Version history

{
  "scope": "mouse barrel cortex (S1) L2/3, awake, all-optical two-photon, behavioral detection task",
  "claim_text": "In mouse barrel cortex L2/3, two-photon all-optical activation of ensembles as small as ~14 pyramidal neurons is sufficient for trained mice to detect cortical activation, placing a lower bound on perceptual cortical activity.",
  "raw_fields": {
    "n": 12,
    "doi": "10.7554/elife.58889",
    "claim": "In mouse barrel cortex L2/3, two-photon all-optical activation of ensembles as small as ~14 pyramidal neurons is sufficient for trained mice to detect cortical activation, placing a lower bound on perceptual cortical activity.",
    "cite_key": "Dalgleish2020",
    "evidence": "All-optical (two-photon C1V1 photostimulation + GCaMP6s imaging) targeting of L2/3 pyramidal subsets (200, 100 and smaller numbers) in awake mice trained to report cortical activation; performance measured against catch trials.",
    "effect_size": "~14 L2/3 pyramidal neurons sufficient for behavioral detection",
    "text_access": "fulltext",
    "study_system": "mouse barrel cortex (S1) L2/3, awake, all-optical two-photon, behavioral detection task",
    "argument_role": "supporting",
    "replication_status": "single_study",
    "claim_source_sentence": "By precisely titrating the number of neurons stimulated, we demonstrate that the lower bound for perception of cortical activity is ~14 pyramidal neurons.",
    "source_provenance_status": "ok",
    "replication_evidence_dois": [],
    "effect_size_source_sentence": "By precisely titrating the number of neurons stimulated, we demonstrate that the lower bound for perception of cortical activity is ~14 pyramidal neurons."
  },
  "section_id": "section_05",
  "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_05_evidence_package.json",
  "effect_size": "~14 L2/3 pyramidal neurons sufficient for behavioral detection",
  "review_repo": "ComputationalReviewRecurrence",
  "section_ref": "wiki_page:computationalreviewrecurrence-05-horizontal",
  "source_kind": "review_finding",
  "source_path": "evidence/section_05_evidence_package.json",
  "source_refs": [
    "paper:paper-d2118dd5013a"
  ],
  "source_span": "By precisely titrating the number of neurons stimulated, we demonstrate that the lower bound for perception of cortical activity is ~14 pyramidal neurons.",
  "study_system": "mouse barrel cortex (S1) L2/3, awake, all-optical two-photon, behavioral detection task",
  "evidence_refs": [
    {
      "ref": "paper:paper-d2118dd5013a"
    }
  ],
  "section_title": "5. Horizontal long-range intracortical excitatory connections in mouse — patchy L2/3-L5 axons, similarity tuning, distance-decay",
  "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": "All-optical (two-photon C1V1 photostimulation + GCaMP6s imaging) targeting of L2/3 pyramidal subsets (200, 100 and smaller numbers) in awake mice trained to report cortical activation; performance measured against catch trials.",
  "review_bundle_ref": "analysis_bundle:ab-d9c479db9be9",
  "replication_status": "single_study",
  "review_package_ref": "analysis_bundle:ab-d9c479db9be9",
  "source_artifact_ref": "wiki_page:computationalreviewrecurrence-05-horizontal",
  "origin_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_05_evidence_package.json",
  "commit_sha": "79ce062d54a924ce05953ec90aa9d26044d2b48f",
  "created_by": "persona-jerome-lecoq-gbo-neuroscience",
  "repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence"
}