Abstract

Understanding how the brain controls movements is a critical issue in neuroscience. The role of brain changes rapidly according to movement states. To elucidate the motor control mechanism of brain, it is essential to investigate the changes in brain network in motor-related regions according to movement states. Therefore, the objective of this study was to investigate the brain network transitions according to movement states. We measured whole brain magnetoencephalography (MEG) signals and extracted source signals in 24 motor-related areas. Functional connectivity and centralities were calculated according to time flow. Our results showed that brain networks differed between states of motor planning and movement. Connectivities between most motor-related areas were increased in the motor-planning state. In contrast, only connectivities with cerebellum and basal ganglia were increased while those of other motor-related areas were decreased during movement. Our results indicate that most processes involved in motor control are completed before movement. Further, brain developed network related to feedback rather than motor decision during movements. Our findings also suggest that neural signals during motor planning might be more predictive than neural signals during movement. They facilitate accurate prediction of movement for brain-machine interfaces and provide insight into brain mechanisms in motor control.

Highlights

  • Understanding how the brain controls movements is a critical issue in neuroscience

  • Low-frequency centralities were increased in CB and basal ganglia (BG) during the movement state

  • We demonstrated the transition in connectivity between motor-related areas according to movement states

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Summary

Introduction

Understanding how the brain controls movements is a critical issue in neuroscience. The role of brain changes rapidly according to movement states. To elucidate the motor control mechanism of brain, it is essential to investigate the changes in brain network in motor-related regions according to movement states. Since the early 2000s, the mechanism of communication between different brain areas has been actively investigated[24,25,26,27,28,29,30,31,32] These studies revealed brain networks during resting state or task performance[33,34]. It is essential to analyze the changes in motor-related regions according to movement states to elucidate the brain motor control mechanism, which has yet to be investigated. To analyze the changes in brain networks depending on movement states, the functional connectivity between source areas was calculated using mutual information (MI) according to the time window. The aim of this study was to reveal the transition in brain networks by analyzing the transition of connectivities and centralities according to movement states

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