Emotion-movement relationship: A study using functional brain network and cortico-muscular coupling

Abstract

Background: Emotions play a crucial role in human communication and affect all aspects of human life. However, to date, there have been few studies conducted on how movements under different emotions influence human brain activity and cortico-muscular coupling (CMC).

New methods: In this study, for the first time, electroencephalogram (EEG) and electromyogram physiological electrical signals were used to explore this relationship. We performed frequency domain and nonlinear dynamics analyses on EEG signals and used transfer entropy to explore the CMC associated with the emotion-movement relationship. To study the transmission of information between different brain regions, we also constructed a functional brain network and calculated various network metrics using graph theory.

Results: We found that, compared with a neutral emotional state, movements made during happy and sad emotions had increased CMC strength and EEG power and complexity. The functional brain network metrics of these three emotional states were also different.

Comparison with existing methods: Much of the emotion-movement relationship research has been based on subjective expression and external performance. Our research method, however, focused on the processing of physiological electrical signals, which contain a wealth of information and can objectively reveal the inner mechanisms of the emotion-movement relationship.

Conclusions: Different emotional states can have a significant influence on human movement. This study presents a detailed introduction to brain activity and CMC.

Keywords: Cortico-muscular coupling; Electroencephalogram; Electromyogram; Emotion-movement; Functional brain network.