Version history

{
  "scope": "mouse V1, AL, RL excitatory neurons; EM dendritic reconstruction (MICrONS)",
  "claim_text": "Graph-based machine-learning analysis of >30,000 excitatory neurons reconstructed from the MICrONS millimeter-scale electron-microscopy volume defines a low-dimensional morphological bar-code that recovers continuous and discrete dendritic-morphology classes across mouse V1, AL and RL excitatory populations, supporting projection-class-linked recurrent architectures.",
  "raw_fields": {
    "n": 30000,
    "doi": "10.1038/s41467-025-58763-w",
    "claim": "Graph-based machine-learning analysis of >30,000 excitatory neurons reconstructed from the MICrONS millimeter-scale electron-microscopy volume defines a low-dimensional morphological bar-code that recovers continuous and discrete dendritic-morphology classes across mouse V1, AL and RL excitatory populations, supporting projection-class-linked recurrent architectures.",
    "cite_key": "Weis2025",
    "evidence": "Graph-neural-network embedding of >30,000 excitatory pyramidal dendritic skeletons reconstructed from the MICrONS V1-HVA EM volume; unsupervised clustering and morphological feature analysis to recover excitatory subtype organization.",
    "effect_size": ">30,000 dendritic reconstructions support a continuous-plus-discrete morphological taxonomy",
    "text_access": "fulltext",
    "study_system": "mouse V1, AL, RL excitatory neurons; EM dendritic reconstruction (MICrONS)",
    "argument_role": "supporting",
    "replication_status": "single_study",
    "claim_source_sentence": "Here, we took a data-driven approach using graph-based machine learning methods to obtain a low-dimensional morphological “bar code” describing more than 30,000 excitatory neurons in mouse visual areas V1, AL, and RL that were reconstructed from the millimeter scale MICrONS volume.",
    "source_provenance_status": "ok",
    "replication_evidence_dois": [],
    "effect_size_source_sentence": "Here, we took a data-driven approach using graph-based machine learning methods to obtain a low-dimensional morphological “bar code” describing more than 30,000 excitatory neurons in mouse visual areas V1, AL, and RL that were reconstructed from the millimeter scale MICrONS volume."
  },
  "section_id": "section_05",
  "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_05_evidence_package.json",
  "effect_size": ">30,000 dendritic reconstructions support a continuous-plus-discrete morphological taxonomy",
  "review_repo": "ComputationalReviewRecurrence",
  "section_ref": "wiki_page:computationalreviewrecurrence-05-horizontal",
  "source_kind": "review_finding",
  "source_path": "evidence/section_05_evidence_package.json",
  "source_refs": [
    "paper:paper-4be2ac5ab52e"
  ],
  "source_span": "Here, we took a data-driven approach using graph-based machine learning methods to obtain a low-dimensional morphological “bar code” describing more than 30,000 excitatory neurons in mouse visual areas V1, AL, and RL that were reconstructed from the millimeter scale MICrONS volume.",
  "study_system": "mouse V1, AL, RL excitatory neurons; EM dendritic reconstruction (MICrONS)",
  "evidence_refs": [
    {
      "ref": "paper:paper-4be2ac5ab52e"
    }
  ],
  "section_title": "5. Horizontal long-range intracortical excitatory connections in mouse — patchy L2/3-L5 axons, similarity tuning, distance-decay",
  "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": "Graph-neural-network embedding of >30,000 excitatory pyramidal dendritic skeletons reconstructed from the MICrONS V1-HVA EM volume; unsupervised clustering and morphological feature analysis to recover excitatory subtype organization.",
  "review_bundle_ref": "analysis_bundle:ab-d9c479db9be9",
  "replication_status": "single_study",
  "review_package_ref": "analysis_bundle:ab-d9c479db9be9",
  "source_artifact_ref": "wiki_page:computationalreviewrecurrence-05-horizontal",
  "origin_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_05_evidence_package.json",
  "commit_sha": "79ce062d54a924ce05953ec90aa9d26044d2b48f",
  "created_by": "persona-jerome-lecoq-gbo-neuroscience",
  "repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence"
}