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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/52096


    Title: Reorganization of functional connectivity during the motor task using EEG time-frequency cross mutual information analysis
    Authors: Lu,CF;Teng,S;Hung,CI;Tseng,PJ;Lin,LT;Lee,PL;Wu,YT
    Contributors: 電機工程學系
    Keywords: RESTING-STATE;BETA-SYNCHRONIZATION;DEFAULT-MODE;BRAIN-FUNCTION;MOVEMENT;INTEGRATION;MODULATION;HYPOTHESIS;ATTENTION;COHERENCE
    Date: 2011
    Issue Date: 2012-03-28 10:15:21 (UTC+8)
    Publisher: 國立中央大學
    Abstract: Objective: This study investigates the functional organization of cortical networks during self-determinant arm movement using the time sequences of the alpha (8-12 Hz) and beta (16-25 Hz) bands. Methods: The time-frequency cross mutual information (TFCMI) method was used to estimate the EEG functional connectivity in the alpha and beta bands for seven healthy subjects during four functional states: the resting, preparing, movement-onset, and movement-offset states. Results: In the preparing state, the maintenance of the central-executive network (CEN, prefrontal-parietal connection) suppressed the motor network in the alpha band to plan the next movement, whereas the CEN was deactivated in the beta band to retain visual attention (the frontal-occipital connection). A significant decrease of the CEN in the alpha band occurred after a visual cue in the movement-onset state, followed by a significant increase in motor-network connectivity in the beta band until the movement-offset state. Conclusions: The temporal-spectral modulation mechanism allows the brain to manifest multiple functions subject to energy budget. Significance: The TFCMI method was employed to estimate EEG functional connectivity and effectively demonstrate the reorganization process between four functional states. (C) 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
    Relation: CLINICAL NEUROPHYSIOLOGY
    Appears in Collections:[Department of Electrical Engineering] journal & Dissertation

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