Functional connectivity analysis of multiplex muscle network across frequencies

Area of Science:

• Neuroscience
• Biomedical Engineering
• Systems Physiology

Background:

• Physiological networks illustrate interactions within the human body.
• Understanding the central nervous system (CNS) and musculoskeletal system interplay is crucial for motor control research.

Purpose of the Study:

• To investigate the interaction between the CNS and musculoskeletal system.
• To map functional muscle networks using coherence analysis of surface electromyography (EMG) data.

Main Methods:

• Acquired surface EMG from 36 muscles during upright stance and a bimanual pointing task.
• Utilized non-negative matrix factorization to identify functional connectivity across four frequency bands.
• Applied graph-theory analysis to examine network properties like edge weight distribution, efficiency, and core-periphery structure.

Main Results:

• Functional muscle networks exhibited multiplex organization, with spatial arrangements varying across frequencies.
• Graph-theory analysis revealed a consistent fat-tail distribution of edge weights, specific efficiency values, and core-periphery organization.
• Distinct frequency bands demonstrated unique network properties, suggesting specialized roles.

Conclusions:

• The identified frequency bands may represent spectral fingerprints of distinct neural pathways controlling the musculoskeletal system.
• This research provides novel insights into the neural control of human movement and motor system organization.