Version history

{
  "scope": "Mouse V1 single-unit recordings during locomotion + drifting gratings",
  "claim_text": "Apparent visuomotor 'mismatch' signals in mouse V1 can be reproduced by purely sensory perturbations and are explained by feature selectivity rather than by a dedicated prediction-error channel.",
  "raw_fields": {
    "n": 1019,
    "doi": "10.1016/j.celrep.2021.109772",
    "claim": "Apparent visuomotor 'mismatch' signals in mouse V1 can be reproduced by purely sensory perturbations and are explained by feature selectivity rather than by a dedicated prediction-error channel.",
    "cite_key": "Muzzu2021",
    "evidence": "Mouse V1 recordings during running with drifting gratings that unexpectedly stop; perturbation responses are orientation-tuned (largest at neurons' preferred orientation) and enhanced by running.",
    "effect_size": "345 of 1,019 units increased firing on perturbation; 270 of 1,019 reduced firing",
    "text_access": "fulltext",
    "study_system": "Mouse V1 single-unit recordings during locomotion + drifting gratings",
    "argument_role": "supporting",
    "replication_status": "contested",
    "claim_source_sentence": "We found that most neurons responded to the perturbation by increasing their firing rate (n = 345 of 1,019 versus 270 of 1,019 units that reduced responses; Figure 1 E).",
    "source_provenance_status": "ok",
    "replication_evidence_dois": [
      "10.1016/j.neuron.2017.08.036",
      "10.1038/s41586-024-07851-w"
    ],
    "effect_size_source_sentence": "We found that most neurons responded to the perturbation by increasing their firing rate (n = 345 of 1,019 versus 270 of 1,019 units that reduced responses; Figure 1 E)."
  },
  "section_id": "section_14",
  "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_14_evidence_package.json",
  "effect_size": "345 of 1,019 units increased firing on perturbation; 270 of 1,019 reduced firing",
  "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-dbc169750608"
  ],
  "source_span": "We found that most neurons responded to the perturbation by increasing their firing rate (n = 345 of 1,019 versus 270 of 1,019 units that reduced responses; Figure 1 E).",
  "study_system": "Mouse V1 single-unit recordings during locomotion + drifting gratings",
  "evidence_refs": [
    {
      "ref": "paper:paper-dbc169750608"
    }
  ],
  "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 recordings during running with drifting gratings that unexpectedly stop; perturbation responses are orientation-tuned (largest at neurons' preferred orientation) and enhanced by running.",
  "review_bundle_ref": "analysis_bundle:ab-d9c479db9be9",
  "replication_status": "contested",
  "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"
}