Robust Circuitry-Based Scores of Structural Importance of Human Brain Areas

TL;DR

This study introduces multiple graph-based scoring methods for identifying important brain regions in a human connectome, demonstrating their high correlation and robustness in reflecting anatomical significance.

Contribution

The paper presents seven new orderings based on brain circuitry properties, showing their high similarity and robustness in assessing vertex importance in the human connectome.

Findings

All seven orderings are highly correlated, indicating consistent importance scores.

Important brain regions tend to have many connections with long, thick fibers.

The proposed parameters provide robust measures for brain circuitry analysis.

Abstract

We consider the 1015-vertex human consensus connectome computed from the diffusion MRI data of 1064 subjects. We define seven different orders on these 1015 graph vertices, where the orders depend on parameters derived from the brain circuitry, that is, from the properties of the edges (or connections) incident to the vertices ordered. We order the vertices according to their degree, the sum, the maximum, and the average of the fiber counts on the incident edges, and the sum, the maximum and the average length of the fibers in the incident edges. We analyze the similarities of these seven orders by the Spearman correlation coefficient and by their inversion numbers and have found that all of these seven orders have great similarities. In other words, if we interpret the orders as scoring of the importance of the vertices in the consensus connectome, then the scores of the vertices will be similar in all seven orderings. That is, important vertices of the human connectome typically have many neighbors, connected with long and thick axonal fibers (where thickness is measured by fiber numbers), and their incident edges have high maximum and average values of length and fiber-number parameters, too. Therefore, these parameters may yield robust ways of deciding which vertices are more important in the anatomy of our brain circuitry than the others.