Graph matching of structural and functional brain networks
Abstract
By subdividing the cortex into regions according to a given atlas, we assume that all the regions match across different subjects. However, because of inter-subject variability, it may not be possible to produce a single brain atlas for all subjects. Previous works have proposed to use structural connectomes constructed from diffusion magnetic resonance imaging tractography to align brain regions across a group of subjects, leading to an improved similarity of connectomes. In this work, we propose to simultaneously exploit structural and functional information in the alignment process. This allows us to explore multiple perspective of brain networks. Our results show the permutations induced by one type of connectivity (structural, functional) are not always supported by the other connectivity network, but when considering combined alignment, it is possible to find permutations of regions which are supported by both connectome modalities, leading to an increased similarity of functional and structural connectivity across subjects.
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