Journal Article

Trial‐By‐Trial Changes in Neural Indices of Performance Monitoring Uniquely Correspond to Behavioral Adjustments During a Flanker Task

Baldwin, Scott A., Rast, Philippe, Lutz, Miranda C., Larson, Michael J., Clayson, Peter E., Park, Bohyun

2026

Overview

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. Summary Points Moment‐to‐moment changes in brain activity predict how behavior adjusts from one trial to the next. Analyzing both average and variability patterns shows that neural fluctuations meaningfully track adaptive control. Variability in brain signals reflects adaptive control of behavior, not random noise. Trial‐by‐trial modeling revealed that neural variability in performance‐monitoring ERPs (N2, P3, ERN, Pe) predicts both the mean and variability of response times and mean accuracy in a flanker task. These findings show that fluctuations in brain activity reflect dynamic adjustments in cognitive control, linking neural variability to adaptive behavior.

• Publisher: John Wiley & Sons, Inc,Wiley
• Subject: Accuracy / Adaptation / Adolescent / Adult / Bayesian multilevel location‐scale models / Behavior / Brain - physiology / Electroencephalography / error processing / Event-related potentials / event‐related potentials (ERPs) / Evoked Potentials - physiology / Executive Function - physiology / Female / Humans / intraindividual variability / Male / Modelling / Monitoring / performance monitoring / Psychomotor Performance - physiology / Reaction Time - physiology / response times (RTs) / Variability / Young Adult