Details

scope
rat cortex
claim_text
Using AGm neural activity to calibrate M1 predicted forelimb movement can improve decoding performance significantly compared to neural decoders without calibration.
section_id
section_14
source_url
https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_14_evidence_package.json
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
We demonstrate that using AGm neural activity to calibrate M1 predicted forelimb movement can improve decoding performance significantly compared to neural decoders without calibration.
study_system
rat cortex
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
review_bundle_ref
analysis_bundle:ab-d9c479db9be9
replication_status
uncertain
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 (5)
raw_fields
{
  "n": 0,
  "doi": "10.1142/s012906572350051x",
  "claim": "Using AGm neural activity to calibrate M1 predicted forelimb movement can improve decoding performance significantly compared to neural decoders without calibration.",
  "cite_key": "Wang2023f",
  "evidence": "International journal of neural systems 2023; PMID 37632142. Enhancing Prediction of Forelimb Movement Trajectory through a Calibrating-Feedback Paradigm Incorporating RAT Primary Motor and Agranular Cortical Ensemble Activity in the Goal-Directed Reaching Task.",
  "effect_size": null,
  "text_access": "abstract_only",
  "study_system": "rat cortex",
  "argument_role": "supporting",
  "replication_status": "uncertain",
  "claim_source_sentence": "We demonstrate that using AGm neural activity to calibrate M1 predicted forelimb movement can improve decoding performance significantly compared to neural decoders without calibration.",
  "source_provenance_status": "non_substring_match",
  "replication_evidence_dois": [],
  "claim_rewritten_from_source": true,
  "effect_size_source_sentence": null
}
source_refs
[
  "paper:paper-fa560b942d67"
]
evidence_refs
[
  {
    "ref": "paper:paper-fa560b942d67"
  }
]
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
International journal of neural systems 2023; PMID 37632142. Enhancing Prediction of Forelimb Movement Trajectory through a Calibrating-Feedback Paradigm Incorporating RAT Primary Motor and Agranular Cortical Ensemble Activity in the Goal-Directed Reaching Task.

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