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- Live5/17/2026, 4:35:28 PM
05d6ef018113Content 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" }