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Updated: Apr 27, 2026

Corticospinal Excitability Modulation During Action Observation
Published on: December 31, 2013
The reorganization of corticomuscular coherence during a transition between sensorimotor states
Saeid Mehrkanoon1, Michael Breakspear2, Tjeerd W Boonstra3
1School of Psychiatry, University of New South Wales, Sydney, Australia; Black Dog Institute, Sydney, Australia.
Abstract:
Recent research suggests that neural oscillations in different frequency bands support distinct and sometimes parallel processing streams in neural circuits. Studies of the neural dynamics of human motor control have primarily focused on oscillations in the beta band (15-30 Hz). During sustained muscle contractions, corticomuscular coherence is mainly present in the beta band, while coherence in the alpha (8-12 Hz) and gamma (30-80 Hz) bands has not been consistently found. Here we test the hypothesis that the frequency of corticomuscular coherence changes during transitions between sensorimotor states. Corticomuscular coherence was investigated in twelve participants making rapid transitions in force output between two targets. Corticomuscular coherence was present in the beta band during sustained contractions but vanished before movement onset, being replaced by transient synchronization in the alpha and gamma bands during dynamic force output. Analysis of the phase spectra suggested a time delay from muscle to cortex for alpha-band coherence, by contrast to a time delay from cortex to muscle for gamma-band coherence, indicating afferent and efferent corticospinal interactions respectively. Moreover, alpha and gamma-band coherence revealed distinct spatial topologies, suggesting different generative mechanisms. Coherence in the alpha and gamma bands was almost exclusively confined to trials showing a movement overshoot, suggesting a functional role related to error correction. We interpret the dual-band synchronization in the alpha and gamma bands as parallel streams of corticospinal processing involved in parsing prediction errors and generating new motor predictions.
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