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

Gaelle E. Doucet, Won Hee Lee, Sophia Frangou

Research output: Contribution to journalArticlepeer-review

73 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)4577-4587
Number of pages11
JournalHuman Brain Mapping
Volume40
Issue number15
DOIs
StatePublished - Oct 15 2019
Externally publishedYes

Keywords

  • brain functional atlases
  • consensual atlas
  • functional connectivity
  • resting-state networks
  • spatial variability

ASJC Scopus subject areas

  • Anatomy
  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Neurology
  • Clinical Neurology

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