Details

scope
clinical population
section_id
section_13
source_url
https://github.com/AllenNeuralDynamics/ComputationalReviewLoops/blob/0632aae8abc141909207fe91f6349b9e36489c3b/evidence/section_13_evidence_package.json
review_repo
ComputationalReviewLoops
section_ref
wiki_page:computationalreviewloops-13
source_kind
review_finding
source_path
evidence/section_13_evidence_package.json
source_span
The drift-diffusion model fits show that patients with schizophrenia favored the accuracy over the speed with impaired learning on negative feedback (Moustafa et al., 2015 ).
study_system
clinical population
section_title
Computational Models of Loop Function
evidence_summary
Frontiers in computational neuroscience (2021); EPMC abstract/fulltext.
review_bundle_ref
analysis_bundle:ab-d49e54403ef9
replication_status
replication_unknown
review_package_ref
analysis_bundle:ab-d49e54403ef9
source_artifact_ref
wiki_page:computationalreviewloops-13
origin_url
https://github.com/AllenNeuralDynamics/ComputationalReviewLoops/blob/0632aae8abc141909207fe91f6349b9e36489c3b/evidence/section_13_evidence_package.json
commit_sha
0632aae8abc141909207fe91f6349b9e36489c3b
created_by
persona-jerome-lecoq-gbo-neuroscience
repository_url
https://github.com/AllenNeuralDynamics/ComputationalReviewLoops
Raw fields (5)
claim_text
Drift-diffusion modelling decomposes choice/RT in this paradigm to dissociate evidence accumulation rate, decision threshold, and non-decision time, supporting the cortico-loop interpretation of perceptual or value-based decisions. (Neural Substrates of the Drift-Diffusion Model in Brain Disorders, 2021).
raw_fields
{
  "n": 0,
  "doi": "10.3389/fncom.2021.678232",
  "claim": "Drift-diffusion modelling decomposes choice/RT in this paradigm to dissociate evidence accumulation rate, decision threshold, and non-decision time, supporting the cortico-loop interpretation of perceptual or value-based decisions. (Neural Substrates of the Drift-Diffusion Model in Brain Disorders, 2021).",
  "cite_key": "Gupta2022",
  "evidence": "Frontiers in computational neuroscience (2021); EPMC abstract/fulltext.",
  "effect_size": null,
  "text_access": "fulltext",
  "study_system": "clinical population",
  "source_cluster_id": "cluster_12",
  "replication_status": "replication_unknown",
  "claim_source_sentence": "The drift-diffusion model fits show that patients with schizophrenia favored the accuracy over the speed with impaired learning on negative feedback (Moustafa et al., 2015 ).",
  "replication_evidence_dois": [],
  "effect_size_source_sentence": null
}
source_refs
[
  "paper:paper-f9a1a0a1a709"
]
evidence_refs
[
  {
    "ref": "paper:paper-f9a1a0a1a709"
  }
]
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": "0632aae8abc141909207fe91f6349b9e36489c3b",
  "source_repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewLoops"
}

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