Reconfiguration patterns of large-scale brain networks in motor imagery

Authors

Tao Zhang, University of Electronic Science and Technology of China
Fei Wang, University of Electronic Science and Technology of China
Mengchen Li, University of Electronic Science and Technology of China
Fali Li, University of Electronic Science and Technology of China
Ying Tan, University of Electronic Science and Technology of China
Yangsong Zhang, University of Electronic Science and Technology of China
Hang Yang, University of Electronic Science and Technology of China
Bharat Biswal, University of Electronic Science and Technology of China
Dezhong Yao, University of Electronic Science and Technology of China
Peng Xu, University of Electronic Science and Technology of China

Document Type

Article

Publication Date

3-4-2019

Abstract

Motor imagery (MI) is a multidimensional cognitive ability which recruited multiple brain networks. However, how connections and interactions are adjusted among distributed networks during MI remains unknown. To investigate these issues, we analyze the reconfiguration patterns of large-scale networks for different MI states. In our work, we explored the specific patterns of large-scale functional network organization from rest to different MI tasks using group independent component analysis (ICA), and evaluated the potential relationships between MI and the patterns of large-scale networks. The results indicate that task-related large-scale networks show the balanced relation between the within- and between-network connectivities during MI, and reveal the somatomotor network and dorsal attention network play critical roles in switching context-specific MI, and also demonstrate the change of large-scale networks organization toward effective topology could facilitate MI performance. Moreover, based on the large-scale network connectivities, we could differentiate an individual’s three states (i.e., left-hand MI, right-hand MI and rest) with an 72.73% accuracy using a multi-variant pattern analysis, suggesting that the specific patterns of large-scale network can also provide potential biomarkers to predict an individual’s behavior. Our findings contribute to the further understanding of the neural mechanisms underlying MI from large-scale network patterns and provide new biomarkers to predict the individual’s behaviors.

Identifier

85056604135 (Scopus)

Publication Title

Brain Structure and Function

External Full Text Location

https://doi.org/10.1007/s00429-018-1786-y

e-ISSN

18632661

ISSN

18632653

PubMed ID

30421036

First Page

553

Last Page

566

Issue

2

Volume

224

Grant

2018JY0526

Fund Ref

Sichuan Province Science and Technology Support Program

Recommended Citation

Zhang, Tao; Wang, Fei; Li, Mengchen; Li, Fali; Tan, Ying; Zhang, Yangsong; Yang, Hang; Biswal, Bharat; Yao, Dezhong; and Xu, Peng, "Reconfiguration patterns of large-scale brain networks in motor imagery" (2019). Faculty Publications. 7734.
https://digitalcommons.njit.edu/fac_pubs/7734