Two dominant brain states reflect optimal and suboptimal attention
Attention is not constant but fluctuates from moment to moment. Previous studies dichotomized these fluctuations into optimal and suboptimal states based on behavioral performance and investigated the difference in brain activity between these states. Although these studies implicitly assume there are two states, this assumption is not guaranteed. Here, we reversed the logic of these previous studies and identified unique states of brain activity during a sustained attention task. We demonstrate a systematic relationship between dynamic brain activity patterns (brain states) and behavioral underpinnings of sustained attention by explaining behavior from two dominantly observed brain states. In four independent datasets, a brain state characterized by default mode network activity was behaviorally optimal and a brain state characterized by dorsal attention network activity was suboptimal. Thus, our study provides compelling evidence for behaviorally optimal and suboptimal attentional states from the sole viewpoint of brain activity. We further demonstrated how these brain states were impacted by motivation, mind wandering, and attention-deficit hyperactivity disorder. Within-subject level modulators (motivation and mind wandering) impacted the optimality of behavior in the suboptimal brain state. In contrast, between-subject level differences (ADHD vs healthy controls) impacted the optimal brain state character, namely its frequency.