Editorial: Error-related potentials: Challenges and applications

Error-related potentials (ErrPs) are neurophysiological signals associated with error processing. They are generated when wrong actions are perceived and have been reported in many contexts in the past three decades, namely when a subject perceives that he/she has committed an error and recognizes it immediately in choice reaction time paradigms (“response ErrP”), when a subject receives the feedback of a previous choice without knowing whether it was wrong (“feedback ErrP”), when observing mistakes of another person or an intelligent agent (“observation ErrP”) or during the interaction with a Brain-Computer Interface (BCI) when the feedback is not the expected one (“interaction ErrP”). The components of an ErrP appear within a time window of 500 ms and are naturally elicited in the brain without the user’s explicit intention. Thus, its automatic detection can be used in real-time in myriad ways. Given the importance of error monitoring in social interaction, behavior, human-machine interaction, and cognitive learning, it starts to be recognized that the possibility of automatic detection of error signals through machine learning can be relevant for many real-life applications in clinical and non-clinical contexts. ErrPs have already been applied as a proof-ofconcept in several applications, for detection and correction of BCI choices to increase reliability, to adapt BCI systems over time, or to make artificial intelligent systems learn. Furthermore, in recent years there has been a growing interest in the integration of ErrP-based approaches in clinical applications for disorders where error monitoring is impaired. While the practical use of error signals is still in its infancy and is an open research field, there is also much to know in order to understand their origin and underlying neural mechanisms.