Critical Dynamics of Thalamus Following Partial Sleep Deprivation
Poster No:
2093
Submission Type:
Abstract Submission
Authors:
Fan Yang1, Siqi Cai1, Lixian Zou1, Chunxiang Jiang2, Lijuan Zhang1
Institutions:
1Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, 2Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, shenzhen, guangdong
First Author:
Co-Author(s):
Lixian Zou
Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences
Shenzhen, Guangdong
Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences
Shenzhen, Guangdong
Chunxiang Jiang
Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences
shenzhen, guangdong
Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences
shenzhen, guangdong
Lijuan Zhang
Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences
Shenzhen, Guangdong
Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences
Shenzhen, Guangdong
Introduction:
Sleep deprivation (SD) impairs brain function, but the underlying neural mechanisms remain unclear. Recent studies on dynamics of the brain (Fosque et al., 2021) suggest that prolonged wakefulness deviates the brain from the critical state (Xu et al., 2024). As an integrator of sleep and consciousness, the thalamus may pivot the regulation of this transition. This study aims to explore the neural avalanche behavior of the thalamus after partial SD (pSD) based on resting-state BOLD fMRI.
Methods:
This study was approved by the local institutional review board. Forty-one healthy volunteers with pSD (aged 23-35 years, 35 females) were recruited. FMRI was performed before the start of pSD (pre-pSD), right after pSD (im-pSD), and 3 to 5 days after pSD (post-pSD) on a 3.0T scanner (UIH uMR 790, Shanghai, China) with 32 channel phased array head coil and multi-band accelerated planar echo imaging sequence. The typical imaging parameters were TR/TE 1000/30ms, FA 62°, resolution 2.5x2.5x2.5 mm3, FOV 210x210mm2, 540 volumes.
Data preprocessing was performed using the DPARSF toolkit and the standard procedures (Chao-Gan & Yu-Feng, 2010). BOLD fMRI series were extracted based on the Brainnetome atlas (Fan et al., 2016) including 16 thalamic regions of interest (ROI), and Z-normalized.
Avalanche events were defined using the point process approach with a threshold of 1.4 and 1-second time window. A signal is marked as 1 if it exceeds the threshold for three consecutive time points with a peak at the middle point and other moments are marked as 0, creating a binarized sparse matrix. Cascading event between two 0 values in each ROI row were defined as a neural avalanche. Avalanche size was defined as the total number of events within an avalanche, and duration as the number of time boxes spanned.
Branching parameter σ was calculated as the ratio of events in adjacent time bin within each avalanche, expressed as σ.
Data preprocessing was performed using the DPARSF toolkit and the standard procedures (Chao-Gan & Yu-Feng, 2010). BOLD fMRI series were extracted based on the Brainnetome atlas (Fan et al., 2016) including 16 thalamic regions of interest (ROI), and Z-normalized.
Avalanche events were defined using the point process approach with a threshold of 1.4 and 1-second time window. A signal is marked as 1 if it exceeds the threshold for three consecutive time points with a peak at the middle point and other moments are marked as 0, creating a binarized sparse matrix. Cascading event between two 0 values in each ROI row were defined as a neural avalanche. Avalanche size was defined as the total number of events within an avalanche, and duration as the number of time boxes spanned.
Branching parameter σ was calculated as the ratio of events in adjacent time bin within each avalanche, expressed as σ.
Results:
τs, τt, and γ of the whole brain deviated from the critical state (Fig. 1) after pSD, and returned to the vicinity of the critical state at post-pSD. σ of post-pSD showed a propensity of increase that lasts into sleep restoration.
The thalamus exhibited similar variability in critical exponents (Fig. 2), but σ declined post pSD, and did not recover after sleep restoration. The whole-brain neural avalanches of this study follow a scaling relationship that mimics the mean-field directed percolation universality class (γ=2) (Non-Equilibrium Phase Transitions, 2008). The decrease in the power-law exponents of the whole brain indicated a more even distribution of the neural activity after pSD, suggesting reduced functional integration of the brain. The differences in the power-law exponents between the brain and thalami in this study may be ascribed to the system size effect and the potential distinctiveness of their universality classes. These findings necessitate the separate investigation of cortical and subcortical criticality in future study. The declined scaling relationship between avalanche size and duration for the whole brain after sleep restoration indicates a shortened propagation time of neural activity and weakened information integration over long distances.
The thalamus exhibited similar variability in critical exponents (Fig. 2), but σ declined post pSD, and did not recover after sleep restoration. The whole-brain neural avalanches of this study follow a scaling relationship that mimics the mean-field directed percolation universality class (γ=2) (Non-Equilibrium Phase Transitions, 2008). The decrease in the power-law exponents of the whole brain indicated a more even distribution of the neural activity after pSD, suggesting reduced functional integration of the brain. The differences in the power-law exponents between the brain and thalami in this study may be ascribed to the system size effect and the potential distinctiveness of their universality classes. These findings necessitate the separate investigation of cortical and subcortical criticality in future study. The declined scaling relationship between avalanche size and duration for the whole brain after sleep restoration indicates a shortened propagation time of neural activity and weakened information integration over long distances.
·Figure 1．Whole-brain scale inter-group neural avalanche analysis
·Figure 2．Thalamus scale inter-group neural avalanche analysis
Conclusions:
pSD causes the brain and thalamus to deviate from critical state at differential scales. Decreased thalamic avalanche branching parameters may leverage the decoding of pSD effect on cognitive impairment. Further investigations focusing on the criticality of the cortical and subcortical grey matter are suggested for the future sleep studies.
Modeling and Analysis Methods:
Other Methods 2
Perception, Attention and Motor Behavior:
Sleep and Wakefulness 1
Keywords:
MRI
Sleep
Thalamus
Other - Criticality
1|2Indicates the priority used for review
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Provide references using APA citation style.
2. Fan, L.(2016). The human brainnetome atlas: A new brain atlas based on connectional architecture. Cerebral Cortex (New York, N.Y.: 1991), 26(8), 3508–3526.
3. Fosque, L. J.(2021). Evidence for quasicritical brain dynamics. Physical Review Letters, 126(9), 098101.
4. Henkel, M.(2008). Non-equilibrium phase transitions. Springer Netherlands. Vol. I and II.
5. Xu, Y.(2024) Sleep restores an optimal computational regime in cortical networks. Nature Neuroscience, 27(2), 328–338.
Acknowledgement:
This work was partially supported by Strategic Priority Research Program of the Chinese Academy of Sciences, XDB0930000, Shenzhen Science and Technology Programs (GJHZ20220913142812024), National Natural Science Foundation of China (82341248), the Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of sciences.