Version history

{
  "scope": "Mouse S1; dual retrograde tracing (L1 + local L5); per-layer quantification of double-labelled neurons",
  "claim_text": "In mouse S1, double-retrograde tracing reveals substantial cross-targeting: 45% of L2/3 neurons, 33% of L5a neurons and 20% of L5b neurons both contact L1 and are presynaptic to local L5 pyramidal cells, implying that L1-targeting inputs and L5-targeting inputs are largely sourced from the same intracortical neuron pools.",
  "raw_fields": {
    "n": 0,
    "doi": "10.1093/cercor/bhad371",
    "claim": "In mouse S1, double-retrograde tracing reveals substantial cross-targeting: 45% of L2/3 neurons, 33% of L5a neurons and 20% of L5b neurons both contact L1 and are presynaptic to local L5 pyramidal cells, implying that L1-targeting inputs and L5-targeting inputs are largely sourced from the same intracortical neuron pools.",
    "cite_key": "Ledderose2023",
    "evidence": "Dual retrograde tracing from L1 and from local L5 pyramidal neurons in mouse S1; quantification of double-labelled cells per layer.",
    "effect_size": "Double-labelled fraction: L2/3 = 45%, L5a = 33%, L5b = 20%.",
    "text_access": "fulltext",
    "study_system": "Mouse S1; dual retrograde tracing (L1 + local L5); per-layer quantification of double-labelled neurons",
    "argument_role": "supporting",
    "replication_status": "single_study",
    "claim_source_sentence": "These analyses showed that 45% of all neurons in L2/3, 33% of all neurons in L5a, and 20% of all neurons in L5b were double labeled.",
    "source_provenance_status": "ok",
    "replication_evidence_dois": [],
    "effect_size_source_sentence": "These analyses showed that 45% of all neurons in L2/3, 33% of all neurons in L5a, and 20% of all neurons in L5b were double labeled."
  },
  "section_id": "section_04",
  "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_04_evidence_package.json",
  "effect_size": "Double-labelled fraction: L2/3 = 45%, L5a = 33%, L5b = 20%.",
  "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-189d92c83cf0"
  ],
  "source_span": "These analyses showed that 45% of all neurons in L2/3, 33% of all neurons in L5a, and 20% of all neurons in L5b were double labeled.",
  "study_system": "Mouse S1; dual retrograde tracing (L1 + local L5); per-layer quantification of double-labelled neurons",
  "evidence_refs": [
    {
      "ref": "paper:paper-189d92c83cf0"
    }
  ],
  "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": "Dual retrograde tracing from L1 and from local L5 pyramidal neurons in mouse S1; quantification of double-labelled cells per layer.",
  "review_bundle_ref": "analysis_bundle:ab-d9c479db9be9",
  "replication_status": "single_study",
  "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"
}