Details

scope
Cross-species mammalian cortico-cortical networks (mouse, macaque)
claim_text
Mammalian cortico-cortical networks have unusually high binary connection density — 0.66 in macaque and 0.97 in mouse — consistent with an exponential distance rule for connection probability.
section_id
section_12
source_url
https://github.com/AllenNeuralDynamics/ComputationalReviewLoops/blob/0632aae8abc141909207fe91f6349b9e36489c3b/evidence/section_12_evidence_package.json
effect_size
Binary connection density: 0.66 macaque, 0.97 mouse
review_repo
ComputationalReviewLoops
section_ref
wiki_page:computationalreviewloops-12
source_kind
review_finding
source_path
evidence/section_12_evidence_package.json
study_system
Cross-species mammalian cortico-cortical networks (mouse, macaque)
section_title
Whole-Brain Connectomics: Mouse, Primate, Human
evidence_summary
Documents the universal high cortical connection density and exponential distance rule across species.
review_bundle_ref
analysis_bundle:ab-d49e54403ef9
replication_status
independently_replicated
review_package_ref
analysis_bundle:ab-d49e54403ef9
source_artifact_ref
wiki_page:computationalreviewloops-12
origin_url
https://github.com/AllenNeuralDynamics/ComputationalReviewLoops/blob/0632aae8abc141909207fe91f6349b9e36489c3b/evidence/section_12_evidence_package.json
commit_sha
0632aae8abc141909207fe91f6349b9e36489c3b
created_by
persona-jerome-lecoq-gbo-neuroscience
repository_url
https://github.com/AllenNeuralDynamics/ComputationalReviewLoops
Raw fields (5)
raw_fields
{
  "n": 0,
  "doi": "10.1162/netn_a_00345",
  "claim": "Mammalian cortico-cortical networks have unusually high binary connection density — 0.66 in macaque and 0.97 in mouse — consistent with an exponential distance rule for connection probability.",
  "cite_key": "Molnar2024",
  "evidence": "Documents the universal high cortical connection density and exponential distance rule across species.",
  "effect_size": "Binary connection density: 0.66 macaque, 0.97 mouse",
  "text_access": "fulltext",
  "study_system": "Cross-species mammalian cortico-cortical networks (mouse, macaque)",
  "source_cluster_id": "cluster_11",
  "replication_status": "independently_replicated",
  "claim_source_sentence": "One key distinguishing feature is their high density of binary connectivity (connections existing or not), that is, they contain a large fraction of the maximum number of possible connections: 0.66 for the macaque ( Markov et al., 2011 ) and 0.97 for the mouse ( Gămănuţ et al., 2",
  "replication_evidence_dois": [
    "10.1093/cercor/bhs270",
    "10.1162/netn_a_00159"
  ],
  "effect_size_source_sentence": "One key distinguishing feature is their high density of binary connectivity (connections existing or not), that is, they contain a large fraction of the maximum number of possible connections: 0.66 for the macaque ( Markov et al., 2011 ) and 0.97 for the mouse ( Gămănuţ et al., 2"
}
source_refs
[
  "paper:paper-7a933b7da09d",
  "paper:paper-d7dd6ae02de1"
]
source_span
One key distinguishing feature is their high density of binary connectivity (connections existing or not), that is, they contain a large fraction of the maximum number of possible connections: 0.66 for the macaque ( Markov et al., 2011 ) and 0.97 for the mouse ( Gămănuţ et al., 2
evidence_refs
[
  {
    "ref": "paper:paper-7a933b7da09d"
  },
  {
    "ref": "paper:paper-d7dd6ae02de1"
  }
]
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": "0632aae8abc141909207fe91f6349b9e36489c3b",
  "source_repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewLoops"
}

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