Evaluation of the spatial variability in the major resting-state networks across human brain functional atlases

Hum Brain Mapp. 2019 Oct 15;40(15):4577-4587. doi: 10.1002/hbm.24722. Epub 2019 Jul 19.

Abstract

The human brain is intrinsically organized into resting-state networks (RSNs). Currently, several human brain functional atlases are used to define the spatial constituents of these RSNs. However, there are significant concerns about interatlas variability. In response, we undertook a quantitative comparison of the five major RSNs (default mode [DMN], salience, central executive, sensorimotor, and visual networks) across currently available brain functional atlases (n = 6) in which we demonstrated that (a) similarity between atlases was modest and positively linked to the size of the sample used to construct them; (b) across atlases, spatial overlap among major RSNs ranged between 17 and 76% (mean = 39%), which resulted in variability in their functional connectivity; (c) lower order RSNs were generally spatially conserved across atlases; (d) among higher order RSNs, the DMN was the most conserved across atlases; and (e) voxel-wise flexibility (i.e., the likelihood of a voxel to change network assignment across atlases) was high for subcortical regions and low for the sensory, motor and medial prefrontal cortices, and the precuneus. In order to facilitate RSN reproducibility in future studies, we provide a new freely available Consensual Atlas of REsting-state Networks, based on the most reliable atlases.

Keywords: brain functional atlases; consensual atlas; functional connectivity; resting-state networks; spatial variability.

Publication types

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

MeSH terms

  • Adolescent
  • Adult
  • Anatomy, Artistic*
  • Atlases as Topic*
  • Connectome*
  • Executive Function
  • Female
  • Humans
  • Magnetic Resonance Imaging*
  • Male
  • Middle Aged
  • Nerve Net / anatomy & histology*
  • Nerve Net / physiology
  • Reproducibility of Results
  • Young Adult