Literature DB >> 19943355

Evaluation of the brain network organization from EEG signals: a preliminary evidence in stroke patient.

Fabrizio de Vico Fallani1, Laura Astolfi, Febo Cincotti, Donatella Mattia, Daria la Rocca, Elira Maksuti, Serenella Salinari, Fabio Babiloni, Balazs Vegso, Gyorgy Kozmann, Zoltan Nagy.   

Abstract

Synchronous brain activity in motor cortex in perception or in complex cognitive processing has been the subject of several studies. The advanced analysis of cerebral electro-physiological activity during the course of planning (PRE) or execution of movement (EXE) in a high temporal resolution could reveal interesting information about the brain functional organization in patients following stroke damage. High-power (128 channels) electroencephalography registration was carried out on 8 healthy subjects and on a patient with stroke with capsular lacuna in the right hemisphere. For activation of motor cortex, the finger tapping paradigm was used. In this preliminary study, we tested a theoretical graph approach to characterize the task-related spectral coherence. All of the obtained brain functional networks were analyzed by the connectivity degree, the degree distribution, and efficiency parameters in the Theta, Alpha, Beta, and Gamma bands during the PRE and EXE intervals. All the brain networks were found to hold a regular and ordered topology. However, significant differences (P < 0.01) emerged between the patient with stroke and the control subjects, independently of the neural processes related to the PRE or EXE periods. In the Beta (13-29 Hz) and Gamma (30-40 Hz) bands, the significant (P < 0.01) decrease in global- and local-efficiency in the patient's networks, reflected a lower capacity to integrate communication between distant brain regions and a lower tendency to be modular. This weak organization is principally due to the significant (P < 0.01 Bonferroni corrected) increase in disconnected nodes together with the significant increase in the links in some other crucial vertices. (c) 2009 Wiley-Liss, Inc.

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Year:  2009        PMID: 19943355     DOI: 10.1002/ar.20965

Source DB:  PubMed          Journal:  Anat Rec (Hoboken)        ISSN: 1932-8486            Impact factor:   2.064


  27 in total

1.  β-Oscillations Reflect Recovery of the Paretic Upper Limb in Subacute Stroke.

Authors:  Chih-Wei Tang; Fu-Jung Hsiao; Po-Lei Lee; Yun-An Tsai; Ya-Fang Hsu; Wei-Ta Chen; Yung-Yang Lin; Charlotte J Stagg; I-Hui Lee
Journal:  Neurorehabil Neural Repair       Date:  2020-04-23       Impact factor: 3.919

Review 2.  Reorganization of cerebral networks after stroke: new insights from neuroimaging with connectivity approaches.

Authors:  Christian Grefkes; Gereon R Fink
Journal:  Brain       Date:  2011-03-16       Impact factor: 13.501

3.  Multimodal neuroimaging study reveals dissociable processes between structural and functional networks in patients with subacute intracerebral hemorrhage.

Authors:  Xiaobing Zhang; Xuebin Yu; Qingquan Bao; Liming Yang; Yu Sun; Peng Qi
Journal:  Med Biol Eng Comput       Date:  2019-02-09       Impact factor: 2.602

4.  Connectivity measures are robust biomarkers of cortical function and plasticity after stroke.

Authors:  Jennifer Wu; Erin Burke Quinlan; Lucy Dodakian; Alison McKenzie; Nikhita Kathuria; Robert J Zhou; Renee Augsburger; Jill See; Vu H Le; Ramesh Srinivasan; Steven C Cramer
Journal:  Brain       Date:  2015-06-11       Impact factor: 13.501

5.  Toward neuroimaging-based network biomarkers for transient ischemic attack.

Authors:  Yating Lv; Xiujie Han; Yulin Song; Yu Han; Chengshu Zhou; Dan Zhou; Fuding Zhang; Qiming Xue; Jinling Liu; Lijuan Zhao; Cairong Zhang; Lingyu Li; Jinhui Wang
Journal:  Hum Brain Mapp       Date:  2019-04-19       Impact factor: 5.038

6.  A lateralized functional auditory network is involved in anuran sexual selection.

Authors:  Fei Xue; Guangzhan Fang; Xizi Yue; Ermi Zhao; Steven E Brauth; Yezhong Tang
Journal:  J Biosci       Date:  2016-12       Impact factor: 1.826

Review 7.  Clinical application of a modular ankle robot for stroke rehabilitation.

Authors:  Larry W Forrester; Anindo Roy; Ronald N Goodman; Jeremy Rietschel; Joseph E Barton; Hermano Igo Krebs; Richard F Macko
Journal:  NeuroRehabilitation       Date:  2013       Impact factor: 2.138

Review 8.  Complex networks and deep learning for EEG signal analysis.

Authors:  Zhongke Gao; Weidong Dang; Xinmin Wang; Xiaolin Hong; Linhua Hou; Kai Ma; Matjaž Perc
Journal:  Cogn Neurodyn       Date:  2020-08-29       Impact factor: 3.473

Review 9.  Brain connectivity plasticity in the motor network after ischemic stroke.

Authors:  Lin Jiang; Huijuan Xu; Chunshui Yu
Journal:  Neural Plast       Date:  2013-04-24       Impact factor: 3.599

10.  Motor imagery cognitive network after left ischemic stroke: study of the patients during mental rotation task.

Authors:  Jing Yan; Junfeng Sun; Xiaoli Guo; Zheng Jin; Yao Li; Zhijun Li; Shanbao Tong
Journal:  PLoS One       Date:  2013-10-22       Impact factor: 3.240

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