Coherence-based connectivity analysis of EEG and EMG signals during reach-to-grasp movement involving two weights

Corticomuscular coherence allows studying the mechanism of the cerebral cortex’s control of muscle activity, which reveals the communication in corticospinal pathways between the primary motor cortex and muscles. The present study aims to quantify the connectivity between the motor cortex (EEG signals) and five muscles of the right upper limb (EMG signals) during the manipulation of an object. A public dataset (WAY-EEG-GAL) was used which recorded EEG and EMG of twelve healthy subjects who performed movements of reaching, grasping, holding, and replacing objects of two different weights. Corticomuscular connectivity was established using the coherence algorithm for 3 EEG channels and 5 upper-limb muscles varying two objects' weights (0.165 kg and 0.660 kg). Results show that the 0.165 kg weight shows greater coherence between the signals for all analyses than the 0.660 kg weight. Furthermore, the results show that there is a contralateral and ipsilateral behavior in the EEG-EMG coherence.