Electromyogram of pericranial muscles in frequency bands β and γ comparing various cognitive and emotional states

Results of comparison of power of electromyogram (EMG) of six pericranial muscles in electroencephalographic frequency bands β 1 , β 2 and γ are presented corresponding to performances of the tasks bound to inductions of affective experiences. The external induction was implemented by means of prese...

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Bibliographic Details
Published in:Human physiology Vol. 40; no. 2; pp. 117 - 124
Main Authors: Danko, S. G., Gratcheva, L. V., Boytsova, J. A., Solovjeva, M. L.
Format: Journal Article
Language:English
Published: Moscow Pleiades Publishing 01-03-2014
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Summary:Results of comparison of power of electromyogram (EMG) of six pericranial muscles in electroencephalographic frequency bands β 1 , β 2 and γ are presented corresponding to performances of the tasks bound to inductions of affective experiences. The external induction was implemented by means of presentation of images and the internal induction by means of autobiographical memoirs revived. The tasks were focused on an induction of affective experiences with different emotional valences—positive, negative and neutral. The EMG was derived, registered and processed by means of computer electroencephalography techniques. Self-assessments of signs and intensities of experienced emotions were recorded as well. The study involved two groups of healthy subjects—students-actors ( N = 39), and students of other specialties ( N = 32). Statistically reliable, reproducible and diverse differences of mean EMG power of the pericranial muscles took place in comparisons of psychophysiological states with different valences of emotions, and certain differences in comparisons of states without expressed emotional differences, but differing in the direction of attention took place also. Therefore it is obviously necessary for an assessment of a degree of muscular contamination in records of high-frequency scalp electroencephalograms (EEG) to supplement psychophysiological EEG methods with EMG registration and statistical analysis and to do such registration for several facial muscles.
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ISSN:0362-1197
1608-3164
DOI:10.1134/S0362119714010022