Version history

{
  "scope": "SSN model relevant to cortex (cat/mouse); theoretical / numerical",
  "claim_text": "The stabilized supralinear network (SSN) supports bistable, oscillatory, and persistent activity regimes — extending the SSN framework beyond normalization/surround suppression to dynamics relevant for working memory and decision making in cortex.",
  "raw_fields": {
    "n": 0,
    "doi": "10.1073/pnas.1700080115",
    "claim": "The stabilized supralinear network (SSN) supports bistable, oscillatory, and persistent activity regimes — extending the SSN framework beyond normalization/surround suppression to dynamics relevant for working memory and decision making in cortex.",
    "cite_key": "Kraynyukova2018",
    "evidence": "Analytic and numerical bifurcation analysis of two-population SSN with strong recurrent E→E coupling stabilized by inhibition; identifies connectivity regimes yielding bistability, persistent activity, and Hopf-induced oscillations.",
    "effect_size": "qualitative — three new dynamical regimes derived analytically",
    "text_access": "fulltext",
    "study_system": "SSN model relevant to cortex (cat/mouse); theoretical / numerical",
    "argument_role": "supporting",
    "replication_status": "independently_replicated",
    "claim_source_sentence": "In particular, we show that the SSN model supports the following three effects.",
    "source_provenance_status": "ok",
    "replication_evidence_dois": [
      "10.7554/eLife.54875",
      "10.1523/JNEUROSCI.2830-20.2021"
    ],
    "effect_size_source_sentence": null
  },
  "section_id": "section_09",
  "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_09_evidence_package.json",
  "effect_size": "qualitative — three new dynamical regimes derived analytically",
  "review_repo": "ComputationalReviewRecurrence",
  "section_ref": "wiki_page:computationalreviewrecurrence-09-amplification-isn",
  "source_kind": "review_finding",
  "source_path": "evidence/section_09_evidence_package.json",
  "source_refs": [
    "paper:paper-5989bc007d71"
  ],
  "source_span": "In particular, we show that the SSN model supports the following three effects.",
  "study_system": "SSN model relevant to cortex (cat/mouse); theoretical / numerical",
  "evidence_refs": [
    {
      "ref": "paper:paper-5989bc007d71"
    }
  ],
  "section_title": "9. Physiological signature I — recurrent amplification of weak inputs in mouse cortex; balanced-amplification regimes; ISN operation",
  "source_policy": {
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    "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": "Analytic and numerical bifurcation analysis of two-population SSN with strong recurrent E→E coupling stabilized by inhibition; identifies connectivity regimes yielding bistability, persistent activity, and Hopf-induced oscillations.",
  "review_bundle_ref": "analysis_bundle:ab-d9c479db9be9",
  "replication_status": "independently_replicated",
  "review_package_ref": "analysis_bundle:ab-d9c479db9be9",
  "source_artifact_ref": "wiki_page:computationalreviewrecurrence-09-amplification-isn",
  "origin_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_09_evidence_package.json",
  "commit_sha": "79ce062d54a924ce05953ec90aa9d26044d2b48f",
  "created_by": "persona-jerome-lecoq-gbo-neuroscience",
  "repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence"
}