Enhancing Error Awareness Under Cognitive Load: How Neurostimulation Improves Self-Monitoring via Working Memory

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Authors: Xiaohan Huang, Jiahui Wu, Ming Zhou, Xuemin Zhang
Cited by: 1
References: 73

Abstract

Error awareness—the ability to detect error, adjust strategies, and prevent mistakes—is critical in high-stakes human-computer interaction (e.g., aviation, autonomous system supervision), as well as in everyday life and work. However, this ability deteriorates under heavy cognitive load, and effective countermeasures remain scarce. We investigate whether transcranial direct current stimulation (tDCS) can mitigate this deficit. Using a multi-rule task with EEG, we found that under high load, tDCS over the left dorsolateral prefrontal cortex (DLPFC) significantly improved error awareness, as reflected in both behavioral measures and a neural index (ERN amplitude). Crucially, mediation analysis showed this effect was achieved by improving working memory capacity, which facilitated better real-time error detection. Our findings demonstrate that neurostimulation sustains self-monitoring precisely by augmenting depleted cognitive resources (e.g., working memory). We formalize this in the Dynamic Cognitive Resource Barrel Theory: error awareness is limited by the most depleted cognitive “stave” after primary task demands. These results offer a principled path for designing neuroadaptive systems that predict and support these specific processes in critical moments.

Fields of Study & Subjects

Human-Automation Interaction and Safety Neural and Behavioral Psychology Studies Personal Information Management and User Behavior

Publication details

Journal / source
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Pages
1–18
Publication date
13 April 2026