning time interval (TI, long-term>short-term), network membership (NM, networks excluding negative correlations>networks including negative correlations) and network type (NT, binarized networks>weighted networks). The dependence was modulated by another factor of node definition (ND) strategy. The local nodal reliability exhibited large variability across nodal metrics and a spatially heterogeneous distribution. Nodal degree was the most reliable metric and varied the least across the factors above. Hub regions in association and limbic/paralimbic cortices showed moderate TRT reliability. Importantly, nodal reliability was robust to above-mentioned four factors. Simulation analysis revealed that global network metrics were extremely sensitive (but varying degrees) to noise in functional connectivity and weighted networks generated numerically more reliable results in compared with binarized networks. For nodal network metrics, they showed high resistance to noise in functional connectivity and no NT related differences were found in the resistance. These findings provide important implications on how to choose reliable analytical schemes and network metrics of interest. PMID:21818285

  15. Sparse dictionary learning of resting state fMRI networks.

    Science.gov (United States)

    Eavani, Harini; Filipovych, Roman; Davatzikos, Christos; Satterthwaite, Theodore D; Gur, Raquel E; Gur, Ruben C

    2012-07-02

    Research in resting state fMRI (rsfMRI) has revealed the presence of stable, anti-correlated functional subnetworks in the brain. Task-positive networks are active during a cognitive process and are anti-correlated with task-negative networks, which are active during rest. In this paper, based on the assumption that the structure of the resting state functional brain connectivity is sparse, we utilize sparse dictionary modeling to identify distinct functional sub-networks. We propose two ways of formulating the sparse functional network learning problem that characterize the underlying functional connectivity from different perspectives. Our results show that the whole-brain functional connectivity can be concisely represented with highly modular, overlapping task-positive/negative pairs of sub-networks.

  16. 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 (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. Copyright © 2016 Elsevier Inc. All rights reserved.

  17. 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.

  18. Resting state functional connectivity predicts neurofeedback response

    Directory of Open Access Journals (Sweden)

    Dustin eScheinost

    2014-09-01

    Full Text Available Tailoring treatments to the specific needs and biology of individual patients – personalized medicine – requires delineation of reliable predictors of response. Unfortunately, these have been slow to emerge, especially in neuropsychiatric disorders. We have recently described a real-time functional magnetic resonance imaging (rt-fMRI neurofeedback protocol that can reduce contamination-related anxiety, a prominent symptom of many cases of obsessive-compulsive disorder (OCD. Individual response to this intervention is variable. Here we used patterns of brain functional connectivity, as measured by baseline resting-state fMRI (rs-fMRI, to predict improvements in contamination anxiety after neurofeedback training. Activity of a region of the orbitofrontal cortex (OFC and anterior prefrontal cortex, Brodmann area (BA 10, associated with contamination anxiety in each subject was measured in real time and presented as a neurofeedback signal, permitting subjects to learn to modulate this target brain region. We have previously reported both enhanced OFC/BA 10 control and improved anxiety in a group of subclinically anxious subjects after neurofeedback. Five individuals with contamination-related OCD who underwent the same protocol also showed improved clinical symptomatology. In both groups, these behavioral improvements were strongly correlated with baseline whole-brain connectivity in the OFC/BA 10, computed from rs-fMRI collected several days prior to neurofeedback training. These pilot data suggest that rs-fMRI can be used to identify individuals likely to benefit from rt-fMRI neurofeedback training to control contamination anxiety.

  19. Effects of morphine and alcohol on functional brain connectivity during "resting state": A placebo-controlled crossover study in healthy young men

    NARCIS (Netherlands)

    Khalili-Mahani, N.; Zoethout, R.M.; Beckmann, Christian; Baerends, E.J.; de Kam, M.L.; Soeter, R.P.; Dahan, A.; van Buchem, M.A.; van Gerven, J.M.; Rombouts, S.A.

    2012-01-01

    A major challenge in central nervous system (CNS) drug research is to develop a generally applicable methodology for repeated measurements of drug effects on the entire CNS, without task-related interactions and a priori models. For this reason, data-driven resting-state fMRI methods are promising

  20. Efficiency at rest: magnetoencephalographic resting-state connectivity and individual differences in verbal working memory.

    Science.gov (United States)

    del Río, David; Cuesta, Pablo; Bajo, Ricardo; García-Pacios, Javier; López-Higes, Ramón; del-Pozo, Francisco; Maestú, Fernando

    2012-11-01

    Inter-individual differences in cognitive performance are based on an efficient use of task-related brain resources. However, little is known yet on how these differences might be reflected on resting-state brain networks. Here we used Magnetoencephalography resting-state recordings to assess the relationship between a behavioral measurement of verbal working memory and functional connectivity as measured through Mutual Information. We studied theta (4-8 Hz), low alpha (8-10 Hz), high alpha (10-13 Hz), low beta (13-18 Hz) and high beta (18-30 Hz) frequency bands. A higher verbal working memory capacity was associated with a lower mutual information in the low alpha band, prominently among right-anterior and left-lateral sensors. The results suggest that an efficient brain organization in the domain of verbal working memory might be related to a lower resting-state functional connectivity across large-scale brain networks possibly involving right prefrontal and left perisylvian areas. Copyright © 2012 Elsevier B.V. All rights reserved.

  1. Different patterns of spontaneous brain activity between tremor-dominant and postural instability/gait difficulty subtypes of Parkinson's disease: a resting-state fMRI study.

    Science.gov (United States)

    Chen, Hui-Min; Wang, Zhi-Jiang; Fang, Jin-Ping; Gao, Li-Yan; Ma, Ling-Yan; Wu, Tao; Hou, Ya-Nan; Zhang, Jia-Rong; Feng, Tao

    2015-10-01

    Postural instability/gait difficulty (PIGD) and tremor-dominant (TD) subtypes of Parkinson's disease (PD) show different clinical manifestations; however, their underlying neural substrates remain incompletely understood. This study aimed at investigating the subtype-specific patterns of spontaneous brain activity in PD. Thirty-one patients with PD (12 TD/19 PIGD) and 22 healthy gender- and age-matched controls were recruited. Resting-state functional magnetic resonance imaging data were collected, and amplitude of low-frequency fluctuations (ALFF) was measured. Voxelwise one-way analysis of covariance and post hoc analyses of ALFF were performed among the three groups, with age and gender as covariates (levodopa daily dosage and gray matter volume as additional covariates for validation analysis). Correlations of clinical variables (e.g., disease duration and PIGD/tremor subscale score) with ALFF values were examined. Compared with controls, patients with TD exhibited higher ALFF in the right cerebellar posterior lobe and patients with PIGD exhibited lower ALFF in the bilateral putamen and cerebellar posterior lobe, and higher values primarily in several cortical areas including the inferior and superior temporal gyrus, superior frontal, and parietal gyrus. Compared with patients with PIGD, patients with TD had higher ALFF in the bilateral putamen and the cerebellar posterior lobe, as well as lower ALFF in the bilateral temporal gyrus and the left superior parietal lobule. In all patients, ALFF in the bilateral cerebellar posterior lobe positively correlated with tremor score and ALFF in the bilateral putamen negatively correlated with PIGD score. Different patterns of spontaneous neural activity in the cerebellum and putamen may underlie the neural substrate of PD motor subtypes. © 2015 John Wiley & Sons Ltd.

  2. 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

  3. 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)

    Ni, Ling; Qi, Rongfeng; Zhang, Long Jiang; Zhong, Jianhui; Zheng, Gang; Wu, Xingjiang; Fan, Xinxin; Lu, Guang Ming

    2014-01-01

    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. Your resting brain CAREs about your risky behavior.

    Directory of Open Access Journals (Sweden)

    Christine L Cox

    2010-08-01

    Full Text Available 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.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.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 risk seeking and risk-averse tendencies. Our results suggest that

  5. Altered resting brain function and structure in professional badminton players.

    Science.gov (United States)

    Di, Xin; Zhu, Senhua; Jin, Hua; Wang, Pin; Ye, Zhuoer; Zhou, Ke; Zhuo, Yan; Rao, Hengyi

    2012-01-01

    Neuroimaging studies of professional athletic or musical training have demonstrated considerable practice-dependent plasticity in various brain structures, which may reflect distinct training demands. In the present study, structural and functional brain alterations were examined in professional badminton players and compared with healthy controls using magnetic resonance imaging (MRI) and resting-state functional MRI. Gray matter concentration (GMC) was assessed using voxel-based morphometry (VBM), and resting-brain functions were measured by amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity. Results showed that the athlete group had greater GMC and ALFF in the right and medial cerebellar regions, respectively. The athlete group also demonstrated smaller ALFF in the left superior parietal lobule and altered functional connectivity between the left superior parietal and frontal regions. These findings indicate that badminton expertise is associated with not only plastic structural changes in terms of enlarged gray matter density in the cerebellum, but also functional alterations in fronto-parietal connectivity. Such structural and functional alterations may reflect specific experiences of badminton training and practice, including high-capacity visuo-spatial processing and hand-eye coordination in addition to refined motor skills.

  6. Rest but busy: Aberrant resting-state functional connectivity of triple network model in insomnia.

    Science.gov (United States)

    Dong, Xiaojuan; Qin, Haixia; Wu, Taoyu; Hu, Hua; Liao, Keren; Cheng, Fei; Gao, Dong; Lei, Xu

    2018-02-01

    One classical hypothesis among many models to explain the etiology and maintenance of insomnia disorder (ID) is hyperarousal. Aberrant functional connectivity among resting-state large-scale brain networks may be the underlying neurological mechanisms of this hypothesis. The aim of current study was to investigate the functional network connectivity (FNC) among large-scale brain networks in patients with insomnia disorder (ID) during resting state. In the present study, the resting-state fMRI was used to evaluate whether patients with ID showed aberrant FNC among dorsal attention network (DAN), frontoparietal control network (FPC), anterior default mode network (aDMN), and posterior default mode network (pDMN) compared with healthy good sleepers (HGSs). The Pearson's correlation analysis was employed to explore whether the abnormal FNC observed in patients with ID was associated with sleep parameters, cognitive and emotional scores, and behavioral performance assessed by questionnaires and tasks. Patients with ID had worse subjective thought control ability measured by Thought Control Ability Questionnaire (TCAQ) and more negative affect than HGSs. Intriguingly, relative to HGSs, patients with ID showed a significant increase in FNC between DAN and FPC, but a significant decrease in FNC between aDMN and pDMN. Exploratory analysis in patients with ID revealed a significantly positive correlation between the DAN-FPC FNC and reaction time (RT) of psychomotor vigilance task (PVT). The current study demonstrated that even during the resting state, the task-activated and task-deactivated large-scale brain networks in insomniacs may still maintain a hyperarousal state, looking quite similar to the pattern in a task condition with external stimuli. Those results support the hyperarousal model of insomnia.

  7. Changes in dynamic resting state network connectivity following aphasia therapy.

    Science.gov (United States)

    Duncan, E Susan; Small, Steven L

    2017-10-24

    Resting state magnetic resonance imaging (rsfMRI) permits observation of intrinsic neural networks produced by task-independent correlations in low frequency brain activity. Various resting state networks have been described, with each thought to reflect common engagement in some shared function. There has been limited investigation of the plasticity in these network relationships after stroke or induced by therapy. Twelve individuals with language disorders after stroke (aphasia) were imaged at multiple time points before (baseline) and after an imitation-based aphasia therapy. Language assessment using a narrative production task was performed at the same time points. Group independent component analysis (ICA) was performed on the rsfMRI data to identify resting state networks. A sliding window approach was then applied to assess the dynamic nature of the correlations among these networks. Network correlations during each 30-second window were used to cluster the data into ten states for each window at each time point for each subject. Correlation was performed between changes in time spent in each state and therapeutic gains on the narrative task. The amount of time spent in a single one of the (ten overall) dynamic states was positively associated with behavioral improvement on the narrative task at the 6-week post-therapy maintenance interval, when compared with either baseline or assessment immediately following therapy. This particular state was characterized by minimal correlation among the task-independent resting state networks. Increased functional independence and segregation of resting state networks underlies improvement on a narrative production task following imitation-based aphasia treatment. This has important clinical implications for the targeting of noninvasive brain stimulation in post-stroke remediation.

  8. 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 individual autonomic tone and psychological variability influence resting brain activity in brain regions, previously shown to be associated with autonomic arousal (dorsal ACC) and 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.

  9. Discovering EEG resting state alterations of semantic dementia.

    Science.gov (United States)

    Grieder, Matthias; Koenig, Thomas; Kinoshita, Toshihiko; Utsunomiya, Keita; Wahlund, Lars-Olof; Dierks, Thomas; Nishida, Keiichiro

    2016-05-01

    Diagnosis of semantic dementia relies on cost-intensive MRI or PET, although resting EEG markers of other dementias have been reported. Yet the view still holds that resting EEG in patients with semantic dementia is normal. However, studies using increasingly sophisticated EEG analysis methods have demonstrated that slightest alterations of functional brain states can be detected. We analyzed the common four resting EEG microstates (A, B, C, and D) of 8 patients with semantic dementia in comparison with 8 healthy controls and 8 patients with Alzheimer's disease. Topographical differences between the groups were found in microstate classes B and C, while microstate classes A and D were comparable. The data showed that the semantic dementia group had a peculiar microstate E, but the commonly found microstate C was lacking. Furthermore, the presence of microstate E was significantly correlated with lower MMSE and language scores. Alterations in resting EEG can be found in semantic dementia. Topographical shifts in microstate C might be related to semantic memory deficits. This is the first study that discovered resting state EEG abnormality in semantic dementia. The notion that resting EEG in this dementia subtype is normal has to be revised. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  10. Fast computation of voxel-level brain connectivity maps from resting-state functional MRI using l₁-norm as approximation of Pearson's temporal correlation: proof-of-concept and example vector hardware implementation.

    Science.gov (United States)

    Minati, Ludovico; Zacà, Domenico; D'Incerti, Ludovico; Jovicich, Jorge

    2014-09-01

    An outstanding issue in graph-based analysis of resting-state functional MRI is choice of network nodes. Individual consideration of entire brain voxels may represent a less biased approach than parcellating the cortex according to pre-determined atlases, but entails establishing connectedness for 1(9)-1(11) links, with often prohibitive computational cost. Using a representative Human Connectome Project dataset, we show that, following appropriate time-series normalization, it may be possible to accelerate connectivity determination replacing Pearson correlation with l1-norm. Even though the adjacency matrices derived from correlation coefficients and l1-norms are not identical, their similarity is high. Further, we describe and provide in full an example vector hardware implementation of l1-norm on an array of 4096 zero instruction-set processors. Calculation times correlation in very high-density resting-state functional connectivity analyses. Copyright © 2014 IPEM. Published by Elsevier Ltd. All rights reserved.

  11. The Effects of Long Duration Bed Rest on Functional Mobility and Balance: Relationship to Resting State Motor Cortex Connectivity

    Science.gov (United States)

    Erdeniz, B.; Koppelmans, V.; Bloomberg, J. J.; Kofman, I. S.; DeDios, Y. E.; Riascos-Castaneda, R. F.; Wood, S. J.; Mulavara, A. P.; Seidler, R. D.

    2014-01-01

    NASA offers researchers from a variety of backgrounds the opportunity to study bed rest as an experimental analog for space flight. Extended exposure to a head-down tilt position during long duration bed rest can resemble many of the effects of a low-gravity environment such as reduced sensory inputs, body unloading and increased cephalic fluid distribution. The aim of our study is to a) identify changes in brain function that occur with prolonged bed rest and characterize their recovery time course; b) assess whether and how these changes impact behavioral and neurocognitive performance. Thus far, we completed data collection from six participants that include task based and resting state fMRI. The data have been acquired through the bed rest facility located at the University of Texas Medical Branch (Galveston, TX). Subjects remained in bed with their heads tilted down 6 degrees below their feet for 70 consecutive days. Behavioral measures and neuroimaging assessments were obtained at seven time points: a) 7 and 12 days before bed rest; b) 7, 30, and 65 days during bed rest; and c) 7 and 12 days after bed rest. Functional connectivity magnetic resonance imaging (FcMRI) analysis was performed to assess the connectivity of motor cortex in and out of bed rest. We found a decrease in motor cortex connectivity with vestibular cortex and the cerebellum from pre bed rest to in bed rest. We also used a battery of behavioral measures including the functional mobility test and computerized dynamic posturography collected before and after bed rest. We will report the preliminary results of analyses relating brain and behavior changes. Furthermore, we will also report the preliminary results of a spatial working memory task and vestibular stimulation during in and out of bed rest.

  12. Memory Processing: Ripples in the Resting Brain.

    Science.gov (United States)

    Walker, Matthew P; Robertson, Edwin M

    2016-03-21

    Recent work has shown that, during sleep, a functional circuit is created amidst a general breakdown in connectivity following fast-frequency bursts of brain activity. The findings question the unconscious nature of deep sleep, and provide an explanation for its contribution to memory processing. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. 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. Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.

  14. Alterations in brain metabolism and function following administration of low-dose codeine phosphate: 1H-magnetic resonance spectroscopy and resting-state functional magnetic resonance imaging studies

    OpenAIRE

    Cao, Zhen; Lin, Pei-Yin; Shen, Zhi-Wei; Wu, Ren-Hua; Xiao, Ye-Yu

    2016-01-01

    The aim of the present study was to identify alterations in brain function following administration of a single, low-dose of codeine phosphate in healthy volunteers using resting-state functional magnetic resonance imaging (fMRI). In addition, the metabolic changes in the two sides of the frontal lobe were identified using 1H-magnetic resonance spectroscopy (1H-MRS). A total of 20 right-handed healthy participants (10 males, 10 females) were evaluated, and a Signa HDx 1.5T MRI scanner was use...

  15. Neuroaging through the Lens of the Resting State Networks

    Directory of Open Access Journals (Sweden)

    Filippo Cieri

    2018-01-01

    Full Text Available Resting state functional magnetic resonance imaging (rs-fMRI allows studying spontaneous brain activity in absence of task, recording changes of Blood Oxygenation Level Dependent (BOLD signal. rs-fMRI enables identification of brain networks also called Resting State Networks (RSNs including the most studied Default Mode Network (DMN. The simplicity and speed of execution make rs-fMRI applicable in a variety of normal and pathological conditions. Since it does not require any task, rs-fMRI is particularly useful for protocols on patients, children, and elders, increasing participant’s compliance and reducing intersubjective variability due to the task performance. rs-fMRI has shown high sensitivity in identification of RSNs modifications in several diseases also in absence of structural modifications. In this narrative review, we provide the state of the art of rs-fMRI studies about physiological and pathological aging processes. First, we introduce the background of resting state; then we review clinical findings provided by rs-fMRI in physiological aging, Mild Cognitive Impairment (MCI, Alzheimer Dementia (AD, and Late Life Depression (LLD. Finally, we suggest future directions in this field of research and its potential clinical applications.

  16. 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.…

  17. From "rest" to language task: Task activation selects and prunes from broader resting-state network.

    Science.gov (United States)

    Doucet, Gaelle E; He, Xiaosong; Sperling, Michael R; Sharan, Ashwini; Tracy, Joseph I

    2017-05-01

    Resting-state networks (RSNs) show spatial patterns generally consistent with networks revealed during cognitive tasks. However, the exact degree of overlap between these networks has not been clearly quantified. Such an investigation shows promise for decoding altered functional connectivity (FC) related to abnormal language functioning in clinical populations such as temporal lobe epilepsy (TLE). In this context, we investigated the network configurations during a language task and during resting state using FC. Twenty-four healthy controls, 24 right and 24 left TLE patients completed a verb generation (VG) task and a resting-state fMRI scan. We compared the language network revealed by the VG task with three FC-based networks (seeding the left inferior frontal cortex (IFC)/Broca): two from the task (ON, OFF blocks) and one from the resting state. We found that, for both left TLE patients and controls, the RSN recruited regions bilaterally, whereas both VG-on and VG-off conditions produced more left-lateralized FC networks, matching more closely with the activated language network. TLE brings with it variability in both task-dependent and task-independent networks, reflective of atypical language organization. Overall, our findings suggest that our RSN captured bilateral activity, reflecting a set of prepotent language regions. We propose that this relationship can be best understood by the notion of pruning or winnowing down of the larger language-ready RSN to carry out specific task demands. Our data suggest that multiple types of network analyses may be needed to decode the association between language deficits and the underlying functional mechanisms altered by disease. Hum Brain Mapp 38:2540-2552, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  18. "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

    NARCIS (Netherlands)

    Verbeke, W.J.M.I.; Pozharliev, R.; van Strien, J.W.; Belschak, F.; Bagozzi, R.P.

    2014-01-01

    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

  19. Patterns of resting state connectivity in human primary visual cortical areas: a 7T fMRI study

    NARCIS (Netherlands)

    Raemaekers, Mathijs; Schellekens, Wouter; van Wezel, Richard Jack Anton; Petridou, Natalia; Kristo, Gert; Ramsey, Nick F.

    2014-01-01

    The nature and origin of fMRI resting state fluctuations and connectivity are still not fully known. More detailed knowledge on the relationship between resting state patterns and brain function may help to elucidate this matter. We therefore performed an in depth study of how resting state

  20. Cognition Is Related to Resting-State Small-World Network Topology: An Magnetoencephalographic Study

    NARCIS (Netherlands)

    Douw, L.; Schoonheim, M.M.; Landi, D.; van der Meer, M.L.; Geurts, J.J.G.; Reijneveld, J.C.; Klein, M.; Stam, C.J.

    2011-01-01

    Brain networks and cognition have recently begun to attract attention: studies suggest that more efficiently wired resting-state brain networks are indeed correlated with better cognitive performance. "Small-world" brain networks combine local segregation with global integration, hereby subserving

  1. 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...... of resting state as functional coherent groups we search for functional units of the brain that communicate with other parts of the brain in a coherent manner as measured by mutual information. We use the infinite relational model (IRM) to quantify functional coherent groups of resting state networks...

  2. Value of Frequency Domain Resting-State Functional Magnetic Resonance Imaging Metrics Amplitude of Low-Frequency Fluctuation and Fractional Amplitude of Low-Frequency Fluctuation in the Assessment of Brain Tumor-Induced Neurovascular Uncoupling.

    Science.gov (United States)

    Agarwal, Shruti; Lu, Hanzhang; Pillai, Jay J

    2017-08-01

    The aim of this study was to explore whether the phenomenon of brain tumor-related neurovascular uncoupling (NVU) in resting-state blood oxygen level-dependent functional magnetic resonance imaging (BOLD fMRI) (rsfMRI) may also affect the resting-state fMRI (rsfMRI) frequency domain metrics the amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF). Twelve de novo brain tumor patients, who underwent clinical fMRI examinations, including task-based fMRI (tbfMRI) and rsfMRI, were included in this Institutional Review Board-approved study. Each patient displayed decreased/absent tbfMRI activation in the primary ipsilesional (IL) sensorimotor cortex in the absence of a corresponding motor deficit or suboptimal task performance, consistent with NVU. Z-score maps for the motor tasks were obtained from general linear model analysis (reflecting motor activation vs. rest). Seed-based correlation analysis (SCA) maps of sensorimotor network, ALFF, and fALFF were calculated from rsfMRI data. Precentral and postcentral gyri in contralesional (CL) and IL hemispheres were parcellated using an automated anatomical labeling template for each patient. Region of interest (ROI) analysis was performed on four maps: tbfMRI, SCA, ALFF, and fALFF. Voxel values in the CL and IL ROIs of each map were divided by the corresponding global mean of ALFF and fALFF in the cortical brain tissue. Group analysis revealed significantly decreased IL ALFF (p = 0.02) and fALFF (p = 0.03) metrics compared with CL ROIs, consistent with similar findings of significantly decreased IL BOLD signal for tbfMRI (p = 0.0005) and SCA maps (p = 0.0004). The frequency domain metrics ALFF and fALFF may be markers of lesion-induced NVU in rsfMRI similar to previously reported alterations in tbfMRI activation and SCA-derived resting-state functional connectivity maps.

  3. Short-term effects of escitalopram on regional brain function in first-episode drug-naive patients with major depressive disorder assessed by resting-state functional magnetic resonance imaging.

    Science.gov (United States)

    Wang, L; Li, K; Zhang, Q; Zeng, Y; Dai, W; Su, Y; Wang, G; Tan, Y; Jin, Z; Yu, X; Si, T

    2014-05-01

    Most knowledge regarding the effects of antidepressant drugs is at the receptor level, distal from the nervous system effects that mediate their clinical efficacy. Using functional magnetic resonance imaging (fMRI), this study investigated the effects of escitalopram, a selective serotonin reuptake inhibitor (SSRI), on resting-state brain function in patients with major depressive disorder (MDD). Fourteen first-episode drug-naive MDD patients completed two fMRI scans before and after 8 weeks of escitalopram therapy. Scans were also acquired in 14 matched healthy subjects. Data were analyzed using the regional homogeneity (ReHo) approach. Compared to controls, MDD patients before treatment demonstrated decreased ReHo in the frontal (right superior frontal gyrus), temporal (left middle and right inferior temporal gyri), parietal (right precuneus) and occipital (left superior occipital gyrus and right cuneus) cortices, and increased ReHo in the left dorsal medial prefrontal gyrus and left anterior lobe of the cerebellum. Compared to the unmedicated state, ReHo in the patients after treatment was decreased in the left dorsal medial prefrontal gyrus, the right insula and the bilateral thalamus, and increased in the right superior frontal gyrus. Compared to controls, patients after treatment displayed a ReHo decrease in the right precuneus and a ReHo increase in the left anterior lobe of the cerebellum. Successful treatment with escitalopram may be associated with modulation of resting-state brain activity in regions within the fronto-limbic circuit. This study provides new insight into the effects of antidepressants on functional brain systems in MDD.

  4. Alterations in Resting-State Activity Relate to Performance in a Verbal Recognition Task

    Science.gov (United States)

    López Zunini, Rocío A.; Thivierge, Jean-Philippe; Kousaie, Shanna; Sheppard, Christine; Taler, Vanessa

    2013-01-01

    In the brain, resting-state activity refers to non-random patterns of intrinsic activity occurring when participants are not actively engaged in a task. We monitored resting-state activity using electroencephalogram (EEG) both before and after a verbal recognition task. We show a strong positive correlation between accuracy in verbal recognition and pre-task resting-state alpha power at posterior sites. We further characterized this effect by examining resting-state post-task activity. We found marked alterations in resting-state alpha power when comparing pre- and post-task periods, with more pronounced alterations in participants that attained higher task accuracy. These findings support a dynamical view of cognitive processes where patterns of ongoing brain activity can facilitate –or interfere– with optimal task performance. PMID:23785436

  5. 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

  6. Habenula functional resting-state connectivity in pediatric CRPS.

    Science.gov (United States)

    Erpelding, Nathalie; Sava, Simona; Simons, Laura E; Lebel, Alyssa; Serrano, Paul; Becerra, Lino; Borsook, David

    2014-01-01

    The habenula (Hb) is a small brain structure located in the posterior end of the medial dorsal thalamus and through medial (MHb) and lateral (LHb) Hb connections, it acts as a conduit of information between forebrain and brainstem structures. The role of the Hb in pain processing is well documented in animals and recently also in acute experimental pain in humans. However, its function remains unknown in chronic pain disorders. Here, we investigated Hb resting-state functional connectivity (rsFC) in patients with complex regional pain syndrome (CRPS) compared with healthy controls. Twelve pediatric patients with unilateral lower-extremity CRPS (9 females; 10-17 yr) and 12 age- and sex-matched healthy controls provided informed consent to participate in the study. In healthy controls, Hb functional connections largely overlapped with previously described anatomical connections in cortical, subcortical, and brainstem structures. Compared with controls, patients exhibited an overall Hb rsFC reduction with the rest of the brain and, specifically, with the anterior midcingulate cortex, dorsolateral prefrontal cortex, supplementary motor cortex, primary motor cortex, and premotor cortex. Our results suggest that Hb rsFC parallels anatomical Hb connections in the healthy state and that overall Hb rsFC is reduced in patients, particularly connections with forebrain areas. Patients' decreased Hb rsFC to brain regions implicated in motor, affective, cognitive, and pain inhibitory/modulatory processes may contribute to their symptomatology.

  7. Resting brain activity varies with dream recall frequency between subjects.

    Science.gov (United States)

    Eichenlaub, Jean-Baptiste; Nicolas, Alain; Daltrozzo, Jérôme; Redouté, Jérôme; Costes, Nicolas; Ruby, Perrine

    2014-06-01

    Dreaming is still poorly understood. Notably, its cerebral underpinning remains unclear. Neuropsychological studies have shown that lesions in the temporoparietal junction (TPJ) and/or the white matter of the medial prefrontal cortex (MPFC) lead to the global cessation of dream reports, suggesting that these regions of the default mode network have key roles in the dreaming process (forebrain 'dream-on' hypothesis). To test this hypothesis, we measured regional cerebral blood flow (rCBF) using [(15)O]H2O positron emission tomography in healthy subjects with high and low dream recall frequencies (DRFs) during wakefulness (rest) and sleep (rapid eye movement (REM) sleep, N2, and N3). Compared with Low recallers (0.5 ± 0.3 dream recall per week in average), High recallers (5.2 ± 1.4) showed higher rCBF in the TPJ during REM sleep, N3, and wakefulness, and in the MPFC during REM sleep and wakefulness. We demonstrate that the resting states of High recallers and Low recallers differ during sleep and wakefulness. It coheres with previous ERP results and confirms that a high/low DRF is associated with a specific functional organization of the brain. These results support the forebrain 'dream-on' hypothesis and suggest that TPJ and MPFC are not only involved in dream recall during wakefulness but also have a role in dreaming during sleep (production and/or encoding). Increased activity in the TPJ and MPFC might promote the mental imagery and/or memory encoding of dreams. Notably, increased activity in TPJ might facilitate attention orienting toward external stimuli and promote intrasleep wakefulness, facilitating the encoding of the dreams in memory.

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

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    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.

  9. 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. Copyright © 2013 Elsevier B.V. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    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

  11. 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.

  12. Long-chain n-3 PUFAs from fish oil enhance resting state brain glucose utilization and reduce anxiety in an adult nonhuman primate, the grey mouse lemur.

    Science.gov (United States)

    Pifferi, Fabien; Dorieux, Olène; Castellano, Christian-Alexandre; Croteau, Etienne; Masson, Marie; Guillermier, Martine; Van Camp, Nadja; Guesnet, Philippe; Alessandri, Jean-Marc; Cunnane, Stephen; Dhenain, Marc; Aujard, Fabienne

    2015-08-01

    Decreased brain content of DHA, the most abundant long-chain n-3 polyunsaturated fatty acid (n-3 LCPUFA) in the brain, is accompanied by severe neurosensorial impairments linked to impaired neurotransmission and impaired brain glucose utilization. In the present study, we hypothesized that increasing n-3 LCPUFA intake at an early age may help to prevent or correct the glucose hypometabolism observed during aging and age-related cognitive decline. The effects of 12 months' supplementation with n-3 LCPUFA on brain glucose utilization assessed by positron emission tomography was tested in young adult mouse lemurs (Microcebus murinus). Cognitive function was tested in parallel in the same animals. Lemurs supplemented with n-3 LCPUFA had higher brain glucose uptake and cerebral metabolic rate of glucose compared with controls in all brain regions. The n-3 LCPUFA-supplemented animals also had higher exploratory activity in an open-field task and lower evidence of anxiety in the Barnes maze. Our results demonstrate for the first time in a nonhuman primate that n-3 LCPUFA supplementation increases brain glucose uptake and metabolism and concomitantly reduces anxiety. Copyright © 2015 by the American Society for Biochemistry and Molecular Biology, Inc.

  13. 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.; hide

    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

  14. Altered amygdalar resting-state connectivity in depression is explained by both genes and environment.

    Science.gov (United States)

    Córdova-Palomera, Aldo; Tornador, Cristian; Falcón, Carles; Bargalló, Nuria; Nenadic, Igor; Deco, Gustavo; Fañanás, Lourdes

    2015-10-01

    Recent findings indicate that alterations of the amygdalar resting-state fMRI connectivity play an important role in the etiology of depression. While both depression and resting-state brain activity are shaped by genes and environment, the relative contribution of genetic and environmental factors mediating the relationship between amygdalar resting-state connectivity and depression remain largely unexplored. Likewise, novel neuroimaging research indicates that different mathematical representations of resting-state fMRI activity patterns are able to embed distinct information relevant to brain health and disease. The present study analyzed the influence of genes and environment on amygdalar resting-state fMRI connectivity, in relation to depression risk. High-resolution resting-state fMRI scans were analyzed to estimate functional connectivity patterns in a sample of 48 twins (24 monozygotic pairs) informative for depressive psychopathology (6 concordant, 8 discordant and 10 healthy control pairs). A graph-theoretical framework was employed to construct brain networks using two methods: (i) the conventional approach of filtered BOLD fMRI time-series and (ii) analytic components of this fMRI activity. Results using both methods indicate that depression risk is increased by environmental factors altering amygdalar connectivity. When analyzing the analytic components of the BOLD fMRI time-series, genetic factors altering the amygdala neural activity at rest show an important contribution to depression risk. Overall, these findings show that both genes and environment modify different patterns the amygdala resting-state connectivity to increase depression risk. The genetic relationship between amygdalar connectivity and depression may be better elicited by examining analytic components of the brain resting-state BOLD fMRI signals. © 2015 Wiley Periodicals, Inc.

  15. A resting state functional magnetic resonance imaging study of concussion in collegiate athletes.

    Science.gov (United States)

    Czerniak, Suzanne M; Sikoglu, Elif M; Liso Navarro, Ana A; McCafferty, Joseph; Eisenstock, Jordan; Stevenson, J Herbert; King, Jean A; Moore, Constance M

    2015-06-01

    Sports-related concussions are currently diagnosed through multi-domain assessment by a medical professional and may utilize neurocognitive testing as an aid. However, these tests have only been able to detect differences in the days to week post-concussion. Here, we investigate a measure of brain function, namely resting state functional connectivity, which may detect residual brain differences in the weeks to months after concussion. Twenty-one student athletes (9 concussed within 6 months of enrollment; 12 non-concussed; between ages 18 and 22 years) were recruited for this study. All participants completed the Wisconsin Card Sorting Task and the Color-Word Interference Test. Neuroimaging data, specifically resting state functional Magnetic Resonance Imaging data, were acquired to examine resting state functional connectivity. Two sample t-tests were used to compare the neurocognitive scores and resting state functional connectivity patterns among concussed and non-concussed participants. Correlations between neurocognitive scores and resting state functional connectivity measures were also determined across all subjects. There were no significant differences in neurocognitive performance between concussed and non-concussed groups. Concussed subjects had significantly increased connections between areas of the brain that underlie executive function. Across all subjects, better neurocognitive performance corresponded to stronger brain connectivity. Even at rest, brains of concussed athletes may have to 'work harder' than their healthy peers to achieve similar neurocognitive results. Resting state brain connectivity may be able to detect prolonged brain differences in concussed athletes in a more quantitative manner than neurocognitive test scores.

  16. 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. Copyright © 2015 Elsevier B.V. All rights reserved.

  17. Rapid whole-brain resting-state fMRI at 3 T: Efficiency-optimized three-dimensional EPI versus repetition time-matched simultaneous-multi-slice EPI.

    Science.gov (United States)

    Stirnberg, Rüdiger; Huijbers, Willem; Brenner, Daniel; Poser, Benedikt A; Breteler, Monique; Stöcker, Tony

    2017-12-01

    State-of-the-art simultaneous-multi-slice (SMS-)EPI and 3D-EPI share several properties that benefit functional MRI acquisition. Both sequences employ equivalent parallel imaging undersampling with controlled aliasing to achieve high temporal sampling rates. As a volumetric imaging sequence, 3D-EPI offers additional means of acceleration complementary to 2D-CAIPIRINHA sampling, such as fast water excitation and elliptical sampling. We performed an application-oriented comparison between a tailored, six-fold CAIPIRINHA-accelerated 3D-EPI protocol at 530 ms temporal and 2.4 mm isotropic spatial resolution and an SMS-EPI protocol with identical spatial and temporal resolution for whole-brain resting-state fMRI at 3 T. The latter required eight-fold slice acceleration to compensate for the lack of elliptical sampling and fast water excitation. Both sequences used vendor-supplied on-line image reconstruction. We acquired test/retest resting-state fMRI scans in ten volunteers, with simultaneous acquisition of cardiac and respiration data, subsequently used for optional physiological noise removal (nuisance regression). We found that the 3D-EPI protocol has significantly increased temporal signal-to-noise ratio throughout the brain as compared to the SMS-EPI protocol, especially when employing motion and nuisance regression. Both sequence types reliably identified known functional networks with stronger functional connectivity values for the 3D-EPI protocol. We conclude that the more time-efficient 3D-EPI primarily benefits from reduced parallel imaging noise due to a higher, actual k-space sampling density compared to SMS-EPI. The resultant BOLD sensitivity increase makes 3D-EPI a valuable alternative to SMS-EPI for whole-brain fMRI at 3 T, with voxel sizes well below 3 mm isotropic and sampling rates high enough to separate dominant cardiac signals from BOLD signals in the frequency domain. Copyright © 2017 Elsevier Inc. All rights reserved.

  18. Gender Differences in Regional Brain Activity in Patients with Chronic Primary Insomnia: Evidence from a Resting-State fMRI Study.

    Science.gov (United States)

    Dai, Xi-Jian; Nie, Xiao; Liu, Xuming; Pei, Li; Jiang, Jian; Peng, De-chang; Gong, Hong-Han; Zeng, Xian-Jun; Wáng, Yì-Xiáng J; Zhan, Yang

    2016-03-01

    To explore the regional brain activities in patients with chronic primary insomnia (PCPIs) and their sex differences. Forty-two PCPIs (27 females, 15 males) and 42 good sleepers (GSs; 24 females, 18 males) were recruited. Six PCPIs (3 males, 3 females) were scanned twice by MRI to examine the test-retest reliability. Amplitude of low frequency fluctuation (ALFF) method was used to assess the local brain features. The mean signal values of the different ALFF areas were analyzed with a receiver operating characteristic (ROC) curve. Simple linear regression analysis was performed to investigate the relationships between clinical features and different brain areas. Both female and male PCPIs showed higher ALFF in the temporal lobe and occipital lobe, especially in female PCPIs. Female PCPIs had lower ALFF in the bilateral cerebellum posterior lobe, left dorsolateral prefrontal cortex, and bilateral limbic lobe; however, male PCPIs showed lower ALFF in the left occipital gyrus. The mean signal value of the cerebellum in female PCPIs showed negative correlations with negative emotions. Compared with male PCPIs, female PCPIs showed higher ALFF in the bilateral middle temporal gyrus and lower ALFF in the left limbic lobe. The different areas showed high test-retest stability (Clusters of contiguous volumes ≥ 1080 mm(3) with an intraclass correlation coefficient ≥ 0.80) and high degree of sensitivity and specificity. Female PCPIs showed more regional brain differences with higher and lower ALFF responses than male PCPIs. However, they shared analogous excessive hyperarousal mechanism and wide variations in aberrant brain areas. © 2016 American Academy of Sleep Medicine.

  19. Comparison of continuously acquired resting state and extracted analogues from active tasks.

    Science.gov (United States)

    Ganger, Sebastian; Hahn, Andreas; Küblböck, Martin; Kranz, Georg S; Spies, Marie; Vanicek, Thomas; Seiger, René; Sladky, Ronald; Windischberger, Christian; Kasper, Siegfried; Lanzenberger, Rupert

    2015-10-01

    Functional connectivity analysis of brain networks has become an important tool for investigation of human brain function. Although functional connectivity computations are usually based on resting-state data, the application to task-specific fMRI has received growing attention. Three major methods for extraction of resting-state data from task-related signal have been proposed (1) usage of unmanipulated task data for functional connectivity; (2) regression against task effects, subsequently using the residuals; and (3) concatenation of baseline blocks located in-between task blocks. Despite widespread application in current research, consensus on which method best resembles resting-state seems to be missing. We, therefore, evaluated these techniques in a sample of 26 healthy controls measured at 7 Tesla. In addition to continuous resting-state, two different task paradigms were assessed (emotion discrimination and right finger-tapping) and five well-described networks were analyzed (default mode, thalamus, cuneus, sensorimotor, and auditory). Investigating the similarity to continuous resting-state (Dice, Intraclass correlation coefficient (ICC), R(2) ) showed that regression against task effects yields functional connectivity networks most alike to resting-state. However, all methods exhibited significant differences when compared to continuous resting-state and similarity metrics were lower than test-retest of two resting-state scans. Omitting global signal regression did not change these findings. Visually, the networks are highly similar, but through further investigation marked differences can be found. Therefore, our data does not support referring to resting-state when extracting signals from task designs, although functional connectivity computed from task-specific data may indeed yield interesting information. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

  20. Morphological brain plasticity induced by musical expertise is accompanied by modulation of functional connectivity at rest.

    Science.gov (United States)

    Fauvel, Baptiste; Groussard, Mathilde; Chételat, Gaël; Fouquet, Marine; Landeau, Brigitte; Eustache, Francis; Desgranges, Béatrice; Platel, Hervé

    2014-04-15

    The aim of this study was to explore whether musical practice-related gray matter increases in brain regions are accompanied by modifications in their resting-state functional connectivity. 16 young musically experienced adults and 17 matched nonmusicians underwent an anatomical magnetic resonance imaging (MRI) and a resting-state functional MRI (rsfMRI). A whole-brain two-sample t test run on the T1-weighted structural images revealed four clusters exhibiting significant increases in gray matter (GM) volume in the musician group, located within the right posterior and middle cingulate gyrus, left superior temporal gyrus and right inferior orbitofrontal gyrus. Each cluster was used as a seed region to generate and compare whole-brain resting-state functional connectivity maps. The two clusters within the cingulate gyrus exhibited greater connectivity for musicians with the right prefrontal cortex and left temporal pole, which play a role in autobiographical and semantic memory, respectively. The cluster in the left superior temporal gyrus displayed enhanced connectivity with several language-related areas (e.g., left premotor cortex, bilateral supramarginal gyri). Finally, the cluster in the right inferior frontal gyrus displayed more synchronous activity at rest with claustrum, areas thought to play a role in binding sensory and motor information. We interpreted these findings as the consequence of repeated collaborative use in general networks supporting some of the memory, perceptual-motor and emotional features of musical practice. Copyright © 2014 Elsevier Inc. All rights reserved.

  1. The brain’s resting state activity is shaped by synchronized cross frequency coupling of neural oscillations (Author’s Manuscript)

    Science.gov (United States)

    2015-02-11

    subject so that their influence should be negligible . Fifth, time-frequency representations of ā(k, n, f) were averaged across all k epochs as shown in...reports obtained with invasive recording techniques and restricted to a limited number of brain regions (Canolty et al., 2006; Tort et al., 2008, 2009...al., 2006; Steriade et al., 1996). Related to this edges in the data lead to artificial PAC (Kramer, Tort , and Kopell, 2008). Still PAC has been found

  2. 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

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

    OpenAIRE

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

    2014-01-01

    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 tha...

  4. Selective vulnerability related to aging in large-scale resting brain networks.

    Science.gov (United States)

    Zhang, Hong-Ying; Chen, Wen-Xin; Jiao, Yun; Xu, Yao; Zhang, Xiang-Rong; Wu, Jing-Tao

    2014-01-01

    Normal aging is associated with cognitive decline. Evidence indicates that large-scale brain networks are affected by aging; however, it has not been established whether aging has equivalent effects on specific large-scale networks. In the present study, 40 healthy subjects including 22 older (aged 60-80 years) and 18 younger (aged 22-33 years) adults underwent resting-state functional MRI scanning. Four canonical resting-state networks, including the default mode network (DMN), executive control network (ECN), dorsal attention network (DAN) and salience network, were extracted, and the functional connectivities in these canonical networks were compared between the younger and older groups. We found distinct, disruptive alterations present in the large-scale aging-related resting brain networks: the ECN was affected the most, followed by the DAN. However, the DMN and salience networks showed limited functional connectivity disruption. The visual network served as a control and was similarly preserved in both groups. Our findings suggest that the aged brain is characterized by selective vulnerability in large-scale brain networks. These results could help improve our understanding of the mechanism of degeneration in the aging brain. Additional work is warranted to determine whether selective alterations in the intrinsic networks are related to impairments in behavioral performance.

  5. Role of Spontaneous Brain Activity in Explicit and Implicit Aspects of Cognitive Flexibility under Socially Conflicting Situations: A Resting-state fMRI Study using Fractional Amplitude of Low-frequency Fluctuations.

    Science.gov (United States)

    Fujino, Junya; Tei, Shisei; Jankowski, Kathryn F; Kawada, Ryosaku; Murai, Toshiya; Takahashi, Hidehiko

    2017-12-26

    We are constantly exposed to socially conflicting situations in everyday life, and cognitive flexibility is essential for adaptively coping with such difficulties. Flexible goal choice and pursuit are not exclusively conscious, and therefore cognitive flexibility involves both explicit and implicit forms of processing. However, it is unclear how individual differences in explicit and implicit aspects of flexibility are associated with neural activity in a resting state. Here, we measured intrinsic fractional amplitude of low-frequency fluctuations (fALFF) by resting-state functional magnetic resonance imaging (RS-fMRI) as an indicator of regional brain spontaneous activity, together with explicit and implicit aspects of cognitive flexibility using the Cognitive Flexibility Scale (CFS) and Implicit Association Test (IAT). Consistent with the dual processing theory, there was a strong association between explicit aspects of flexibility (CFS score) and "rationalism" thinking style and between implicit aspects (IAT effect) and "experientialism." The level of explicit flexibility was also correlated with fALFF values in the left lateral prefrontal cortex, whereas the level of implicit flexibility was correlated with fALFF values in the right cerebellum. Furthermore, the fALFF values in both regions predicted individual preference for flexible decision-making strategy in a vignettes simulation task. These results add to our understanding of the neural mechanisms underlying flexible decision-making for solving social conflicts. More generally, our findings highlight the utility of RS-fMRI combined with both explicit and implicit psychometric measures for better understanding individual differences in social cognition. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  6. 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.

  7. Altered Brain Functional Activity in Infants with Congenital Bilateral Severe Sensorineural Hearing Loss: A Resting-State Functional MRI Study under Sedation

    Directory of Open Access Journals (Sweden)

    Shuang Xia

    2017-01-01

    Full Text Available Early hearing deprivation could affect the development of auditory, language, and vision ability. Insufficient or no stimulation of the auditory cortex during the sensitive periods of plasticity could affect the function of hearing, language, and vision development. Twenty-three infants with congenital severe sensorineural hearing loss (CSSHL and 17 age and sex matched normal hearing subjects were recruited. The amplitude of low frequency fluctuations (ALFF and regional homogeneity (ReHo of the auditory, language, and vision related brain areas were compared between deaf infants and normal subjects. Compared with normal hearing subjects, decreased ALFF and ReHo were observed in auditory and language-related cortex. Increased ALFF and ReHo were observed in vision related cortex, which suggest that hearing and language function were impaired and vision function was enhanced due to the loss of hearing. ALFF of left Brodmann area 45 (BA45 was negatively correlated with deaf duration in infants with CSSHL. ALFF of right BA39 was positively correlated with deaf duration in infants with CSSHL. In conclusion, ALFF and ReHo can reflect the abnormal brain function in language, auditory, and visual information processing in infants with CSSHL. This demonstrates that the development of auditory, language, and vision processing function has been affected by congenital severe sensorineural hearing loss before 4 years of age.

  8. Resting-state functional connectivity differences in premature children

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    Eswar Damaraju

    2010-06-01

    Full Text Available We examine the coherence in the spontaneous brain activity of sleeping children as measured by the blood oxygenation level dependent (BOLD functional magnetic resonance imaging (fMRI signals. The results are described in terms of resting-state networks (RSN and their properties. More specifically, in this study we examine the effect of severe prematurity on the spatial location of the visual, temporal, motor, basal ganglia, and the default mode networks, the temporal response properties of each of these networks, and the functional connectivity between them. Our results suggest that the anatomical locations of the RSNs are well developed by 18 months of age and their spatial locations are not distinguishable between premature and term born infants at 18 months or at 36 months, with the exception of small spatial differences noted in the basal ganglia area and the visual cortex. The two major differences between term and preterm children were present at 36 but not 18 months and include: 1 increased spectral energy in the low frequency range (0.01 – 0.06 Hz for pre-term children in the basal ganglia component, and 2 stronger connectivity between RSNs in term children. We speculate that children born very prematurely are vulnerable to injury resulting in weaker connectivity between resting state networks by 36 months of age. Further work is required to determine whether this could be a clinically useful tool to identify children at risk of developmental delay related to premature birth.

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

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    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.

  10. Resting State Functional Connectivity in Early Blind Humans

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    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.

  11. 孤独障碍儿童静息状态脑功能磁共振研究%A resting-state functional magnetic resonance imaging study of brain activity in children with autism

    Institute of Scientific and Technical Information of China (English)

    李雪; 刘靖; 杨文; 张晓丽; 贾美香

    2013-01-01

    目的 探讨孤独障碍儿童静息状态脑功能特点.方法 选取符合《美国精神障碍诊断与统计手册(第4版)》(DSM-Ⅳ)孤独障碍诊断标准、《孤独症诊断访谈量表(修订版)》(ADI-R)评分超过孤独障碍诊断界限分及《韦氏儿童智力量表》测查总智商≥70分的孤独障碍患儿(儿童孤独障碍组)16例,同时选取性别、年龄相匹配的正常对照(对照组)16名,分别进行静息状态全脑的核磁共振脑功能扫描.采用局部一致性(ReHo)作为测量指标,比较儿童孤独障碍组与对照组之间静息态脑功能的差异.结果 在静息状态下,与对照组相比,孤独障碍组右侧颞上回、额下回、岛叶、前扣带回、小脑后叶,左侧楔前叶,双侧颞中回ReHo减弱(=3.92,5.29,2.85,2.97,4.05,4.10,3.23,2.18;P均<0.05);左侧额上回及右侧中央旁小叶、扣带回和楔叶,双侧额中回和中央后回ReHo增强(t=2.82,2.82,1.76,2.49,4.70,3.15,5.00,2.41;P均<0.05).结论 孤独障碍患儿在静息状态下存在多个脑区功能的异常.%Objective To study the differences of brain function between autistic children and normal controls by resting-state functional magnetic resonance imaging (fMRI).Methods Sixteen children meeting the Diagnostic and Statistical Manual of Mental Disorders,Fourth Edition (DSM-Ⅳ) criteria for autism and Autism Diagnostic Interview-Revised (ADI-R)and sixteen healthy subjects matched on age and gender were enrolled and examined with fMRI in resting state.Regional homogeneity (ReHo) approach was used to analyze blood oxygen level-dependent fMRI (BOLD-fMRI) data.Results The functions of brain regions showed significant differences between two groups.Compared with the normal controls,autistic children showed significantly decreased ReHo in right superior temporal gyrus,right inferior frontal gyrus,right insula,right anterior cingulate,right cerebellum posterior lobe,left precuneus,bilateral middle temporal gyrus (t =3.92,5

  12. Resting state networks' corticotopy: the dual intertwined rings architecture.

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    Salma Mesmoudi

    Full Text Available How does the brain integrate multiple sources of information to support normal sensorimotor and cognitive functions? To investigate this question we present an overall brain architecture (called "the dual intertwined rings architecture" that relates the functional specialization of cortical networks to their spatial distribution over the cerebral cortex (or "corticotopy". Recent results suggest that the resting state networks (RSNs are organized into two large families: 1 a sensorimotor family that includes visual, somatic, and auditory areas and 2 a large association family that comprises parietal, temporal, and frontal regions and also includes the default mode network. We used two large databases of resting state fMRI data, from which we extracted 32 robust RSNs. We estimated: (1 the RSN functional roles by using a projection of the results on task based networks (TBNs as referenced in large databases of fMRI activation studies; and (2 relationship of the RSNs with the Brodmann Areas. In both classifications, the 32 RSNs are organized into a remarkable architecture of two intertwined rings per hemisphere and so four rings linked by homotopic connections. The first ring forms a continuous ensemble and includes visual, somatic, and auditory cortices, with interspersed bimodal cortices (auditory-visual, visual-somatic and auditory-somatic, abbreviated as VSA ring. The second ring integrates distant parietal, temporal and frontal regions (PTF ring through a network of association fiber tracts which closes the ring anatomically and ensures a functional continuity within the ring. The PTF ring relates association cortices specialized in attention, language and working memory, to the networks involved in motivation and biological regulation and rhythms. This "dual intertwined architecture" suggests a dual integrative process: the VSA ring performs fast real-time multimodal integration of sensorimotor information whereas the PTF ring performs multi

  13. Resting State Networks' Corticotopy: The Dual Intertwined Rings Architecture

    Science.gov (United States)

    Mesmoudi, Salma; Perlbarg, Vincent; Rudrauf, David; Messe, Arnaud; Pinsard, Basile; Hasboun, Dominique; Cioli, Claudia; Marrelec, Guillaume; Toro, Roberto; Benali, Habib; Burnod, Yves

    2013-01-01

    How does the brain integrate multiple sources of information to support normal sensorimotor and cognitive functions? To investigate this question we present an overall brain architecture (called “the dual intertwined rings architecture”) that relates the functional specialization of cortical networks to their spatial distribution over the cerebral cortex (or “corticotopy”). Recent results suggest that the resting state networks (RSNs) are organized into two large families: 1) a sensorimotor family that includes visual, somatic, and auditory areas and 2) a large association family that comprises parietal, temporal, and frontal regions and also includes the default mode network. We used two large databases of resting state fMRI data, from which we extracted 32 robust RSNs. We estimated: (1) the RSN functional roles by using a projection of the results on task based networks (TBNs) as referenced in large databases of fMRI activation studies; and (2) relationship of the RSNs with the Brodmann Areas. In both classifications, the 32 RSNs are organized into a remarkable architecture of two intertwined rings per hemisphere and so four rings linked by homotopic connections. The first ring forms a continuous ensemble and includes visual, somatic, and auditory cortices, with interspersed bimodal cortices (auditory-visual, visual-somatic and auditory-somatic, abbreviated as VSA ring). The second ring integrates distant parietal, temporal and frontal regions (PTF ring) through a network of association fiber tracts which closes the ring anatomically and ensures a functional continuity within the ring. The PTF ring relates association cortices specialized in attention, language and working memory, to the networks involved in motivation and biological regulation and rhythms. This “dual intertwined architecture” suggests a dual integrative process: the VSA ring performs fast real-time multimodal integration of sensorimotor information whereas the PTF ring performs multi

  14. REST: a toolkit for resting-state functional magnetic resonance imaging data processing.

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    Xiao-Wei Song

    Full Text Available Resting-state fMRI (RS-fMRI has been drawing more and more attention in recent years. However, a publicly available, systematically integrated and easy-to-use tool for RS-fMRI data processing is still lacking. We developed a toolkit for the analysis of RS-fMRI data, namely the RESting-state fMRI data analysis Toolkit (REST. REST was developed in MATLAB with graphical user interface (GUI. After data preprocessing with SPM or AFNI, a few analytic methods can be performed in REST, including functional connectivity analysis based on linear correlation, regional homogeneity, amplitude of low frequency fluctuation (ALFF, and fractional ALFF. A few additional functions were implemented in REST, including a DICOM sorter, linear trend removal, bandpass filtering, time course extraction, regression of covariates, image calculator, statistical analysis, and slice viewer (for result visualization, multiple comparison correction, etc.. REST is an open-source package and is freely available at http://www.restfmri.net.

  15. Changes in Brain Lateralization in Patients with Mild Cognitive Impairment and Alzheimer’s Disease: A Resting-State Functional Magnetic Resonance Study from Alzheimer’s Disease Neuroimaging Initiative

    Directory of Open Access Journals (Sweden)

    Hao Liu

    2018-02-01

    Full Text Available PurposeTo detect changes in brain lateralization in patients with mild cognitive impairment (MCI and Alzheimer’s disease (AD using resting-state functional magnetic resonance imaging (fMRI.Materials and methodsData from 61 well-matched right-handed subjects were obtained from the Alzheimer’s Disease Neuroimaging Initiative, including 19 healthy controls (HCs, 25 patients with MCI, and 17 patients with AD. First, we divided 256 pairs of seed regions from each hemisphere covering the entire cerebral gray matter. Then, we used the intrinsic laterality index (iLI approach to quantify the functional laterality using fMRI. One-way ANOVA was employed to estimate the differences in iLI among the three groups. The sum, number and mean value of the iLI were calculated within the thresholds of 0 < |iLI| < 0.2, 0.2 ≤ |iLI| < 0.4, 0.4 ≤ |iLI| < 0.8, and |iLI| ≥ 0.8, to explore the changes in the lateralization of resting-state brain function in patients with MCI and AD.ResultsOne-way ANOVA revealed that the iLIs of the three groups were significantly different. The HCs showed a significant leftward interhemispheric difference within |iLI| ≥ 0.8. Compared with the HCs, the patients with MCI manifested a distinct abnormal rightward interhemispheric asymmetry, mainly within the thresholds of 0.2 ≤ |iLI| < 0.4 and 0.4 ≤ |iLI| < 0.8; in the patients with AD, the normal leftward lateralization that was observed in the HCs disappeared, and an abnormal rightward laterality was expressed within 0.4 ≤ |iLI| < 0.8. By directly comparing the patients with MCI with the patients with AD, an exclusive abnormal rightward laterality was observed in the patients with MCI within the 0.2 ≤ |iLI| < 0.4 threshold, and the normal leftward asymmetry vanished in the patients with AD within the |iLI| ≥ 0.8 threshold.ConclusionGlobal brain lateralization was different among three groups. The

  16. Activity flow over resting-state networks shapes cognitive task activations.

    Science.gov (United States)

    Cole, Michael W; Ito, Takuya; Bassett, Danielle S; Schultz, Douglas H

    2016-12-01

    Resting-state functional connectivity (FC) has helped reveal the intrinsic network organization of the human brain, yet its relevance to cognitive task activations has been unclear. Uncertainty remains despite evidence that resting-state FC patterns are highly similar to cognitive task activation patterns. Identifying the distributed processes that shape localized cognitive task activations may help reveal why resting-state FC is so strongly related to cognitive task activations. We found that estimating task-evoked activity flow (the spread of activation amplitudes) over resting-state FC networks allowed prediction of cognitive task activations in a large-scale neural network model. Applying this insight to empirical functional MRI data, we found that cognitive task activations can be predicted in held-out brain regions (and held-out individuals) via estimated activity flow over resting-state FC networks. This suggests that task-evoked activity flow over intrinsic networks is a large-scale mechanism explaining the relevance of resting-state FC to cognitive task activations.

  17. Resting-state abnormalities in amnestic mild cognitive impairment: a meta-analysis.

    Science.gov (United States)

    Lau, W K W; Leung, M-K; Lee, T M C; Law, A C K

    2016-04-26

    Amnestic mild cognitive impairment (aMCI) is a prodromal stage of Alzheimer's disease (AD). As no effective drug can cure AD, early diagnosis and intervention for aMCI are urgently needed. The standard diagnostic procedure for aMCI primarily relies on subjective neuropsychological examinations that require the judgment of experienced clinicians. The development of other objective and reliable aMCI markers, such as neural markers, is therefore required. Previous neuroimaging findings revealed various abnormalities in resting-state activity in MCI patients, but the findings have been inconsistent. The current study provides an updated activation likelihood estimation meta-analysis of resting-state functional magnetic resonance imaging (fMRI) data on aMCI. The authors searched on the MEDLINE/PubMed databases for whole-brain resting-state fMRI studies on aMCI published until March 2015. We included 21 whole-brain resting-state fMRI studies that reported a total of 156 distinct foci. Significant regional resting-state differences were consistently found in aMCI patients relative to controls, including the posterior cingulate cortex, right angular gyrus, right parahippocampal gyrus, left fusiform gyrus, left supramarginal gyrus and bilateral middle temporal gyri. Our findings support that abnormalities in resting-state activities of these regions may serve as neuroimaging markers for aMCI.

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

    NARCIS (Netherlands)

    Gravel, Nicolás G; Harvey, Ben M; Renken, Remco K; Dumoulin, Serge O; Cornelissen, Frans W

    2018-01-01

    Resting-state fMRI is widely used to study brain function and connectivity. However, interpreting patterns of resting state (RS) fMRI activity remains challenging as they may arise from different neuronal mechanisms than those triggered by exogenous events. Currently, this limits the use of RS-fMRI

  19. The Effects of Acutely Administered 3,4-Methylenedioxymethamphetamine on Spontaneous Brain Function in Healthy Volunteers Measured with Arterial Spin Labeling and Blood Oxygen Level–Dependent Resting State Functional Connectivity

    Science.gov (United States)

    Carhart-Harris, Robin L.; Murphy, Kevin; Leech, Robert; Erritzoe, David; Wall, Matthew B.; Ferguson, Bart; Williams, Luke T.J.; Roseman, Leor; Brugger, Stefan; De Meer, Ineke; Tanner, Mark; Tyacke, Robin; Wolff, Kim; Sethi, Ajun; Bloomfield, Michael A.P.; Williams, Tim M.; Bolstridge, Mark; Stewart, Lorna; Morgan, Celia; Newbould, Rexford D.; Feilding, Amanda; Curran, H. Val; Nutt, David J.

    2015-01-01

    Background The compound 3,4-methylenedioxymethamphetamine (MDMA) is a potent monoamine releaser that produces an acute euphoria in most individuals. Methods In a double-blind, placebo-controlled, balanced-order study, MDMA was orally administered to 25 physically and mentally healthy individuals. Arterial spin labeling and seed-based resting state functional connectivity (RSFC) were used to produce spatial maps displaying changes in cerebral blood flow (CBF) and RSFC after MDMA administration. Participants underwent two arterial spin labeling and two blood oxygen level–dependent scans in a 90-minute scan session; MDMA and placebo study days were separated by 1 week. Results Marked increases in positive mood were produced by MDMA. Decreased CBF only was observed after MDMA, and this was localized to the right medial temporal lobe (MTL), thalamus, inferior visual cortex, and the somatosensory cortex. Decreased CBF in the right amygdala and hippocampus correlated with ratings of the intensity of global subjective effects of MDMA. The RSFC results complemented the CBF results, with decreases in RSFC between midline cortical regions, the medial prefrontal cortex, and MTL regions, and increases between the amygdala and hippocampus. There were trend-level correlations between these effects and ratings of intense and positive subjective effects. Conclusions The MTLs appear to be specifically implicated in the mechanism of action of MDMA, but further work is required to elucidate how the drug’s characteristic subjective effects arise from its modulation of spontaneous brain activity. PMID:24495461

  20. The Effects of Acutely Administered 3,4-Methylenedioxymethamphetamine on Spontaneous Brain Function in Healthy Volunteers Measured with Arterial Spin Labeling and Blood Oxygen Level-Dependent Resting State Functional Connectivity.

    Science.gov (United States)

    Carhart-Harris, Robin L; Murphy, Kevin; Leech, Robert; Erritzoe, David; Wall, Matthew B; Ferguson, Bart; Williams, Luke T J; Roseman, Leor; Brugger, Stefan; De Meer, Ineke; Tanner, Mark; Tyacke, Robin; Wolff, Kim; Sethi, Ajun; Bloomfield, Michael A P; Williams, Tim M; Bolstridge, Mark; Stewart, Lorna; Morgan, Celia; Newbould, Rexford D; Feilding, Amanda; Curran, H Val; Nutt, David J

    2015-10-15

    The compound 3,4-methylenedioxymethamphetamine (MDMA) is a potent monoamine releaser that produces an acute euphoria in most individuals. In a double-blind, placebo-controlled, balanced-order study, MDMA was orally administered to 25 physically and mentally healthy individuals. Arterial spin labeling and seed-based resting state functional connectivity (RSFC) were used to produce spatial maps displaying changes in cerebral blood flow (CBF) and RSFC after MDMA administration. Participants underwent two arterial spin labeling and two blood oxygen level-dependent scans in a 90-minute scan session; MDMA and placebo study days were separated by 1 week. Marked increases in positive mood were produced by MDMA. Decreased CBF only was observed after MDMA, and this was localized to the right medial temporal lobe (MTL), thalamus, inferior visual cortex, and the somatosensory cortex. Decreased CBF in the right amygdala and hippocampus correlated with ratings of the intensity of global subjective effects of MDMA. The RSFC results complemented the CBF results, with decreases in RSFC between midline cortical regions, the medial prefrontal cortex, and MTL regions, and increases between the amygdala and hippocampus. There were trend-level correlations between these effects and ratings of intense and positive subjective effects. The MTLs appear to be specifically implicated in the mechanism of action of MDMA, but further work is required to elucidate how the drug's characteristic subjective effects arise from its modulation of spontaneous brain activity. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

    Doruyter, Alex; Groenewold, Nynke A; Dupont, Patrick; Stein, Dan J; Warwick, James M

    2017-09-01

    Many psychiatric disorders are characterized by altered social cognition. The importance of social cognition has previously been recognized by the National Institute of Mental Health Research Domain Criteria project, in which it features as a core domain. Social task-based functional magnetic resonance imaging (fMRI) currently offers the most direct insight into how the brain processes social information; however, resting-state fMRI may be just as important in understanding the biology and network nature of social processing. Resting-state fMRI allows researchers to investigate the functional relationships between brain regions in a neutral state: so-called resting functional connectivity (RFC). There is evidence that RFC is predictive of how the brain processes information during social tasks. This is important because it shifts the focus from possibly context-dependent aberrations to context-independent aberrations in functional network architecture. Rather than being analysed in isolation, the study of resting-state brain networks shows promise in linking results of task-based fMRI results, structural connectivity, molecular imaging findings, and performance measures of social cognition-which may prove crucial in furthering our understanding of the social brain. Copyright © 2017 John Wiley & Sons, Ltd.

  2. The Effects of Long Duration Bed Rest as a Spaceflight Analogue on Resting State Sensorimotor Network Functional Connectivity and Neurocognitive Performance

    Science.gov (United States)

    Cassady, K.; Koppelmans, V.; Yuan, P.; Cooke, K.; De Dios, Y.; Stepanyan, V.; Szecsy, D.; Gadd, N.; Wood, S.; Reuter-Lorenz, P.; hide

    2015-01-01

    Long duration spaceflight has been associated with detrimental alterations in human sensorimotor systems and neurocognitive performance. Prolonged exposure to a head-down tilt 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 neurocognitive performance is largely unknown, but of potential importance to the health and performance of astronauts both during and post-flight. The aims of the present study are 1) to identify changes in sensorimotor resting state functional connectivity that occur with extended bed rest exposure, and to characterize their recovery time course; 2) to evaluate how these neural changes correlate with neurocognitive performance. Resting-state functional magnetic resonance imaging (rsfMRI) data were collected from 17 male participants. The data were acquired through the NASA bed rest facility, located at the University of Texas Medical Branch (Galveston, TX). Participants remained in bed with their heads tilted down six degrees below their feet for 70 consecutive days. RsfMRI data were obtained at seven time points: 7 and 12 days before bed rest; 7, 50, and 65 days during bed rest; and 7 and 12 days after bed rest. Functional connectivity magnetic resonance imaging (fcMRI) analysis was performed to measure the connectivity of sensorimotor networks in the brain before, during, and post-bed rest. We found a decrease in left putamen connectivity with the pre- and post-central gyri from pre bed rest to the last day in bed rest. In addition, vestibular cortex connectivity with the posterior cingulate cortex decreased from pre to post bed rest. Furthermore, connectivity between cerebellar right superior posterior fissure and other cerebellar regions decreased from

  3. Resting-state functional connectivity remains unaffected by preceding exposure to aversive visual stimuli.

    Science.gov (United States)

    Geissmann, Léonie; Gschwind, Leo; Schicktanz, Nathalie; Deuring, Gunnar; Rosburg, Timm; Schwegler, Kyrill; Gerhards, Christiane; Milnik, Annette; Pflueger, Marlon O; Mager, Ralph; de Quervain, Dominique J F; Coynel, David

    2018-02-15

    While much is known about immediate brain activity changes induced by the confrontation with emotional stimuli, the subsequent temporal unfolding of emotions has yet to be explored. To investigate whether exposure to emotionally aversive pictures affects subsequent resting-state networks differently from exposure to neutral pictures, a resting-state fMRI study implementing a two-group repeated-measures design in healthy young adults (N = 34) was conducted. We focused on investigating (i) patterns of amygdala whole-brain and hippocampus connectivity in both a seed-to-voxel and seed-to-seed approach, (ii) whole-brain resting-state networks with an independent component analysis coupled with dual regression, and (iii) the amygdala's fractional amplitude of low frequency fluctuations, all while EEG recording potential fluctuations in vigilance. In spite of the successful emotion induction, as demonstrated by stimuli rating and a memory-facilitating effect of negative emotionality, none of the resting-state measures was differentially affected by picture valence. In conclusion, resting-state networks connectivity as well as the amygdala's low frequency oscillations appear to be unaffected by preceding exposure to widely used emotionally aversive visual stimuli in healthy young adults. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  4. Magnetic resonance imaging of functional connectivity in Parkinson disease in the resting brain

    International Nuclear Information System (INIS)

    Liu Xian; Liu Bo; Luo Xiaodong; Li Ningna; Chen Zhiguang; Chen Jun

    2009-01-01

    Objective: To investigate functional connectivity changes in Parkinson disease in the resting brain using functional magnetic resonance imaging. Methods: Nine patients with Parkinson disease and eight age-matched healthy volunteers were entered into the study. The bilateral globus pallidus were chosen as seed points, the functional MR data acquired in the resting state were processed to investigate functional connectivity in PD patients and the results were compared with those of the controls. Results: In age-matched healthy controls, there are regions which had functional connectivity with bilateral globus pallidus, including bilateral temporal poles, bilateral hippocampus, bilateral thalami, posterior cingulate cortex, right middle occipital gyms and right superior parietal gyms. In PD patients, brain regions including bilateral cerebellum, left hippocampus, bilateral superior temporal gyri, left inferior frontal gyrus, left middle frontal gyrus, left precentral gyrus, left inferior parietal gyrus and left superior parietal gyrus, had functional connectivity with bilateral globus pallidus. Compared to healthy controls, increased functional connectivity in bilateral cerebellum, bilateral temporal lobes, left frontal lobe and left parietal lobe, and decreased functional connectivity in bilateral thalami were observed in PD patients. Conclusion: Abnormal changes of brain functional connectivity exists in Parkinson's disease in the resting state. (authors)

  5. Does resting-state connectivity reflect depressive rumination? A tale of two analyses.

    Science.gov (United States)

    Berman, Marc G; Misic, Bratislav; Buschkuehl, Martin; Kross, Ethan; Deldin, Patricia J; Peltier, Scott; Churchill, Nathan W; Jaeggi, Susanne M; Vakorin, Vasily; McIntosh, Anthony R; Jonides, John

    2014-12-01

    Major Depressive Disorder (MDD) is characterized by rumination. Prior research suggests that resting-state brain activation reflects rumination when depressed individuals are not task engaged. However, no study has directly tested this. Here we investigated whether resting-state epochs differ from induced ruminative states for healthy and depressed individuals. Most previous research on resting-state networks comes from seed-based analyses with the posterior cingulate cortex (PCC). By contrast, we examined resting state connectivity by using the complete multivariate connectivity profile (i.e., connections across all brain nodes) and by comparing these results to seeded analyses. We find that unconstrained resting-state intervals differ from active rumination states in strength of connectivity and that overall connectivity was higher for healthy vs. depressed individuals. Relationships between connectivity and subjective mood (i.e., behavior) were strongly observed during induced rumination epochs. Furthermore, connectivity patterns that related to subjective mood were strikingly different for MDD and healthy control (HC) groups suggesting different mood regulation mechanisms. Copyright © 2014 Elsevier Inc. All rights reserved.

  6. Visual learning alters the spontaneous activity of the resting human brain: an fNIRS study.

    Science.gov (United States)

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

    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 discrimination task constrained to the right visual field, resting HbO functional connectivity and directed mutual interaction between high-level visual cortex and frontal/central areas involved in the top-down control were significantly modified. Moreover, these changes, which correlated with the degree of perceptual learning, were not limited to the trained left visual cortex. We conclude that the resting oxygenated hemoglobin functional connectivity could be used as a predictor of visual learning, supporting the involvement of high-level visual cortex and the involvement of frontal/central cortex during visual perceptual learning.

  7. Complexity Analysis of Resting-State MEG Activity in Early-Stage Parkinson's Disease Patients

    NARCIS (Netherlands)

    Gómez, C.; Olde Dubbelink, K.T.E.; Stam, C.J.; Abasolo, D.; Berendse, H.W.; Hornero, R.

    2011-01-01

    The aim of the present study was to analyze resting-state brain activity in patients with Parkinson's disease (PD), a degenerative disorder of the nervous system. Magnetoencephalography (MEG) signals were recorded with a 151-channel whole-head radial gradiometer MEG system in 18 early-stage

  8. 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

  9. Time of acquisition and network stability in pediatric resting-state functional magnetic resonance imaging

    NARCIS (Netherlands)

    T.J.H. White (Tonya); R.L. Muetzel (Ryan); M. Schmidt (Marcus); S.J.E. Langeslag (Sandra); V.W.V. Jaddoe (Vincent); A. Hofman (Albert); V.D. Calhoun Vince D. (V.); F.C. Verhulst (Frank); H.W. Tiemeier (Henning)

    2014-01-01

    textabstractResting-state functional magnetic resonance imaging (rs-fMRI) has been shown to elucidate reliable patterns of brain networks in both children and adults. Studies in adults have shown that rs-fMRI acquisition times of ∼5 to 6 min provide adequate sampling to produce stable spatial maps

  10. Resting-State Alpha in Autism Spectrum Disorder and Alpha Associations with Thalamic Volume

    Science.gov (United States)

    Edgar, J. Christopher; Heiken, Kory; Chen, Yu-Han; Herrington, John D.; Chow, Vivian; Liu, Song; Bloy, Luke; Huang, Mingxiong; Pandey, Juhi; Cannon, Katelyn M.; Qasmieh, Saba; Levy, Susan E.; Schultz, Robert T.; Roberts, Timothy P. L.

    2015-01-01

    Alpha circuits (8-12 Hz), necessary for basic and complex brain processes, are abnormal in autism spectrum disorder (ASD). The present study obtained estimates of resting-state (RS) alpha activity in children with ASD and examined associations between alpha activity, age, and clinical symptoms. Given that the thalamus modulates cortical RS alpha…

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

    Science.gov (United States)

    Wen, Haiguang; Liu, Zhongming

    2016-06-01

    Spontaneous activity observed with resting-state fMRI is used widely to uncover the brain's intrinsic functional networks in health and disease. Although many networks appear modular and specific, global and nonspecific fMRI fluctuations also exist and both pose a challenge and present an opportunity for characterizing and understanding brain networks. Here, we used a multimodal approach to investigate the neural correlates to the global fMRI signal in the resting state. Like fMRI, resting-state power fluctuations of broadband and arrhythmic, or scale-free, macaque electrocorticography and human magnetoencephalography activity were correlated globally. The power fluctuations of scale-free human electroencephalography (EEG) were coupled with the global component of simultaneously acquired resting-state fMRI, with the global hemodynamic change lagging the broadband spectral change of EEG by ∼5 s. The levels of global and nonspecific fluctuation and synchronization in scale-free population activity also varied across and depended on arousal states. Together, these results suggest that the neural origin of global resting-state fMRI activity is the broadband power fluctuation in scale-free population activity observable with macroscopic electrical or magnetic recordings. Moreover, the global fluctuation in neurophysiological and hemodynamic activity is likely modulated through diffuse neuromodulation pathways that govern arousal states and vigilance levels. This study provides new insights into the neural origin of resting-state fMRI. Results demonstrate that the broadband power fluctuation of scale-free electrophysiology is globally synchronized and directly coupled with the global component of spontaneous fMRI signals, in contrast to modularly synchronized fluctuations in oscillatory neural activity. These findings lead to a new hypothesis that scale-free and oscillatory neural processes account for global and modular patterns of functional connectivity observed

  12. Speech networks at rest and in action: interactions between functional brain networks controlling speech production

    Science.gov (United States)

    Fuertinger, Stefan

    2015-01-01

    Speech production is one of the most complex human behaviors. Although brain activation during speaking has been well investigated, our understanding of interactions between the brain regions and neural networks remains scarce. We combined seed-based interregional correlation analysis with graph theoretical analysis of functional MRI data during the resting state and sentence production in healthy subjects to investigate the interface and topology of functional networks originating from the key brain regions controlling speech, i.e., the laryngeal/orofacial motor cortex, inferior frontal and superior temporal gyri, supplementary motor area, cingulate cortex, putamen, and thalamus. During both resting and speaking, the interactions between these networks were bilaterally distributed and centered on the sensorimotor brain regions. However, speech production preferentially recruited the inferior parietal lobule (IPL) and cerebellum into the large-scale network, suggesting the importance of these regions in facilitation of the transition from the resting state to speaking. Furthermore, the cerebellum (lobule VI) was the most prominent region showing functional influences on speech-network integration and segregation. Although networks were bilaterally distributed, interregional connectivity during speaking was stronger in the left vs. right hemisphere, which may have underlined a more homogeneous overlap between the examined networks in the left hemisphere. Among these, the laryngeal motor cortex (LMC) established a core network that fully overlapped with all other speech-related networks, determining the extent of network interactions. Our data demonstrate complex interactions of large-scale brain networks controlling speech production and point to the critical role of the LMC, IPL, and cerebellum in the formation of speech production network. PMID:25673742

  13. Speech networks at rest and in action: interactions between functional brain networks controlling speech production.

    Science.gov (United States)

    Simonyan, Kristina; Fuertinger, Stefan

    2015-04-01

    Speech production is one of the most complex human behaviors. Although brain activation during speaking has been well investigated, our understanding of interactions between the brain regions and neural networks remains scarce. We combined seed-based interregional correlation analysis with graph theoretical analysis of functional MRI data during the resting state and sentence production in healthy subjects to investigate the interface and topology of functional networks originating from the key brain regions controlling speech, i.e., the laryngeal/orofacial motor cortex, inferior frontal and superior temporal gyri, supplementary motor area, cingulate cortex, putamen, and thalamus. During both resting and speaking, the interactions between these networks were bilaterally distributed and centered on the sensorimotor brain regions. However, speech production preferentially recruited the inferior parietal lobule (IPL) and cerebellum into the large-scale network, suggesting the importance of these regions in facilitation of the transition from the resting state to speaking. Furthermore, the cerebellum (lobule VI) was the most prominent region showing functional influences on speech-network integration and segregation. Although networks were bilaterally distributed, interregional connectivity during speaking was stronger in the left vs. right hemisphere, which may have underlined a more homogeneous overlap between the examined networks in the left hemisphere. Among these, the laryngeal motor cortex (LMC) established a core network that fully overlapped with all other speech-related networks, determining the extent of network interactions. Our data demonstrate complex interactions of large-scale brain networks controlling speech production and point to the critical role of the LMC, IPL, and cerebellum in the formation of speech production network. Copyright © 2015 the American Physiological Society.

  14. Comparison of spontaneous brain activity revealed by regional homogeneity in AQP4-IgG neuromyelitis optica-optic neuritis versus MOG-IgG optic neuritis patients: a resting-state functional MRI study

    Directory of Open Access Journals (Sweden)

    Wang J

    2017-10-01

    Ho values in the posterior lobe of the right cerebellum.AQP4-Ig+NMO-ON subjects showed higher ReHo values in the left precentral/postcentral gyrus and right superior temporal gyrus. Conclusion: AQP4-IgG+NMO-ON and MOG-IgG+ON subjects showed abnormal synchronized neuronal activity in many brain regions, which is consistent with deficits in visual, motor, and cognitive function. Furthermore, different patterns of synchronized neuronal activity occurred in the AQP4-IgG+NMO-ON and MOG-IgG+ON. Keywords: neuromyelitis optica-optic neuritis, MOG-IgG, AQP4-IgG, regional homogeneity, resting state, functional magnetic resonance imaging

  15. Rest and action tremor in Parkinson's disease: effects of Deep Brain Stimulation

    NARCIS (Netherlands)

    Heida, Tjitske; Wentink, E.C.

    2010-01-01

    One of the cardinal symptoms of Parkinson’s disease is rest tremor. While rest tremor generally disappears during sleep and voluntary movement, action tremor may be triggered by voluntary movement, and may even be more disabling than rest tremor. Deep brain stimulation (DBS) in the subthalamic

  16. Cross coherence independent component analysis in resting and action states EEG discrimination

    International Nuclear Information System (INIS)

    Almurshedi, A; Ismail, A K

    2014-01-01

    Cross Coherence time frequency transform and independent component analysis (ICA) method were used to analyse the electroencephalogram (EEG) signals in resting and action states during open and close eyes conditions. From the topographical scalp distributions of delta, theta, alpha, and beta power spectrum can clearly discriminate between the signal when the eyes were open or closed, but it was difficult to distinguish between resting and action states when the eyes were closed. In open eyes condition, the frontal area (Fp1, Fp2) was activated (higher power) in delta and theta bands whilst occipital (O1, O2) and partial (P3, P4, Pz) area of brain was activated alpha band in closed eyes condition. The cross coherence method of time frequency analysis is capable of discrimination between rest and action brain signals in closed eyes condition

  17. 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.

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

    Science.gov (United States)

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

    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 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.

  19. 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.; hide

    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

  20. Temporal reliability and lateralization of the resting-state language network.

    Science.gov (United States)

    Zhu, Linlin; Fan, Yang; Zou, Qihong; Wang, Jue; Gao, Jia-Hong; Niu, Zhendong

    2014-01-01

    The neural processing loop of language is complex but highly associated with Broca's and Wernicke's areas. The left dominance of these two areas was the earliest observation of brain asymmetry. It was demonstrated that the language network and its functional asymmetry during resting state were reproducible across institutions. However, the temporal reliability of resting-state language network and its functional asymmetry are still short of knowledge. In this study, we established a seed-based resting-state functional connectivity analysis of language network with seed regions located at Broca's and Wernicke's areas, and investigated temporal reliability of language network and its functional asymmetry. The language network was found to be temporally reliable in both short- and long-term. In the aspect of functional asymmetry, the Broca's area was found to be left lateralized, while the Wernicke's area is mainly right lateralized. Functional asymmetry of these two areas revealed high short- and long-term reliability as well. In addition, the impact of global signal regression (GSR) on reliability of the resting-state language network was investigated, and our results demonstrated that GSR had negligible effect on the temporal reliability of the resting-state language network. Our study provided methodology basis for future cross-culture and clinical researches of resting-state language network and suggested priority of adopting seed-based functional connectivity for its high reliability.

  1. Temporal reliability and lateralization of the resting-state language network.

    Directory of Open Access Journals (Sweden)

    Linlin Zhu

    Full Text Available The neural processing loop of language is complex but highly associated with Broca's and Wernicke's areas. The left dominance of these two areas was the earliest observation of brain asymmetry. It was demonstrated that the language network and its functional asymmetry during resting state were reproducible across institutions. However, the temporal reliability of resting-state language network and its functional asymmetry are still short of knowledge. In this study, we established a seed-based resting-state functional connectivity analysis of language network with seed regions located at Broca's and Wernicke's areas, and investigated temporal reliability of language network and its functional asymmetry. The language network was found to be temporally reliable in both short- and long-term. In the aspect of functional asymmetry, the Broca's area was found to be left lateralized, while the Wernicke's area is mainly right lateralized. Functional asymmetry of these two areas revealed high short- and long-term reliability as well. In addition, the impact of global signal regression (GSR on reliability of the resting-state language network was investigated, and our results demonstrated that GSR had negligible effect on the temporal reliability of the resting-state language network. Our study provided methodology basis for future cross-culture and clinical researches of resting-state language network and suggested priority of adopting seed-based functional connectivity for its high reliability.

  2. Temporal Reliability and Lateralization of the Resting-State Language Network

    Science.gov (United States)

    Zou, Qihong; Wang, Jue; Gao, Jia-Hong; Niu, Zhendong

    2014-01-01

    The neural processing loop of language is complex but highly associated with Broca's and Wernicke's areas. The left dominance of these two areas was the earliest observation of brain asymmetry. It was demonstrated that the language network and its functional asymmetry during resting state were reproducible across institutions. However, the temporal reliability of resting-state language network and its functional asymmetry are still short of knowledge. In this study, we established a seed-based resting-state functional connectivity analysis of language network with seed regions located at Broca's and Wernicke's areas, and investigated temporal reliability of language network and its functional asymmetry. The language network was found to be temporally reliable in both short- and long-term. In the aspect of functional asymmetry, the Broca's area was found to be left lateralized, while the Wernicke's area is mainly right lateralized. Functional asymmetry of these two areas revealed high short- and long-term reliability as well. In addition, the impact of global signal regression (GSR) on reliability of the resting-state language network was investigated, and our results demonstrated that GSR had negligible effect on the temporal reliability of the resting-state language network. Our study provided methodology basis for future cross-culture and clinical researches of resting-state language network and suggested priority of adopting seed-based functional connectivity for its high reliability. PMID:24475058

  3. Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons

    Science.gov (United States)

    Ma, Ying; Shaik, Mohammed A.; Kozberg, Mariel G.; Portes, Jacob P.; Timerman, Dmitriy

    2016-01-01

    Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by wide-field Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI. PMID:27974609

  4. Hubs of Anticorrelation in High-Resolution Resting-State Functional Connectivity Network Architecture.

    Science.gov (United States)

    Gopinath, Kaundinya; Krishnamurthy, Venkatagiri; Cabanban, Romeo; Crosson, Bruce A

    2015-06-01

    A major focus of brain research recently has been to map the resting-state functional connectivity (rsFC) network architecture of the normal brain and pathology through functional magnetic resonance imaging. However, the phenomenon of anticorrelations in resting-state signals between different brain regions has not been adequately examined. The preponderance of studies on resting-state fMRI (rsFMRI) have either ignored anticorrelations in rsFC networks or adopted methods in data analysis, which have rendered anticorrelations in rsFC networks uninterpretable. The few studies that have examined anticorrelations in rsFC networks using conventional methods have found anticorrelations to be weak in strength and not very reproducible across subjects. Anticorrelations in rsFC network architecture could reflect mechanisms that subserve a number of important brain processes. In this preliminary study, we examined the properties of anticorrelated rsFC networks by systematically focusing on negative cross-correlation coefficients (CCs) among rsFMRI voxel time series across the brain with graph theory-based network analysis. A number of methods were implemented to enhance the neuronal specificity of resting-state functional connections that yield negative CCs, although at the cost of decreased sensitivity. Hubs of anticorrelation were seen in a number of cortical and subcortical brain regions. Examination of the anticorrelation maps of these hubs indicated that negative CCs in rsFC network architecture highlight a number of regulatory interactions between brain networks and regions, including reciprocal modulations, suppression, inhibition, and neurofeedback.

  5. What goes on in the resting-state? A qualitative glimpse into resting-state experience in the scanner

    Science.gov (United States)

    Hurlburt, Russell T.; Alderson-Day, Ben; Fernyhough, Charles; Kühn, Simone

    2015-01-01

    The brain’s resting-state has attracted considerable interest in recent years, but currently little is known either about typical experience during the resting-state or about whether there are inter-individual differences in resting-state phenomenology. We used descriptive experience sampling (DES) in an attempt to apprehend high fidelity glimpses of the inner experience of five participants in an extended fMRI study. Results showed that the inner experiences and the neural activation patterns (as quantified by amplitude of low frequency fluctuations analysis) of the five participants were largely consistent across time, suggesting that our extended-duration scanner sessions were broadly similar to typical resting-state sessions. However, there were very large individual differences in inner phenomena, suggesting that the resting-state itself may differ substantially from one participant to the next. We describe these individual differences in experiential characteristics and display some typical moments of resting-state experience. We also show that retrospective characterizations of phenomena can often be very different from moment-by-moment reports. We discuss implications for the assessment of inner experience in neuroimaging studies more generally, concluding that it may be possible to use fMRI to investigate neural correlates of phenomena apprehended in high fidelity. PMID:26500590

  6. Modifications of resting state networks in spinocerebellar ataxia type 2.

    Science.gov (United States)

    Cocozza, Sirio; Saccà, Francesco; Cervo, Amedeo; Marsili, Angela; Russo, Cinzia Valeria; Giorgio, Sara Maria Delle Acque; De Michele, Giuseppe; Filla, Alessandro; Brunetti, Arturo; Quarantelli, Mario

    2015-09-01

    We aimed to investigate the integrity of the Resting State Networks in spinocerebellar ataxia type 2 (SCA2) and the correlations between the modification of these networks and clinical variables. Resting-state functional magnetic resonance imaging (RS-fMRI) data from 19 SCA2 patients and 29 healthy controls were analyzed using an independent component analysis and dual regression, controlling at voxel level for the effect of atrophy by co-varying for gray matter volume. Correlations between the resting state networks alterations and disease duration, age at onset, number of triplets, and clinical score were assessed by Spearman's coefficient, for each cluster which was significantly different in SCA2 patients compared with healthy controls. In SCA2 patients, disruption of the cerebellar components of all major resting state networks was present, with supratentorial involvement only for the default mode network. When controlling at voxel level for gray matter volume, the reduction in functional connectivity in supratentorial regions of the default mode network, and in cerebellar regions within the default mode, executive and right fronto-parietal networks, was still significant. No correlations with clinical variables were found for any of the investigated resting state networks. The SCA2 patients show significant alterations of the resting state networks, only partly explained by the atrophy. The default mode network is the only resting state network that shows also supratentorial changes, which appear unrelated to the cortical gray matter volume. Further studies are needed to assess the clinical significance of these changes. © 2015 International Parkinson and Movement Disorder Society.

  7. Regional homogeneity and resting state functional connectivity: associations with exposure to early life stress.

    Science.gov (United States)

    Philip, Noah S; Kuras, Yuliya I; Valentine, Thomas R; Sweet, Lawrence H; Tyrka, Audrey R; Price, Lawrence H; Carpenter, Linda L

    2013-12-30

    Early life stress (ELS) confers risk for psychiatric illness. Previous literature suggests ELS is associated with decreased resting-state functional connectivity (rs-FC) in adulthood, but there are no studies of resting-state neuronal activity in this population. This study investigated whether ELS-exposed individuals demonstrate resting-state activity patterns similar to those found in PTSD. Twenty-seven adults (14 with at least moderate ELS), who were medication-free and without psychiatric or medical illness, underwent MRI scans during two 4-minute rest periods. Resting-state activity was examined using regional homogeneity (ReHo), which estimates regional activation patterns through indices of localized concordance. ReHo values were compared between groups, followed by rs-FC analyses utilizing ReHo-localized areas as seeds to identify other involved regions. Relative to controls, ELS subjects demonstrated diminished ReHo in the inferior parietal lobule (IPL) and superior temporal gyrus (STG). ReHo values were inversely correlated with ELS severity. Secondary analyses revealed decreased rs-FC between the IPL and right precuneus/posterior cingulate, left fusiform gyrus, cerebellum and caudate in ELS subjects. These findings indicate that ELS is associated with altered resting-state activity and connectivity in brain regions involved in trauma-related psychiatric disorders. Future studies are needed to evaluate whether these associations represent potential imaging biomarkers of stress exposure. Published by Elsevier Ireland Ltd.

  8. Resting-State Functional Magnetic Resonance Imaging for Language Preoperative Planning

    Science.gov (United States)

    Branco, Paulo; Seixas, Daniela; Deprez, Sabine; Kovacs, Silvia; Peeters, Ronald; Castro, São L.; Sunaert, Stefan

    2016-01-01

    Functional magnetic resonance imaging (fMRI) is a well-known non-invasive technique for the study of brain function. One of its most common clinical applications is preoperative language mapping, essential for the preservation of function in neurosurgical patients. Typically, fMRI is used to track task-related activity, but poor task performance and movement artifacts can be critical limitations in clinical settings. Recent advances in resting-state protocols open new possibilities for pre-surgical mapping of language potentially overcoming these limitations. To test the feasibility of using resting-state fMRI instead of conventional active task-based protocols, we compared results from fifteen patients with brain lesions while performing a verb-to-noun generation task and while at rest. Task-activity was measured using a general linear model analysis and independent component analysis (ICA). Resting-state networks were extracted using ICA and further classified in two ways: manually by an expert and by using an automated template matching procedure. The results revealed that the automated classification procedure correctly identified language networks as compared to the expert manual classification. We found a good overlay between task-related activity and resting-state language maps, particularly within the language regions of interest. Furthermore, resting-state language maps were as sensitive as task-related maps, and had higher specificity. Our findings suggest that resting-state protocols may be suitable to map language networks in a quick and clinically efficient way. PMID:26869899

  9. Altered thalamo-cortical resting state functional connectivity in smokers.

    Science.gov (United States)

    Wang, Chaoyan; Bai, Jie; Wang, Caihong; von Deneen, Karen M; Yuan, Kai; Cheng, Jingliang

    2017-07-13

    The thalamus has widespread connections with the prefrontal cortex (PFC) and modulates communication between the striatum and PFC, which is crucial to the neural mechanisms of smoking. However, relatively few studies focused on the thalamic resting state functional connectivity (RSFC) patterns and their association with smoking behaviors in smokers. 24 young male smokers and 24 non-smokers were enrolled in our study. Fagerström Test for Nicotine Dependence (FTND) was used to assess the nicotine dependence level. The bilateral thalamic RSFC patterns were compared between smokers and non-smokers. The relationship between neuroimaging findings and smoking behaviors (FTND and pack-years) were also investigated in smokers. Relative to nonsmokers, smokers showed reduced RSFC strength between the left thalamus and several brain regions, i.e. the right dorsolateral prefrontal cortex (dlPFC), the anterior cingulate cortex (ACC) and the bilateral caudate. In addition, the right thalamus showed reduced RSFC with the right dlPFC as well as the bilateral insula in smokers. Therefore, the findings in the current study revealed the reduced RSFC of the thalamus with the dlPFC, the ACC, the insula and the caudate in smokers, which provided new insights into the roles of the thalamus in nicotine addiction from a function integration perspective. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Frequency specific patterns of resting-state networks development from childhood to adolescence: A magnetoencephalography study.

    Science.gov (United States)

    Meng, Lu; Xiang, Jing

    2016-11-01

    The present study investigated frequency dependent developmental patterns of the brain resting-state networks from childhood to adolescence. Magnetoencephalography (MEG) data were recorded from 20 healthy subjects at resting-state with eyes-open. The resting-state networks (RSNs) was analyzed at source-level. Brain network organization was characterized by mean clustering coefficient and average path length. The correlations between brain network measures and subjects' age during development from childhood to adolescence were statistically analyzed in delta (1-4Hz), theta (4-8Hz), alpha (8-12Hz), and beta (12-30Hz) frequency bands. A significant positive correlation between functional connectivity with age was found in alpha and beta frequency bands. A significant negative correlation between average path lengths with age was found in beta frequency band. The results suggest that there are significant developmental changes of resting-state networks from childhood to adolescence, which matures from a lattice network to a small-world network. Copyright © 2016 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

  11. Abnormal resting-state connectivity of motor and cognitive networks in early manifest Huntington's disease.

    Science.gov (United States)

    Wolf, R C; Sambataro, F; Vasic, N; Depping, M S; Thomann, P A; Landwehrmeyer, G B; Süssmuth, S D; Orth, M

    2014-11-01

    Functional magnetic resonance imaging (fMRI) of multiple neural networks during the brain's 'resting state' could facilitate biomarker development in patients with Huntington's disease (HD) and may provide new insights into the relationship between neural dysfunction and clinical symptoms. To date, however, very few studies have examined the functional integrity of multiple resting state networks (RSNs) in manifest HD, and even less is known about whether concomitant brain atrophy affects neural activity in patients. Using MRI, we investigated brain structure and RSN function in patients with early HD (n = 20) and healthy controls (n = 20). For resting-state fMRI data a group-independent component analysis identified spatiotemporally distinct patterns of motor and prefrontal RSNs of interest. We used voxel-based morphometry to assess regional brain atrophy, and 'biological parametric mapping' analyses to investigate the impact of atrophy on neural activity. Compared with controls, patients showed connectivity changes within distinct neural systems including lateral prefrontal, supplementary motor, thalamic, cingulate, temporal and parietal regions. In patients, supplementary motor area and cingulate cortex connectivity indices were associated with measures of motor function, whereas lateral prefrontal connectivity was associated with cognition. This study provides evidence for aberrant connectivity of RSNs associated with motor function and cognition in early manifest HD when controlling for brain atrophy. This suggests clinically relevant changes of RSN activity in the presence of HD-associated cortical and subcortical structural abnormalities.

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

    Science.gov (United States)

    Göttlich, Martin; Jandl, Nico M; Wojak, Jann F; Sprenger, Andreas; von der Gablentz, Janina; Münte, Thomas F; Krämer, Ulrike M; Helmchen, Christoph

    2014-01-01

    Patients with bilateral vestibular failure (BVF) suffer from gait unsteadiness, oscillopsia and impaired spatial orientation. Brain imaging studies applying caloric irrigation to patients with BVF have shown altered neural activity of cortical visual-vestibular interaction: decreased bilateral neural activity in the posterior insula and parietal operculum and decreased deactivations in the visual cortex. It is unknown how this affects functional connectivity in the resting brain and how changes in connectivity are related to vestibular impairment. We applied a novel data driven approach based on graph theory to investigate altered whole-brain resting-state functional connectivity in BVF patients (n= 22) compared to age- and gender-matched healthy controls (n= 25) using resting-state fMRI. Changes in functional connectivity were related to subjective (vestibular scores) and objective functional parameters of vestibular impairment, specifically, the adaptive changes during active (self-guided) and passive (investigator driven) head impulse test (HIT) which reflects the integrity of the vestibulo-ocular reflex (VOR). BVF patients showed lower bilateral connectivity in the posterior insula and parietal operculum but higher connectivity in the posterior cerebellum compared to controls. Seed-based analysis revealed stronger connectivity from the right posterior insula to the precuneus, anterior insula, anterior cingulate cortex and the middle frontal gyrus. Excitingly, functional connectivity in the supramarginal gyrus (SMG) of the inferior parietal lobe and posterior cerebellum correlated with the increase of VOR gain during active as compared to passive HIT, i.e., the larger the adaptive VOR changes the larger was the increase in regional functional connectivity. 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

  13. 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.

  14. Resting-State Network Topology Differentiates Task Signals across the Adult Life Span.

    Science.gov (United States)

    Chan, Micaela Y; Alhazmi, Fahd H; Park, Denise C; Savalia, Neil K; Wig, Gagan S

    2017-03-08

    Brain network connectivity differs across individuals. For example, older adults exhibit less segregated resting-state subnetworks relative to younger adults (Chan et al., 2014). It has been hypothesized that individual differences in network connectivity impact the recruitment of brain areas during task execution. While recent studies have described the spatial overlap between resting-state functional correlation (RSFC) subnetworks and task-evoked activity, it is unclear whether individual variations in the connectivity pattern of a brain area (topology) relates to its activity during task execution. We report data from 238 cognitively normal participants (humans), sampled across the adult life span (20-89 years), to reveal that RSFC-based network organization systematically relates to the recruitment of brain areas across two functionally distinct tasks (visual and semantic). The functional activity of brain areas (network nodes) were characterized according to their patterns of RSFC: nodes with relatively greater connections to nodes in their own functional system ("non-connector" nodes) exhibited greater activity than nodes with relatively greater connections to nodes in other systems ("connector" nodes). This "activation selectivity" was specific to those brain systems that were central to each of the tasks. Increasing age was accompanied by less differentiated network topology and a corresponding reduction in activation selectivity (or differentiation) across relevant network nodes. The results provide evidence that connectional topology of brain areas quantified at rest relates to the functional activity of those areas during task. Based on these findings, we propose a novel network-based theory for previous reports of the "dedifferentiation" in brain activity observed in aging. SIGNIFICANCE STATEMENT Similar to other real-world networks, the organization of brain networks impacts their function. As brain network connectivity patterns differ across

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

    Science.gov (United States)

    Khazaee, Ali; Ebrahimzadeh, Ata; Babajani-Feremi, Abbas

    2015-11-01

    Study of brain network on the basis of resting-state functional magnetic resonance imaging (fMRI) has provided promising results to investigate changes in connectivity among different brain regions because of diseases. Graph theory can efficiently characterize different aspects of the brain network by calculating measures of integration and segregation. In this study, we combine graph theoretical approaches with advanced machine learning methods to study functional brain network alteration in patients with Alzheimer's disease (AD). Support vector machine (SVM) was used to explore the ability of graph measures in diagnosis of AD. We applied our method on the resting-state fMRI data of twenty patients with AD and twenty age and gender matched healthy subjects. The data were preprocessed and each subject's graph was constructed by parcellation of the whole brain into 90 distinct regions using the automated anatomical labeling (AAL) atlas. The graph measures were then calculated and used as the discriminating features. Extracted network-based features were fed to different feature selection algorithms to choose most significant features. In addition to the machine learning approach, statistical analysis was performed on connectivity matrices to find altered connectivity patterns in patients with AD. Using the selected features, we were able to accurately classify patients with AD from healthy subjects with accuracy of 100%. Results of this study show that pattern recognition and graph of brain network, on the basis of the resting state fMRI data, can efficiently assist in the diagnosis of AD. Classification based on the resting-state fMRI can be used as a non-invasive and automatic tool to diagnosis of Alzheimer's disease. Copyright © 2015 International Federation of Clinical Neurophysiology. All rights reserved.

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

    Science.gov (United States)

    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

    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 measure of the power spectrum intensity of spontaneous brain oscillations. This approach was used here to identify differences in the resting-state activity of the human brain in IBS subjects compared with healthy controls (HCs) and to identify the role of sex-related differences. We found that both the female HCs and female IBS subjects had a frequency power distribution skewed toward high frequency to a greater extent in the amygdala and hippocampus compared with male subjects. In addition, female IBS subjects had a frequency power distribution skewed toward high frequency in the insula and toward low frequency in the sensorimotor cortex to a greater extent than male IBS subjects. Correlations were observed between resting-state blood oxygen level-dependent signal dynamics and some clinical symptom measures (e.g., abdominal discomfort). These findings provide the first insight into sex-related differences in IBS subjects compared with HCs using resting-state fMRI. PMID:23864686

  17. Neural correlate of resting-state functional connectivity under α2 adrenergic receptor agonist, medetomidine.

    Science.gov (United States)

    Nasrallah, Fatima A; Lew, Si Kang; Low, Amanda Si-Min; Chuang, Kai-Hsiang

    2014-01-01

    Correlative fluctuations in functional MRI (fMRI) signals across the brain at rest have been taken as a measure of functional connectivity, but the neural basis of this resting-state MRI (rsMRI) signal is not clear. Previously, we found that the α2 adrenergic agonist, medetomidine, suppressed the rsMRI correlation dose-dependently but not the stimulus evoked activation. To understand the underlying electrophysiology and neurovascular coupling, which might be altered due to the vasoconstrictive nature of medetomidine, somatosensory evoked potential (SEP) and resting electroencephalography (EEG) were measured and correlated with corresponding BOLD signals in rat brains under three dosages of medetomidine. The SEP elicited by electrical stimulation to both forepaws was unchanged regardless of medetomidine dosage, which was consistent with the BOLD activation. Identical relationship between the SEP and BOLD signal under different medetomidine dosages indicates that the neurovascular coupling was not affected. Under resting state, EEG power was the same but a depression of inter-hemispheric EEG coherence in the gamma band was observed at higher medetomidine dosage. Different from medetomidine, both resting EEG power and BOLD power and coherence were significantly suppressed with increased isoflurane level. Such reduction was likely due to suppressed neural activity as shown by diminished SEP and BOLD activation under isoflurane, suggesting different mechanisms of losing synchrony at resting-state. Even though, similarity between electrophysiology and BOLD under stimulation and resting-state implicates a tight neurovascular coupling in both medetomidine and isoflurane. Our results confirm that medetomidine does not suppress neural activity but dissociates connectivity in the somatosensory cortex. The differential effect of medetomidine and its receptor specific action supports the neuronal origin of functional connectivity and implicates the mechanism of its sedative

  18. Overview of potential procedural and participant-related confounds for neuroimaging of the resting state

    Science.gov (United States)

    Duncan, Niall W.; Northoff, Georg

    2013-01-01

    Studies of intrinsic brain activity in the resting state have become increasingly common. A productive discussion of what analysis methods are appropriate, of the importance of physiologic correction and of the potential interpretations of results has been ongoing. However, less attention has been paid to factors other than physiologic noise that may confound resting-state experiments. These range from straightforward factors, such as ensuring that participants are all instructed in the same manner, to more obscure participant-related factors, such as body weight. We provide an overview of such potentially confounding factors, along with some suggested approaches for minimizing their impact. A particular theme that emerges from the overview is the range of systematic differences between types of study groups (e.g., between patients and controls) that may influence resting-state study results. PMID:22964258

  19. GPi oscillatory activity differentiates tics from the resting state, voluntary movements, and the unmedicated parkinsonian state

    Directory of Open Access Journals (Sweden)

    Joohi Jimenez-Shahed

    2016-09-01

    Full Text Available 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 (13-30Hz at rest which consistently modulated the amplitude of the co-existent HFOs observed between 200-400Hz, indicating the presence of beta-HFO CFC. In all 3 TS patients at rest, we observed theta band activity (4-7Hz and HFOs. Two patients had beta band activity, though at lower power than theta oscillations. Tic activity was associated with increased high frequency (200-400Hz and gamma band (35-200Hz activity. There was no beta-HFO CFC in TS patients at rest. However, CFC between the phase of 5-10Hz 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, resting

  20. Resting States Are Resting Traits – An fMRI Study of Sex Differences and Menstrual Cycle Effects in Resting State Cognitive Control Networks

    OpenAIRE

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

    2014-01-01

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

  1. 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.

  2. Resting-state fMRI study of patients with fragile X syndrome

    Science.gov (United States)

    Isanova, E.; Petrovskiy, E.; Savelov, A.; Yudkin, D.; Tulupov, A.

    2017-08-01

    The study aimed to assess the neural activity of different brain regions in patients with fragile X syndrome (FXS) and the healthy volunteers by resting-state functional magnetic resonance imaging (fMRI) on a 1.5 T MRI Achieva scanner (Philips). Results: The fMRI study showed a DMN of brain function in patients with FXS, as well as in the healthy volunteers. Furthermore, it was found that a default mode network of the brain in patients with FXS and healthy volunteers does not have statistically significant differences (p>0.05), which may indicate that the basal activity of neurons in patients with FXS is not reduced. In addition, we have found a significant (pright inferior parietal and right angular gyrus in the resting state in patients with FXS. Conclusion: New data of functional status of the brain in patients with FXS were received. The significant increase in the resting state functional connectivity within the right inferior parietal and right angular gyrus (p<0.001) in patients with FXS was found.

  3. Resting state functional connectivity changes in adults with developmental stuttering: an initial sLORETA study.

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    Kathleen eJoos

    2014-10-01

    Full Text Available Introduction: Stuttering is defined as speech characterized by verbal dysfluencies, but should not be seen as an isolated speech disorder, but as a generalized sensorimotor timing deficit due to impaired communication between speech related brain areas. Therefore we focused on resting state brain activity and functional connectivity.Method: We included 11 patients with developmental stuttering and 11 age matched controls. To objectify stuttering severity and the impact on the quality of life (QoL, we used the Dutch validated Test for Stuttering Severity-Readers (TSS-R and the Overall Assessment of the Speaker’s Experience of Stuttering (OASES, respectively. Furthermore, we used standardized low resolution brain electromagnetic tomography (sLORETA analyses to look at resting state activity and functional connectivity differences and their correlations with the TSS-R and OASES.Results: No resting state activity differences were identified in comparison to fluently speaking controls or in correlation with stuttering severity or QoL measures. Significant alterations in resting state functional connectivity were found, predominantly interhemispheric, i.e. a decreased functional connectivity for high frequency oscillations (beta and gamma between motor speech areas (BA44 and 45 and the contralateral premotor (BA 6 and motor (BA 4 areas. A positive correlation was found between functional connectivity at low frequency oscillations (theta and alpha and stuttering severity, while a mixed increased and decreased functional connectivity at low and high frequency oscillations correlated with QoL.Discussion: PWS are characterized by decreased high frequency interhemispheric functional connectivity between motor speech, premotor and motor areas in the resting state, while higher functional connectivity in the low frequency bands indicates more severe speech disturbances, suggesting that increased interhemispheric and right sided functional connectivity is

  4. Antiproton-neutron annihilations at rest: Search for broad states

    International Nuclear Information System (INIS)

    Kalogeropoulos, T.E.

    1985-01-01

    The searches so far for meson states produced in p-bar annihilations at rest into π+X have been sensitive to narrow X states. The combinatorial background and the narrow phase space width in missing mass spectra are the main problems. Most of the theoretical models predict broad states. We have measured in a high statistis experiment p-bar(at rest)d→π/sup +- /+Anything inclusive spectra. Using a novel analysis technique the π + π - difference spectra, it is shown that the p-barn annihilation is dominated by two-body cascades. Two new states of opposite G-parity of (mass, width) = (1480, 100) MeV/c 2 are dominant. The G = +1 state has a large decay branching ratio into rho 0 rho 0 . Other features are presented

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

    Science.gov (United States)

    Rondinoni, C; Amaro, E; Cendes, F; dos Santos, A C; Salmon, C E G

    2013-04-01

    Functional MRI (fMRI) resting-state experiments are aimed at identifying brain networks that support basal brain function. Although most investigators consider a 'resting-state' fMRI experiment with no specific external stimulation, subjects are unavoidably under heavy acoustic noise produced by the equipment. In the present study, we evaluated the influence of auditory input on the resting-state networks (RSNs). Twenty-two healthy subjects were scanned using two similar echo-planar imaging sequences in the same 3T MRI scanner: a default pulse sequence and a reduced "silent" pulse sequence. Experimental sessions consisted of two consecutive 7-min runs with noise conditions (default or silent) counterbalanced across subjects. A self-organizing group independent component analysis was applied to fMRI data in order to recognize the RSNs. The insula, left middle frontal gyrus and right precentral and left inferior parietal lobules showed significant differences in the voxel-wise comparison between RSNs depending on noise condition. In the presence of low-level noise, these areas Granger-cause oscillations in RSNs with cognitive implications (dorsal attention and entorhinal), while during high noise acquisition, these connectivities are reduced or inverted. Applying low noise MR acquisitions in research may allow the detection of subtle differences of the RSNs, with implications in experimental planning for resting-state studies, data analysis, and ergonomic factors.

  6. Caffeine reduces resting-state BOLD functional connectivity in the motor cortex.

    Science.gov (United States)

    Rack-Gomer, Anna Leigh; Liau, Joy; Liu, Thomas T

    2009-05-15

    In resting-state functional magnetic resonance imaging (fMRI), correlations between spontaneous low-frequency fluctuations in the blood oxygenation level dependent (BOLD) signal are used to assess functional connectivity between different brain regions. Changes in resting-state BOLD connectivity measures are typically interpreted as changes in coherent neural activity across spatially distinct brain regions. However, this interpretation can be complicated by the complex dependence of the BOLD signal on both neural and vascular factors. For example, prior studies have shown that vasoactive agents that alter baseline cerebral blood flow, such as caffeine and carbon dioxide, can significantly alter the amplitude and dynamics of the task-related BOLD response. In this study, we examined the effect of caffeine (200 mg dose) on resting-state BOLD connectivity in the motor cortex across a sample of healthy young subjects (N=9). We found that caffeine significantly (pcaffeine. These results suggest that caffeine usage should be carefully considered in the design and interpretation of resting-state BOLD fMRI studies.

  7. 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.

  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. Bayesian network analysis revealed the connectivity difference of the default mode network from the resting-state to task-state

    Science.gov (United States)

    Wu, Xia; Yu, Xinyu; Yao, Li; Li, Rui

    2014-01-01

    Functional magnetic resonance imaging (fMRI) studies have converged to reveal the default mode network (DMN), a constellation of regions that display co-activation during resting-state but co-deactivation during attention-demanding tasks in the brain. Here, we employed a Bayesian network (BN) analysis method to construct a directed effective connectivity model of the DMN and compared the organizational architecture and interregional directed connections under both resting-state and task-state. The analysis results indicated that the DMN was consistently organized into two closely interacting subsystems in both resting-state and task-state. The directed connections between DMN regions, however, changed significantly from the resting-state to task-state condition. The results suggest that the DMN intrinsically maintains a relatively stable structure whether at rest or performing tasks but has different information processing mechanisms under varied states. PMID:25309414

  10. 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…

  11. Infraslow Electroencephalographic and Dynamic Resting State Network Activity.

    Science.gov (United States)

    Grooms, Joshua K; Thompson, Garth J; Pan, Wen-Ju; Billings, Jacob; Schumacher, Eric H; Epstein, Charles M; Keilholz, Shella D

    2017-06-01

    A number of studies have linked the blood oxygenation level dependent (BOLD) signal to electroencephalographic (EEG) signals in traditional frequency bands (δ, θ, α, β, and γ), but the relationship between BOLD and its direct frequency correlates in the infraslow band (resting state magnetic resonance imaging data were acquired simultaneously. The DC EEG signals were correlated with the BOLD signal in patterns that resembled resting state networks. Subsequent dynamic analysis showed that the correlation between DC EEG and the BOLD signal varied substantially over time, even within individual subjects. The variation in DC EEG appears to reflect the time-varying contribution of different resting state networks. Furthermore, some of the patterns of DC EEG and BOLD correlation are consistent with previous work demonstrating quasiperiodic spatiotemporal patterns of large-scale network activity in resting state. These findings demonstrate that infraslow electrical activity is linked to BOLD fluctuations in humans and that it may provide a basis for large-scale organization comparable to that observed in animal studies.

  12. 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.

  13. Effects of Methylphenidate on Resting-State Functional Connectivity of the Mesocorticolimbic Dopamine Pathways in Cocaine Addiction

    Energy Technology Data Exchange (ETDEWEB)

    Konova, Anna B.; Moeller, Scott J.; Tomasi, Dardo; Volkow, Nora D.; Goldstein, Rita Z.

    2013-08-01

    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. 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.

  14. Changes in Resting-State Connectivity following Melody-Based Therapy in a Patient with Aphasia

    OpenAIRE

    Bitan, Tali; Simic, Tijana; Saverino, Cristina; Jones, Cheryl; Glazer, Joanna; Collela, Brenda; Wiseman-Hakes, Catherine; Green, Robin; Rochon, Elizabeth

    2018-01-01

    Melody-based treatments for patients with aphasia rely on the notion of preserved musical abilities in the RH, following left hemisphere damage. However, despite evidence for their effectiveness, the role of the RH is still an open question. We measured changes in resting-state functional connectivity following melody-based intervention, to identify lateralization of treatment-related changes. A patient with aphasia due to left frontal and temporal hemorrhages following traumatic brain injuri...

  15. Gender differences in brain activity and the relationship between brain activity and differences in prevalence rates between male and female major depressive disorder patients: a resting-state fMRI study.

    Science.gov (United States)

    Yao, Zhijian; Yan, Rui; Wei, Maobin; Tang, Hao; Qin, Jiaolong; Lu, Qing

    2014-11-01

    We examined the gender-difference effect on abnormal spontaneous neuronal activity of male and female major depressive disorder (MDD) patients using the amplitude of low-frequency fluctuation (ALFF) and the further clarified the relationship between the abnormal ALFF and differences in MDD prevalence rates between male and female patients. Fourteen male MDD patients, 13 female MDD patients and 15 male and 15 female well matched healthy controls (HCs) completed this study. The ALFF approach was used, and Pearson correlation was conducted to observe a possible clinical relevance. There were widespread differences in ALFF values between female and male MDD patients, including some important parts of the frontoparietal network, auditory network, attention network and cerebellum network. In female MDD patients, there was a positive correlation between average ALFF values of the left postcentral gyrus and the severity of weight loss symptom. The gender-difference effect leading to abnormal brain activity is an important underlying pathomechanism for different somatic symptoms in MDD patients of different genders and is likely suggestive of higher MDD prevalence rates in females. The abnormal ALFF resulting from the gender-difference effect might improve our understanding of the differences in prevalence rates between male and female MDD patients from another perspective. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  16. 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

  17. 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.

  18. Enhanced subject-specific resting-state network detection and extraction with fast fMRI.

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    Akin, Burak; Lee, Hsu-Lei; Hennig, Jürgen; LeVan, Pierre

    2017-02-01

    Resting-state networks have become an important tool for the study of brain function. An ultra-fast imaging technique that allows to measure brain function, called Magnetic Resonance Encephalography (MREG), achieves an order of magnitude higher temporal resolution than standard echo-planar imaging (EPI). This new sequence helps to correct physiological artifacts and improves the sensitivity of the fMRI analysis. In this study, EPI is compared with MREG in terms of capability to extract resting-state networks. Healthy controls underwent two consecutive resting-state scans, one with EPI and the other with MREG. Subject-level independent component analyses (ICA) were performed separately for each of the two datasets. Using Stanford FIND atlas parcels as network templates, the presence of ICA maps corresponding to each network was quantified in each subject. The number of detected individual networks was significantly higher in the MREG data set than for EPI. Moreover, using short time segments of MREG data, such as 50 seconds, one can still detect and track consistent networks. Fast fMRI thus results in an increased capability to extract distinct functional regions at the individual subject level for the same scan times, and also allow the extraction of consistent networks within shorter time intervals than when using EPI, which is notably relevant for the analysis of dynamic functional connectivity fluctuations. Hum Brain Mapp 38:817-830, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  19. Dynamic brain glucose metabolism identifies anti-correlated cortical-cerebellar networks at rest.

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    Tomasi, Dardo G; Shokri-Kojori, Ehsan; Wiers, Corinde E; Kim, Sunny W; Demiral, Şukru B; Cabrera, Elizabeth A; Lindgren, Elsa; Miller, Gregg; Wang, Gene-Jack; Volkow, Nora D

    2017-12-01

    It remains unclear whether resting state functional magnetic resonance imaging (rfMRI) networks are associated with underlying synchrony in energy demand, as measured by dynamic 2-deoxy-2-[ 18 F]fluoroglucose (FDG) positron emission tomography (PET). We measured absolute glucose metabolism, temporal metabolic connectivity (t-MC) and rfMRI patterns in 53 healthy participants at rest. Twenty-two rfMRI networks emerged from group independent component analysis (gICA). In contrast, only two anti-correlated t-MC emerged from FDG-PET time series using gICA or seed-voxel correlations; one included frontal, parietal and temporal cortices, the other included the cerebellum and medial temporal regions. Whereas cerebellum, thalamus, globus pallidus and calcarine cortex arose as the strongest t-MC hubs, the precuneus and visual cortex arose as the strongest rfMRI hubs. The strength of the t-MC linearly increased with the metabolic rate of glucose suggesting that t-MC measures are strongly associated with the energy demand of the brain tissue, and could reflect regional differences in glucose metabolism, counterbalanced metabolic network demand, and/or differential time-varying delivery of FDG. The mismatch between metabolic and functional connectivity patterns computed as a function of time could reflect differences in the temporal characteristics of glucose metabolism as measured with PET-FDG and brain activation as measured with rfMRI.

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

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

    2016-01-01

    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

  1. 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

  2. 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.

  3. Quantifying fluctuations of resting state networks using arterial spin labeling perfusion MRI.

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    Dai, Weiying; Varma, Gopal; Scheidegger, Rachel; Alsop, David C

    2016-03-01

    Blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) has been widely used to investigate spontaneous low-frequency signal fluctuations across brain resting state networks. However, BOLD only provides relative measures of signal fluctuations. Arterial Spin Labeling (ASL) MRI holds great potential for quantitative measurements of resting state network fluctuations. This study systematically quantified signal fluctuations of the large-scale resting state networks using ASL data from 20 healthy volunteers by separating them from global signal fluctuations and fluctuations caused by residual noise. Global ASL signal fluctuation was 7.59% ± 1.47% relative to the ASL baseline perfusion. Fluctuations of seven detected resting state networks vary from 2.96% ± 0.93% to 6.71% ± 2.35%. Fluctuations of networks and residual noise were 6.05% ± 1.18% and 6.78% ± 1.16% using 4-mm resolution ASL data applied with Gaussian smoothing kernel of 6mm. However, network fluctuations were reduced by 7.77% ± 1.56% while residual noise fluctuation was markedly reduced by 39.75% ± 2.90% when smoothing kernel of 12 mm was applied to the ASL data. Therefore, global and network fluctuations are the dominant structured noise sources in ASL data. Quantitative measurements of resting state networks may enable improved noise reduction and provide insights into the function of healthy and diseased brain. © The Author(s) 2015.

  4. Modeling resting-state functional networks when the cortex falls asleep: local and global changes.

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    Deco, Gustavo; Hagmann, Patric; Hudetz, Anthony G; Tononi, Giulio

    2014-12-01

    The transition from wakefulness to sleep represents the most conspicuous change in behavior and the level of consciousness occurring in the healthy brain. It is accompanied by similarly conspicuous changes in neural dynamics, traditionally exemplified by the change from "desynchronized" electroencephalogram activity in wake to globally synchronized slow wave activity of early sleep. However, unit and local field recordings indicate that the transition is more gradual than it might appear: On one hand, local slow waves already appear during wake; on the other hand, slow sleep waves are only rarely global. Studies with functional magnetic resonance imaging also reveal changes in resting-state functional connectivity (FC) between wake and slow wave sleep. However, it remains unclear how resting-state networks may change during this transition period. Here, we employ large-scale modeling of the human cortico-cortical anatomical connectivity to evaluate changes in resting-state FC when the model "falls asleep" due to the progressive decrease in arousal-promoting neuromodulation. When cholinergic neuromodulation is parametrically decreased, local slow waves appear, while the overall organization of resting-state networks does not change. Furthermore, we show that these local slow waves are structured macroscopically in networks that resemble the resting-state networks. In contrast, when the neuromodulator decrease further to very low levels, slow waves become global and resting-state networks merge into a single undifferentiated, broadly synchronized network. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  5. Resting-state functional connectivity differentiates anxious apprehension and anxious arousal.

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    Burdwood, Erin N; Infantolino, Zachary P; Crocker, Laura D; Spielberg, Jeffrey M; Banich, Marie T; Miller, Gregory A; Heller, Wendy

    2016-10-01

    Brain regions in the default mode network (DMN) display greater functional connectivity at rest or during self-referential processing than during goal-directed tasks. The present study assessed resting-state connectivity as a function of anxious apprehension and anxious arousal, independent of depressive symptoms, in order to understand how these dimensions disrupt cognition. Whole-brain, seed-based analyses indicated differences between anxious apprehension and anxious arousal in DMN functional connectivity. Lower connectivity associated with higher anxious apprehension suggests decreased adaptive, inner-focused thought processes, whereas higher connectivity at higher levels of anxious arousal may reflect elevated monitoring of physiological responses to threat. These findings further the conceptualization of anxious apprehension and anxious arousal as distinct psychological dimensions with distinct neural instantiations. © 2016 Society for Psychophysiological Research.

  6. The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?

    Science.gov (United States)

    Murphy, Kevin; Birn, Rasmus M; Handwerker, Daniel A; Jones, Tyler B; Bandettini, Peter A

    2009-02-01

    Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step.

  7. Localized reductions in resting-state functional connectivity in children with prenatal alcohol exposure.

    Science.gov (United States)

    Fan, Jia; Taylor, Paul A; Jacobson, Sandra W; Molteno, Christopher D; Gohel, Suril; Biswal, Bharat B; Jacobson, Joseph L; Meintjes, Ernesta M

    2017-10-01

    Fetal alcohol spectrum disorders (FASD) are characterized by impairment in cognitive function that may or may not be accompanied by craniofacial anomalies, microcephaly, and/or growth retardation. Resting-state functional MRI (rs-fMRI), which examines the low-frequency component of the blood oxygen level dependent (BOLD) signal in the absence of an explicit task, provides an efficient and powerful mechanism for studying functional brain networks even in low-functioning and young subjects. Studies using independent component analysis (ICA) have identified a set of resting-state networks (RSNs) that have been linked to distinct domains of cognitive and perceptual function, which are believed to reflect the intrinsic functional architecture of the brain. This study is the first to examine resting-state functional connectivity within these RSNs in FASD. Rs-fMRI scans were performed on 38 children with FASD (19 with either full fetal alcohol syndrome (FAS) or partial FAS (PFAS), 19 nonsyndromal heavily exposed (HE)), and 19 controls, mean age 11.3 ± 0.9 years, from the Cape Town Longitudinal Cohort. Nine resting-state networks were generated by ICA. Voxelwise group comparison between a combined FAS/PFAS group and controls revealed localized dose-dependent functional connectivity reductions in five regions in separate networks: anterior default mode, salience, ventral and dorsal attention, and R executive control. The former three also showed lower connectivity in the HE group. Gray matter connectivity deficits in four of the five networks appear to be related to deficits in white matter tracts that provide intra-RSN connections. Hum Brain Mapp 38:5217-5233, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  8. Altered intrinsic organisation of brain networks implicated in attentional processes in adult attention-deficit/hyperactivity disorder: a resting-state study of attention, default mode and salience network connectivity.

    Science.gov (United States)

    Sidlauskaite, Justina; Sonuga-Barke, Edmund; Roeyers, Herbert; Wiersema, Jan R

    2016-06-01

    Deficits in task-related attentional engagement in attention-deficit/hyperactivity disorder (ADHD) have been hypothesised to be due to altered interrelationships between attention, default mode and salience networks. We examined the intrinsic connectivity during rest within and between these networks. Six-minute resting-state scans were obtained. Using a network-based approach, connectivity within and between the dorsal and ventral attention, the default mode and the salience networks was compared between the ADHD and control group. The ADHD group displayed hyperconnectivity between the two attention networks and within the default mode and ventral attention network. The salience network was hypoconnected to the dorsal attention network. There were trends towards hyperconnectivity within the dorsal attention network and between the salience and ventral attention network in ADHD. Connectivity within and between other networks was unrelated to ADHD. Our findings highlight the altered connectivity within and between attention networks, and between them and the salience network in ADHD. One hypothesis to be tested in future studies is that individuals with ADHD are affected by an imbalance between ventral and dorsal attention systems with the former playing a dominant role during task engagement, making individuals with ADHD highly susceptible to distraction by salient task-irrelevant stimuli.

  9. Resting-State Functional Connectivity and Cognitive Impairment in Children with Perinatal Stroke

    Directory of Open Access Journals (Sweden)

    Nigul Ilves

    2016-01-01

    Full Text Available Perinatal stroke is a leading cause of congenital hemiparesis and neurocognitive deficits in children. Dysfunctions in the large-scale resting-state functional networks may underlie cognitive and behavioral disability in these children. We studied resting-state functional connectivity in patients with perinatal stroke collected from the Estonian Pediatric Stroke Database. Neurodevelopment of children was assessed by the Pediatric Stroke Outcome Measurement and the Kaufman Assessment Battery. The study included 36 children (age range 7.6–17.9 years: 10 with periventricular venous infarction (PVI, 7 with arterial ischemic stroke (AIS, and 19 controls. There were no differences in severity of hemiparesis between the PVI and AIS groups. A significant increase in default mode network connectivity (FDR 0.1 and lower cognitive functions (p<0.05 were found in children with AIS compared to the controls and the PVI group. The children with PVI had no significant differences in the resting-state networks compared to the controls and their cognitive functions were normal. Our findings demonstrate impairment in cognitive functions and neural network profile in hemiparetic children with AIS compared to children with PVI and controls. Changes in the resting-state networks found in children with AIS could possibly serve as the underlying derangements of cognitive brain functions in these children.

  10. Electrophysiological resting-state biomarker for diagnosing mesial temporal lobe epilepsy with hippocampal sclerosis.

    Science.gov (United States)

    Jin, Seung-Hyun; Chung, Chun Kee

    2017-01-01

    The main aim of the present study was to evaluate whether resting-state functional connectivity of magnetoencephalography (MEG) signals can differentiate patients with mesial temporal lobe epilepsy (MTLE) from healthy controls (HC) and can differentiate between right and left MTLE as a diagnostic biomarker. To this end, a support vector machine (SVM) method among various machine learning algorithms was employed. We compared resting-state functional networks between 46 MTLE (right MTLE=23; left MTLE=23) patients with histologically proven HS who were free of seizure after surgery, and 46 HC. The optimal SVM group classifier distinguished MTLE patients with a mean accuracy of 95.1% (sensitivity=95.8%; specificity=94.3%). Increased connectivity including the right posterior cingulate gyrus and decreased connectivity including at least one sensory-related resting-state network were key features reflecting the differences between MTLE patients and HC. The optimal SVM model distinguished between right and left MTLE patients with a mean accuracy of 76.2% (sensitivity=76.0%; specificity=76.5%). We showed the potential of electrophysiological resting-state functional connectivity, which reflects brain network reorganization in MTLE patients, as a possible diagnostic biomarker to differentiate MTLE patients from HC and differentiate between right and left MTLE patients. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. Altered resting-state functional connectivity in women with chronic fatigue syndrome.

    Science.gov (United States)

    Kim, Byung-Hoon; Namkoong, Kee; Kim, Jae-Jin; Lee, Seojung; Yoon, Kang Joon; Choi, Moonjong; Jung, Young-Chul

    2015-12-30

    The biological underpinnings of the psychological factors characterizing chronic fatigue syndrome (CFS) have not been extensively studied. Our aim was to evaluate alterations of resting-state functional connectivity in CFS patients. Participants comprised 18 women with CFS and 18 age-matched female healthy controls who were recruited from the local community. Structural and functional magnetic resonance images were acquired during a 6-min passive-viewing block scan. Posterior cingulate cortex seeded resting-state functional connectivity was evaluated, and correlation analyses of connectivity strength were performed. Graph theory analysis of 90 nodes of the brain was conducted to compare the global and local efficiency of connectivity networks in CFS patients with that in healthy controls. The posterior cingulate cortex in CFS patients showed increased resting-state functional connectivity with the dorsal and rostral anterior cingulate cortex. Connectivity strength of the posterior cingulate cortex to the dorsal anterior cingulate cortex significantly correlated with the Chalder Fatigue Scale score, while the Beck Depression Inventory (BDI) score was controlled. Connectivity strength to the rostral anterior cingulate cortex significantly correlated with the Chalder Fatigue Scale score. Global efficiency of the posterior cingulate cortex was significantly lower in CFS patients, while local efficiency showed no difference from findings in healthy controls. The findings suggest that CFS patients show inefficient increments in resting-state functional connectivity that are linked to the psychological factors observed in the syndrome. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  12. Changes in community structure of resting state functional connectivity in unipolar depression.

    Directory of Open Access Journals (Sweden)

    Anton Lord

    Full Text Available Major depression is a prevalent disorder that imposes a significant burden on society, yet objective laboratory-style tests to assist in diagnosis are lacking. We employed network-based analyses of "resting state" functional neuroimaging data to ascertain group differences in the endogenous cortical activity between healthy and depressed subjects.We additionally sought to use machine learning techniques to explore the ability of these network-based measures of resting state activity to provide diagnostic information for depression. Resting state fMRI data were acquired from twenty two depressed outpatients and twenty two healthy subjects matched for age and gender. These data were anatomically parcellated and functional connectivity matrices were then derived using the linear correlations between the BOLD signal fluctuations of all pairs of cortical and subcortical regions.We characterised the hierarchical organization of these matrices using network-based matrics, with an emphasis on their mid-scale "modularity" arrangement. Whilst whole brain measures of organization did not differ between groups, a significant rearrangement of their community structure was observed. Furthermore we were able to classify individuals with a high level of accuracy using a support vector machine, primarily through the use of a modularity-based metric known as the participation index.In conclusion, the application of machine learning techniques to features of resting state fMRI network activity shows promising potential to assist in the diagnosis of major depression, now suggesting the need for validation in independent data sets.

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

    Science.gov (United States)

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

    2016-04-27

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

  14. Influence of Anodal Transcranial Direct Current Stimulation (tDCS) over the Right Angular Gyrus on Brain Activity during Rest

    Science.gov (United States)

    Clemens, Benjamin; Jung, Stefanie; Mingoia, Gianluca; Weyer, David; Domahs, Frank; Willmes, Klaus

    2014-01-01

    Although numerous studies examined resting-state networks (RSN) in the human brain, so far little is known about how activity within RSN might be modulated by non-invasive brain stimulation applied over parietal cortex. Investigating changes in RSN in response to parietal cortex stimulation might tell us more about how non-invasive techniques such as transcranial direct current stimulation (tDCS) modulate intrinsic brain activity, and further elaborate our understanding of how the resting brain responds to external stimulation. Here we examined how activity within the canonical RSN changed in response to anodal tDCS applied over the right angular gyrus (AG). We hypothesized that changes in resting-state activity can be induced by a single tDCS session and detected with functional magnetic resonance imaging (fMRI). Significant differences between two fMRI sessions (pre-tDCS and post-tDCS) were found in several RSN, including the cerebellar, medial visual, sensorimotor, right frontoparietal, and executive control RSN as well as the default mode and the task positive network. The present results revealed decreased and increased RSN activity following tDCS. Decreased RSN activity following tDCS was found in bilateral primary and secondary visual areas, and in the right putamen. Increased RSN activity following tDCS was widely distributed across the brain, covering thalamic, frontal, parietal and occipital regions. From these exploratory results we conclude that a single session of anodal tDCS over the right AG is sufficient to induce large-scale changes in resting-state activity. These changes were localized in sensory and cognitive areas, covering regions close to and distant from the stimulation site. PMID:24760013

  15. Influence of anodal transcranial direct current stimulation (tDCS) over the right angular gyrus on brain activity during rest.

    Science.gov (United States)

    Clemens, Benjamin; Jung, Stefanie; Mingoia, Gianluca; Weyer, David; Domahs, Frank; Willmes, Klaus

    2014-01-01

    Although numerous studies examined resting-state networks (RSN) in the human brain, so far little is known about how activity within RSN might be modulated by non-invasive brain stimulation applied over parietal cortex. Investigating changes in RSN in response to parietal cortex stimulation might tell us more about how non-invasive techniques such as transcranial direct current stimulation (tDCS) modulate intrinsic brain activity, and further elaborate our understanding of how the resting brain responds to external stimulation. Here we examined how activity within the canonical RSN changed in response to anodal tDCS applied over the right angular gyrus (AG). We hypothesized that changes in resting-state activity can be induced by a single tDCS session and detected with functional magnetic resonance imaging (fMRI). Significant differences between two fMRI sessions (pre-tDCS and post-tDCS) were found in several RSN, including the cerebellar, medial visual, sensorimotor, right frontoparietal, and executive control RSN as well as the default mode and the task positive network. The present results revealed decreased and increased RSN activity following tDCS. Decreased RSN activity following tDCS was found in bilateral primary and secondary visual areas, and in the right putamen. Increased RSN activity following tDCS was widely distributed across the brain, covering thalamic, frontal, parietal and occipital regions. From these exploratory results we conclude that a single session of anodal tDCS over the right AG is sufficient to induce large-scale changes in resting-state activity. These changes were localized in sensory and cognitive areas, covering regions close to and distant from the stimulation site.

  16. Gray matter deficits and altered resting-state connectivity in the superior temporal gyrus among individuals with problematic hypersexual behavior.

    Science.gov (United States)

    Seok, Ji-Woo; Sohn, Jin-Hun

    2018-04-01

    Neuroimaging studies on the characteristics of hypersexual disorder have been accumulating, yet alternations in brain structures and functional connectivity in individuals with problematic hypersexual behavior (PHB) has only recently been studied. This study aimed to investigate gray matter deficits and resting-state abnormalities in individuals with PHB using voxel-based morphometry and resting-state connectivity analysis. Seventeen individuals with PHB and 19 age-matched healthy controls participated in this study. Gray matter volume of the brain and resting-state connectivity were measured using 3T magnetic resonance imaging. Compared to healthy subjects, individuals with PHB had significant reductions in gray matter volume in the left superior temporal gyrus (STG) and right middle temporal gyrus. Individuals with PHB also exhibited a decrease in resting-state functional connectivity between the left STG and left precuneus and between the left STG and right caudate. The gray matter volume of the left STG and its resting-state functional connectivity with the right caudate both showed significant negative correlations with the severity of PHB. The findings suggest that structural deficits and resting-state functional impairments in the left STG might be linked to PHB and provide new insights into the underlying neural mechanisms of PHB. Copyright © 2018 Elsevier B.V. All rights reserved.

  17. Abnormal Resting-State Functional Connectivity in Progressive Supranuclear Palsy and Corticobasal Syndrome

    Directory of Open Access Journals (Sweden)

    Komal Bharti

    2017-06-01

    Full Text Available BackgroundPathological and MRI-based evidence suggests that multiple brain structures are likely to be involved in functional disconnection between brain areas. Few studies have investigated resting-state functional connectivity (rsFC in progressive supranuclear palsy (PSP and corticobasal syndrome (CBS. In this study, we investigated within- and between-network rsFC abnormalities in these two conditions.MethodsTwenty patients with PSP, 11 patients with CBS, and 16 healthy subjects (HS underwent a resting-state fMRI study. Resting-state networks (RSNs were extracted to evaluate within- and between-network rsFC using the Melodic and FSLNets software packages.ResultsIncreased within-network rsFC was observed in both PSP and CBS patients, with a larger number of RSNs being involved in CBS. Within-network cerebellar rsFC positively correlated with mini-mental state examination scores in patients with PSP. Compared to healthy volunteers, PSP and CBS patients exhibit reduced functional connectivity between the lateral visual and auditory RSNs, with PSP patients additionally showing lower functional connectivity between the cerebellar and insular RSNs. Moreover, rsFC between the salience and executive-control RSNs was increased in patients with CBS compared to HS.ConclusionThis study provides evidence of functional brain reorganization in both PSP and CBS. Increased within-network rsFC could represent a higher degree of synchronization in damaged brain areas, while between-network rsFC abnormalities may mainly reflect degeneration of long-range white matter fibers.

  18. How restful is it with all that noise? Comparison of Interleaved silent steady state (ISSS) and conventional imaging in resting-state fMRI.

    Science.gov (United States)

    Andoh, J; Ferreira, M; Leppert, I R; Matsushita, R; Pike, B; Zatorre, R J

    2017-02-15

    Resting-state fMRI studies have become very important in cognitive neuroscience because they are able to identify BOLD fluctuations in brain circuits involved in motor, cognitive, or perceptual processes without the use of an explicit task. Such approaches have been fruitful when applied to various disordered populations, or to children or the elderly. However, insufficient attention has been paid to the consequences of the loud acoustic scanner noise associated with conventional fMRI acquisition, which could be an important confounding factor affecting auditory and/or cognitive networks in resting-state fMRI. Several approaches have been developed to mitigate the effects of acoustic noise on fMRI signals, including sparse sampling protocols and interleaved silent steady state (ISSS) acquisition methods, the latter being used only for task-based fMRI. Here, we developed an ISSS protocol for resting-state fMRI (rs-ISSS) consisting of rapid acquisition of a set of echo planar imaging volumes following each silent period, during which the steady state longitudinal magnetization was maintained with a train of relatively silent slice-selective excitation pulses. We evaluated the test-retest reliability of intensity and spatial extent of connectivity networks of fMRI BOLD signal across three different days for rs-ISSS and compared it with a standard resting-state fMRI (rs-STD). We also compared the strength and distribution of connectivity networks between rs-ISSS and rs-STD. We found that both rs-ISSS and rs-STD showed high reproducibility of fMRI signal across days. In addition, rs-ISSS showed a more robust pattern of functional connectivity within the somatosensory and motor networks, as well as an auditory network compared with rs-STD. An increased connectivity between the default mode network and the language network and with the anterior cingulate cortex (ACC) network was also found for rs-ISSS compared with rs-STD. Finally, region of interest analysis showed

  19. Brain REST/NRSF Is Not Only a Silent Repressor but Also an Active Protector.

    Science.gov (United States)

    Zhao, Yangang; Zhu, Min; Yu, Yanlan; Qiu, Linli; Zhang, Yuanyuan; He, Li; Zhang, Jiqiang

    2017-01-01

    During neurogenesis, specific transcription factors are needed to repress neuronal genes in nonneuronal cells to ensure precise development. Repressor element-1 binding transcription factor (REST), or neuron-restrictive silencer factor (NRSF), has been shown to be an important regulator for the establishment of neuronal specificity. It restricts the expression of neuronal genes by binding to the neuron-restrictive silencer element (NRSE/RE1) domain in neuron-specific genes. REST/NRSF regulates many target genes in stem cells, nonneural cells, and neurons, which are involved in neuronal differentiation, axonal growth, vesicular transport, and release as well as ionic conductance. However, it is also regulated by some cytokines/regulators such as epigenetic factors (microRNAs) and even its truncated isoform. REST/NRSF is widely detected in brain regions and has been shown to be highly expressed in nonneuronal cells, but current findings also reveal that, at least in the human brain, it is also highly expressed in neurons and increases with ageing. However, its loss in expression and cytoplasmic translocation seems to play a pivotal role in several human dementias. Additionally, REST/NRSF knockdown leads to malformations in nerve and nonneural tissues and embryonic lethality. Altered REST/NRSF expression has been not only related to deficient brain functions such as neurodegenerative diseases, mental disorders, brain tumors, and neurobehavioral disorders but also highly correlated to brain injuries such as alcoholism and stroke. Encouragingly, several compounds such as valproic acid and X5050 that target REST/NRSF have been shown to be clinically effective at rescuing seizures or Niemann-Pick type C disease. Surprisingly, studies have also shown that REST/NRSF can function as an activator to induce neuronal differentiation. These findings strongly indicate that REST/NRSF is not only a classical repressor to maintain normal neurogenesis, but it is also a fine

  20. Migraine classification using magnetic resonance imaging resting-state functional connectivity data.

    Science.gov (United States)

    Chong, Catherine D; Gaw, Nathan; Fu, Yinlin; Li, Jing; Wu, Teresa; Schwedt, Todd J

    2017-08-01

    Background This study used machine-learning techniques to develop discriminative brain-connectivity biomarkers from resting-state functional magnetic resonance neuroimaging ( rs-fMRI) data that distinguish between individual migraine patients and healthy controls. Methods This study included 58 migraine patients (mean age = 36.3 years; SD = 11.5) and 50 healthy controls (mean age = 35.9 years; SD = 11.0). The functional connections of 33 seeded pain-related regions were used as input for a brain classification algorithm that tested the accuracy of determining whether an individual brain MRI belongs to someone with migraine or to a healthy control. Results The best classification accuracy using a 10-fold cross-validation method was 86.1%. Resting functional connectivity of the right middle temporal, posterior insula, middle cingulate, left ventromedial prefrontal and bilateral amygdala regions best discriminated the migraine brain from that of a healthy control. Migraineurs with longer disease durations were classified more accurately (>14 years; 96.7% accuracy) compared to migraineurs with shorter disease durations (≤14 years; 82.1% accuracy). Conclusions Classification of migraine using rs-fMRI provides insights into pain circuits that are altered in migraine and could potentially contribute to the development of a new, noninvasive migraine biomarker. Migraineurs with longer disease burden were classified more accurately than migraineurs with shorter disease burden, potentially indicating that disease duration leads to reorganization of brain circuitry.

  1. The self and its resting state in consciousness: an investigation of the vegetative state.

    Science.gov (United States)

    Huang, Zirui; Dai, Rui; Wu, Xuehai; Yang, Zhi; Liu, Dongqiang; Hu, Jin; Gao, Liang; Tang, Weijun; Mao, Ying; Jin, Yi; Wu, Xing; Liu, Bin; Zhang, Yao; Lu, Lu; Laureys, Steven; Weng, Xuchu; Northoff, Georg

    2014-05-01

    Recent studies have demonstrated resting-state abnormalities in midline regions in vegetative state/unresponsive wakefulness syndrome and minimally conscious state patients. However, the functional implications of these resting-state abnormalities remain unclear. Recent findings in healthy subjects have revealed a close overlap between the neural substrate of self-referential processing and the resting-state activity in cortical midline regions. As such, we investigated task-related neural activity during active self-referential processing and various measures of resting-state activity in 11 patients with disorders of consciousness (DOC) and 12 healthy control subjects. Overall, the results revealed that DOC patients exhibited task-specific signal changes in anterior and posterior midline regions, including the perigenual anterior cingulate cortex (PACC) and posterior cingulate cortex (PCC). However, the degree of signal change was significantly lower in DOC patients compared with that in healthy subjects. Moreover, reduced signal differentiation in the PACC predicted the degree of consciousness in DOC patients. Importantly, the same midline regions (PACC and PCC) in DOC patients also exhibited severe abnormalities in the measures of resting-state activity, that is functional connectivity and the amplitude of low-frequency fluctuations. Taken together, our results provide the first evidence of neural abnormalities in both the self-referential processing and the resting state in midline regions in DOC patients. This novel finding has important implications for clinical utility and general understanding of the relationship between the self, the resting state, and consciousness. Copyright © 2013 Wiley Periodicals, Inc.

  2. Differential resting-state EEG patterns associated with comorbid depression in Internet addiction.

    Science.gov (United States)

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

    2014-04-03

    Many researchers have reported a relationship between Internet addiction and depression. In the present study, we compared the resting-state quantitative electroencephalography (QEEG) activity of treatment-seeking patients with comorbid Internet addiction and depression with those of treatment-seeking patients with Internet addiction without depression, and healthy controls to investigate the neurobiological markers that differentiate pure Internet addiction from Internet addiction with comorbid depression. Thirty-five patients diagnosed with Internet addiction and 34 age-, sex-, and IQ-matched healthy controls were enrolled in this study. Patients with Internet addiction were divided into two groups according to the presence (N=18) or absence (N=17) of depression. Resting-state, eye-closed QEEG was recorded, and the absolute and relative power of the brain were analyzed. The Internet addiction group without depression had decreased absolute delta and beta powers in all brain regions, whereas the Internet addiction group with depression had increased relative theta and decreased relative alpha power in all regions. These neurophysiological changes were not related to clinical variables. The current findings reflect differential resting-state QEEG patterns between both groups of participants with Internet addiction and healthy controls and also suggest that decreased absolute delta and beta powers are neurobiological markers of Internet addiction. Copyright © 2013 Elsevier Inc. All rights reserved.

  3. Neuroticism and Functional Connectomics of the Resting Adolescent Brain

    DEFF Research Database (Denmark)

    Baruël Johansen, Louise

    The personality trait neuroticism is a well-known risk factor for anxiety and mood disorders that typically have their onset in childhood and adolescence. This period is characterized by ongoing structural and functional maturation of the brain, which can be traced with magnetic resonance imaging...... network organization on the global level, while network characteristics of fronto-limbic regions, involved in emotional processing, are implicated on a local level. Little is known about neuroticism and functional brain organization in childhood and adolescence. The main aim of this thesis was therefore...

  4. Low frequency fluctuations in resting-state functional magnetic resonance imaging and their applications

    International Nuclear Information System (INIS)

    Küblböck, M.

    2015-01-01

    Over the course of the last two decades, functional magnetic resonance imaging (fMRI) has emerged as a widely used, highly accepted and very popular method for the assessment of neuronal activity in the human brain. It is a completely non-invasive imaging technique with high temporal resolution, which relies on the measurement of local differences in magnetic susceptibility between oxygenated and deoxygenated blood. Therefore, fMRI can be regarded as an indirect measure of neuronal activity via measurement of localised changes in cerebral blood flow and cerebral oxygen consumption. Maps of neuronal activity are calculated from fMRI data acquired either in the presence of an explicit task (task-based fMRI) or in absence of a task (resting-state fMRI). While in task-based fMRI task-specific patterns of brain activity are subject to research, resting-state fMRI reveals fundamental networks of intrinsic brain activity. These networks are characterized by low-frequency oscillations in the power spectrum of resting-state fMRI data. In the present work, we first introduce the physical principles and the technical background that allow us to measure these changes in blood oxygenation, followed by an introduction to the blood oxygenation level dependent (BOLD) effect and to analysis methods for both task-based and resting-state fMRI data. We also analyse the temporal signal-to-noise ratio (tSNR) of a novel 2D-EPI sequence, which allows the experimenter to acquire several slices simultaneously in order to assess the optimal parameter settings for this sequence at 3T. We then proceed to investigate the temporal properties of measures for the amplitude of low-frequency oscillations in resting-state fMRI data, which are regarded as potential biomarkers for a wide range of mental diseases in various clinical studies and show the high stability and robustness of these data, which are important prerequisites for application as a biomarker as well as their dependency on head motion

  5. Signal Sampling for Efficient Sparse Representation of Resting State FMRI Data

    Science.gov (United States)

    Ge, Bao; Makkie, Milad; Wang, Jin; Zhao, Shijie; Jiang, Xi; Li, Xiang; Lv, Jinglei; Zhang, Shu; Zhang, Wei; Han, Junwei; Guo, Lei; Liu, Tianming

    2015-01-01

    As the size of brain imaging data such as fMRI grows explosively, it provides us with unprecedented and abundant information about the brain. How to reduce the size of fMRI data but not lose much information becomes a more and more pressing issue. Recent literature studies tried to deal with it by dictionary learning and sparse representation methods, however, their computation complexities are still high, which hampers the wider application of sparse representation method to large scale fMRI datasets. To effectively address this problem, this work proposes to represent resting state fMRI (rs-fMRI) signals of a whole brain via a statistical sampling based sparse representation. First we sampled the whole brain’s signals via different sampling methods, then the sampled signals were aggregate into an input data matrix to learn a dictionary, finally this dictionary was used to sparsely represent the whole brain’s signals and identify the resting state networks. Comparative experiments demonstrate that the proposed signal sampling framework can speed-up by ten times in reconstructing concurrent brain networks without losing much information. The experiments on the 1000 Functional Connectomes Project further demonstrate its effectiveness and superiority. PMID:26646924

  6. Functional network centrality in obesity: A resting-state and task fMRI study.

    Science.gov (United States)

    García-García, Isabel; Jurado, María Ángeles; Garolera, Maite; Marqués-Iturria, Idoia; Horstmann, Annette; Segura, Bàrbara; Pueyo, Roser; Sender-Palacios, María José; Vernet-Vernet, Maria; Villringer, Arno; Junqué, Carme; Margulies, Daniel S; Neumann, Jane

    2015-09-30

    Obesity is associated with structural and functional alterations in brain areas that are often functionally distinct and anatomically distant. This suggests that obesity is associated with differences in functional connectivity of regions distributed across the brain. However, studies addressing whole brain functional connectivity in obesity remain scarce. Here, we compared voxel-wise degree centrality and eigenvector centrality between participants with obesity (n=20) and normal-weight controls (n=21). We analyzed resting state and task-related fMRI data acquired from the same individuals. Relative to normal-weight controls, participants with obesity exhibited reduced degree centrality in the right middle frontal gyrus in the resting-state condition. During the task fMRI condition, obese participants exhibited less degree centrality in the left middle frontal gyrus and the lateral occipital cortex along with reduced eigenvector centrality in the lateral occipital cortex and occipital pole. Our results highlight the central role of the middle frontal gyrus in the pathophysiology of obesity, a structure involved in several brain circuits signaling attention, executive functions and motor functions. Additionally, our analysis suggests the existence of task-dependent reduced centrality in occipital areas; regions with a role in perceptual processes and that are profoundly modulated by attention. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  7. 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.

  8. Decreased resting-state interhemispheric coordination in first-episode, drug-naive paranoid schizophrenia.

    Science.gov (United States)

    Guo, Wenbin; Xiao, Changqing; Liu, Guiying; Wooderson, Sarah C; Zhang, Zhikun; Zhang, Jian; Yu, Liuyu; Liu, Jianrong

    2014-01-03

    Dysconnectivity hypothesis posits that schizophrenia relates to abnormalities in neuronal connectivity. However, little is known about the alterations of the interhemispheric resting-state functional connectivity (FC) in patients with paranoid schizophrenia. In the present study, we used a newly developed voxel-mirrored homotopic connectivity (VMHC) method to investigate the interhemispheric FC of the whole brain in patients with paranoid schizophrenia at rest. Forty-nine first-episode, drug-naive patients with paranoid schizophrenia and 50 age-, gender-, and education-matched healthy subjects underwent a resting-state functional magnetic resonance imaging (fMRI) scans. An automated VMHC approach was used to analyze the data. Patients exhibited lower VMHC than healthy subjects in the precuneus (PCu), the precentral gyrus, the superior temporal gyrus (STG), the middle occipital gyrus (MOG), and the fusiform gyrus/cerebellum lobule VI. No region showed greater VMHC in the patient group than in the control group. Significantly negative correlation was observed between VMHC in the precentral gyrus and the PANSS positive/total scores, and between VMHC in the STG and the PANSS positive/negative/total scores. Our results suggest that interhemispheric resting-state FC of VMHC is reduced in paranoid schizophrenia with clinical implications for psychiatric symptomatology thus further contribute to the dysconnectivity hypothesis of schizophrenia. © 2013.

  9. Changes in resting-state functionally connected parietofrontal networks after videogame practice.

    Science.gov (United States)

    Martínez, Kenia; Solana, Ana Beatriz; Burgaleta, Miguel; Hernández-Tamames, Juan Antonio; Alvarez-Linera, Juan; Román, Francisco J; Alfayate, Eva; Privado, Jesús; Escorial, Sergio; Quiroga, María A; Karama, Sherif; Bellec, Pierre; Colom, Roberto

    2013-12-01

    Neuroimaging studies provide evidence for organized intrinsic activity under task-free conditions. This activity serves functionally relevant brain systems supporting cognition. Here, we analyze changes in resting-state functional connectivity after videogame practice applying a test-retest design. Twenty young females were selected from a group of 100 participants tested on four standardized cognitive ability tests. The practice and control groups were carefully matched on their ability scores. The practice group played during two sessions per week across 4 weeks (16 h total) under strict supervision in the laboratory, showing systematic performance improvements in the game. A group independent component analysis (GICA) applying multisession temporal concatenation on test-retest resting-state fMRI, jointly with a dual-regression approach, was computed. Supporting the main hypothesis, the key finding reveals an increased correlated activity during rest in certain predefined resting state networks (albeit using uncorrected statistics) attributable to practice with the cognitively demanding tasks of the videogame. Observed changes were mainly concentrated on parietofrontal networks involved in heterogeneous cognitive functions. Copyright © 2012 Wiley Periodicals, Inc.

  10. Predicting Risk-Taking Behavior from Prefrontal Resting-State Activity and Personality

    Science.gov (United States)

    Studer, Bettina; Pedroni, Andreas; Rieskamp, Jörg

    2013-01-01

    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. PMID:24116176

  11. Resting-state theta band connectivity and graph analysis in generalized social anxiety disorder.

    Science.gov (United States)

    Xing, Mengqi; Tadayonnejad, Reza; MacNamara, Annmarie; Ajilore, Olusola; DiGangi, Julia; Phan, K Luan; Leow, Alex; Klumpp, Heide

    2017-01-01

    Functional magnetic resonance imaging (fMRI) resting-state studies show generalized social anxiety disorder (gSAD) is associated with disturbances in networks involved in emotion regulation, emotion processing, and perceptual functions, suggesting a network framework is integral to elucidating the pathophysiology of gSAD. However, fMRI does not measure the fast dynamic interconnections of functional networks. Therefore, we examined whole-brain functional connectomics with electroencephalogram (EEG) during resting-state. Resting-state EEG data was recorded for 32 patients with gSAD and 32 demographically-matched healthy controls (HC). Sensor-level connectivity analysis was applied on EEG data by using Weighted Phase Lag Index (WPLI) and graph analysis based on WPLI was used to determine clustering coefficient and characteristic path length to estimate local integration and global segregation of networks. WPLI results showed increased oscillatory midline coherence in the theta frequency band indicating higher connectivity in the gSAD relative to HC group during rest. Additionally, WPLI values positively correlated with state anxiety levels within the gSAD group but not the HC group. Our graph theory based connectomics analysis demonstrated increased clustering coefficient and decreased characteristic path length in theta-based whole brain functional organization in subjects with gSAD compared to HC. Theta-dependent interconnectivity was associated with state anxiety in gSAD and an increase in information processing efficiency in gSAD (compared to controls). Results may represent enhanced baseline self-focused attention, which is consistent with cognitive models of gSAD and fMRI studies implicating emotion dysregulation and disturbances in task negative networks (e.g., default mode network) in gSAD.

  12. Initial angular momentum state in pp annihilation at rest

    CERN Document Server

    Bizzarri, R

    1972-01-01

    The author shows that no quantitative statement on the relative importance of initial P-states in pp annihilation can be made. Annihilations in flight indicate that P-wave annihilation into K/sub 1 //sup 0/K/sub 1//sup 0/ is inhibited while annihilation into pi pi is enhanced and might suggest a P-wave contamination approximately 10%. The observatory of the final state K/sub 1//sup 0/K/sub 1//sup 0/n from annihilations at rest indicates that the depression of the K/sub 1//sup 0/K/sub 1//sup 0/ final state is not so important and suggests a P-wave contamination smaller than 4%. Furthermore the successes obtained in the analysis of various final states on the assumption of S-wave annihilation are hard to reconcile with a P-wave contribution bigger than approximately 5%. (20 refs).

  13. 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

    2015-07-08

    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. Copyright © 2015 the authors 0270-6474/15/359786-13$15.00/0.

  14. 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.

  15. Superior colliculus resting state networks in post-traumatic stress disorder and its dissociative subtype.

    Science.gov (United States)

    Olivé, Isadora; Densmore, Maria; Harricharan, Sherain; Théberge, Jean; McKinnon, Margaret C; Lanius, Ruth

    2018-01-01

    The innate alarm system (IAS) models the neurocircuitry involved in threat processing in posttraumatic stress disorder (PTSD). Here, we investigate a primary subcortical structure of the IAS model, the superior colliculus (SC), where the SC is thought to contribute to the mechanisms underlying threat-detection in PTSD. Critically, the functional connectivity between the SC and other nodes of the IAS remains unexplored. We conducted a resting-state fMRI study to investigate the functional architecture of the IAS, focusing on connectivity of the SC in PTSD (n = 67), its dissociative subtype (n = 41), and healthy controls (n = 50) using region-of-interest seed-based analysis. We observed group-specific resting state functional connectivity between the SC for both PTSD and its dissociative subtype, indicative of dedicated IAS collicular pathways in each group of patients. When comparing PTSD to its dissociative subtype, we observed increased resting state functional connectivity between the left SC and the right dorsolateral prefrontal cortex (DLPFC) in PTSD. The DLPFC is involved in modulation of emotional processes associated with active defensive responses characterising PTSD. Moreover, when comparing PTSD to its dissociative subtype, increased resting state functional connectivity was observed between the right SC and the right temporoparietal junction in the dissociative subtype. The temporoparietal junction is involved in depersonalization responses associated with passive defensive responses typical of the dissociative subtype. Our findings suggest that unique resting state functional connectivity of the SC parallels the unique symptom profile and defensive responses observed in PTSD and its dissociative subtype. Hum Brain Mapp 39:563-574, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  16. Bupropion Administration Increases Resting-State Functional Connectivity in Dorso-Medial Prefrontal Cortex.

    Science.gov (United States)

    Rzepa, Ewelina; Dean, Zola; McCabe, Ciara

    2017-06-01

    Patients on the selective serotonergic reuptake inhibitors like citalopram report emotional blunting. We showed previously that citalopram reduces resting-state functional connectivity in healthy volunteers in a number of brain regions, including the dorso-medial prefrontal cortex, which may be related to its clinical effects. Bupropion is a dopaminergic and noradrenergic reuptake inhibitor and is not reported to cause emotional blunting. However, how bupropion affects resting-state functional connectivity in healthy controls remains unknown. Using a within-subjects, repeated-measures, double-blind, crossover design, we examined 17 healthy volunteers (9 female, 8 male). Volunteers received 7 days of bupropion (150 mg/d) and 7 days of placebo treatment and underwent resting-state functional Magnetic Resonance Imaging. We selected seed regions in the salience network (amygdala and pregenual anterior cingulate cortex) and the central executive network (dorsal medial prefrontal cortex). Mood and anhedonia measures were also recorded and examined in relation to resting-state functional connectivity. Relative to placebo, bupropion increased resting-state functional connectivity in healthy volunteers between the dorsal medial prefrontal cortex seed region and the posterior cingulate cortex and the precuneus cortex, key parts of the default mode network. These results are