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Large scale brain networks

Xueling Suo, Du Lei, Fuqin Chen, Min Wu, Lei Li, Ling Sun, Xiaoli Wei, Hongyan Zhu, Lingjiang Li, Graham J Kemp, Qiyong Gong
Purpose To use diffusion-tensor (DT) imaging and graph theory approaches to explore the brain structural connectome in pediatric posttraumatic stress disorder (PTSD). Materials and Methods This study was approved by the relevant research ethics committee, and all participants' parents or guardians provided informed consent. Twenty-four pediatric patients with PTSD and 23 control subjects exposed to trauma but without PTSD were recruited after the 2008 Sichuan earthquake. The structural connectome was constructed by using DT imaging tractography and thresholding the mean fractional anisotropy of 90 brain regions to yield 90 × 90 partial correlation matrixes...
October 25, 2016: Radiology
Michael F Regner, Naomi Saenz, Keeran Maharajh, Dorothy J Yamamoto, Brianne Mohl, Korey Wylie, Jason Tregellas, Jody Tanabe
OBJECTIVE: We hypothesized that compared to healthy controls, long-term abstinent substance dependent individuals (SDI) will differ in their effective connectivity between large-scale brain networks and demonstrate increased directional information from executive control to interoception-, reward-, and habit-related networks. In addition, using graph theory to compare network efficiencies we predicted decreased small-worldness in SDI compared to controls. METHODS: 50 SDI and 50 controls of similar sex and age completed psychological surveys and resting state fMRI...
2016: PloS One
Britta Wandschneider, Matthias J Koepp
Functional MRI studies have helped to elucidate underlying mechanisms in complex neurological and neuropsychiatric disorders. Disease processes often involve complex large-scale network interactions, extending beyond the presumed main disease focus. Given both the complexity of the clinical phenotype and the underlying dysfunctional brain circuits, so called pharmaco-fMRI (ph-MRI) studies probe pharmacological effects on functional neuro-anatomy, and can help to determine early treatment response, mechanisms of drug efficacy and side effects, and potentially advance CNS drug development...
2016: NeuroImage: Clinical
Hyejung Won, Luis de la Torre-Ubieta, Jason L Stein, Neelroop N Parikshak, Jerry Huang, Carli K Opland, Michael J Gandal, Gavin J Sutton, Farhad Hormozdiari, Daning Lu, Changhoon Lee, Eleazar Eskin, Irina Voineagu, Jason Ernst, Daniel H Geschwind
Three-dimensional physical interactions within chromosomes dynamically regulate gene expression in a tissue-specific manner. However, the 3D organization of chromosomes during human brain development and its role in regulating gene networks dysregulated in neurodevelopmental disorders, such as autism or schizophrenia, are unknown. Here we generate high-resolution 3D maps of chromatin contacts during human corticogenesis, permitting large-scale annotation of previously uncharacterized regulatory relationships relevant to the evolution of human cognition and disease...
October 19, 2016: Nature
Francesco Corrivetti, Guillaume Herbet, Sylvie Moritz-Gasser, Hugues Duffau
BACKGROUND: Face recognition is a complex function sustained by a distributed large-scale neural network, with a core system involving the ventral occipito-temporal cortex, the inferior longitudinal fasciculus (ILF) and the splenial commissural fibers. This circuit seems to be bilaterally organized, with however a right hemispheric dominance. According to this anatomo-functional model, prosopagnosia is usually, but not exclusively, generated by a damage of the right part of this brain network...
October 15, 2016: World Neurosurgery
Lin Li, Mary Cazzell, Olajide Babawale, Hanli Liu
Atlas-guided diffuse optical tomography (atlas-DOT) is a computational means to image changes in cortical hemodynamic signals during human brain activities. Graph theory analysis (GTA) is a network analysis tool commonly used in functional neuroimaging to study brain networks. Atlas-DOT has not been analyzed with GTA to derive large-scale brain connectivity/networks based on near-infrared spectroscopy (NIRS) measurements. We introduced an automated voxel classification (AVC) method that facilitated the use of GTA with atlas-DOT images by grouping unequal-sized finite element voxels into anatomically meaningful regions of interest within the human brain...
October 2016: Neurophotonics
Antonello Baldassarre, Lenny E Ramsey, Joshua S Siegel, Gordon L Shulman, Maurizio Corbetta
PURPOSE OF REVIEW: An important challenge in neurology is identifying the neural mechanisms underlying behavioral deficits after brain injury. Here, we review recent advances in understanding the effects of focal brain lesions on brain networks and behavior. RECENT FINDINGS: Neuroimaging studies indicate that the human brain is organized in large-scale resting state networks (RSNs) defined via functional connectivity, that is the temporal correlation of spontaneous activity between different areas...
October 5, 2016: Current Opinion in Neurology
Milad Makkie, Shijie Zhao, Xi Jiang, Jinglei Lv, Yu Zhao, Bao Ge, Xiang Li, Junwei Han, Tianming Liu
Tremendous efforts have thus been devoted on the establishment of functional MRI informatics systems that recruit a comprehensive collection of statistical/computational approaches for fMRI data analysis. However, the state-of-the-art fMRI informatics systems are especially designed for specific fMRI sessions or studies of which the data size is not really big, and thus has difficulty in handling fMRI 'big data.' Given the size of fMRI data are growing explosively recently due to the advancement of neuroimaging technologies, an effective and efficient fMRI informatics system which can process and analyze fMRI big data is much needed...
December 2015: Brain Informatics
Roscoe O Brady, Neeraj Tandon, Grace A Masters, Allison Margolis, Bruce M Cohen, Matcheri Keshavan, Dost Öngür
BACKGROUND: This study aimed to identify how the activity of large-scale brain networks differs between mood states in bipolar disorder. The authors measured spontaneous brain activity in subjects with bipolar disorder in mania and euthymia and compared these states to a healthy comparison population. METHODS: 23 subjects with bipolar disorder type I in a manic episode, 24 euthymic bipolar I subjects, and 23 matched healthy comparison (HC) subjects underwent resting state fMRI scans...
October 6, 2016: Journal of Affective Disorders
Jiaolong Qin, Haiyan Liu, Maobin Wei, Ke Zhao, Jianhuai Chen, Jingyu Zhu, Xiangyu Shen, Rui Yan, Zhijian Yao, Qing Lu
BACKGROUND: The role of abnormal communications among large-scale brain networks have been given increasing attentions in the pathophysiology of major depressive disorder (MDD). However, few studies have investigated the effect of antidepressant medication treatment on the information communication of structural brain networks, especially converged from the individual analysis. METHODS: Nineteen unipolar MDD patients completed two diffusion tensor imaging (DTI) scans before and after 8-week treatment with selective serotonin reuptake inhibitor...
September 29, 2016: Journal of Affective Disorders
M J Paldino, F Golriz, M L Chapieski, W Zhang, Z D Chu
BACKGROUND AND PURPOSE: The biologic basis for intelligence rests to a large degree on the capacity for efficient integration of information across the cerebral network. We aimed to measure the relationship between network architecture and intelligence in the pediatric, epileptic brain. MATERIALS AND METHODS: Patients were retrospectively identified with the following: 1) focal epilepsy; 2) brain MR imaging at 3T, including resting-state functional MR imaging; and 3) full-scale intelligence quotient measured by a pediatric neuropsychologist...
October 13, 2016: AJNR. American Journal of Neuroradiology
Xia Wu, Qing Li, Xinyu Yu, Kewei Chen, Adam S Fleisher, Xiaojuan Guo, Jiacai Zhang, Eric M Reiman, Li Yao, Rui Li
The triple network model, consisting of the central executive network (CEN), salience network (SN) and default mode network (DMN), has been recently employed to understand dysfunction in core networks across various disorders. Here we used the triple network model to investigate the large-scale brain networks in cognitively normal apolipoprotein e4 (APOE4) carriers who are at risk of Alzheimer's disease (AD). To explore the functional connectivity for each of the three networks and the effective connectivity among them, we evaluated 17 cognitively normal individuals with a family history of AD and at least one copy of the APOE4 allele and compared the findings to those of 12 individuals who did not carry the APOE4 gene or have a family history of AD, using independent component analysis (ICA) and Bayesian network (BN) approach...
2016: Frontiers in Aging Neuroscience
Xinqi Zhou, Taoyu Wu, Jing Yu, Xu Lei
Accumulating evidence supports that sleep deprivation (SD) and aging have similar effects: decreased cognition performance and impaired brain function. Some investigators even proposed the SD as a model of aging. However, few direct comparisons were ever explored between the effects of SD and aging by network module analysis with the resting-state fMRI. In this study, both within- and between-module connectivities were calculated in the whole brain to describe a complete picture of brain networks' functional connectivity among three groups (young normal sleep, young SD and old group)...
October 12, 2016: Brain Connectivity
Soyoung Kwon, Masataka Watanabe, Elvira Fischer, Andreas Bartels
Attention allows our brain to focus its limited resources on a given task. It does so by selective modulation of neural activity and of functional connectivity (FC) across brain-wide networks. While there is extensive literature on activity changes, surprisingly few studies examined brain-wide FC modulations that can be cleanly attributed to attention compared to matched visual processing. In contrast to prior approaches, we used an ultra-long trial design that avoided transients from trial onsets, included slow fluctuations (<0...
October 9, 2016: NeuroImage
Sara de la Salle, Joelle Choueiry, Dhrasti Shah, Hayley Bowers, Judy McIntosh, Vadim Ilivitsky, Verner Knott
N-methyl-D-aspartate (NMDA) receptor antagonists administered to healthy humans results in schizophrenia-like symptoms, which preclinical research suggests are due to glutamatergically altered brain oscillations. Here, we examined resting-state electroencephalographic activity in 21 healthy volunteers assessed in a placebo-controlled, double-blind, randomized study involving administration of either a saline infusion or a sub-anesthetic dose of ketamine, an NMDA receptor antagonist. Frequency-specific current source density (CSD) was assessed at sensor-level and source-level using eLORETA within regions of interest of a triple network model of schizophrenia (this model posits a dysfunctional switching between large-scale Default Mode and Central Executive networks by the monitor-controlling Salience Network)...
2016: Frontiers in Pharmacology
Laura D Lewis, Kawin Setsompop, Bruce R Rosen, Jonathan R Polimeni
Oscillatory neural dynamics play an important role in the coordination of large-scale brain networks. High-level cognitive processes depend on dynamics evolving over hundreds of milliseconds, so measuring neural activity in this frequency range is important for cognitive neuroscience. However, current noninvasive neuroimaging methods are not able to precisely localize oscillatory neural activity above 0.2 Hz. Electroencephalography and magnetoencephalography have limited spatial resolution, whereas fMRI has limited temporal resolution because it measures vascular responses rather than directly recording neural activity...
October 11, 2016: Proceedings of the National Academy of Sciences of the United States of America
Michael W Cole, Takuya Ito, Danielle S Bassett, Douglas H Schultz
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...
October 10, 2016: Nature Neuroscience
F Xavier Castellanos, Yuta Aoki
Functional magnetic resonance imaging (fMRI) without an explicit task, i.e., resting state fMRI, of individuals with Attention-Deficit/Hyperactivity Disorder (ADHD) is growing rapidly. Early studies were unaware of the vulnerability of this method to even minor degrees of head motion, a major concern in the field. Recent efforts are implementing various strategies to address this source of artifact along with a growing set of analytical tools. Availability of the ADHD-200 Consortium dataset, a large-scale multi-site repository, is facilitating increasingly sophisticated approaches...
May 2016: Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
Henning Dickten, Stephan Porz, Christian E Elger, Klaus Lehnertz
Epilepsy can be regarded as a network phenomenon with functionally and/or structurally aberrant connections in the brain. Over the past years, concepts and methods from network theory substantially contributed to improve the characterization of structure and function of these epileptic networks and thus to advance understanding of the dynamical disease epilepsy. We extend this promising line of research and assess-with high spatial and temporal resolution and using complementary analysis approaches that capture different characteristics of the complex dynamics-both strength and direction of interactions in evolving large-scale epileptic brain networks of 35 patients that suffered from drug-resistant focal seizures with different anatomical onset locations...
October 6, 2016: Scientific Reports
Sepideh Sadaghiani, Andreas Kleinschmidt
The most salient electrical signal measured from the human brain is the α-rhythm, neural activity oscillating at ∼100ms intervals. Recent findings challenge the longstanding dogma of α-band oscillations as the signature of a passively idling brain state but diverge in terms of interpretation. Despite firm correlations with behavior, the mechanistic role of the α-rhythm in brain function remains debated. We suggest that three large-scale brain networks involved in different facets of top-down cognitive control differentially modulate α-oscillations, ranging from power within and synchrony between brain regions...
October 1, 2016: Trends in Cognitive Sciences
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