State-independent and state-dependent patterns in the rat default mode network

Wei Jing, Yang Xia, Min Li, Yan Cui, Mingming Chen, Miaomiao Xue, Daqing Guo, Bharat B. Biswal, Dezhong Yao

Research output: Contribution to journalArticlepeer-review

Abstract

Resting-state studies have typically assumed constant functional connectivity (FC) between brain regions, and these parameters of interest provide meaningful descriptions of the functional organization of the brain. A number of studies have recently provided evidence pointing to dynamic FC fluctuations in the resting brain, especially in higher-order regions such as the default mode network (DMN). The neural activities underlying dynamic FC remain poorly understood. Here, we recorded electrophysiological signals from DMN regions in freely behaving rats. The dynamic FCs between signals within the DMN were estimated by the phase locking value (PLV) method with sliding time windows across vigilance states [quiet wakefulness (QW) and slow-wave and rapid eye movement sleep (SWS and REMS)]. Factor analysis was then performed to reveal the hidden patterns within the DMN. We identified distinct spatial FC patterns according to the similarities between their temporal dynamics. Interestingly, some of these patterns were vigilance state-dependent, while others were independent across states. The temporal contributions of these patterns fluctuated over time, and their interactive relationships were different across vigilance states. These spatial patterns with dynamic temporal contributions and combinations may offer a flexible framework for efficiently integrating information to support cognition and behavior. These findings provide novel insights into the dynamic functional organization of the rat DMN.

Original languageEnglish (US)
Article number118148
JournalNeuroImage
Volume237
DOIs
StatePublished - Aug 15 2021

All Science Journal Classification (ASJC) codes

  • Neurology
  • Cognitive Neuroscience

Keywords

  • Default mode network
  • Dynamic functional connectivity
  • Electrophysiological signals
  • Factor analysis
  • Vigilance state

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