Version history

{
  "scope": "V1 SSN model (mouse, ferret, primate data); rate + spiking simulations",
  "claim_text": "A stabilized supralinear network model with appropriate excitatory connectivity reproduces center-surround visual cortical phenomena (surround suppression, surround/center orientation matching, contrast-dependent summation fields), tying recurrent E→E gain to nonlinear contextual computations in V1.",
  "raw_fields": {
    "n": 0,
    "doi": "10.1523/eneuro.0459-24.2025",
    "claim": "A stabilized supralinear network model with appropriate excitatory connectivity reproduces center-surround visual cortical phenomena (surround suppression, surround/center orientation matching, contrast-dependent summation fields), tying recurrent E→E gain to nonlinear contextual computations in V1.",
    "cite_key": "Obeid2025",
    "evidence": "Rate-based and conductance-based spiking SSN model with power-law transfer functions; comparison to V1 surround data from mouse and other species.",
    "effect_size": "qualitative — SSN reproduces decrease in inhibition with surround suppression, orientation-matching tuning, contrast-dependent summation",
    "text_access": "fulltext",
    "study_system": "V1 SSN model (mouse, ferret, primate data); rate + spiking simulations",
    "argument_role": "supporting",
    "replication_status": "independently_replicated",
    "claim_source_sentence": "We demonstrate that the SSN, a mechanism that accounts for a multitude of cortical response properties, can also account for these phenomena, given appropriate connectivity.",
    "source_provenance_status": "ok",
    "replication_evidence_dois": [
      "10.1073/pnas.1700080115",
      "10.1371/journal.pcbi.1012190"
    ],
    "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 — SSN reproduces decrease in inhibition with surround suppression, orientation-matching tuning, contrast-dependent summation",
  "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-87e1cd00ec60"
  ],
  "source_span": "We demonstrate that the SSN, a mechanism that accounts for a multitude of cortical response properties, can also account for these phenomena, given appropriate connectivity.",
  "study_system": "V1 SSN model (mouse, ferret, primate data); rate + spiking simulations",
  "evidence_refs": [
    {
      "ref": "paper:paper-87e1cd00ec60"
    }
  ],
  "section_title": "9. Physiological signature I — recurrent amplification of weak inputs in mouse cortex; balanced-amplification regimes; ISN operation",
  "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": "Rate-based and conductance-based spiking SSN model with power-law transfer functions; comparison to V1 surround data from mouse and other species.",
  "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"
}