Details
- 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.
- 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_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)
- 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
- 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
Raw fields (4)
- 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." }- source_refs
[ "paper:paper-89ce835df6b0" ]
- evidence_refs
[ { "ref": "paper:paper-89ce835df6b0" } ]- 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" }