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Free keywords:
fMRI; Neuroimaging; Cortical; Parcellation; Language
Abstract:
Broca's region is comprised of two adjacent cytoarchitectonic areas, 44 and 45, which have distinct connectivity to superior temporal and inferior parietal regions in both macaque monkeys and humans. The current study aimed to make use of prior knowledge of sulcal anatomy and resting-state functional connectivity, together with a novel visualization technique, to manually parcellate areas 44 and 45 in individual brains in vivo. 101 resting-state functional magnetic resonance imaging datasets were used from the Human Connectome Project. Left-hemisphere surface-based correlation matrices were computed and visualized in brainGL. By observing differences in the connectivity patterns of neighboring nodes, areas 44 and 45 were manually parcellated in individual brains, and then compared at the group-level. Additionally, the manual labeling approach was compared to parcellation results based on several data-driven clustering techniques. Areas 44 and 45 could be clearly distinguished from each other in all individuals and the manual segmentation method demonstrated high test-retest reliability. Group−-level probability maps of the areas 44 and 45 showed spatial consistency across individuals and correspond well to cytoarchitectonic probability maps. Group-level connectivity maps were consistent with previous studies showing distinct connectivity patterns of areas 44 and 45. Data-driven parcellation techniques produced clusters with varying degrees of spatial overlap with the manual labels, indicating the need for further investigation and validation of machine learning cortical segmentation approaches. The current study provides a reliable method for individual-level cortical parcellation that could be applied to regions distinguishable by even the most subtle differences in patterns of functional connectivity.
