Version history

{
  "scope": "Mouse V1 in vivo extracellular recordings during visual sequence learning",
  "claim_text": "Expected stimuli are suppressed in late V1 responses (100-150 ms) after sequence learning, while novel and omitted stimuli elicit increased firing — consistent with predictive coding.",
  "raw_fields": {
    "n": null,
    "doi": "10.1093/cercor/bhad163",
    "claim": "Expected stimuli are suppressed in late V1 responses (100-150 ms) after sequence learning, while novel and omitted stimuli elicit increased firing — consistent with predictive coding.",
    "cite_key": "Price2023",
    "evidence": "Mouse V1 spiking under a sequence-learning paradigm analyzed with Model-Based Targeted Dimensionality Reduction (MbTDR); both stimulus substitution and omission drove elevated firing.",
    "effect_size": "Late-window suppression in 100-150 ms; omission-driven firing persisted ≥300 ms",
    "text_access": "abstract_only",
    "study_system": "Mouse V1 in vivo extracellular recordings during visual sequence learning",
    "argument_role": "supporting",
    "replication_status": "independently_replicated",
    "claim_source_sentence": "Neural responses to expected stimuli were suppressed in a late window (100-150 ms) after stimulus onset following training, whereas responses to novel stimuli were not.",
    "source_provenance_status": "non_substring_match",
    "replication_evidence_dois": [
      "10.1038/s41467-023-36608-8",
      "10.1093/cercor/bhad215"
    ],
    "effect_size_source_sentence": "Substituting a novel stimulus for a familiar one led to increases in firing that persisted for at least 300 ms."
  },
  "section_id": "section_14",
  "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_14_evidence_package.json",
  "effect_size": "Late-window suppression in 100-150 ms; omission-driven firing persisted ≥300 ms",
  "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-d6acd7459360"
  ],
  "source_span": "Neural responses to expected stimuli were suppressed in a late window (100-150 ms) after stimulus onset following training, whereas responses to novel stimuli were not.",
  "study_system": "Mouse V1 in vivo extracellular recordings during visual sequence learning",
  "evidence_refs": [
    {
      "ref": "paper:paper-d6acd7459360"
    }
  ],
  "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": "Mouse V1 spiking under a sequence-learning paradigm analyzed with Model-Based Targeted Dimensionality Reduction (MbTDR); both stimulus substitution and omission drove elevated firing.",
  "review_bundle_ref": "analysis_bundle:ab-d9c479db9be9",
  "replication_status": "independently_replicated",
  "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"
}