{
  "abstract": "Background / Introduction: Biologically inspired spiking neural networks offer a mechanistic framework for adaptive behavior, yet learning multiple goals remains challenging when synaptic updates for different targets interfere. We investigated whether multi-timescale plasticity and context-specific credit assignment improve interleaved multi-goal learning in a spiking navigation system inspired by entorhinal-hippocampal circuitry. Methods: We introduce evidence-gated plasticity (EGP), in which reward-modulated spike-timing-dependent plasticity (STDP) generates transient synaptic proposals and need-weighted behavioral evidence modulates their slower consolidation into durable weights. Global EGP pools these proposals and the corresponding evidence across goals. Target-context EGP extends this framework through goal-specific proposal and evidence stores and additional need-dependent scaling of consolidation. We compared the algorithms across paired spiking networks, tested learned weights with plasticity disabled, and examined upstream representations and consolidation components. Results: Global EGP supported multi-goal learning and durable navigation. Target-context EGP improved early reward across 40 paired networks, including an independently specified 30-pair replication. Across eight paired networks trained for 2000 episodes, target-context EGP maintained a reward advantage, increased target-contact success, and reduced expected time to reach the target when unsuccessful blocks were included. Independent fixed-weight evaluation demonstrated durable navigation in both algorithms, with seven of eight networks favoring target-context EGP. A component experiment reproduced the target-context reward advantage and identified additional need-dependent scaling of context-specific consolidation as the only component with adjusted statistical support for improved reward. Conclusions: EGP supports durable multi-goal learning in spiking neural networks, and its target-context extension improves acquisition and conditional target selectivity in this interleaved navigation task. The framework offers a basis for testing context-sensitive, evidence-modulated plasticity in other multi-context learning problems.",
  "abstract_shown": true,
  "affiliations": [
    "Nathan S. Kline Institute for Psychiatric Research"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 7,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "S. A. Neymotin"
    },
    {
      "name": "H. Hazan"
    },
    {
      "name": "G. Unal"
    },
    {
      "name": "C. Earl"
    },
    {
      "name": "H. Anwar"
    },
    {
      "name": "P. Franaszczuk"
    },
    {
      "name": "D. Boothe"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/bnc6fw1n6pe3p.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.06.25.734613",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.06.25.734613v2.full",
  "id": "bnc6fw1n6pe3p",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.06.25.734613v2",
  "language": null,
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "neuroscience"
    ],
    [
      "openalex",
      "2805|Memory and Neural Mechanisms"
    ]
  ],
  "openalex": "W7166693518",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.06.25.734613v2.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-06-25",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/bnc6fw1n6pe3p.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:26:57Z",
      "native_id": "10.64898/2026.06.25.734613",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.06.25.734613v2"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:neuroscience",
      "subfield": "neuroscience"
    }
  ],
  "title": "Evidence-Gated Plasticity and Context-Dependent Consolidation for Multi-Goal Learning in Spiking Neural Networks",
  "title_text": "Evidence-Gated Plasticity and Context-Dependent Consolidation for Multi-Goal Learning in Spiking Neural Networks",
  "type": "preprint",
  "updated_at": "2026-10-30T12:26:57Z",
  "url": "https://research.draconitic.com/paper/bnc6fw1n6pe3p",
  "venue": "bioRxiv",
  "versions": []
}