Version history

{
  "scope": "Mouse barrel cortex L4 (vS1), data-constrained spiking network model + in vivo recordings",
  "claim_text": "In mouse barrel cortex L4, recurrent excitation among E neurons amplifies thalamic touch responses; data-constrained network model with strong synapses operates in a balanced regime where moderate recurrent E→E gain extends response duration but excessive gain causes runaway excitation.",
  "raw_fields": {
    "n": 0,
    "doi": "10.1371/journal.pcbi.1005576",
    "claim": "In mouse barrel cortex L4, recurrent excitation among E neurons amplifies thalamic touch responses; data-constrained network model with strong synapses operates in a balanced regime where moderate recurrent E→E gain extends response duration but excessive gain causes runaway excitation.",
    "cite_key": "Gutnisky2017",
    "evidence": "Data-constrained spiking network model of mouse L4 barrel cortex including VPM thalamic, L4 excitatory, and FS interneuron populations; parameter sweep on recurrent excitatory weight; validated against cell-type-specific in vivo recordings.",
    "effect_size": "elevating recurrent excitatory conductance by ~2× beyond optimal causes runaway excitation; balanced regime gives proportional firing-rate scaling",
    "text_access": "fulltext",
    "study_system": "Mouse barrel cortex L4 (vS1), data-constrained spiking network model + in vivo recordings",
    "argument_role": "supporting",
    "replication_status": "within_lab",
    "claim_source_sentence": "amplifies touch responsesand() [], mostly by increasing the duration of touch responses ().",
    "source_provenance_status": "ok",
    "replication_evidence_dois": [],
    "effect_size_source_sentence": "Similarly,> 0 is required to amplify touch signals, but elevatingby a factor of two beyond the optimal level causes run-away excitation ()."
  },
  "section_id": "section_09",
  "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_09_evidence_package.json",
  "effect_size": "elevating recurrent excitatory conductance by ~2× beyond optimal causes runaway excitation; balanced regime gives proportional firing-rate scaling",
  "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:02525fad-059b-4ffc-ba1c-e5445baddd4d"
  ],
  "source_span": "amplifies touch responsesand() [], mostly by increasing the duration of touch responses ().",
  "study_system": "Mouse barrel cortex L4 (vS1), data-constrained spiking network model + in vivo recordings",
  "evidence_refs": [
    {
      "ref": "paper:02525fad-059b-4ffc-ba1c-e5445baddd4d"
    }
  ],
  "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": "Data-constrained spiking network model of mouse L4 barrel cortex including VPM thalamic, L4 excitatory, and FS interneuron populations; parameter sweep on recurrent excitatory weight; validated against cell-type-specific in vivo recordings.",
  "review_bundle_ref": "analysis_bundle:ab-d9c479db9be9",
  "replication_status": "within_lab",
  "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"
}