Abstract
Human brain connectivity is extremely complex and variable across subjects. While long association and projection bundles are stable and have been deeply studied, short association bundles present higher intersubject variability, and few studies have been carried out to adequately describe the structure, shape, and reproducibility of these bundles. However, their analysis is crucial to understand brain function and better characterize the human connectome. In this study, we propose an automatic method to identify reproducible short association bundles of the superficial white matter, based on intersubject hierarchical clustering. The method is applied to the whole brain and finds representative clusters of similar fibers belonging to a group of subjects, according to a distance metric between fibers. We experimented with both affine and non-linear registrations and, due to better reproducibility, chose the results obtained from non-linear registration. Once the clusters are calculated, our method performs automatic labeling of the most stable connections based on individual cortical parcellations. We compare results between two independent groups of subjects from a HARDI database to generate reproducible connections for the creation of an atlas. To perform a better validation of the results, we used a bagging strategy that uses pairs of groups of 27 subjects from a database of 74 subjects. The result is an atlas with 44 bundles in the left hemisphere and 49 in the right hemisphere, of which 33 bundles are found in both hemispheres. Finally, we use the atlas to automatically segment 78 new subjects from a different HARDI database and to analyze stability and lateralization results.
Highlights
One of the goals of white matter (WM) studies is the construction of an atlas of human brain connections, which is an important step toward the understanding of human brain function (Sporns, 2013)
We propose a method for the study of superficial white matter (SWM) based on the intersubject clustering of whole-brain short white matter fibers
Automatic segmentation was applied to test the reproducibility of the final atlas of SWM bundles (Section 3.3)
Summary
One of the goals of white matter (WM) studies is the construction of an atlas of human brain connections, which is an important step toward the understanding of human brain function (Sporns, 2013). Long association and projection bundles have been deeply studied due to their large size and stability across subjects. Few studies about short association bundles of superficial white matter (SWM) exist. These bundles have a smaller size, an Clustering of Short Association Bundles unknown structure, and a high intersubject variability, resulting in higher difficulties for their study. The analysis of SWM fibers is important to describe the human connectome to explain and predict human brain functions. Their study can improve the knowledge of specific local connections by helping to understand functions and features that can be altered in some psychiatric disorders or neurological pathologies
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