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https://www.readbyqxmd.com/read/28336496/functional-eeg-network-analysis-in-schizophrenia-evidence-of-larger-segregation-and-deficit-of-modulation
#1
Javier Gomez-Pilar, Alba Lubeiro, Jesús Poza, Roberto Hornero, Marta Ayuso, César Valcárcel, Karim Haidar, José A Blanco, Vicente Molina
OBJECTIVE: Higher mental functions depend on global cerebral functional coordination. Our aim was to study fast modulation of functional networks in schizophrenia that has not been previously assessed. METHODS: Graph-theory was used to analyze the electroencephalographic (EEG) activity during an odd-ball task in 57 schizophrenia patients (18 first episode patients, FEPs) and 59 healthy controls. Clustering coefficient (CLC), characteristic path length (PL) and small-worldness (SW) were computed at baseline ([-300 0] ms prior to stimulus delivery) and response ([150 450] ms post-stimulus) windows...
March 20, 2017: Progress in Neuro-psychopharmacology & Biological Psychiatry
https://www.readbyqxmd.com/read/28334882/decreased-integration-and-information-capacity-in-stroke-measured-by-whole-brain-models-of-resting-state-activity
#2
Mohit H Adhikari, Carl D Hacker, Josh S Siegel, Alessandra Griffa, Patric Hagmann, Gustavo Deco, Maurizio Corbetta
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...
February 20, 2017: Brain: a Journal of Neurology
https://www.readbyqxmd.com/read/28324955/identifying-important-regions-in-eeg-epilepsy-brain-networks
#3
Nantia D Iakovidou, Manolis Christodoulakis, Eleftherios S Papathanasiou, Savvas S Papacostas, Georgios D Mitsis
The human brain has been called the most complex object in the known universe and in many ways it constitutes the final frontier of science. Lately, the functional connectivity in human brain has been regarded and studied as a complex network using electroencephalography (EEG) signals. This means that the brain is studied as a connected system, where nodes represent different specialized brain regions and links or connections, represent communication pathways between the nodes. It is also fairly established that graph theory provides a variety of measures, methods and tools that can be useful to efficiently model, analyze and study an EEG network...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28323202/enhanced-structural-connectivity-within-a-brain-sub-network-supporting-working-memory-and-engagement-processes-after-cognitive-training
#4
Francisco J Román, Yasser Iturria-Medina, Kenia Martínez, Sherif Karama, Miguel Burgaleta, Alan C Evans, Susanne M Jaeggi, Roberto Colom
The structural connectome provides relevant information about experience and training-related changes in the brain. Here, we used network-based statistics (NBS) and graph theoretical analyses to study structural changes in the brain as a function of cognitive training. Fifty-six young women were divided in two groups (experimental and control). We assessed their cognitive function before and after completing a working memory intervention using a comprehensive battery that included fluid and crystallized abilities, working memory and attention control, and we also obtained structural MRI images...
March 16, 2017: Neurobiology of Learning and Memory
https://www.readbyqxmd.com/read/28293468/a-method-for-independent-component-graph-analysis-of-resting-state-fmri
#5
Demetrius Ribeiro de Paula, Erik Ziegler, Pubuditha M Abeyasinghe, Tushar K Das, Carlo Cavaliere, Marco Aiello, Lizette Heine, Carol di Perri, Athena Demertzi, Quentin Noirhomme, Vanessa Charland-Verville, Audrey Vanhaudenhuyse, Johan Stender, Francisco Gomez, Jean-Flory L Tshibanda, Steven Laureys, Adrian M Owen, Andrea Soddu
INTRODUCTION: Independent component analysis (ICA) has been extensively used for reducing task-free BOLD fMRI recordings into spatial maps and their associated time-courses. The spatially identified independent components can be considered as intrinsic connectivity networks (ICNs) of non-contiguous regions. To date, the spatial patterns of the networks have been analyzed with techniques developed for volumetric data. OBJECTIVE: Here, we detail a graph building technique that allows these ICNs to be analyzed with graph theory...
March 2017: Brain and Behavior
https://www.readbyqxmd.com/read/28290133/the-effects-of-acute-gaba-treatment-on-the-functional-connectivity-and-network-topology-of-cortical-cultures
#6
Yao Han, Hong Li, Yiran Lang, Yuwei Zhao, Hongji Sun, Peng Zhang, Xuan Ma, Jiuqi Han, Qiyu Wang, Jin Zhou, Changyong Wang
γ-Aminobutyric acid (GABA) is an inhibitory transmitter, acting on receptor channels to reduce neuronal excitability in matured neural systems. However, electrophysiological responses of whole neuronal ensembles to the exposure to GABA are still unclear. We used micro-electrode arrays (MEAs) to study the effects of the increasing amount of GABA on functional network of cortical neural cultures. Then the recorded data were analyzed by the cross-covariance analysis and graph theory. Results showed that after the GABA treatment, the activity parameters of firing rate, bursting rate, bursting duration and network burst frequency in neural cultures decreased as expected...
March 13, 2017: Neurochemical Research
https://www.readbyqxmd.com/read/28290074/abnormal-brain-white-matter-network-in-young-smokers-a-graph-theory-analysis-study
#7
Yajuan Zhang, Min Li, Ruonan Wang, Yanzhi Bi, Yangding Li, Zhang Yi, Jixin Liu, Dahua Yu, Kai Yuan
Previous diffusion tensor imaging (DTI) studies had investigated the white matter (WM) integrity abnormalities in some specific fiber bundles in smokers. However, little is known about the changes in topological organization of WM structural network in young smokers. In current study, we acquired DTI datasets from 58 male young smokers and 51 matched nonsmokers and constructed the WM networks by the deterministic fiber tracking approach. Graph theoretical analysis was used to compare the topological parameters of WM network (global and nodal) and the inter-regional fractional anisotropy (FA) weighted WM connections between groups...
March 13, 2017: Brain Imaging and Behavior
https://www.readbyqxmd.com/read/28286918/altered-effective-connectivity-network-in-childhood-absence-epilepsy-a-multi-frequency-meg-study
#8
Caiyun Wu, Jing Xiang, Wenwen Jiang, Shuyang Huang, Yuan Gao, Lu Tang, Yuchen Zhou, Di Wu, Qiqi Chen, Zheng Hu, Xiaoshan Wang
Using multi-frequency magnetoencephalography (MEG) data, we investigated whether the effective connectivity (EC) network of patients with childhood absence epilepsy (CAE) is altered during the inter-ictal period in comparison with healthy controls. MEG data from 13 untreated CAE patients and 10 healthy controls were recorded. Correlation analysis and Granger causality analysis were used to construct an EC network at the source level in eight frequency bands. Alterations in the spatial pattern and topology of the network in CAE were investigated by comparing the patients with the controls...
March 12, 2017: Brain Topography
https://www.readbyqxmd.com/read/28285941/how-far-can-we-go-in-chronic-disorders-of-consciousness-differential-diagnosis-the-use-of-neuromodulation-in-detecting-internal-and-external-awareness
#9
Antonino Naro, Antonino Leo, Alfredo Manuli, Antonino Cannavò, Alessia Bramanti, Placido Bramanti, Rocco Salvatore Calabrò
Awareness generation and modulation may depend on a balanced information integration and differentiation across default mode network (DMN) and external awareness networks (EAN). Neuromodulation approaches, capable of shaping information processing, may highlight residual network activities supporting awareness, which are not detectable through active paradigms, thus allowing to differentiate chronic disorders of consciousness (DoC). We studied aftereffects of repetitive transcranial magnetic stimulation (rTMS) by applying graph theory within canonical frequency bands to compare the markers of these networks in the electroencephalographic data from 20 patients with DoC...
March 8, 2017: Neuroscience
https://www.readbyqxmd.com/read/28269169/functional-connectivity-analysis-using-whole-brain-and-regional-network-metrics-in-ms-patients
#10
V C Chirumamilla, V Fleischer, A Droby, T Anjum, M Muthuraman, F Zipp, S Groppa
In the present study we investigated brain network connectivity differences between patients with relapsing-remitting multiple sclerosis (RRMS) and healthy controls (HC) as derived from functional resonance magnetic imaging (fMRI) using graph theory. Resting state fMRI data of 18 RRMS patients (12 female, mean age ± SD: 42 ± 12.06 years) and 25 HC (8 female, 29.2 ± 5.38 years) were analyzed. In order to obtain information of differences in entire brain network, we focused on both, local and global network connectivity parameters...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268525/estimating-multimodal-brain-connectivity-in-multiple-sclerosis-an-exploratory-factor-analysis
#11
Matteo Mancini, Giovanni Giulietti, Barbara Spano, Marco Bozzali, Mara Cercignani, Silvia Conforto
Graph-theoretical approaches have become a popular way to model brain data collected using magnetic resonance imaging (MRI), both from the structural and the functional perspectives. In structural networks, tract-based mapping allows to model different aspects of brain structures by means of the specific characteristics of the different MRI modalities. However, there has been little effort to join the information carried by each modality and to understand what level of common variance is shown in these data...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268427/a-node-wise-analysis-of-the-uterine-muscle-networks-for-pregnancy-monitoring
#12
N Nader, M Hassan, W Falou, C Marque, M Khalil
The recent past years have seen a noticeable increase of interest in the correlation analysis of electrohysterographic (EHG) signals in the perspective of improving the pregnancy monitoring. Here we propose a new approach based on the functional connectivity between multichannel (4×4 matrix) EHG signals recorded from the women's abdomen. The proposed pipeline includes i) the computation of the statistical couplings between the multichannel EHG signals, ii) the characterization of the connectivity matrices, computed by using the imaginary part of the coherence, based on the graph-theory analysis and iii) the use of these measures for pregnancy monitoring...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268424/novel-measure-of-the-weigh-distribution-balance-on-the-brain-network-graph-complexity-applied-to-schizophrenia
#13
J Gomez-Pilar, J Poza, A Bachiller, P Nunez, C Gomez, A Lubeiro, V Molina, R Hornero
The aim of this study was to assess brain complexity dynamics in schizophrenia (SCH) patients during an auditory oddball task. For this task, we applied a novel graph measure based on the balance of the node weights distribution. Previous studies applied complexity parameters that were strongly dependent on network topology. This could bias the results, as well as making correction techniques, such as surrogating process, necessary. In the present study, we applied a novel graph complexity measure derived from the information theory: Shannon Graph Complexity (SGC)...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268353/continuous-theta-burst-transcranial-magnetic-stimulation-affects-brain-functional-connectivity
#14
Dan Cao, Yingjie Li, Ling Wei, Yingying Tang
Prefrontal cortex (PFC) plays an important role in the emotional processing as well as in the functional brain network. Hyperactivity in the right dorsolateral prefrontal cortex (DLPFC) would be found in anxious participants. However, it is still unclear what the role of PFC played in a resting functional network. Continuous theta burst transcranial magnetic stimulation (cTBS) is an effective tool to create virtual lesions on brain regions. In this paper, we applied cTBS over right prefrontal area, and investigated the effects of cTBS on the brain activity for functional connectivity by the method of graph theory...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28266518/altered-topological-properties-of-brain-networks-in-social-anxiety-disorder-a-resting-state-functional-mri-study
#15
Hongru Zhu, Changjian Qiu, Yajing Meng, Minlan Yuan, Yan Zhang, Zhengjia Ren, Yuchen Li, Xiaoqi Huang, Qiyong Gong, Su Lui, Wei Zhang
Recent studies involving connectome analysis including graph theory have yielded potential biomarkers for mental disorders. In this study, we aimed to investigate the differences of resting-state network between patients with social anxiety disorder (SAD) and healthy controls (HCs), as well as to distinguish between individual subjects using topological properties. In total, 42 SAD patients and the same number of HCs underwent resting functional MRI, and the topological organization of the whole-brain functional network was calculated using graph theory...
March 7, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28266321/the-left-middle-temporal-gyrus-in-the-middle-of-an-impaired-social-affective-communication-network-in-social-anxiety-disorder
#16
Je-Yeon Yun, Jae-Chang Kim, Jeonghun Ku, Jung-Eun Shin, Jae-Jin Kim, Soo-Hee Choi
BACKGROUND: Previous studies on patients diagnosed with social anxiety disorder (SAD) reported changed patterns of the resting-state functional connectivity network (rs-FCN) between the prefrontal cortices and other prefrontal, amygdalar or striatal regions. Using a graph theory approach, this study explored the modularity-based community profile and patterns of inter-/intra-modular communication for the rs-FCN in SAD. METHODS: In total, for 28 SAD patients and 27 healthy controls (HC), functional magnetic resonance imaging (fMRI) data were acquired in resting-state and subjected to a graph theory analysis...
March 4, 2017: Journal of Affective Disorders
https://www.readbyqxmd.com/read/28249008/characterization-of-the-resting-state-brain-network-topology-in-the-6-hydroxydopamine-rat-model-of-parkinson-s-disease
#17
Robert Westphal, Camilla Simmons, Michel B Mesquita, Tobias C Wood, Steve C R Williams, Anthony C Vernon, Diana Cash
Resting-state functional MRI (rsfMRI) is an imaging technology that has recently gained attention for its ability to detect disruptions in functional brain networks in humans, including in patients with Parkinson's disease (PD), revealing early and widespread brain network abnormalities. This methodology is now readily applicable to experimental animals offering new possibilities for cross-species translational imaging. In this context, we herein describe the application of rsfMRI to the unilaterally-lesioned 6-hydroxydopamine (6-OHDA) rat, a robust experimental model of the dopamine depletion implicated in PD...
2017: PloS One
https://www.readbyqxmd.com/read/28231324/a-framework-for-analyzing-contagion-in-assortative-banking-networks
#18
Thomas R Hurd, James P Gleeson, Sergey Melnik
We introduce a probabilistic framework that represents stylized banking networks with the aim of predicting the size of contagion events. Most previous work on random financial networks assumes independent connections between banks, whereas our framework explicitly allows for (dis)assortative edge probabilities (i.e., a tendency for small banks to link to large banks). We analyze default cascades triggered by shocking the network and find that the cascade can be understood as an explicit iterated mapping on a set of edge probabilities that converges to a fixed point...
2017: PloS One
https://www.readbyqxmd.com/read/28227399/functional-connectivity-analysis-using-whole-brain-and-regional-network-metrics-in-ms-patients
#19
V C Chirumamilla, V Fleischer, A Droby, T Anjum, M Muthuraman, F Zipp, S Groppa, V C Chirumamilla, V Fleischer, A Droby, T Anjum, M Muthuraman, F Zipp, S Groppa, A Droby, S Groppa, F Zipp, V C Chirumamilla, T Anjum, V Fleischer, M Muthuraman
In the present study we investigated brain network connectivity differences between patients with relapsing-remitting multiple sclerosis (RRMS) and healthy controls (HC) as derived from functional resonance magnetic imaging (fMRI) using graph theory. Resting state fMRI data of 18 RRMS patients (12 female, mean age ± SD: 42 ± 12.06 years) and 25 HC (8 female, 29.2 ± 5.38 years) were analyzed. In order to obtain information of differences in entire brain network, we focused on both, local and global network connectivity parameters...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226699/estimating-multimodal-brain-connectivity-in-multiple-sclerosis-an-exploratory-factor-analysis
#20
Matteo Mancini, Giovanni Giulietti, Barbara Spano, Marco Bozzali, Mara Cercignani, Silvia Conforto, Matteo Mancini, Giovanni Giulietti, Barbara Spano, Marco Bozzali, Mara Cercignani, Silvia Conforto, Giovanni Giulietti, Mara Cercignani, Silvia Conforto, Matteo Mancini, Barbara Spano, Marco Bozzali
Graph-theoretical approaches have become a popular way to model brain data collected using magnetic resonance imaging (MRI), both from the structural and the functional perspectives. In structural networks, tract-based mapping allows to model different aspects of brain structures by means of the specific characteristics of the different MRI modalities. However, there has been little effort to join the information carried by each modality and to understand what level of common variance is shown in these data...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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