Diffusion tensor imaging (DTI) and tractography have revealed many critical insights about how the human brain is organized as a large-scale complex network. As multisite imaging studies are becoming increasingly popular within the neuroimaging field, it is imperative to develop methods that can correct for inter-site differences, facilitating the combination of data from multiple sites. In this study, we present a normalization scheme that will correct for site-specific differences in diffusion-based structural connectivity data, and demonstrate its efficacy through multivariate regression experiments using the normalized structural connectivity features to predict subject’s age.
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