Managing electromyogram contamination in scalp recordings: an approach identifying reliable beta and gamma EEG features of psychoses or other disorders

Author:

Pope Kenneth J.,Lewis Trent W.,Fitzgibbon Sean P.,Janani Azin S.,Grummett Tyler S.,Williams Patricia A.H.,Battersby Malcolm,Bastiampillai Tarun,Whitham Emma M.,Willoughby John O.

Abstract

AbstractObjectiveIn publications on the electroencephalographic (EEG) features of psychoses and other disorders, various methods are utilised to diminish electromyogram (EMG) contamination. The extent of residual EMG contamination using these methods has not been recognised. Here, we seek to emphasise the extent of residual EMG contamination of EEG.MethodsWe compared scalp electrical recordings after applying different EMG-pruning methods with recordings of EMG-free data from 6 fully-paralysed healthy subjects. We calculated the ratio of the power of pruned, normal scalp electrical recordings in the 6 subjects, to the power of unpruned recordings in the same subjects when paralysed. We produced “contamination graphs” for different pruning methods.ResultsEMG contamination exceeds EEG signals progressively more as frequencies exceed 25 Hz and with distance from the vertex. In contrast, Laplacian signals are spared in central scalp areas, even to 100 Hz.ConclusionGiven probable EMG contamination of EEG in psychiatric and other studies, few findings on beta- or gamma-frequency power can be relied upon. Based on the effectiveness of current methods of EEG de-contamination, investigators should be able to re-analyse recorded data, re-evaluate conclusions from high frequency EEG data and be aware of limitations of the methods.

Publisher

Cold Spring Harbor Laboratory

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