Version history

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  1. Live f554b31d9a56
    5/17/2026, 4:35:28 PM
    Content snapshot
    {
      "scope": "mouse LP and dLGN axonal projections to V1 (two-photon imaging)",
      "claim_text": "The mouse pulvinar homologue (LP) provides V1 with diverse contextual signals (visual, motor, visuomotor mismatch), whereas dLGN delivers retinotopically precise sensory signals.",
      "raw_fields": {
        "n": 1825,
        "doi": "10.1038/nn.4197",
        "claim": "The mouse pulvinar homologue (LP) provides V1 with diverse contextual signals (visual, motor, visuomotor mismatch), whereas dLGN delivers retinotopically precise sensory signals.",
        "cite_key": "Roth2015",
        "evidence": "In vivo two-photon calcium imaging of LP and dLGN axonal boutons in mouse V1 during locomotion and visual flow manipulation.",
        "effect_size": "dLGN n=2317 RFs (7 mice); LP n=1825 RFs (13 mice); V1 n=356 RFs (4 mice). LP visuomotor mismatch activity 30±7%, dLGN 6±8%.",
        "text_access": "fulltext",
        "study_system": "mouse LP and dLGN axonal projections to V1 (two-photon imaging)",
        "source_cluster_id": "cluster_05",
        "replication_status": "independently_replicated",
        "claim_source_sentence": "We found that dLGN conveys retinotopically precise visual signals, while LP provides distributed information from the visual scene.",
        "replication_evidence_dois": [
          "10.1038/nn.4197",
          "10.1126/science.1223082"
        ],
        "effect_size_source_sentence": "Interestingly, LP boutons on the whole were more active in response to an onset of visuomotor divergence than during a period of varying but sustained visuomotor discrepancies (mean difference in activity, LP: 30 ± 7%; P = 10 −4 , Wilcoxon signed-rank test)."
      },
      "section_id": "section_06",
      "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewLoops/blob/0632aae8abc141909207fe91f6349b9e36489c3b/evidence/section_06_evidence_package.json",
      "effect_size": "dLGN n=2317 RFs (7 mice); LP n=1825 RFs (13 mice); V1 n=356 RFs (4 mice). LP visuomotor mismatch activity 30±7%, dLGN 6±8%.",
      "review_repo": "ComputationalReviewLoops",
      "section_ref": "wiki_page:computationalreviewloops-06",
      "source_kind": "review_finding",
      "source_path": "evidence/section_06_evidence_package.json",
      "source_refs": [
        "paper:paper-b92f6eb9a796"
      ],
      "source_span": "We found that dLGN conveys retinotopically precise visual signals, while LP provides distributed information from the visual scene.",
      "study_system": "mouse LP and dLGN axonal projections to V1 (two-photon imaging)",
      "evidence_refs": [
        {
          "ref": "paper:paper-b92f6eb9a796"
        }
      ],
      "section_title": "Thalamic Feedback: Closing the Loop",
      "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": "0632aae8abc141909207fe91f6349b9e36489c3b",
        "source_repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewLoops"
      },
      "evidence_summary": "In vivo two-photon calcium imaging of LP and dLGN axonal boutons in mouse V1 during locomotion and visual flow manipulation.",
      "review_bundle_ref": "analysis_bundle:ab-d49e54403ef9",
      "replication_status": "independently_replicated",
      "review_package_ref": "analysis_bundle:ab-d49e54403ef9",
      "source_artifact_ref": "wiki_page:computationalreviewloops-06",
      "origin_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewLoops/blob/0632aae8abc141909207fe91f6349b9e36489c3b/evidence/section_06_evidence_package.json",
      "commit_sha": "0632aae8abc141909207fe91f6349b9e36489c3b",
      "created_by": "persona-jerome-lecoq-gbo-neuroscience",
      "repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewLoops"
    }