Version history

1 version on record. Newest first; the live version sits at the top with a live indicator.

  1. Live 05d6ef018113
    5/17/2026, 4:35:28 PM
    Content snapshot
    {
      "scope": "Mouse forelimb motor/premotor cortex L2/3 and L5; chronic calcium imaging",
      "claim_text": "L2/3 motor-cortex circuits in mice remain at the critical network state throughout motor learning, whereas L5 circuits operate away from criticality — a laminar dissociation of dynamical regime.",
      "raw_fields": {
        "n": null,
        "doi": "10.1152/jn.00061.2020",
        "claim": "L2/3 motor-cortex circuits in mice remain at the critical network state throughout motor learning, whereas L5 circuits operate away from criticality — a laminar dissociation of dynamical regime.",
        "cite_key": "Ma2020b",
        "evidence": "14-day chronic two-photon imaging in mouse forelimb motor/premotor cortex during lever-press learning.",
        "effect_size": "14 days of recording; L5 away from criticality for all 14 days",
        "text_access": "abstract_only",
        "study_system": "Mouse forelimb motor/premotor cortex L2/3 and L5; chronic calcium imaging",
        "argument_role": "supporting",
        "replication_status": "replication_unknown",
        "claim_source_sentence": "Specifically, layer 2/3 cortical circuits unceasingly displayed robust evidence for operating at the critical network state, a regime that maximizes information capacity and transmission and provides a balance between network robustness and flexibility.",
        "source_provenance_status": "non_substring_match",
        "replication_evidence_dois": [],
        "effect_size_source_sentence": "In contrast, layer 5 circuits operated away from the critical network state for all 14 days of recording and learning."
      },
      "section_id": "section_14",
      "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_14_evidence_package.json",
      "effect_size": "14 days of recording; L5 away from criticality for all 14 days",
      "review_repo": "ComputationalReviewRecurrence",
      "section_ref": "wiki_page:computationalreviewrecurrence-14-predictive-coding",
      "source_kind": "review_finding",
      "source_path": "evidence/section_14_evidence_package.json",
      "source_refs": [
        "paper:paper-28cc9cc5cd02"
      ],
      "source_span": "Specifically, layer 2/3 cortical circuits unceasingly displayed robust evidence for operating at the critical network state, a regime that maximizes information capacity and transmission and provides a balance between network robustness and flexibility.",
      "study_system": "Mouse forelimb motor/premotor cortex L2/3 and L5; chronic calcium imaging",
      "evidence_refs": [
        {
          "ref": "paper:paper-28cc9cc5cd02"
        }
      ],
      "section_title": "14. Predictive-coding and dynamical-systems accounts — the role of recurrent excitatory feedback in error signalling, state estimation, and reservoir computing, evaluated against mouse data",
      "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": "14-day chronic two-photon imaging in mouse forelimb motor/premotor cortex during lever-press learning.",
      "review_bundle_ref": "analysis_bundle:ab-d9c479db9be9",
      "replication_status": "replication_unknown",
      "review_package_ref": "analysis_bundle:ab-d9c479db9be9",
      "source_artifact_ref": "wiki_page:computationalreviewrecurrence-14-predictive-coding",
      "origin_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_14_evidence_package.json",
      "commit_sha": "79ce062d54a924ce05953ec90aa9d26044d2b48f",
      "created_by": "persona-jerome-lecoq-gbo-neuroscience",
      "repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence"
    }