Precision dynamical mapping using topological data analysis reveals a hub-like transition state at rest

• Published in: Nature communications Vol. 13; no. 1; pp. 4791 - 19
• Main Authors: Saggar, Manish, Shine, James M., Liégeois, Raphaël, Dosenbach, Nico U. F., Fair, Damien
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 15.08.2022; Nature Publishing Group; Nature Portfolio
• Subjects: 59/36; 631/114/2408; 631/378/116/1925; Activity patterns; Brain; Brain - diagnostic imaging; Brain Mapping; Configurations; Data Analysis; External stimuli; Functional magnetic resonance imaging; Humanities and Social Sciences; Humans; Magnetic Resonance Imaging; multidisciplinary; Nerve Net - diagnostic imaging; Science; Science (multidisciplinary); Topology
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-022-32381-2

In the absence of external stimuli, neural activity continuously evolves from one configuration to another. Whether these transitions or explorations follow some underlying arrangement or lack a predictable ordered plan remains to be determined. Here, using fMRI data from highly sampled individuals (~5 hours of resting-state data per individual), we aimed to reveal the rules that govern transitions in brain activity at rest. Our Topological Data Analysis based Mapper approach characterized a highly visited transition state of the brain that acts as a switch between different neural configurations to organize the spontaneous brain activity. Further, while the transition state was characterized by a uniform representation of canonical resting-state networks (RSNs), the periphery of the landscape was dominated by a subject-specific combination of RSNs. Altogether, we revealed rules or principles that organize spontaneous brain activity using a precision dynamics approach. Although spontaneous brain activity is complex and clinically relevant, it is still unclear whether transitions in resting brain activity follow an underlying arrangement or whether they are unpredictable. In this work, the authors revealed a transition state of the brain that acts like a switch between states and forms the basis for the continuous evolution of brain activity patterns at rest.