Version history

{
  "scope": "mouse; V1; computational model, spiking network model; Frontiers in computational neuroscience",
  "claim_text": "Neural rhythms are not necessarily intrinsic properties of cortical circuits, but rather they may arise from structural changes elicited by learning-related mechanisms.",
  "raw_fields": {
    "n": null,
    "doi": "10.3389/fncom.2025.1568143",
    "claim": "Neural rhythms are not necessarily intrinsic properties of cortical circuits, but rather they may arise from structural changes elicited by learning-related mechanisms.",
    "cite_key": "Moreni2025b",
    "evidence": "Neural rhythms are ubiquitous in cortical recordings, but it is unclear whether they emerge due to the basic structure of cortical microcircuits or depend on function. Using detailed electrophysiological and anatomical data of mouse V1, we explored this question by building a spiking network model of a cortical column incorporating pyramidal cells, PV, SST, and VIP inhibitory interneurons, and dynamics for AMPA, GABA, and NMDA receptors. The resulting model matchedcell-type-specific firing rates...",
    "effect_size": "Percentage (%)\n\nPV\n\nSST\n\nVIP\n\nL2/3\n\n0.295918\n\n0.214286\n\n0.489796\n\nL4\n\n0.552381\n\n0.295238\n\n0.152381\n\nL5\n\n0.485714\n\n0.428571\n\n0.085714\n\nL6\n\n0.458333\n\n0.458333\n\n0.083333\n\nIn each layer, the inhibitory cells represent 15% of the total number of neurons for that layer.",
    "text_access": "fulltext",
    "study_system": "mouse; V1; computational model, spiking network model; Frontiers in computational neuroscience",
    "argument_role": "supporting",
    "replication_status": "single_study",
    "claim_source_sentence": "Our results suggest that neural rhythms are not necessarily intrinsic properties of cortical circuits, but rather they may arise from structural changes elicited by learning-related mechanisms.",
    "source_provenance_status": "ok",
    "replication_evidence_dois": [],
    "claim_rewritten_from_source": true,
    "effect_size_source_sentence": "Percentage (%)\n\nPV\n\nSST\n\nVIP\n\nL2/3\n\n0.295918\n\n0.214286\n\n0.489796\n\nL4\n\n0.552381\n\n0.295238\n\n0.152381\n\nL5\n\n0.485714\n\n0.428571\n\n0.085714\n\nL6\n\n0.458333\n\n0.458333\n\n0.083333\n\nIn each layer, the inhibitory cells represent 15% of the total number of neurons for that layer."
  },
  "section_id": "section_09",
  "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_09_evidence_package.json",
  "effect_size": "Percentage (%)\n\nPV\n\nSST\n\nVIP\n\nL2/3\n\n0.295918\n\n0.214286\n\n0.489796\n\nL4\n\n0.552381\n\n0.295238\n\n0.152381\n\nL5\n\n0.485714\n\n0.428571\n\n0.085714\n\nL6\n\n0.458333\n\n0.458333\n\n0.083333\n\nIn each layer, the inhibitory cells represent 15% of the total number of neurons for that layer.",
  "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-b58ecaabd35b"
  ],
  "source_span": "Our results suggest that neural rhythms are not necessarily intrinsic properties of cortical circuits, but rather they may arise from structural changes elicited by learning-related mechanisms.",
  "study_system": "mouse; V1; computational model, spiking network model; Frontiers in computational neuroscience",
  "evidence_refs": [
    {
      "ref": "paper:paper-b58ecaabd35b"
    }
  ],
  "section_title": "9. Physiological signature I — recurrent amplification of weak inputs in mouse cortex; balanced-amplification regimes; ISN operation",
  "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": "Neural rhythms are ubiquitous in cortical recordings, but it is unclear whether they emerge due to the basic structure of cortical microcircuits or depend on function. Using detailed electrophysiological and anatomical data of mouse V1, we explored this question by building a spiking network model of a cortical column incorporating pyramidal cells, PV, SST, and VIP inhibitory interneurons, and dynamics for AMPA, GABA, and NMDA receptors. The resulting model matchedcell-type-specific firing rates...",
  "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"
}