Brain Network Analysis Results of Finger Motor Execution and Motor Imagery

Fengyue Liu, Lin Lu, Abdelkader Nasreddine Belkacem, Jiaxin Zhang, Penghai Li, Jun Liang, Changming Wang, Chao Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In recent years, finger movement execution and motor imagery have become a new method in the field of motor function rehabilitation after stroke, which has important reference value for the rehabilitation of patients with motor dysfunction. The ability of motor imagery retained by stroke patients makes it possible to recover the function of neural plasticity motor system. In this paper, conditional Granger causality analysis method is used. On the premise that the residuals of the subjects meet the Durbin White test criterion (P>0.60), five network nodes directly related to motor function are selected to analyze and compare the conditional Granger causality connectivity and connection strength between these regions. Drawing the whole brain network diagram of left-hand finger movement execution and movement imagination, getting the connection direction and connection strength of each brain network node, looking for objective quantitative indicators, which can be used as indicators of rehabilitation of stroke patients. The whole brain network diagram clearly shows that the left pre-motor area (PMA) has a stimulating connection to the other three regions during the execution of the left-hand finger movement. In the process of left-handed finger motion imagination, the left-PMA has stimulating connections to the other two regions, and the stimulating connections to other regions are the most in the five regions. Through the study, it was found that in the exercise execution and motor imagination of the left hand, the stimulation of the left-PMA on other regions was more obvious than that of other regions, and the connection between this region and other regions was also stronger, which could accelerate the recovery process of patients by strengthening the treatment of the left-PMA in the late treatment of stroke patients.

Original languageEnglish
Title of host publicationProceedings of the 2022 11th International Conference on Computing and Pattern Recognition, ICCPR 2022
PublisherAssociation for Computing Machinery
Number of pages7
ISBN (Electronic)9781450397056
Publication statusPublished - Nov 17 2022
Event11th International Conference on Computing and Pattern Recognition, ICCPR 2022 - Virtual, Online, China
Duration: Nov 17 2022Nov 19 2022

Publication series

NameACM International Conference Proceeding Series


Conference11th International Conference on Computing and Pattern Recognition, ICCPR 2022
CityVirtual, Online


  • Granger causality coefficient 4
  • movement execution 1
  • movement imagination 2
  • stroke 3

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software


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