White Matter Functional Connectivity in Resting-State fMRI: Robustness, Reliability, and Relationships to Gray Matter

Pan Wang, Jianlin Wang, Andrew Michael, Zedong Wang, Benjamin Klugah-Brown, Chun Meng, Bharat B. Biswal

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

A comprehensive characterization of the spatiotemporal organization in the whole brain is critical to understand both the function and dysfunction of the human brain. Resting-state functional connectivity (FC) of gray matter (GM) has helped in uncovering the inherent baseline networks of brain. However, the white matter (WM), which composes almost half of brain, has been largely ignored in this characterization despite studies indicating that FC in WM does change during task and rest functional magnetic resonance imaging (fMRI). In this study, we identify 9 white matter functional networks (WM-FNs) and 9 gray matter functional networks (GM-FNs) of resting fMRI. Intraclass correlation coefficient (ICC) was calculated on multirun fMRI data to estimate the reliability of static functional connectivity (SFC) and dynamic functional connectivity (DFC). Associations between SFC, DFC, and their respective ICCs are estimated for GM-FNs, WM-FNs, and GM-WM-FNs. SFC of GM-FNs were stronger than that of WM-FNs, but the corresponding DFC of GM-FNs was lower, indicating that WM-FNs were more dynamic. Associations between SFC, DFC, and their ICCs were similar in both GM- and WM-FNs. These findings suggest that WM fMRI signal contains rich spatiotemporal information similar to that of GM and may hold important cues to better establish the functional organization of the whole brain.

Original languageEnglish (US)
Pages (from-to)1547-1559
Number of pages13
JournalCerebral Cortex
Volume32
Issue number8
DOIs
StatePublished - Apr 15 2022

All Science Journal Classification (ASJC) codes

  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience

Keywords

  • dynamic functional connectivity
  • intraclass correlation coefficient
  • robustness
  • spatiotemporal organization
  • white matter functional networks

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