Version history

{
  "scope": "Cortical network simulations (data benchmarks from mouse V1 optogenetic ISN experiments)",
  "claim_text": "In realistic cortical network models, detecting an inhibition-stabilized (high-gain E→E) regime via paradoxical perturbation requires perturbing a large fraction of the inhibitory population — explaining why earlier small-perturbation experiments failed to find paradoxical effects despite cortex likely being ISN.",
  "raw_fields": {
    "n": 0,
    "doi": "10.1523/jneurosci.0963-17.2017",
    "claim": "In realistic cortical network models, detecting an inhibition-stabilized (high-gain E→E) regime via paradoxical perturbation requires perturbing a large fraction of the inhibitory population — explaining why earlier small-perturbation experiments failed to find paradoxical effects despite cortex likely being ISN.",
    "cite_key": "Sadeh2017",
    "evidence": "Simulations of cortical networks of increasing realism with parametric variation of perturbation extent and inhibitory fraction; comparison to published optogenetic ISN experiments.",
    "effect_size": "qualitative — narrow-perturbation paradigms fail; large-fraction perturbation required",
    "text_access": "abstract_only",
    "study_system": "Cortical network simulations (data benchmarks from mouse V1 optogenetic ISN experiments)",
    "argument_role": "supporting",
    "replication_status": "independently_replicated",
    "claim_source_sentence": "Our models predict that a large proportion of the inhibitory network must be perturbed to reliably detect an ISN regime robustly in cortex.",
    "source_provenance_status": "non_substring_match",
    "replication_evidence_dois": [
      "10.7554/eLife.54875",
      "10.7554/eLife.49967"
    ],
    "effect_size_source_sentence": "Current experimental methods for inhibitory perturbation are unlikely to satisfy this requirement, implying that existing experimental observations are inconclusive about the computational regime of cortex."
  },
  "section_id": "section_09",
  "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_09_evidence_package.json",
  "effect_size": "qualitative — narrow-perturbation paradigms fail; large-fraction perturbation required",
  "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-5135d667ceac"
  ],
  "source_span": "Our models predict that a large proportion of the inhibitory network must be perturbed to reliably detect an ISN regime robustly in cortex.",
  "study_system": "Cortical network simulations (data benchmarks from mouse V1 optogenetic ISN experiments)",
  "evidence_refs": [
    {
      "ref": "paper:paper-5135d667ceac"
    }
  ],
  "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": "Simulations of cortical networks of increasing realism with parametric variation of perturbation extent and inhibitory fraction; comparison to published optogenetic ISN experiments.",
  "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"
}