RT Journal Article
SR Electronic
T1 Graph Ricci Curvatures Reveal Atypical Functional Connectivity in Autism Spectrum Disorder
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2021.11.28.470231
DO 10.1101/2021.11.28.470231
A1 Pavithra Elumalai
A1 Yasharth Yadav
A1 Nitin Williams
A1 Emil Saucan
A1 Jürgen Jost
A1 Areejit Samal
YR 2021
UL http://biorxiv.org/content/early/2021/12/21/2021.11.28.470231.abstract
AB While standard graph-theoretic measures have been widely used to characterize atypical resting-state functional connectivity in autism spectrum disorder (ASD), geometry-inspired network measures have not been applied. In this study, we apply Forman-Ricci and Ollivier-Ricci curvatures to compare networks of ASD and typically developing individuals (N = 1112) from the Autism Brain Imaging Data Exchange I (ABIDE-I) dataset. We find brain-wide and region-specific ASD-related differences for both Forman-Ricci and Ollivier-Ricci curvatures, with region-specific differences concentrated in Default Mode, Somatomotor and Ventral Attention networks for Forman-Ricci curvature. We use meta-analysis decoding to demonstrate that brain regions with curvature differences are associated to those cognitive domains known to be impaired in ASD. Further, we show that brain regions with curvature differences overlap with those brain regions whose non-invasive stimulation improves ASD-related symptoms. These results suggest the utility of graph Ricci curvatures in characterizing atypical connectivity of clinically relevant regions in ASD and other neurodevelopmental disorders.Competing Interest StatementThe authors have declared no competing interest.