Dynamic resting state functional connectivity in awake and anesthetized rodents

Zhifeng Liang, Xiao Liu, Nanyin Zhang

Research output: Contribution to journalArticle

61 Scopus citations

Abstract

Since its introduction, resting-state functional magnetic resonance imaging (rsfMRI) has been a powerful tool for investigating functional neural networks in both normal and pathological conditions. When measuring resting-state functional connectivity (RSFC), most rsfMRI approaches do not consider its temporal variations and thus only provide the averaged RSFC over the scan time. Recently, there has been a surge of interest to investigate the dynamic characteristics of RSFC in humans, and promising results have been yielded. However, our knowledge regarding the dynamic RSFC in animals remains sparse. In the present study we utilized the single-volume co-activation method to systematically study the dynamic properties of RSFC within the networks of infralimbic cortex (IL) and primary somatosensory cortex (S1) in both awake and anesthetized rats. Our data showed that both IL and S1 networks could be decomposed into several spatially reproducible but temporally changing co-activation patterns (CAPs), suggesting that dynamic RSFC was indeed a characteristic feature in rodents. In addition, we demonstrated that anesthesia profoundly impacted the dynamic RSFC of neural circuits subserving cognitive and emotional functions but had less effects on sensorimotor systems. Finally, we examined the temporal characteristics of each CAP, and found that individual CAPs exhibited consistent temporal evolution patterns. Together, these results suggest that dynamic RSFC might be a general phenomenon in vertebrate animals. In addition, this study has paved the way for further understanding the alterations of dynamic RSFC in animal models of brain disorders.

Original languageEnglish (US)
Pages (from-to)89-99
Number of pages11
JournalNeuroImage
Volume104
DOIs
StatePublished - Jan 1 2015

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All Science Journal Classification (ASJC) codes

  • Neurology
  • Cognitive Neuroscience

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