Version history

{
  "scope": "Mouse V1 multi-interneuron network model (theoretical, connectivity from experiment)",
  "claim_text": "In multi-interneuron (PV, SOM, VIP) recurrent network models with mouse V1 connectivity, recurrent excitatory dynamics require inhibitory stabilization; perturbations of distinct interneuron subtypes recruit specific changes in network activity that reflect strong E→E recurrent coupling.",
  "raw_fields": {
    "n": 0,
    "doi": "10.1152/jn.00732.2015",
    "claim": "In multi-interneuron (PV, SOM, VIP) recurrent network models with mouse V1 connectivity, recurrent excitatory dynamics require inhibitory stabilization; perturbations of distinct interneuron subtypes recruit specific changes in network activity that reflect strong E→E recurrent coupling.",
    "cite_key": "LitwinKumar2016",
    "evidence": "Rate-network theory and simulations of cortical circuits with experimentally measured PV/SOM/VIP connectivity from mouse V1; analysis of stability, surround suppression, and tuning curve modulation.",
    "effect_size": "qualitative analytic conditions for stability and disinhibition; novel predictions for optogenetic manipulations",
    "text_access": "abstract_only",
    "study_system": "Mouse V1 multi-interneuron network model (theoretical, connectivity from experiment)",
    "argument_role": "supporting",
    "replication_status": "independently_replicated",
    "claim_source_sentence": "Our theory describes conditions under which the activity of such networks is stable and how perturbations of distinct neuronal subtypes recruit changes in activity through recurrent synaptic projections.",
    "source_provenance_status": "non_substring_match",
    "replication_evidence_dois": [
      "10.7554/eLife.49967",
      "10.7554/eLife.54875"
    ],
    "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 analytic conditions for stability and disinhibition; novel predictions for optogenetic manipulations",
  "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-8f25714ab7fe"
  ],
  "source_span": "Our theory describes conditions under which the activity of such networks is stable and how perturbations of distinct neuronal subtypes recruit changes in activity through recurrent synaptic projections.",
  "study_system": "Mouse V1 multi-interneuron network model (theoretical, connectivity from experiment)",
  "evidence_refs": [
    {
      "ref": "paper:paper-8f25714ab7fe"
    }
  ],
  "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-network theory and simulations of cortical circuits with experimentally measured PV/SOM/VIP connectivity from mouse V1; analysis of stability, surround suppression, and tuning curve modulation.",
  "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"
}