Analyzing the Cortical Thickness of the Primate Brain through the Segmentation of Magnetic Resonance Imaging

Abstract

Cortical thickness has been tied to atypical brain development and associated with numerous neurological disorders, including Autism Spectrum Disorder, Alzheimer’s diseases, and epilepsy. Primate brains have a broad range of morphologies that range from lissencephalic to gyrencephalic and from walnut-sized to grapefruit-sized, making them an excellent testing ground for hypotheses on brain development. The purpose of the present study was to investigate how cortical thickness changes with the different brain morphologies found in primate species. Five brains from five different species were volumetrically segmented using BrainBox, an open-source imaging software. The segmentations were then run through a custom-built Python pipeline which was developed to calculate the cortical thickness of a brain when segmented masks were provided. The cortical thickness was calculated using a three-dimensional Euclidean distance algorithm where the minimum distance between the cerebrum and subcortex surfaces at each node on the cerebrum was stored. To minimize the computational time, the volume of the subcortex that was explored was constrained by using a logic switch to create a cubic sub-matrix. The initial results have shown that the cortical thickness scales with the brain volume as was expected. Future work will look into how the cortical thickness varies with gyrification index and between sulcal and gyral regions of the primate brain. The curvature of the cerebrum will also be investigated to accurately label nodes on the surface as lying in a sulcal or gyral region.