Journal
SCIENTIFIC DATA
Volume 9, Issue 1, Pages -Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41597-022-01219-3
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By building and analyzing the rat brainstem connectome database, we gain better understanding of the structure and function of neural networks. The database can be accessed through connectivity tables and web-based tools, and pattern analysis and community analysis are utilized to reveal its network organization.
Connectivity data of the nervous system and subdivisions, such as the brainstem, cerebral cortex and subcortical nuclei, are necessary to understand connectional structures, predict effects of connectional disorders and simulate network dynamics. For that purpose, a database was built and analyzed which comprises all known directed and weighted connections within the rat brainstem. A longterm metastudy of original research publications describing tract tracing results form the foundation of the brainstem connectome (BC) database which can be analyzed directly in the framework neuroVIISAS. The BC database can be accessed directly by connectivity tables, a web-based tool and the framework. Analysis of global and local network properties, a motif analysis, and a community analysis of the brainstem connectome provides insight into its network organization. For example, we found that BC is a scale-free network with a small-world connectivity. The Louvain modularity and weighted stochastic block matching resulted in partially matching of functions and connectivity. BC modeling was performed to demonstrate signal propagation through the somatosensory pathway which is affected in Multiple sclerosis.
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