Version history

{
  "scope": "Motor cortex population recordings + hybrid neural network simulation",
  "claim_text": "Continuous external input — not purely autonomous recurrent dynamics — drives motor-cortex state transitions during reaching, challenging strict autonomous-dynamical-systems models.",
  "raw_fields": {
    "n": null,
    "doi": "10.21203/rs.3.rs-8585660/v1",
    "claim": "Continuous external input — not purely autonomous recurrent dynamics — drives motor-cortex state transitions during reaching, challenging strict autonomous-dynamical-systems models.",
    "cite_key": "Schwartz2026",
    "evidence": "Hybrid neural networks with empirical firing rates + artificial connectivity reproduce population state transitions only when given continuous extrinsic input.",
    "effect_size": "Episodic external drive produced consistent pre-threshold input integration statistics that explained state transitions",
    "text_access": "abstract_only",
    "study_system": "Motor cortex population recordings + hybrid neural network simulation",
    "argument_role": "supporting",
    "replication_status": "replication_unknown",
    "claim_source_sentence": "Instead of the reported primacy of intrinsic action, we found that input from extrinsic sources was responsible for these results.",
    "source_provenance_status": "non_substring_match",
    "replication_evidence_dois": [],
    "effect_size_source_sentence": "Episodic external drive produced consistent changes in the statistics of pre-threshold input integration to cause the state transitions."
  },
  "section_id": "section_14",
  "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_14_evidence_package.json",
  "effect_size": "Episodic external drive produced consistent pre-threshold input integration statistics that explained state transitions",
  "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-b7b7c70baa83"
  ],
  "source_span": "Instead of the reported primacy of intrinsic action, we found that input from extrinsic sources was responsible for these results.",
  "study_system": "Motor cortex population recordings + hybrid neural network simulation",
  "evidence_refs": [
    {
      "ref": "paper:paper-b7b7c70baa83"
    }
  ],
  "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": "Hybrid neural networks with empirical firing rates + artificial connectivity reproduce population state transitions only when given continuous extrinsic input.",
  "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"
}