{
  "id": 3028725,
  "title": "Temporally distinct reward and action prediction error signals during value learning and habit formation",
  "url": "https://urgent.news/2026/08/24/temporally-distinct-reward-and-action-prediction-error-signals-during",
  "topic": "science",
  "section": "Science",
  "published": "2026-08-24T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.08.19.745693v1?rss=1"
  },
  "original_language": "en",
  "account": "Effective decision making in uncertain situations necessitates a balance between adaptable value-based learning and a stabilizing effect of habitual action selection. Dopamine-mediated reward prediction errors (RPEs) are known to play a role in value learning, but the mechanisms behind habit-like behavior are less understood. In this study, researchers examined the decision-making process of mice engaged in a probabilistic choice task, in which the actions taken were not immediately tied to the outcome on each trial. The team found that choice behavior was best explained by a model that integrated value-based, habitual, and risk-sensitive components, each of which was updated by separate reward- and action-related learning signals.\n\nThe researchers observed that dopamine activity in the dorsolateral striatum carried not only RPE-like signals when making a choice and receiving a result, but also temporally distinct action prediction errors (APEs) following the completion of a choice. These findings support a framework in which dopamine signals in the dorsolateral striatum carry parallel but distinct reward- and action-related learning signals to facilitate value- and habit-based processes.",
  "summary": "Effective decision making in stochastic environments requires balancing flexible, value-based learning with a stabilising influence of habitual action selection. While dopamine-mediated reward prediction errors (RPEs) are a well-established component of value learning, the mechanisms underlying habit-like behaviour remain less clear. Here, we combined behavioural analysis, computational…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}