Details

scope
Theoretical model; biophysical simulations referenced to cat V1 data
section_id
section_09
source_url
https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_09_evidence_package.json
effect_size
qualitative — non-normal amplification arises in any balanced E/I recurrent network
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
Theoretical model; biophysical simulations referenced to cat V1 data
section_title
9. Physiological signature I — recurrent amplification of weak inputs in mouse cortex; balanced-amplification regimes; ISN operation
evidence_summary
Linear analysis of E/I recurrent network with Dale's law shows non-normal dynamics with hidden feedforward connectivity between activity patterns; biophysical model reproduces V1 ongoing activity statistics.
review_bundle_ref
analysis_bundle:ab-d9c479db9be9
replication_status
independently_replicated
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 (6)
claim_text
In recurrent cortical circuits with strong but balanced excitation and inhibition, 'balanced amplification' arises as a non-normal mechanism that selectively amplifies activity patterns without slowing dynamics — providing the theoretical framework for E→E recurrent gain in cortex.
raw_fields
{
  "n": 0,
  "doi": "10.1016/j.neuron.2009.02.005",
  "claim": "In recurrent cortical circuits with strong but balanced excitation and inhibition, 'balanced amplification' arises as a non-normal mechanism that selectively amplifies activity patterns without slowing dynamics — providing the theoretical framework for E→E recurrent gain in cortex.",
  "cite_key": "Murphy2009",
  "evidence": "Linear analysis of E/I recurrent network with Dale's law shows non-normal dynamics with hidden feedforward connectivity between activity patterns; biophysical model reproduces V1 ongoing activity statistics.",
  "effect_size": "qualitative — non-normal amplification arises in any balanced E/I recurrent network",
  "text_access": "fulltext",
  "study_system": "Theoretical model; biophysical simulations referenced to cat V1 data",
  "argument_role": "supporting",
  "replication_status": "independently_replicated",
  "claim_source_sentence": "When excitation and inhibition are both strong but balanced, as is thought to be the case in cerebral cortex, balanced amplification arises: small patterned fluctuations of the difference between excitation and inhibition drive large patterned fluctuations of the sum.",
  "source_provenance_status": "ok",
  "replication_evidence_dois": [
    "10.1103/PhysRevE.86.011909",
    "10.1016/j.neuron.2018.02.031",
    "10.1016/j.neuron.2023.11.005"
  ],
  "effect_size_source_sentence": null
}
source_refs
[
  "paper:paper-73146022940d"
]
source_span
When excitation and inhibition are both strong but balanced, as is thought to be the case in cerebral cortex, balanced amplification arises: small patterned fluctuations of the difference between excitation and inhibition drive large patterned fluctuations of the sum.
evidence_refs
[
  {
    "ref": "paper:paper-73146022940d"
  }
]
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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