A graph-matching based metric of functional connectome distance between pairs of individuals varies with their ages, cognitive performances and familial relationships.

Functional connectomes (FCs), represented by networks or graphs that summarize coactivation patterns between pairs of brain regions, have been related at a population level to age, sex, cognitive/behavioral scores, life experience, genetics and disease/disorders. However, quantifying FC differences between pairs of individuals also provides a rich source of information with which to map to differences in those individuals biology, experience, genetics or behavior. In this study, graph matching is used to create a novel inter-individual FC metric, called swap distance, that quantifies the distance between pairs of individuals FCs. We apply graph matching to align FCs between pairs of individuals from the the Human Connectome Project (N = 997) and find that swap distance i) increases with increasing familial distance, ii) increases with subjects ages, iii) is smaller for pairs of females compared to pairs of males, and iv) is larger for females with lower cognitive scores compared to females with larger cognitive scores. Regions that contributed most to individuals swap distances were in higher-order networks, i.e. default-mode and fronto-parietal, that underlie executive function and memory. These higher-order networks regions also had swap frequencies that varied monotonically with familial relatedness of the individuals in question. We posit that the proposed graph matching technique provides a novel way to study inter-subject differences in FC and enables quantification of how FC may vary with age, relatedness, sex and behavior.