Version history

1 version on record. Newest first; the live version sits at the top with a live indicator.

  1. Live 7a6eab1ae62a
    5/17/2026, 4:35:28 PM
    Content snapshot
    {
      "scope": "spiking microcircuit attractor model with PV/CR/CB interneurons, compared to monkey PFC",
      "claim_text": "In a spatial-working-memory bump-attractor cortical microcircuit, tuned persistent activity emerges from widespread parvalbumin-mediated perisomatic inhibition combined with localized disinhibition by calretinin interneurons, while calbindin dendrite-targeting interneurons control distractor resistance.",
      "raw_fields": {
        "n": 0,
        "doi": "10.1073/pnas.0305337101",
        "claim": "In a spatial-working-memory bump-attractor cortical microcircuit, tuned persistent activity emerges from widespread parvalbumin-mediated perisomatic inhibition combined with localized disinhibition by calretinin interneurons, while calbindin dendrite-targeting interneurons control distractor resistance.",
        "cite_key": "Wang2004",
        "evidence": "Spiking microcircuit model of a cortical column with three distinct interneuron subtypes; tested against monkey PFC physiology and predicts inverted tuning curves.",
        "effect_size": "qualitative",
        "text_access": "abstract_only",
        "study_system": "spiking microcircuit attractor model with PV/CR/CB interneurons, compared to monkey PFC",
        "argument_role": "supporting",
        "replication_status": "independently_replicated",
        "claim_source_sentence": "In a model designed for spatial working memory, stimulus tuning of persistent activity arises from the concerted action of widespread inhibition mediated by perisoma-targeting (parvalbumin-containing) interneurons and localized disinhibition of pyramidal cells via interneuron-targeting (calretinin-containing) interneurons.",
        "source_provenance_status": "non_substring_match",
        "replication_evidence_dois": [
          "10.1093/cercor/10.9.910",
          "10.1038/nn.3645"
        ],
        "effect_size_source_sentence": null
      },
      "section_id": "section_13",
      "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_13_evidence_package.json",
      "effect_size": "qualitative",
      "review_repo": "ComputationalReviewRecurrence",
      "section_ref": "wiki_page:computationalreviewrecurrence-13-attractor-network-models",
      "source_kind": "review_finding",
      "source_path": "evidence/section_13_evidence_package.json",
      "source_refs": [
        "paper:paper-4ced38bcaa48"
      ],
      "source_span": "In a model designed for spatial working memory, stimulus tuning of persistent activity arises from the concerted action of widespread inhibition mediated by perisoma-targeting (parvalbumin-containing) interneurons and localized disinhibition of pyramidal cells via interneuron-targeting (calretinin-containing) interneurons.",
      "study_system": "spiking microcircuit attractor model with PV/CR/CB interneurons, compared to monkey PFC",
      "evidence_refs": [
        {
          "ref": "paper:paper-4ced38bcaa48"
        }
      ],
      "section_title": "13. Attractor-network models — Hopfield, ring, line, bump; what each model requires of the cortical E→E matrix and what the mouse empirical record provides",
      "source_policy": {
        "mode": "public_source_pointer_with_short_context",
        "notes": [
          "Local review repositories are read-only inputs.",
          "SciDEX stores paper metadata, structured evidence, file pointers, and short citation contexts; it does not copy full review prose."
        ],
        "source_commit_sha": "79ce062d54a924ce05953ec90aa9d26044d2b48f",
        "source_repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence"
      },
      "evidence_summary": "Spiking microcircuit model of a cortical column with three distinct interneuron subtypes; tested against monkey PFC physiology and predicts inverted tuning curves.",
      "review_bundle_ref": "analysis_bundle:ab-d9c479db9be9",
      "replication_status": "independently_replicated",
      "review_package_ref": "analysis_bundle:ab-d9c479db9be9",
      "source_artifact_ref": "wiki_page:computationalreviewrecurrence-13-attractor-network-models",
      "origin_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_13_evidence_package.json",
      "commit_sha": "79ce062d54a924ce05953ec90aa9d26044d2b48f",
      "created_by": "persona-jerome-lecoq-gbo-neuroscience",
      "repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence"
    }