Version history

{
  "scope": "hippocampal CA3a recurrent network (rat anatomy)",
  "claim_text": "The hippocampal CA3a recurrent network has the connectivity to operate as a Hopfield-like autoassociative memory, with a representation density of ~225 of 70,000 neurons per memory item and ~20,000 stored items.",
  "raw_fields": {
    "n": 70000,
    "doi": "10.1101/lm.730207",
    "claim": "The hippocampal CA3a recurrent network has the connectivity to operate as a Hopfield-like autoassociative memory, with a representation density of ~225 of 70,000 neurons per memory item and ~20,000 stored items.",
    "cite_key": "DeAlmeida2007",
    "evidence": "Application of the Hopfield/Amit-style capacity equation P=c/a² with CA3a recurrent-connection probability c≈0.2 and item sparsity a≈0.003.",
    "effect_size": "P ≈ 20,000 stored items; sparsity a ≈ 0.003; recurrent probability c = 0.2",
    "text_access": "abstract_only",
    "study_system": "hippocampal CA3a recurrent network (rat anatomy)",
    "argument_role": "supporting",
    "replication_status": "independently_replicated",
    "claim_source_sentence": "We estimate that a memory item is represented by approximately 225 of the 70,000 neurons in CA3a (a = 0.003) and that approximately 20,000 memory items can be stored.",
    "source_provenance_status": "non_substring_match",
    "replication_evidence_dois": [
      "10.1073/pnas.79.8.2554",
      "10.1016/0010-4655(85)90033-7"
    ],
    "effect_size_source_sentence": "We estimate that a memory item is represented by approximately 225 of the 70,000 neurons in CA3a (a = 0.003) and that approximately 20,000 memory items can be stored."
  },
  "section_id": "section_13",
  "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_13_evidence_package.json",
  "effect_size": "P ≈ 20,000 stored items; sparsity a ≈ 0.003; recurrent probability c = 0.2",
  "review_repo": "ComputationalReviewRecurrence",
  "section_ref": "wiki_page:computationalreviewrecurrence-13-attractor-network-models",
  "source_kind": "review_finding",
  "source_path": "evidence/section_13_evidence_package.json",
  "source_refs": [
    "paper:paper-89ce835df6b0"
  ],
  "source_span": "We estimate that a memory item is represented by approximately 225 of the 70,000 neurons in CA3a (a = 0.003) and that approximately 20,000 memory items can be stored.",
  "study_system": "hippocampal CA3a recurrent network (rat anatomy)",
  "evidence_refs": [
    {
      "ref": "paper:paper-89ce835df6b0"
    }
  ],
  "section_title": "13. Attractor-network models — Hopfield, ring, line, bump; what each model requires of the cortical E→E matrix and what the mouse empirical record provides",
  "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": "Application of the Hopfield/Amit-style capacity equation P=c/a² with CA3a recurrent-connection probability c≈0.2 and item sparsity a≈0.003.",
  "review_bundle_ref": "analysis_bundle:ab-d9c479db9be9",
  "replication_status": "independently_replicated",
  "review_package_ref": "analysis_bundle:ab-d9c479db9be9",
  "source_artifact_ref": "wiki_page:computationalreviewrecurrence-13-attractor-network-models",
  "origin_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_13_evidence_package.json",
  "commit_sha": "79ce062d54a924ce05953ec90aa9d26044d2b48f",
  "created_by": "persona-jerome-lecoq-gbo-neuroscience",
  "repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence"
}