Details
- 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.
- 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_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
- 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
- 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
Raw fields (4)
- 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." }- source_refs
[ "paper:paper-b7b7c70baa83" ]
- evidence_refs
[ { "ref": "paper:paper-b7b7c70baa83" } ]- 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" }