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01-03-2019 | Original Paper

Brain Network Reconfiguration During Motor Imagery Revealed by a Large-Scale Network Analysis of Scalp EEG

Authors: Fali Li, Chanlin Yi, Limeng Song, Yuanling Jiang, Wenjing Peng, Yajing Si, Tao Zhang, Rui Zhang, Dezhong Yao, Yangsong Zhang, Peng Xu

Published in: Brain Topography | Issue 2/2019

Abstract

Mentally imagining rather physically executing the motor behaviors is defined as motor imagery (MI). During MI, the mu rhythmical oscillation of cortical neurons is the event-related desynchronization (ERD) subserving the physiological basis of MI-based brain-computer interface. In our work, we investigated the specific brain network reconfiguration from rest idle to MI task states, and also probed the underlying relationship between the brain network reconfiguration and MI related ERD. Findings revealed that comparing to rest state, the MI showed the enhanced motor area related linkages and the deactivated activity of default mode network. In addition, the reconfigured network index was closely related to the ERDs, i.e., the higher the reconfigured network index was, the more obvious the ERDs were. These findings consistently implied that the reconfiguration from rest to task states underlaid the reallocation of related brain resources, and the efficient brain reconfiguration corresponded to a better MI performance, which provided the new insights into understanding the mechanism of MI as well as the potential biomarker to evaluate the rehabilitation quality for those patients with deficits of motor function.

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Title: Brain Network Reconfiguration During Motor Imagery Revealed by a Large-Scale Network Analysis of Scalp EEG
Authors: Fali Li
Chanlin Yi
Limeng Song
Yuanling Jiang
Wenjing Peng
Yajing Si
Tao Zhang
Rui Zhang
Dezhong Yao
Yangsong Zhang
Peng Xu
Publication date: 01-03-2019
Publisher: Springer US
Published in: Brain Topography / Issue 2/2019
Print ISSN: 0896-0267
Electronic ISSN: 1573-6792
DOI: https://doi.org/10.1007/s10548-018-0688-x

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Brain Network Reconfiguration During Motor Imagery Revealed by a Large-Scale Network Analysis of Scalp EEG

Abstract

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Abstract

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