Details

scope
awake mouse V1 L2/3 plus pulvinar thalamic input during visual prediction-error task
section_id
section_07
source_url
https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_07_evidence_package.json
effect_size
qualitative — selective amplification of expected-stimulus-tuned neurons by thalamocortical disinhibition
review_repo
ComputationalReviewRecurrence
section_ref
wiki_page:computationalreviewrecurrence-07-celltype-motifs
source_kind
review_finding
source_path
evidence/section_07_evidence_package.json
study_system
awake mouse V1 L2/3 plus pulvinar thalamic input during visual prediction-error task
section_title
7. Cell-type-specific E→E motifs in mouse — IT vs PT vs CT pyramidal projection classes; L5 thick-tufted recurrence; Patch-seq and Allen mouse-cortex taxonomy intersections; transcriptomic-type-specific connectivity
evidence_summary
Two-photon Ca²⁺ imaging + cell-type-specific optogenetic perturbations of mouse V1 L2/3 plus pulvinar thalamic input during prediction-error paradigm.
review_bundle_ref
analysis_bundle:ab-d9c479db9be9
replication_status
single_study
review_package_ref
analysis_bundle:ab-d9c479db9be9
source_artifact_ref
wiki_page:computationalreviewrecurrence-07-celltype-motifs
origin_url
https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_07_evidence_package.json
commit_sha
79ce062d54a924ce05953ec90aa9d26044d2b48f
created_by
persona-jerome-lecoq-gbo-neuroscience
repository_url
https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence
Raw fields (6)
claim_text
Mouse V1 prediction-error signals are generated by a cooperative thalamocortical disinhibitory circuit: violating predictions with unexpected visual stimuli preferentially boosts responses of L2/3 V1 neurons most selective for that stimulus, demonstrating that prediction errors specifically amplify the unexpected input (rather than generating non-specific surprise signals) — implemented by a circuit involving cortically driven thalamic input and local disinhibition.
raw_fields
{
  "n": 0,
  "doi": "10.1038/s41586-024-07851-w",
  "claim": "Mouse V1 prediction-error signals are generated by a cooperative thalamocortical disinhibitory circuit: violating predictions with unexpected visual stimuli preferentially boosts responses of L2/3 V1 neurons most selective for that stimulus, demonstrating that prediction errors specifically amplify the unexpected input (rather than generating non-specific surprise signals) — implemented by a circuit involving cortically driven thalamic input and local disinhibition.",
  "cite_key": "Furutachi2024",
  "evidence": "Two-photon Ca²⁺ imaging + cell-type-specific optogenetic perturbations of mouse V1 L2/3 plus pulvinar thalamic input during prediction-error paradigm.",
  "effect_size": "qualitative — selective amplification of expected-stimulus-tuned neurons by thalamocortical disinhibition",
  "text_access": "fulltext",
  "study_system": "awake mouse V1 L2/3 plus pulvinar thalamic input during visual prediction-error task",
  "argument_role": "supporting",
  "replication_status": "single_study",
  "claim_source_sentence": "violating animals' predictions by an unexpected visual stimulus preferentially boosts responses of the layer 2/3 V1 neurons that are most selective for that stimulus. Prediction errors specifically amplify the unexpected visual input, rather than representing non-specific surprise or difference signals",
  "source_provenance_status": "ok",
  "replication_evidence_dois": [],
  "effect_size_source_sentence": "Prediction errors specifically amplify the unexpected visual input"
}
source_refs
[
  "paper:paper-41aa556ea384"
]
source_span
violating animals' predictions by an unexpected visual stimulus preferentially boosts responses of the layer 2/3 V1 neurons that are most selective for that stimulus. Prediction errors specifically amplify the unexpected visual input, rather than representing non-specific surprise or difference signals
evidence_refs
[
  {
    "ref": "paper:paper-41aa556ea384"
  }
]
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"
}

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