PT  - JOURNAL ARTICLE
AU  - Nicholas W Barendregt
AU  - Joshua I Gold
AU  - Krešimir Josić
AU  - Zachary P Kilpatrick
TI  - Normative Decision Rules in Changing Environments
AID  - 10.1101/2022.04.27.489722
DP  - 2022 Jan 01
TA  - bioRxiv
PG  - 2022.04.27.489722
4099  - http://biorxiv.org/content/early/2022/05/17/2022.04.27.489722.short
4100  - http://biorxiv.org/content/early/2022/05/17/2022.04.27.489722.full
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.