Pulse Focus: Validation of the Focus Performance Score as a Behavioral Signal for Human Attentional State Modeling Toward Attention-Aware AI

Abstract: Artificial intelligence systems that model and support human cognition require reliable measures of cognitive state. We present the Focus Performance Score (FPS) from the Pulse Focus mobile Stroop application and evaluate whether it measures attentional control during color-word conflict resolution. We conduct behavioral, neural, and formula validation analyses. Behavioral results (N=466, 111,133 trials) show that FPS captures the Stroop interference effect, tracks individual differences in attentional control, and demonstrates strong test-retest reliability. Neural validation using the DMCC55B fMRI dataset (N=55) shows that the primary FPS component, mean incongruent reaction time, is significantly associated with anterior cingulate cortex activation, a key neural substrate of conflict monitoring. Formula validation identifies and resolves structural redundancy within the scoring framework and provides convergent support for the weighting design. Together, these findings establish FPS as a behaviorally valid, reliable, and neurally grounded measure of attentional control. FPS provides a defensible behavioral signal for evaluating human attentional state and supports future work on attention-aware human-AI interaction and physiological state modeling.