Characterization of Brain Cortical Morphology Using Localized Topology-Encoding Graphs

TL;DR

This paper introduces a novel graph-based method to encode and analyze the complex morphology of the human brain cortex, aiding in individual discrimination and longitudinal studies.

Contribution

It proposes a new graph encoding technique for cortical morphology and explores spectral features as descriptors for individual differentiation.

Findings

Spectral graph features can distinguish individuals by sex.

The method captures global and localized cortical structures.

Graph descriptors show potential in brain morphology analysis.

Abstract

The human brain cortical layer has a convoluted morphology that is unique to each individual. Characterization of the cortical morphology is necessary in longitudinal studies of structural brain change, as well as in discriminating individuals in health and disease. A method for encoding the cortical morphology in the form of a graph is presented. The design of graphs that encode the global cerebral hemisphere cortices as well as localized cortical regions is proposed. Spectral features of these graphs are then studied and proposed as descriptors of cortical morphology. As proof-of-concept of their applicability in characterizing cortical morphology, the descriptors are studied in the context of discriminating individuals based on their sex.