Mapping anatomical connectivity of the primate cerebral cortex using diffusion MRI
Damen, Frederick William
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The human brain can be modeled as a small-world network that has the capability of handling complex cognitive function. However, that network as a whole still remains poorly understood partly due to a limited understanding of our non-human primate relatives’ whole brain networks. A significant roadblock regarding non-human primate data is the lack of reliable cortical region labels, as almost all human whole brain network studies rely on such region-wise labeled brain masks, otherwise known as parcellation masks. The goal of this study is to develop a method to parcellate the cerebral cortex in primate brains independently of any pre-defined cortical region labels. This mask will then be used in future whole brain network analysis, where the connective white matter structures will be reconstructed between each region in the mask. For this study, derived methods were developed using data from our closest living primate relative, the chimpanzee. An initial method included the non-linear transformation of the human automatic anatomical labeling (AAL) cortical template to chimpanzee template space; however, structural and functional mismatches discredited that technique. The derived anatomically independent parcellation (AIP) method employed dynamic region growth of each node derived in the gray/white matter interface mask, and demonstrated high-resolution segmentation of the cortical regions over several inputted node numbers (200, 500, 1000, and 3000). Using the derived parcellation masks in network analysis, future applications of this technique in cross-species comparisons could help gain significant insight into the evolutionary changes in the organization of brain architecture, as well as the origins of some neurodegenerative diseases in both human and non-human primates.