{
  "id": 6329386,
  "title": "PRISM-M: A Recurrent Framework for the Formation of Stable Internal Neural Models",
  "url": "https://urgent.news/2026/09/08/prism-m-a-recurrent-framework-for-the-formation-of-stable-internal",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-08T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.09.02.748818v1?rss=1"
  },
  "original_language": "en",
  "account": null,
  "summary": "How transient neural representations become integrated and stable enough to function as internal neural models remains incompletely understood. Grounded in efficient coding, Bayesian and predictive frameworks, recurrent and attractor dynamics, neural state-space models, and systems neuroscience, the Principle of Representation Integration for Stable Models (PRISM) proposes five operations:…",
  "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."
}