Validation of regression-based myogenic correction techniques for scalp and source-localized EEG.
EEG and EEG source-estimation are susceptible to electromyographic artifacts (EMG) generated by the cranial muscles. EMG can mask genuine effects or masquerade as a legitimate effect-even in low frequencies, such as alpha (8-13 Hz). Although regression-based correction has been used previously, only cursory attempts at validation exist, and the utility for source-localized data is unknown. To address this, EEG was recorded from 17 participants while neurogenic and myogenic activity were factorially varied. We assessed the sensitivity and specificity of four regression-based techniques: between-subjects, between-subjects using difference-scores, within-subjects condition-wise, and within-subject epoch-wise on the scalp and in data modeled using the LORETA algorithm. Although within-subject epoch-wise showed superior performance on the scalp, no technique succeeded in the source-space. Aside from validating the novel epoch-wise methods on the scalp, we highlight methods requiring further development.
McMenamin
Brenton W
BW
University of MinnesotaTwin Cities, Minneapolis-Saint Paul, Minnesota, USA. mcmen020@umn.edu
Shackman
Alexander J
AJ
Maxwell
Jeffrey S
JS
Greischar
Lawrence L
LL
Davidson
Richard J
RJ
D000328:Adult; D000465:Algorithms; D004569:Electroencephalography / Q000379:methods* / Q000592:standards; D004576:Electromyography; D005260:Female; D006801:Humans; D008297:Male; D018482:Muscle, Skeletal / Q000502:physiology*; D012044:Regression Analysis; D015203:Reproducibility of Results; D012535:Scalp; D055815:Young Adult