¹ College of Osteopathic Medicine, Pacific Northwest University of Health Sciences, Yakima, United States of America ² College of Osteopathic Medicine, Pacific Northwest University of Health Sciences, Yakima, United States of America ³College of Osteopathic Medicine, Pacific Northwest University of Health Sciences, Yakima, United States of America
Email:smbrown@pnwu.edu
Introduction
Pathology in dynamic functional connectivity is well documented but lacks explanatory rationale.Dynamicfunctional connectivityparallels the existence of discrete state transitions,the study ofwhich may provide further elucidation. In this study, weutilizedTopological Data Analysis (TDA) toobservethe shape of whole brain networks and the transitions between them. Further, we aim to understand thestructure-function relationship of brain states with neuronal physiology. Methods fMRI scans were obtainedand preprocessedfrom the Human Connectome Project motor task dataset.States were definedrelativeto an anticipatory visual cue. We initially used the Euclidian distance (L2) toclusterstateshierarchically.We converted brain states to Vietoris-Rips complexestoidentifytopology.Distances between these complexes were then measured using the Wasserstein distanceandaggregatedusinghierarchicalclustering. Results Wedemonstratethateach L2 state label mustonly havea single topology, but the same topology may exist in multiple states.Under this assumption, many combinations of L2 and topology wereobservedto be invalid.Thisisreconciled by anintrinsichierarchy of brain states. Discussion Weobservethatbrainstates maybedrastically different networks but share the same topology. For instance,resting versus task states mayexhibitthesame topology.In contrast, similar states may also differ in topology.We findthat topology may have a unique role in neuronal physiology andprovidesa potential framework for further studies that explorebrain dynamics.
