RT Journal Article SR Electronic T1 Normative Decision Rules in Changing Environments JF bioRxiv FD Cold Spring Harbor Laboratory SP 2022.04.27.489722 DO 10.1101/2022.04.27.489722 A1 Nicholas W Barendregt A1 Joshua I Gold A1 Krešimir Josić A1 Zachary P Kilpatrick YR 2022 UL http://biorxiv.org/content/early/2022/05/17/2022.04.27.489722.abstract AB Models based on normative principles have played a major role in our understanding of how the brain forms decisions. However, these models have typically been derived for simple, stable environments, and their relevance to decisions under more naturalistic, dynamic conditions is unclear. We previously derived a normative decision model in which evidence accumulation is adapted to environmental dynamics (Glaze et al., 2015), but the evolution of commitment rules (e.g., thresholds on the accumulated evidence) under such dynamic conditions is not fully understood. Here we derive a normative model for decisions based on changing evidence or reward. In these cases, performance (reward rate) is maximized using adaptive decision thresholds that best account for diverse environmental changes, in contrast to predictions of many previous decision models. These adaptive thresholds exhibit several distinct temporal motifs that depend on the specific, predicted and experienced changes in task conditions. These adaptive decision strategies perform robustly even when implemented imperfectly (noisily) and can account for observed response times on a task with time-varying evidence better than commonly used constant-threshold or urgency-gating models. These results further link normative and neural decision-making while expanding our view of both as dynamic, adaptive processes that update and use expectations to govern both deliberation and commitment.Competing Interest StatementJoshua Gold: Senior editor, eLife. The other authors declare that no competing interests exist.