Version history

{
  "scope": "mouse V1; two-photon 'optomapping' optogenetic input mapping",
  "claim_text": "Optomapping of 30,454 candidate inputs in mouse V1 reveals 1,790 excitatory inputs distributed across cell types with log-normal synaptic-efficacy distribution; pyramidal-cell input reproduces the canonical L4→L2/3→L5 microcircuit while basket-cell excitation concentrates in L5 and Martinotti-cell excitation dominates in L2/3.",
  "raw_fields": {
    "n": 1790,
    "doi": "10.1016/j.xinn.2024.100735",
    "claim": "Optomapping of 30,454 candidate inputs in mouse V1 reveals 1,790 excitatory inputs distributed across cell types with log-normal synaptic-efficacy distribution; pyramidal-cell input reproduces the canonical L4→L2/3→L5 microcircuit while basket-cell excitation concentrates in L5 and Martinotti-cell excitation dominates in L2/3.",
    "cite_key": "Chou2025",
    "evidence": "Two-photon optogenetic 'optomapping', ~100x faster than paired patch, in mouse V1 across cell types.",
    "effect_size": "30,454 candidate inputs; 1,790 excitatory inputs; log-normal efficacy distribution.",
    "text_access": "abstract_only",
    "study_system": "mouse V1; two-photon 'optomapping' optogenetic input mapping",
    "argument_role": "supporting",
    "replication_status": "independently_replicated",
    "claim_source_sentence": "In mouse primary visual cortex (V1), we optomapped 30,454 candidate inputs to reveal 1,790 excitatory inputs to pyramidal, basket, and Martinotti cells. Across these cell types, log-normal distribution of synaptic efficacies emerged as a principle. For pyramidal cells, optomapping reproduced the canonical circuit but unexpectedly uncovered that the excitation of basket cells concentrated to layer 5 and that of Martinotti cells dominated in layer 2/3.",
    "source_provenance_status": "non_substring_match",
    "replication_evidence_dois": [
      "10.7554/eLife.71103",
      "10.1038/s41586-025-08840-3"
    ],
    "effect_size_source_sentence": "In mouse primary visual cortex (V1), we optomapped 30,454 candidate inputs to reveal 1,790 excitatory inputs to pyramidal, basket, and Martinotti cells."
  },
  "section_id": "section_04",
  "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_04_evidence_package.json",
  "effect_size": "30,454 candidate inputs; 1,790 excitatory inputs; log-normal efficacy distribution.",
  "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-20192df165b8"
  ],
  "source_span": "In mouse primary visual cortex (V1), we optomapped 30,454 candidate inputs to reveal 1,790 excitatory inputs to pyramidal, basket, and Martinotti cells. Across these cell types, log-normal distribution of synaptic efficacies emerged as a principle. For pyramidal cells, optomapping reproduced the canonical circuit but unexpectedly uncovered that the excitation of basket cells concentrated to layer 5 and that of Marti...",
  "study_system": "mouse V1; two-photon 'optomapping' optogenetic input mapping",
  "evidence_refs": [
    {
      "ref": "paper:paper-20192df165b8"
    }
  ],
  "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": "Two-photon optogenetic 'optomapping', ~100x faster than paired patch, in mouse V1 across cell types.",
  "review_bundle_ref": "analysis_bundle:ab-d9c479db9be9",
  "replication_status": "independently_replicated",
  "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"
}