title: Cross-frequency information transfer from EEG to EMG in grasping.
abstract: This paper presents an investigation into the cortico-muscular relationship during a grasping task by evaluating the information transfer between EEG and EMG signals. Information transfer was computed via a non-linear model-free measure, transfer entropy (TE). To examine the cross-frequency interaction, TEs were computed after the times series were decomposed into various frequency ranges via wavelet transform. Our results demonstrate the capability of TE to capture the direct interaction between EEG and EMG. In addition, the cross-frequency analysis revealed instantaneous decrease in information transfer from EEG to the high frequency component of EMG (100-200Hz) during the onset of movement.
authors.forename: Winnie K Y
authors.initials: WK
authors.lastname: So
authors.lastname: Lingling Yang
authors.forename: Beth
authors.initials: B
authors.lastname: Jelfs
authors.lastname: Qi She
authors.forename: Savio W H
authors.initials: SW
authors.lastname: Wong
authors.forename: Joseph N
authors.initials: JN
authors.lastname: Mak
authors.forename: Rosa H M
authors.initials: RH
authors.lastname: Chan
mesh_terms: D002540:Cerebral Cortex / Q000502:physiology*; D004569:Electroencephalography / Q000379:methods*; D004576:Electromyography / Q000379:methods*; D018737:Hand Strength; D006801:Humans; D009132:Muscles / Q000502:physiology*; D058067:Wavelet Analysis