Version history

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

  1. Live 36ef2b132daa
    5/17/2026, 4:35:28 PM
    Content snapshot
    {
      "scope": "human and mouse neocortical fast-spiking basket cells, computational model",
      "claim_text": "Human fast-spiking basket cells express abundant HCN1/HCN2 channels at the soma, accelerating membrane kinetics and EPSP-to-spike coupling compared to sparse HCN expression in rodent FS cells",
      "raw_fields": {
        "n": 0,
        "doi": "10.1371/journal.pbio.3002001",
        "claim": "Human fast-spiking basket cells express abundant HCN1/HCN2 channels at the soma, accelerating membrane kinetics and EPSP-to-spike coupling compared to sparse HCN expression in rodent FS cells",
        "evidence": "Electrophysiology, pharmacology, immunohistochemistry, and computational modeling comparing human and mouse FS basket cells",
        "effect_size": "HCN channels speed up human FS cell membrane kinetics to attain input-output rate close to rodent cells",
        "text_access": "fulltext",
        "study_system": "human and mouse neocortical fast-spiking basket cells, computational model",
        "replication_status": "replication_unknown",
        "claim_source_sentence": "Computational modeling demonstrated that HCN channel activity at the human fast-spiking cell soma membrane is sufficient to accelerate the input–output function as observed in cell recordings.",
        "replication_evidence_dois": [],
        "effect_size_source_sentence": "HCN channels speed up human cell membrane potential kinetics and help attain an input–output rate close to that of rodent cells."
      },
      "section_id": "section_12_evidence_package",
      "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewPV/blob/df9fc7e8d455b084152c9d713558dae0013cef21/evidence/section_12_evidence_package.json",
      "effect_size": "HCN channels speed up human FS cell membrane kinetics to attain input-output rate close to rodent cells",
      "review_repo": "ComputationalReviewPV",
      "section_ref": "wiki_page:computationalreviewpv-12",
      "source_kind": "review_finding",
      "source_path": "evidence/section_12_evidence_package.json",
      "source_refs": [
        "paper:paper-8fdecf25a0b5"
      ],
      "source_span": "Computational modeling demonstrated that HCN channel activity at the human fast-spiking cell soma membrane is sufficient to accelerate the input–output function as observed in cell recordings.",
      "study_system": "human and mouse neocortical fast-spiking basket cells, computational model",
      "evidence_refs": [
        {
          "ref": "paper:paper-8fdecf25a0b5"
        }
      ],
      "section_title": "Computational Models of PV Circuit Function",
      "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": "df9fc7e8d455b084152c9d713558dae0013cef21",
        "source_repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewPV"
      },
      "evidence_summary": "Electrophysiology, pharmacology, immunohistochemistry, and computational modeling comparing human and mouse FS basket cells",
      "review_bundle_ref": "analysis_bundle:ab-e6261c8263e7",
      "replication_status": "replication_unknown",
      "review_package_ref": "analysis_bundle:ab-e6261c8263e7",
      "source_artifact_ref": "wiki_page:computationalreviewpv-12",
      "origin_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewPV/blob/df9fc7e8d455b084152c9d713558dae0013cef21/evidence/section_12_evidence_package.json",
      "commit_sha": "df9fc7e8d455b084152c9d713558dae0013cef21",
      "created_by": "persona-jerome-lecoq-gbo-neuroscience",
      "repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewPV"
    }