Version history

{
  "scope": "computational model of mouse V1 multilayer microcircuit (pyramidal + PV + SST + VIP, superficial and deep)",
  "claim_text": "Modelling of mouse V1 multilayer microcircuits demonstrates that both superficial and deep layers implement ultrasensitive bistable switches built on mutual inhibition among SST, PV and VIP interneurons that toggle pyramidal neurons between high- and low-firing-rate states, with translaminar excitatory connectivity synchronizing the two layer-switches and producing asymmetric layer-specific oscillation frequency and power changes during state transitions.",
  "raw_fields": {
    "n": 0,
    "doi": "10.7554/elife.77594",
    "claim": "Modelling of mouse V1 multilayer microcircuits demonstrates that both superficial and deep layers implement ultrasensitive bistable switches built on mutual inhibition among SST, PV and VIP interneurons that toggle pyramidal neurons between high- and low-firing-rate states, with translaminar excitatory connectivity synchronizing the two layer-switches and producing asymmetric layer-specific oscillation frequency and power changes during state transitions.",
    "cite_key": "Hahn2022",
    "evidence": "Biophysical / rate model of mouse V1 multilayer microcircuit with SST, PV, VIP and pyramidal populations in superficial and deep layers; analytical and numerical analysis of bistability and oscillations.",
    "effect_size": "Two ultrasensitive bistable switches per layer; cross-layer synchrony via translaminar excitatory connectivity; asymmetric frequency/power changes at transitions.",
    "text_access": "abstract_only",
    "study_system": "computational model of mouse V1 multilayer microcircuit (pyramidal + PV + SST + VIP, superficial and deep)",
    "argument_role": "supporting",
    "replication_status": "modeling",
    "claim_source_sentence": "The switches toggle pyramidal neurons between high and low firing rate states that are synchronized across layers through translaminar connectivity.",
    "source_provenance_status": "non_substring_match",
    "replication_evidence_dois": [
      "10.1371/journal.pcbi.1004090"
    ],
    "effect_size_source_sentence": null
  },
  "section_id": "section_04",
  "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_04_evidence_package.json",
  "effect_size": "Two ultrasensitive bistable switches per layer; cross-layer synchrony via translaminar excitatory connectivity; asymmetric frequency/power changes at transitions.",
  "review_repo": "ComputationalReviewRecurrence",
  "section_ref": "wiki_page:computationalreviewrecurrence-04-translaminar",
  "source_kind": "review_finding",
  "source_path": "evidence/section_04_evidence_package.json",
  "source_refs": [
    "paper:paper-bbc707d63f15"
  ],
  "source_span": "The switches toggle pyramidal neurons between high and low firing rate states that are synchronized across layers through translaminar connectivity.",
  "study_system": "computational model of mouse V1 multilayer microcircuit (pyramidal + PV + SST + VIP, superficial and deep)",
  "evidence_refs": [
    {
      "ref": "paper:paper-bbc707d63f15"
    }
  ],
  "section_title": "4. Translaminar excitatory loops in mouse — L4→L2/3→L5→L6→L4 within the column; asymmetry of forward and backward intracortical projections",
  "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": "Biophysical / rate model of mouse V1 multilayer microcircuit with SST, PV, VIP and pyramidal populations in superficial and deep layers; analytical and numerical analysis of bistability and oscillations.",
  "review_bundle_ref": "analysis_bundle:ab-d9c479db9be9",
  "replication_status": "modeling",
  "review_package_ref": "analysis_bundle:ab-d9c479db9be9",
  "source_artifact_ref": "wiki_page:computationalreviewrecurrence-04-translaminar",
  "origin_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_04_evidence_package.json",
  "commit_sha": "79ce062d54a924ce05953ec90aa9d26044d2b48f",
  "created_by": "persona-jerome-lecoq-gbo-neuroscience",
  "repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence"
}