Mesoscopic patterns of functional connectivity alterations in autism by contrast subgraphs
Despite the breakthrough achievements in understanding structural and functional connectivity alterations that underlie autism spectrum disorder (ASD), the exact nature and type of such alterations are not yet clear due to conflicting reports of hyper-connectivity, hypo-connectivity, and -in some cases- combinations of both. In this work, we approach the debate about hyper- vs hypoconnectivity in ASD using a novel network comparison technique designed to capture mesoscopic-scale differential structures. In particular, we build on recent algorithmic advances in the sparsification of functional connectivity matrices, in the extraction of contrast subgraphs, and in the computation of statistically significant maximal frequent itemsets, and develop a method to identify mesoscale structural subgraphs that are maximally dense and different in terms of connectivity levels between the different sets of networks. We apply our method to analyse brain networks of typically developed individuals and ASD patients across different developmental phases and find a set of altered cortical-subcortical circuits between healthy subjects and patients affected by ASD. Specifically, our analysis highlights in ASD patients a significantly larger number of functional connections among regions of the occipital cortex and between the left precuneus and the superior parietal gyrus. At the same time, reduced connectivity characterised the superior frontal gyrus and the temporal lobe regions. More importantly, we can simultaneously detect regions of the brain that show hyper and hypo-connectivity in ASD in children and adolescents, recapitulating within a single framework multiple previous separate observations.