New insights into neural networks of error monitoring and clinical implications: a systematic review of ERP studies in neurological diseases

Abstract

Error monitoring allows for the efficient performance of goal-directed behaviors and successful learning. Furthermore, error monitoring as a metacognitive ability may play a crucial role for neuropsychological interventions, such as rehabilitation. In the past decades, research has suggested two electrophysiological markers for error monitoring: the error-related negativity (ERN) and the error positivity (Pe), thought to reflect, respectively, error detection and error awareness. Studies on several neurological diseases have investigated the alteration of the ERN and the Pe, but these findings have not been summarized. Accordingly, a systematic review was conducted to understand what neurological conditions present alterations of error monitoring event-related potentials and their relation with clinical measures. Overall, ERN tended to be reduced in most neurological conditions while results related to Pe integrity are less clear. ERN and Pe were found to be associated with several measures of clinical severity. Additionally, we explored the contribution of different brain structures to neural networks underlying error monitoring, further elaborating on the domain-specificity of error processing and clinical implications of findings. In conclusion, electrophysiological signatures of error monitoring could be reliable measures of neurological dysfunction and a robust tool in neuropsychological rehabilitation.

Keywords: ERPs; error positivity; error-related negativity; neurology; self-monitoring.