Analysis of the effects of mechanically induced tremor on EEG-EMG coherence using wavelet and partial directed coherence

Lara M. McManus, Francesco Budini, Francesco Di Russo, Marika Berchicci, Federica Menotti, Andrea Macaluso, Giuseppe De Vito, Madeleine M. Lowery

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Corticomuscular coherence between human cortical rhythms and surface electromyography (sEMG) is commonly observed within the beta (13-35 Hz) and gamma (35-60 Hz) band frequency ranges, but is typically absent within the alpha band (8-12 Hz) in healthy subjects. A recent study has shown that significant alpha band corticomuscular coherence can be mechanically induced in healthy subjects using a spring of appropriate stiffness. Traditional coherence analysis is limited to examining whether a correlation exists between the electroencephalograph (EEG) and EMG recordings, by portraying instances of mutual synchrony. In this study the temporal evolution and directionality of the interaction between the EEG and EMG signals during mechanically induced alpha band coherence were investigated using two recent extensions of classical coherence, wavelet analysis and partial directed coherence. The results indicate a significant increase in directional information flow within the alpha and piper band frequency ranges in the EMG to EEG direction, and appear to provide evidence of the contribution of afferent feedback, and to a lesser extent descending cortical drives, to alpha band corticomuscular coherence.

Original languageEnglish
Title of host publicationInternational IEEE/EMBS Conference on Neural Engineering, NER
Pages561-564
Number of pages4
DOIs
Publication statusPublished - 2013
Event2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013 - San Diego, CA, United States
Duration: Nov 6 2013Nov 8 2013

Other

Other2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013
CountryUnited States
CitySan Diego, CA
Period11/6/1311/8/13

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering

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