Dynamic changes in fractional amplitude of low-frequency fluctuations in patients with chronic insomnia

Wei Chen; Hui Wang; Tianze Sun; Qi Wu; Wenxuan Han; Qian Li; Yong Liu; Yuanping Zhou; Xiuyong He

doi:10.3389/fnins.2022.1050240

Dynamic changes in fractional amplitude of low-frequency fluctuations in patients with chronic insomnia

Front Neurosci. 2022 Nov 29:16:1050240. doi: 10.3389/fnins.2022.1050240. eCollection 2022.

Authors

Wei Chen¹, Hui Wang^{2

3}, Tianze Sun³, Qi Wu¹, Wenxuan Han³, Qian Li¹, Yong Liu¹, Yuanping Zhou¹, Xiuyong He¹

Affiliations

¹ Department of Medical Imaging Center, Ankang Hospital of Traditional Chinese Medicine, Ankang, China.
² School of Future Technology, Xi'an Jiaotong University, Xi'an, China.
³ Department of Medical Imaging, The First Affiliated Hospital of Xi 'an Jiaotong University, Xi'an, China.

Abstract

Background: Previous neuroimaging studies have mostly focused on changes in static functional connectivity in patients with chronic insomnia (CI) . Features of dynamic brain activity in patients with CI have rarely been described in detail. The present study investigated changes in dynamic intrinsic brain activity in patients with CI by dynamic fractional amplitude of low-frequency fluctuation (dfALFF) analysis.

Materials and methods: A total of 30 patients with CI and 27 healthy controls (HCs) were enrolled. We compared dfALFF between these two groups, and examined the correlation between changes in dfALFF and clinical symptoms of CI. Multivariate pattern analysis was performed to differentiate patients with CI from HCs.

Results: Compared with HC subjects, patients with CI showed significantly increased dfALFF in the left insula, right superior temporal gyrus, left parahippocampal gyrus, right amygdala, and bilateral posterior lobes of the cerebellum. Moreover, dfALFF values in the left insula and left parahippocampal gyrus showed a positive correlation with Pittsburgh Sleep Quality Index scores. A logistic regression model was constructed that had 96.7% sensitivity, 80.0% specificity, and 83.0% overall accuracy for distinguishing patients with CI from HCs.

Conclusion: Dynamic local brain activity showed increased instability in patients with CI. The variability in dfALFF in the limbic system and brain areas related to sleep/wakefulness was associated with insomnia symptoms. These findings may provide insight into the neuropathologic basis of CI.

Keywords: chronic insomnia; dynamic fractional amplitude of low-frequency fluctuations; instable brain activity; multivariate pattern analysis; sleep disorder.