Version history

{
  "scope": "SSN circuit model, mouse visual cortex recordings",
  "claim_text": "The stabilized supralinear network (SSN) is a unifying circuit motif underlying multi-input integration: surround suppression, normalization, contrast invariance emerge from supralinear I/O, recurrent excitation, and feedback inhibition",
  "raw_fields": {
    "n": 0,
    "doi": "10.1016/j.neuron.2014.12.026",
    "claim": "The stabilized supralinear network (SSN) is a unifying circuit motif underlying multi-input integration: surround suppression, normalization, contrast invariance emerge from supralinear I/O, recurrent excitation, and feedback inhibition",
    "evidence": "Theoretical analysis and new recordings in visual cortex confirming model predictions",
    "effect_size": null,
    "text_access": "fulltext",
    "study_system": "SSN circuit model, mouse visual cortex recordings",
    "replication_status": "replication_unknown",
    "claim_source_sentence": "A wealth of integrative properties including the above emerge robustly from four properties of cortical circuitry: (1) supralinear neuronal input/output functions; (2) sufficiently strong recurrent excitation; (3) feedback inhibition; (4) simple spatial properties of intracortical connections.",
    "replication_evidence_dois": [],
    "effect_size_source_sentence": null
  },
  "section_id": "section_12_evidence_package",
  "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewPV/blob/df9fc7e8d455b084152c9d713558dae0013cef21/evidence/section_12_evidence_package.json",
  "effect_size": null,
  "review_repo": "ComputationalReviewPV",
  "section_ref": "wiki_page:computationalreviewpv-12",
  "source_kind": "review_finding",
  "source_path": "evidence/section_12_evidence_package.json",
  "source_refs": [
    "paper:paper-e15053dfa039"
  ],
  "source_span": "A wealth of integrative properties including the above emerge robustly from four properties of cortical circuitry: (1) supralinear neuronal input/output functions; (2) sufficiently strong recurrent excitation; (3) feedback inhibition; (4) simple spatial properties of intracortical connections.",
  "study_system": "SSN circuit model, mouse visual cortex recordings",
  "evidence_refs": [
    {
      "ref": "paper:paper-e15053dfa039"
    }
  ],
  "section_title": "Computational Models of PV Circuit Function",
  "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": "df9fc7e8d455b084152c9d713558dae0013cef21",
    "source_repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewPV"
  },
  "evidence_summary": "Theoretical analysis and new recordings in visual cortex confirming model predictions",
  "review_bundle_ref": "analysis_bundle:ab-e6261c8263e7",
  "replication_status": "replication_unknown",
  "review_package_ref": "analysis_bundle:ab-e6261c8263e7",
  "source_artifact_ref": "wiki_page:computationalreviewpv-12",
  "origin_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewPV/blob/df9fc7e8d455b084152c9d713558dae0013cef21/evidence/section_12_evidence_package.json",
  "commit_sha": "df9fc7e8d455b084152c9d713558dae0013cef21",
  "created_by": "persona-jerome-lecoq-gbo-neuroscience",
  "repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewPV"
}