A Large-Scale High-Density Weighted Structural Connectome of the Macaque Brain Acquired by Predicting Missing Links.

ABSTRACT: As a substrate for function, large-scale brain structural networks are crucial for fundamental and systems-level understanding of primate brains. However, it is challenging to acquire a complete primate whole-brain structural connectome using track tracing techniques. Here, we acquired a weighted brain structural network across 91 cortical regions of a whole macaque brain hemisphere with a connectivity density of 59% by predicting missing links from the CoCoMac-based binary network with a low density of 26.3%. The prediction model combines three factors, including spatial proximity, topological similarity, and cytoarchitectural similarity-to predict missing links and assign connection weights. The model was tested on a recently obtained high connectivity density yet partial-coverage experi

SUBMITTER: Chen Y 

PROVIDER: S-EPMC7391281 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature