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The brainstem connectome database.

Oliver Schmitt^1,2, Peter Eipert³, Frauke Ruß³

¹Dep. of Anatomy, University of Rostock, Rostock, Germany. schmitt@med.uni-rostock.de.

Scientific Data

|April 13, 2022

Summary

This study details the rat brainstem connectome (BC) database, revealing its scale-free, small-world network organization. This resource aids in understanding brain connectivity and simulating disorders like Multiple Sclerosis.

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Area of Science:

Neuroscience
Computational Biology
Network Science

Background:

Understanding neural connectivity is crucial for deciphering brain function and dysfunction.
Existing data on brainstem connections are fragmented, hindering comprehensive analysis.

Purpose of the Study:

To construct and analyze a comprehensive database of directed and weighted connections within the rat brainstem (brainstem connectome, BC).
To investigate the network properties and organizational principles of the brainstem connectome.
To demonstrate the utility of the BC database in modeling neurological pathways and disorders.

Main Methods:

A long-term metastudy of tract tracing publications to build the BC database.
Analysis using the neuroVIISAS framework, including global/local network properties, motif, and community analysis.
Modeling of signal propagation through the somatosensory pathway.

Main Results:

The rat brainstem connectome exhibits scale-free network properties and small-world connectivity.
Community analysis revealed partial matching between functional areas and connectivity patterns.
BC modeling successfully demonstrated signal propagation in the somatosensory pathway, relevant to Multiple Sclerosis.

Conclusions:

The BC database provides a valuable resource for studying brainstem network organization.
The identified network properties offer insights into brain function and potential disease mechanisms.
The BC database and framework can be used to model and understand neurological disorders affecting connectivity.