Details

scope
Mouse V1 (visual cortex)
claim_text
Stabilized Supralinear Network Model of Responses to Surround Stimuli in Primary Visual Cortex
section_id
section_06
source_url
https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_06_evidence_package.json
effect_size
review_repo
ComputationalReviewRecurrence
section_ref
wiki_page:computationalreviewrecurrence-06-connectomic-micons
source_kind
review_finding
source_path
evidence/section_06_evidence_package.json
study_system
Mouse V1 (visual cortex)
section_title
6. Connectomic resolution — MICrONS mouse V1/HVA millimetre-scale EM volume; pyramidal-pyramidal wiring statistics derived from it; reconciliation with paired-recording estimates
evidence_summary
Abstract of eNeuro 2025 paper (PMID 40228865).
review_bundle_ref
analysis_bundle:ab-d9c479db9be9
replication_status
replication_unknown
review_package_ref
analysis_bundle:ab-d9c479db9be9
source_artifact_ref
wiki_page:computationalreviewrecurrence-06-connectomic-micons
origin_url
https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_06_evidence_package.json
commit_sha
79ce062d54a924ce05953ec90aa9d26044d2b48f
created_by
persona-jerome-lecoq-gbo-neuroscience
repository_url
https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence
Raw fields (5)
raw_fields
{
  "n": "n_unknown",
  "doi": "10.1523/eneuro.0459-24.2025",
  "claim": "Stabilized Supralinear Network Model of Responses to Surround Stimuli in Primary Visual Cortex",
  "cite_key": "Obeid2025",
  "evidence": "Abstract of eNeuro 2025 paper (PMID 40228865).",
  "effect_size": "",
  "text_access": "abstract_only",
  "study_system": "Mouse V1 (visual cortex)",
  "argument_role": "supporting",
  "replication_status": "replication_unknown",
  "claim_source_sentence": "We show that a stabilized supralinear network (SSN) with biologically plausible connectivity and synaptic efficacies that depend on cortical distance and orientation difference between units can consistently reproduce phenomena (1) and (3), and, qualitatively, phenomenon (2).",
  "source_provenance_status": "non_substring_match",
  "replication_evidence_dois": [],
  "effect_size_source_sentence": ""
}
source_refs
[
  "paper:paper-87e1cd00ec60"
]
source_span
We show that a stabilized supralinear network (SSN) with biologically plausible connectivity and synaptic efficacies that depend on cortical distance and orientation difference between units can consistently reproduce phenomena (1) and (3), and, qualitatively, phenomenon (2).
evidence_refs
[
  {
    "ref": "paper:paper-87e1cd00ec60"
  }
]
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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