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Beyond Peaks and Troughs: Multiplexed Performance Monitoring Signals in the EEG
  • Markus Ullsperger
Markus Ullsperger
Otto-von-Guericke-Universit├Ąt Magdeburg

Corresponding Author:[email protected]

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Abstract

With the discovery of event-related potentials elicited by errors more than thirty years ago, a new avenue of research on performance monitoring, cognitive control, and decision making was opened. Since then, the field has developed and expanded fulminantly. After a brief overview on the EEG correlates of performance monitoring, this article reviews recent advancements in the field of performance monitoring based on single-trial analyses using independent component analysis, multiple regression, and multivariate pattern classification. Given the close interconnection between performance monitoring and reinforcement learning, computational modeling and model-based EEG analyses have made a particularly strong impact. The reviewed findings demonstrate that error- and feedback-related EEG dynamics represent variables reflecting how performance monitoring signals are weighted and transformed into an adaptation signal that guides future decisions and actions. The model-based single-trial analysis approach goes far beyond conventional peak-and-trough analyses of event-related potentials and enables testing mechanistic theories of performance monitoring, cognitive control and decision making.
Submitted to Psychophysiology
27 Jan 2024Review(s) Completed, Editorial Evaluation Pending
08 Feb 20241st Revision Received
09 Feb 2024Submission Checks Completed
09 Feb 2024Assigned to Editor
09 Feb 2024Review(s) Completed, Editorial Evaluation Pending
10 Feb 2024Editorial Decision: Accept