Details

scope
mouse; V1, visual cortex; computational model; Nature
claim_text
In response to prediction errors, VIP neurons inhibit a specific subpopulation of somatostatin-expressing inhibitory interneurons that gate excitatory pulvinar input to V1, resulting in specific pulv…
section_id
section_09
source_url
https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_09_evidence_package.json
review_repo
ComputationalReviewRecurrence
section_ref
wiki_page:computationalreviewrecurrence-09-amplification-isn
source_kind
review_finding
source_path
evidence/section_09_evidence_package.json
study_system
mouse; V1, visual cortex; computational model; Nature
section_title
9. Physiological signature I — recurrent amplification of weak inputs in mouse cortex; balanced-amplification regimes; ISN operation
review_bundle_ref
analysis_bundle:ab-d9c479db9be9
replication_status
single_study
review_package_ref
analysis_bundle:ab-d9c479db9be9
source_artifact_ref
wiki_page:computationalreviewrecurrence-09-amplification-isn
origin_url
https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_09_evidence_package.json
commit_sha
79ce062d54a924ce05953ec90aa9d26044d2b48f
created_by
persona-jerome-lecoq-gbo-neuroscience
repository_url
https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence
Raw fields (7)
raw_fields
{
  "n": null,
  "doi": "10.1038/s41586-024-07851-w",
  "claim": "In response to prediction errors, VIP neurons inhibit a specific subpopulation of somatostatin-expressing inhibitory interneurons that gate excitatory pulvinar input to V1, resulting in specific pulv…",
  "cite_key": "Furutachi2024",
  "evidence": "The brain functions as a prediction machine, utilizing an internal model of the world to anticipate sensations and the outcomes of our actions. Discrepancies between expected and actual events, referred to as prediction errors, are leveraged to update the internal model and guide our attention towards unexpected events. Despite the importance of prediction-error signals for various neural computations across the brain, surprisingly little is known about the neural circuit mechanisms responsible ...",
  "effect_size": "We recorded neural activity of layer 2/3 neurons in V1 using two-photon calcium imaging(Fig.and), and observed a stronger response to a visual stimulus that was novel and therefore unexpected (stimulus C in block 1) compared with the same stimulus when it was expected (stimulus C in second half of block 2,< 1 × 10, hierarchical bootstrapping test; Fig.and Extended Data Fig.), consistent with previous studies in humans, non-human primates and rodents.",
  "text_access": "fulltext",
  "study_system": "mouse; V1, visual cortex; computational model; Nature",
  "argument_role": "supporting",
  "replication_status": "single_study",
  "claim_source_sentence": "In response to prediction errors, VIP neurons inhibit a specific subpopulation of somatostatin-expressing inhibitory interneurons that gate excitatory pulvinar input to V1, resulting in specific pulvinar-driven response amplification of the most stimulus-selective neurons in V1.",
  "source_provenance_status": "ok",
  "replication_evidence_dois": [],
  "claim_rewritten_from_source": true,
  "effect_size_source_sentence": "We recorded neural activity of layer 2/3 neurons in V1 using two-photon calcium imaging(Fig.and), and observed a stronger response to a visual stimulus that was novel and therefore unexpected (stimulus C in block 1) compared with the same stimulus when it was expected (stimulus C in second half of block 2,< 1 × 10, hierarchical bootstrapping test; Fig.and Extended Data Fig.), consistent with previous studies in humans, non-human primates and rodents."
}
effect_size
We recorded neural activity of layer 2/3 neurons in V1 using two-photon calcium imaging(Fig.and), and observed a stronger response to a visual stimulus that was novel and therefore unexpected (stimulus C in block 1) compared with the same stimulus when it was expected (stimulus C in second half of block 2,< 1 × 10, hierarchical bootstrapping test; Fig.and Extended Data Fig.), consistent with previous studies in humans, non-human primates and rodents.
source_refs
[
  "paper:paper-41aa556ea384"
]
source_span
In response to prediction errors, VIP neurons inhibit a specific subpopulation of somatostatin-expressing inhibitory interneurons that gate excitatory pulvinar input to V1, resulting in specific pulvinar-driven response amplification of the most stimulus-selective neurons in V1.
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"
}
evidence_summary
The brain functions as a prediction machine, utilizing an internal model of the world to anticipate sensations and the outcomes of our actions. Discrepancies between expected and actual events, referred to as prediction errors, are leveraged to update the internal model and guide our attention towards unexpected events. Despite the importance of prediction-error signals for various neural computations across the brain, surprisingly little is known about the neural circuit mechanisms responsible ...

Voting as anonymous. Sign in to attribute your signals.

tokens

Replication

No replications yet

Discussion

Posting anonymously. Sign in for attribution.

No comments yet — be the first.