- raw_fields
{
"n": 10,
"doi": "10.1002/hbm.22828",
"claim": "In macaque, dMRI tractography number-of-streamlines correlates positively with retrograde tract-tracing FLN-based connection strengths from CoCoMac and Markov datasets (P<0.001).",
"cite_key": "VandenHeuvel2015",
"evidence": "Cross-validation of in vivo DWI-derived connectivity weights against gold-standard macaque tract-tracing data.",
"effect_size": "P < 0.001 correlation between DWI NOS and tract-tracing connection strength",
"text_access": "abstract_only",
"study_system": "10 ex vivo rhesus macaque brains compared against CoCoMac + Markov tract-tracing datasets",
"source_cluster_id": "cluster_11",
"replication_status": "independently_replicated",
"claim_source_sentence": "NOS and density of reconstructed fiber pathways derived from DWI data acquired across 10 rhesus macaques was found to positively correlate to tract-tracing based measurements of connectivity strength across both the CoCoMac and Markov dataset (both P < 0.001), suggesting DWI NOS to form a valid method of assessment of the projection strength of white matter pathways.",
"replication_evidence_dois": [
"10.1162/netn_a_00098",
"10.1038/s41467-017-01285-x"
],
"effect_size_source_sentence": "NOS and density of reconstructed fiber pathways derived from DWI data acquired across 10 rhesus macaques was found to positively correlate to tract-tracing based measurements of connectivity strength across both the CoCoMac and Markov dataset (both P < 0.001), suggesting DWI NOS to form a valid method of assessment of the projection strength of white matter pathways."
}- source_refs
[
"paper:paper-9fcd61fe4817"
]
- source_span
NOS and density of reconstructed fiber pathways derived from DWI data acquired across 10 rhesus macaques was found to positively correlate to tract-tracing based measurements of connectivity strength across both the CoCoMac and Markov dataset (both P < 0.001), suggesting DWI NOS to form a valid method of assessment of the projection strength of white matter pathways.
- evidence_refs
[
{
"ref": "paper:paper-9fcd61fe4817"
}
]- 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"
}