Cortico-muscular coherence on artifact corrected EEG-EMG data recorded with a MRI scanner
- Simultaneous recording of electroencephalogram (EEG) and electromyogram (EMG) with magnetic resonance imaging (MRI) provides great potential for studying human brain activity with high temporal and spatial resolution. But, due to the MRI, the recorded signals are contaminated with artifacts. The correction of these artifacts is important to use these signals for further spectral analysis. The coherence can reveal the cortical representation of peripheral muscle signal in particular motor tasks, e.g. finger movements. The artifact correction of these signals was done by two different algorithms the Brain vision analyzer (BVA) and the Matlab FMRIB plug-in for EEGLAB. The Welch periodogram method was used for estimating the cortico-muscular coherence. Our analysis revealed coherence with a frequency of 5Hz in the contralateral side of the brain. The entropy is estimated for the calculated coherence to get the distribution of coherence in the scalp. The significance of the paper is toSimultaneous recording of electroencephalogram (EEG) and electromyogram (EMG) with magnetic resonance imaging (MRI) provides great potential for studying human brain activity with high temporal and spatial resolution. But, due to the MRI, the recorded signals are contaminated with artifacts. The correction of these artifacts is important to use these signals for further spectral analysis. The coherence can reveal the cortical representation of peripheral muscle signal in particular motor tasks, e.g. finger movements. The artifact correction of these signals was done by two different algorithms the Brain vision analyzer (BVA) and the Matlab FMRIB plug-in for EEGLAB. The Welch periodogram method was used for estimating the cortico-muscular coherence. Our analysis revealed coherence with a frequency of 5Hz in the contralateral side of the brain. The entropy is estimated for the calculated coherence to get the distribution of coherence in the scalp. The significance of the paper is to identify the optimal algorithm to rectify the MR artifacts and as a first step to use both these signals EEG and EMG in conjunction with MRI for further studies.…
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| Author: | Muthuraman MuthuramanORCiDGND, Andreas Galka, V. N. Hong, U. Heute, Günther Deuschl, Jan Raethjen |
|---|---|
| URN: | urn:nbn:de:bvb:384-opus4-1103373 |
| Frontdoor URL | https://opus.bibliothek.uni-augsburg.de/opus4/110337 |
| ISBN: | 978-1-4577-0216-7OPAC |
| Parent Title (English): | 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 3-7 July 2013, Osaka, Japan |
| Publisher: | IEEE |
| Place of publication: | Piscataway, NJ |
| Editor: | Yoshitaka Hirooka, Tomomi Ide, Takuya Kishi, Masaru Sugimachi |
| Type: | Conference Proceeding |
| Language: | English |
| Year of first Publication: | 2013 |
| Publishing Institution: | Universität Augsburg |
| Release Date: | 2023/12/21 |
| First Page: | 4811 |
| Last Page: | 4814 |
| DOI: | https://doi.org/10.1109/embc.2013.6610624 |
| Institutes: | Fakultät für Angewandte Informatik |
| Fakultät für Angewandte Informatik / Institut für Informatik | |
| Fakultät für Angewandte Informatik / Institut für Informatik / Professur für Informatik in der Medizintechnik | |
| Dewey Decimal Classification: | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik |
| Licence (German): |  Deutsches Urheberrecht |
