ArticleHuman brain mapping2026
Trial-By-Trial Changes in Neural Indices of Performance Monitoring Uniquely Correspond to Behavioral Adjustments During a Flanker Task.
Article in Human brain mapping, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Behavioral and neural indices of performance monitoring are key to understanding behavioral adaptation during task performance. However, associations between performance monitoring event-related potentials (ERPs) and task behavior have been inconsistent. This inconsistency may partly reflect reliance on single-subject averages that obscure trial-by-trial changes in ERPs and behavior, and a tendency to examine only one or two ERP indices at a time. Our objective was to uncover how neural variability during performance monitoring contributes to behavioral adaptation, revealing variability as a functional signature of cognitive control. We investigated whether current-trial response times (RTs) and accuracy can be predicted from previous- and current-trial congruency and accuracy and ERP indices of performance monitoring (N2, P3, error-related negativity [ERN], error positivity, [Pe]). Flanker data from 291 healthy participants (54% female) were analyzed using multilevel location-scale modeling. This modeling framework facilitates simultaneous examination of mean and variance relationships of single-trial data. Previous- and current-trial ERP amplitudes uniquely predict current-trial RTs and accuracy, beyond previous- and current-trial congruency and accuracy effects. Previous- and current-trial N2, P3, ERN, and Pe were concurrently related to the mean and variance of RTs and to accuracy. The observed within-person changes in the relationship between performance-monitoring ERPs and task behavior indicate that trial-by-trial neural fluctuations reflect dynamic adjustments in cognitive control across successive actions. These findings demonstrate the value of modeling intraindividual variability in neurophysiological measures to understand adaptive behavior.
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