Structural MRI of brain similarity networks

Abstract

Recent advances in structural MRI analytics now allow the network organization of individual brains to be comprehensively mapped through the use of the biologically principled metric of anatomical similarity. In this Review, we offer an overview of the measurement and meaning of structural MRI similarity, especially in relation to two key assumptions that often underlie its interpretation: (i) that MRI similarity can be representative of architectonic similarity between cortical areas and (ii) that similar areas are more likely to be axonally connected, as predicted by the homophily principle. We first introduce the historical roots and technical foundations of MRI similarity analysis and compare it with the distinct MRI techniques of structural covariance and tractography analysis. We contextualize this empirical work with two generative models of homophilic networks: an economic model of cost-constrained connectional homophily and a heterochronic model of ontogenetically phased cortical maturation. We then review (i) studies of the genetic and transcriptional architecture of MRI similarity in population-averaged and disorder-specific contexts and (ii) developmental studies of normative cohorts and clinical studies of neurodevelopmental and neurodegenerative disorders. Finally, we prioritize knowledge gaps that must be addressed to consolidate structural MRI similarity as an accessible, valid marker of the architecture and connectivity of an individual brain network. Through use of the anatomical similarity, structural MRI analytics are now enabling the network organization of individual brains to be mapped. In this Review, Sebenius, Dorfschmidt et al. examine this field of structural MRI similarity network analysis.