Cognitive biotypes identified through ECG-derived workload and behavioral accuracy

Individual differences in physiological effort during cognitive workload, which we define as mental effort during task execution, are well established, yet self-reports often fail to reflect actual physiological effort. We hypothesized that combining cognitive performance with ECG-derived workload would reveal distinct biotypes of performance and physiological effort and that these biotypes would differ in how closely subjective appraisals align with objective measures. Participants completed cognitive tasks while ECG data were analyzed in real time using a validated workload classification algorithm. Clustering based on standardized performance accuracy and cognitive workload revealed three biotypes: (1) high performers with low workload, (2) average-to-high accuracy with high workload, and (3) low performers with variable workload. These biotypes exhibited distinct patterns of perceptual bias: Clusters 1 and 3 showed smaller discrepancies between subjective and objective workload, while Cluster 1 notably underestimated task success relative to their actual performance. These findings demonstrate that clustering behavioral and physiological data can reveal meaningful cognitive stress response profiles and suggest that subjective-objective misalignment may serve as a potential marker of cognitive resilience or poor interoception. This taxonomy may aid future efforts to personalize assessments or interventions aimed at optimizing performance under stress.