{
  "id": 9463037,
  "title": "AI-Driven Neural Surrogates for In Silico Design of Cognitive-Affective Neuromodulation Targets",
  "url": "https://urgent.news/2026/09/23/ai-driven-neural-surrogates-for-in-silico-design-of-cognitive",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-23T11:44:30.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.27729v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "In neuropsychiatry, the primary goal is often not only to decode brain activity but to change it, for example to lessen a negative affective bias or an overly salient memory. Motivated by control theory, we develop an AI-driven neural-surrogate framework that proposes candidate representational changes and tests their predicted perceptual effects from snapshots of stimulus-evoked fMRI activity,…",
  "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."
}