Version history

1 version on record. Newest first; the live version sits at the top with a live indicator.

  1. Live d394ea35563d
    5/17/2026, 4:35:28 PM
    Content snapshot
    {
      "scope": "Cortical network model — theoretical analysis applicable to mouse cortex circuits",
      "claim_text": "Local imbalance between excitation and inhibition in recurrent cortical networks gives rise to a distinct amplification mechanism ('imbalanced amplification') that produces purely excitatory or purely inhibitory population responses to stimuli, complementing balanced amplification as a recurrent-network mechanism.",
      "raw_fields": {
        "n": 0,
        "doi": "10.1371/journal.pcbi.1006048",
        "claim": "Local imbalance between excitation and inhibition in recurrent cortical networks gives rise to a distinct amplification mechanism ('imbalanced amplification') that produces purely excitatory or purely inhibitory population responses to stimuli, complementing balanced amplification as a recurrent-network mechanism.",
        "cite_key": "Ebsch2018",
        "evidence": "Mean-field analysis of balanced spiking E-I networks with finite-size correction; demonstrates the mechanism in models of orientation tuning and surround suppression in cortex.",
        "effect_size": "qualitative — analytic finite-size correction to mean-field balance",
        "text_access": "fulltext",
        "study_system": "Cortical network model — theoretical analysis applicable to mouse cortex circuits",
        "argument_role": "supporting",
        "replication_status": "within_lab",
        "claim_source_sentence": "We show that cortical circuits with structure that is incompatible with balance are susceptible to an amplification mechanism arising when excitatory-inhibitory balance is broken at the level of local subpopulations, but maintained at a global level.",
        "source_provenance_status": "ok",
        "replication_evidence_dois": [],
        "effect_size_source_sentence": null
      },
      "section_id": "section_09",
      "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_09_evidence_package.json",
      "effect_size": "qualitative — analytic finite-size correction to mean-field balance",
      "review_repo": "ComputationalReviewRecurrence",
      "section_ref": "wiki_page:computationalreviewrecurrence-09-amplification-isn",
      "source_kind": "review_finding",
      "source_path": "evidence/section_09_evidence_package.json",
      "source_refs": [
        "paper:paper-b08395331756"
      ],
      "source_span": "We show that cortical circuits with structure that is incompatible with balance are susceptible to an amplification mechanism arising when excitatory-inhibitory balance is broken at the level of local subpopulations, but maintained at a global level.",
      "study_system": "Cortical network model — theoretical analysis applicable to mouse cortex circuits",
      "evidence_refs": [
        {
          "ref": "paper:paper-b08395331756"
        }
      ],
      "section_title": "9. Physiological signature I — recurrent amplification of weak inputs in mouse cortex; balanced-amplification regimes; ISN operation",
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        "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": "Mean-field analysis of balanced spiking E-I networks with finite-size correction; demonstrates the mechanism in models of orientation tuning and surround suppression in cortex.",
      "review_bundle_ref": "analysis_bundle:ab-d9c479db9be9",
      "replication_status": "within_lab",
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      "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"
    }