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

Nat Commun. 2022 Aug 15;13(1):4791. 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.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, N.I.H., Extramural

MeSH terms

  • Brain / diagnostic imaging
  • Brain Mapping*
  • Data Analysis*
  • Humans
  • Magnetic Resonance Imaging
  • Nerve Net / diagnostic imaging