{
  "abstract": "Reward-related changes in hippocampal place-cell activity may reflect either different use of an existing spatial map or plasticity that reshapes the map. We separated these contributions in a two-pathway model: a recurrent network learned to predict sensory input and developed a spatial representation, while a reinforcement-learning controller combined this representation with an explicit goal signal to guide behavior. Replaying identical trajectories before and after learning isolated representational plasticity. Goal-directed behavior strongly concentrated place fields near reward, whereas changes to the representation were smaller and more variable. A reward-proximity teaching signal made these changes larger and more consistent, and the change was strongly attenuated when recurrent plasticity was restricted. After reward relocation, goal-related directional tuning adapted more fully than place-field organization, while withdrawing reward and proximity teaching reversed the learned field concentration. Thus, reward affects predictive spatial maps through separable mechanisms: goal information changes how an existing map is used, whereas reward-related teaching signals reshape the map itself. Our results provide a concrete framework for future experiments to disentangle how reward information, plasticity and behavior jointly shape hippocampal activity.",
  "abstract_shown": true,
  "affiliations": [
    "Technion - Israel Institute of Technology & Allen Institute for Neural Dynamics"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "name": "S. Oza"
    },
    {
      "name": "A. Cohen"
    },
    {
      "name": "G. Wager"
    },
    {
      "name": "D. Derdikman"
    },
    {
      "affs": [
        0
      ],
      "name": "S. Recanatesi"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/c5tqc1fnm8qga.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.28.762439",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.28.762439v1.full",
  "id": "c5tqc1fnm8qga",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.28.762439v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "neuroscience"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.28.762439v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-28",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/c5tqc1fnm8qga.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:30:19Z",
      "native_id": "10.64898/2026.10.28.762439",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.28.762439v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:neuroscience",
      "subfield": "neuroscience"
    }
  ],
  "title": "Reward changes the use and structure of predictive spatial maps",
  "title_text": "Reward changes the use and structure of predictive spatial maps",
  "type": "preprint",
  "updated_at": "2026-10-31T00:20:36Z",
  "url": "https://research.draconitic.com/paper/c5tqc1fnm8qga",
  "venue": "bioRxiv",
  "versions": []
}