During cortical Up states in mouse, PV interneurons (not SST) are the dominant…

Details

scope: Mouse cortex (Pyr, PV-Cre, SST-Cre), ex vivo whole-cell patch clamp + computational model of Up states
claim_text: During cortical Up states in mouse, PV interneurons (not SST) are the dominant inhibition stabilizer of recurrent E→E activity, and the Pyr↔PV recurrent inhibitory loop is stronger than the Pyr↔SST loop.
section_id: section_09
source_url: https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_09_evidence_package.json
effect_size: qualitative — paradoxical effect is present in most regimes of two-inhibitory-class model with empirically derived F-I curves; Pyr↔PV loop stronger than Pyr↔SST
review_repo: ComputationalReviewRecurrence
section_ref: wiki_page:computationalreviewrecurrence-09-amplification-isn
source_kind: review_finding
source_path: evidence/section_09_evidence_package.json
source_span: Simulations revealed that the intrinsic properties were sufficient to predict that PV neurons are primarily responsible for generating the nontrivial fixed points representing Up states.
study_system: Mouse cortex (Pyr, PV-Cre, SST-Cre), ex vivo whole-cell patch clamp + computational model of Up states
section_title: 9. Physiological signature I — recurrent amplification of weak inputs in mouse cortex; balanced-amplification regimes; ISN operation
evidence_summary: Combined patch-clamp F-I characterization of Pyr, PV, SST neurons in mouse cortex; three-population computational model parametrized from data; experimental validation of inhibitory loop strengths.
review_bundle_ref: analysis_bundle:ab-d9c479db9be9
replication_status: within_lab
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 (4)

raw_fields

{
  "n": 0,
  "doi": "10.1523/jneurosci.2830-20.2021",
  "claim": "During cortical Up states in mouse, PV interneurons (not SST) are the dominant inhibition stabilizer of recurrent E→E activity, and the Pyr↔PV recurrent inhibitory loop is stronger than the Pyr↔SST loop.",
  "cite_key": "RomeroSosa2021",
  "evidence": "Combined patch-clamp F-I characterization of Pyr, PV, SST neurons in mouse cortex; three-population computational model parametrized from data; experimental validation of inhibitory loop strengths.",
  "effect_size": "qualitative — paradoxical effect is present in most regimes of two-inhibitory-class model with empirically derived F-I curves; Pyr↔PV loop stronger than Pyr↔SST",
  "text_access": "abstract_only",
  "study_system": "Mouse cortex (Pyr, PV-Cre, SST-Cre), ex vivo whole-cell patch clamp + computational model of Up states",
  "argument_role": "supporting",
  "replication_status": "within_lab",
  "claim_source_sentence": "Simulations revealed that the intrinsic properties were sufficient to predict that PV neurons are primarily responsible for generating the nontrivial fixed points representing Up states.",
  "source_provenance_status": "non_substring_match",
  "replication_evidence_dois": [],
  "effect_size_source_sentence": "Simulations and analytical methods demonstrated that while the paradoxical effect is not obligatory in a model with two classes of inhibitory neurons, it is present in most regimes."
}

source_refs

[
  "paper:paper-cf99b8f6c806"
]

evidence_refs

[
  {
    "ref": "paper:paper-cf99b8f6c806"
  }
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source_policy

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  "notes": [
    "Local review repositories are read-only inputs.",
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  "source_repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence"
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During cortical Up states in mouse, PV interneurons (not SST) are the dominant…

Details

Replication

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