A statistical comparison of EEG time- and time–frequency domain representations of error processing

• Published in: Brain research Vol. 1618; pp. 222 - 230
• Main Authors: Munneke, Gert-Jan, Nap, Tanja S., Schippers, Eveline E., Cohen, Michael X
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 27.08.2015
• Subjects: Adult; Brain - physiology; Brain Mapping; Contingent Negative Variation - physiology; EEG; Electroencephalography; ERN; ERP; Error processing; Female; Humans; Male; Neurology; Reaction Time - physiology; Regression Analysis; Theta; Time Factors; Time–frequency; Young Adult; ERN; ERP; Time–frequency; EEG; Error processing; Theta
• ISSN: 0006-8993; 1872-6240; 1872-6240
• DOI: 10.1016/j.brainres.2015.05.030

Successful behavior relies on error detection and subsequent remedial adjustment of behavior. Researchers have identified two electrophysiological signatures of error processing: the time-domain error-related negativity (ERN), and the time–frequency domain increased power in the delta/theta frequency bands (~2–8Hz). The relationship between these two signatures is not entirely clear: on the one hand they occur after the same type of event and with similar latency, but on the other hand, the time-domain ERP component contains only phase-locked activity whereas the time–frequency response additionally contains non-phase-locked dynamics. Here we examined the ERN and error-related delta/theta activity in relation to each other, focusing on within-subject analyses that utilize single-trial data. Using logistic regression, we constructed three statistical models in which the accuracy of each trial was predicted from the ERN, delta/theta power, or both. We found that both the ERN and delta/theta power worked roughly equally well as predictors of single-trial accuracy (~70% accurate prediction). Furthermore, a model including both measures provided a stronger overall prediction compared to either model alone. Based on these findings two conclusions are drawn: first, the phase-locked part of the EEG signal appears to be roughly as predictive of single-trial response accuracy as the non-phase-locked part; second, the single-trial ERP and delta/theta power contain both overlapping and independent information. •We investigated the relationship between ERN and delta/theta EEG error signatures.•Both the ERN and delta/theta activity predict error trials with ~70% accuracy.•A model with both measures predicted better than models with either measure alone.•Both phase-locked and non-phase-locked factors contribute to error-related cognition.