Version history

{
  "scope": "connectome-based multi-region rate models of macaque and mouse neocortex",
  "claim_text": "Connectome-based multi-region cortical models for macaque and mouse predict that experimentally quantified across-area heterogeneity in synaptic excitation and inhibition produces functional modularity (inverted-V timescale pattern) during simulated working memory.",
  "raw_fields": {
    "n": 0,
    "doi": "10.1101/2023.06.04.543639",
    "claim": "Connectome-based multi-region cortical models for macaque and mouse predict that experimentally quantified across-area heterogeneity in synaptic excitation and inhibition produces functional modularity (inverted-V timescale pattern) during simulated working memory.",
    "cite_key": "Wang2023d",
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    "claim_source_sentence": "Our theory starts with a departure from the canonical local circuit principle [5] by highlighting differences between cortical areas in the form of experimentally quantified heterogeneities of synaptic excitation and inhibition.",
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  "section_id": "section_13",
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  "source_span": "Our theory starts with a departure from the canonical local circuit principle [5] by highlighting differences between cortical areas in the form of experimentally quantified heterogeneities of synaptic excitation and inhibition.",
  "study_system": "connectome-based multi-region rate models of macaque and mouse neocortex",
  "evidence_refs": [
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  "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",
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      "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."
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  "evidence_summary": "Connectome-based large-scale rate-network models of macaque and mouse cortex incorporating area-by-area E/I heterogeneity, simulating a delayed-response task.",
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  "replication_status": "replication_unknown",
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}