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. 2024 Jan 17;14(1):1537.
doi: 10.1038/s41598-024-51694-4.

Traces of EEG-fMRI coupling reveals neurovascular dynamics on sleep inertia

Zhitong John Wang  1 , Hsin-Chien Lee  2   3 , Chun-Hsiang Chuang  4 , Fan-Chi Hsiao  5 , Shwu-Hua Lee  6   7 , Ai-Ling Hsu  8   9 , Changwei W Wu  10   11
Affiliations

Traces of EEG-fMRI coupling reveals neurovascular dynamics on sleep inertia

Zhitong John Wang et al. Sci Rep. .

Abstract

Upon emergence from sleep, individuals experience temporary hypo-vigilance and grogginess known as sleep inertia. During the transient period of vigilance recovery from prior nocturnal sleep, the neurovascular coupling (NVC) may not be static and constant as assumed by previous neuroimaging studies. Stemming from this viewpoint of sleep inertia, this study aims to probe the NVC changes as awakening time prolongs using simultaneous EEG-fMRI. The time-lagged coupling between EEG features of vigilance and BOLD-fMRI signals, in selected regions of interest, was calculated with one pre-sleep and three consecutive post-awakening resting-state measures. We found marginal changes in EEG theta/beta ratio and spectral slope across post-awakening sessions, demonstrating alterations of vigilance during sleep inertia. Time-varying EEG-fMRI coupling as awakening prolonged was evidenced by the changing time lags of the peak correlation between EEG alpha-vigilance and fMRI-thalamus, as well as EEG spectral slope and fMRI-anterior cingulate cortex. This study provides the first evidence of potential dynamicity of NVC occurred in sleep inertia and opens new avenues for non-invasive neuroimaging investigations into the neurophysiological mechanisms underlying brain state transitions.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Illustration of experimental design and analytical indices. During sleep inertia, the neurovascular coupling may change along with this recovery period of consciousness. We probed the transitory changes of EEG-fMRI coupling, surrogates of neurovascular coupling, depending on the extended awakening time (A1 to A3).
Figure 2
Figure 2
EEG arousal features across four imaging sessions. (A) Averaged theta/beta ratio per imaging session per each subject was used to compare across four imaging sessions (Friedman test p = 0.09). Theta/beta ratio in A3 is higher than A2 but without statistical significance (Wilcoxon sign-rank test p = 0.06, FDR-corrected). (B) Spectral slope was found to fluctuate significantly across imaging sessions (Friedman test p = 0.025), but no pairs of imaging sessions were found to be significantly different. (C) No significance was found for alpha-vigilance across imaging sessions (Friedman test p > 0.1).
Figure 3
Figure 3
Time lag of peak positive correlation among sessions across sleep inertia. (A) Time lags where maximum positive correlation between thalamus and alpha-vigilance occurs across a [− 6, 14] s range were plotted for each subject. (B) There is a significant effect by imaging session (p = 0.02), where A1 and A2 were found with peak-correlation timings that are significantly later than A3 (**p = 0.01, FDR-corrected). (C) Time lags where maximum positive correlation between thalamus and EEG spectral slope occurs across a [− 6, 14] s range. (D) There is a significant effect by imaging session (p < 0.01), where A2 is found to be significantly earlier than A3 (*p = 0.03, FDR-corrected).
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