scholarly journals Impact of acute sleep deprivation on dynamic functional connectivity states

2019 ◽  
Vol 41 (4) ◽  
pp. 994-1005 ◽  
Author(s):  
Changhong Li ◽  
Judith Fronczek‐Poncelet ◽  
Denise Lange ◽  
Eva Hennecke ◽  
Tina Kroll ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Sleep Deprivation ◽  
Dynamic Functional Connectivity ◽  
Acute Sleep Deprivation

scholarly journals Manifold Learning of Dynamic Functional Connectivity Reliably Identifies Functionally Consistent Coupling Patterns in Human Brains

2019 ◽  
Vol 9 (11) ◽  
pp. 309
Author(s):  
Yuyuan Yang ◽  
Lubin Wang ◽  
Yu Lei ◽  
Yuyang Zhu ◽  
Hui Shen
Keyword(s):  
Functional Connectivity ◽  
Sleep Deprivation ◽  
Manifold Learning ◽  
Temporal Dynamics ◽  
Functional Coupling ◽  
Dimensional Manifold ◽  
Dynamic Functional Connectivity ◽  
Local Linear Embedding ◽  
Human Connectome Project ◽  
Low Dimensional

Most previous work on dynamic functional connectivity (dFC) has focused on analyzing temporal traits of functional connectivity (similar coupling patterns at different timepoints), dividing them into functional connectivity states and detecting their between-group differences. However, the coherent functional connectivity of brain activity among the temporal dynamics of functional connectivity remains unknown. In the study, we applied manifold learning of local linear embedding to explore the consistent coupling patterns (CCPs) that reflect functionally homogeneous regions underlying dFC throughout the entire scanning period. By embedding the whole-brain functional connectivity in a low-dimensional manifold space based on the Human Connectome Project (HCP) resting-state data, we identified ten stable patterns of functional coupling across regions that underpin the temporal evolution of dFC. Moreover, some of these CCPs exhibited significant neurophysiological meaning. Furthermore, we apply this method to HCP rsfMR and tfMRI data as well as sleep-deprivation data and found that the topological organization of these low-dimensional structures has high potential for predicting sleep-deprivation states (classification accuracy of 92.3%) and task types (100% identification for all seven tasks).In summary, this work provides a methodology for distilling coherent low-dimensional functional connectivity structures in complex brain dynamics that play an important role in performing tasks or characterizing specific states of the brain.

Impact of 36 h of total sleep deprivation on resting-state dynamic functional connectivity

2018 ◽  
Vol 1688 ◽  
pp. 22-32 ◽  
Author(s):  
Huaze Xu ◽  
Hui Shen ◽  
Lubin Wang ◽  
Qi Zhong ◽  
Yu Lei ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Sleep Deprivation ◽  
Resting State ◽  
Dynamic Functional Connectivity ◽  
Total Sleep Deprivation ◽  
State Dynamic

scholarly journals Age-related abnormalities of thalamic shape and dynamic functional connectivity after three hours of sleep restriction

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10751
Author(s):  
Zhiliang Long ◽  
Jia Zhao ◽  
Danni Chen ◽  
Xu Lei
Keyword(s):  
Young Adults ◽  
Functional Connectivity ◽  
Sleep Deprivation ◽  
Parietal Cortex ◽  
Shape Analysis ◽  
Sleep Restriction ◽  
Dynamic Functional Connectivity ◽  
Age Related ◽  
Superior Parietal Cortex ◽  
Left Thalamus

Background Previous neuroimaging studies have detected abnormal activation and intrinsic functional connectivity of the thalamus after total sleep deprivation. However, very few studies have investigated age-related changes in the dynamic functional connectivity of the thalamus and the abnormalities in the thalamic shape following partial sleep deprivation. Methods Fifty-five participants consisting of 23 old adults (mean age: 68.8 years) and 32 young adults (mean age: 23.5 years) were included in current study. A vertex-based shape analysis and a dynamic functional connectivity analysis were used to evaluate the age-dependent structural and functional abnormalities after three hours of sleep restriction. Results Shape analysis revealed the significant main effect of deprivation with local atrophy in the left thalamus. In addition, we observed a significant age deprivation interaction effect with reduced variability of functional connectivity between the left thalamus and the left superior parietal cortex following sleep restriction. This reduction was found only in young adults. Moreover, a significantly negative linear correlation was observed between the insomnia severity index and the changes of variability (post-deprivation minus pre-deprivation) in the functional connectivity of the left thalamus with the left superior parietal cortex. Conclusions The results indicated that three hours of sleep restriction could affect both the thalamic structure and its functional dynamics. They also highlighted the role of age in studies of sleep deprivation.

scholarly journals Modular slowing of resting-state dynamic functional connectivity as a marker of cognitive dysfunction induced by sleep deprivation

NeuroImage ◽  
2020 ◽  
Vol 222 ◽  
pp. 117155 ◽  
Author(s):  
Diego Lombardo ◽  
Catherine Cassé-Perrot ◽  
Jean-Philippe Ranjeva ◽  
Arnaud Le Troter ◽  
Maxime Guye ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Sleep Deprivation ◽  
Cognitive Dysfunction ◽  
Resting State ◽  
Dynamic Functional Connectivity ◽  
State Dynamic

scholarly journals Modular slowing of resting-state dynamic Functional Connectivity as a marker of cognitive dysfunction induced by sleep deprivation

2020 ◽  
Author(s):  
Diego Lombardo ◽  
Catherine Cassé-Perrot ◽  
Jean-Philippe Ranjeva ◽  
Arnaud Le Troter ◽  
Maxime Guye ◽  
...  
Keyword(s):  
Random Walk ◽  
Functional Connectivity ◽  
Sleep Deprivation ◽  
Cognitive Performance ◽  
Cognitive Dysfunction ◽  
Resting State ◽  
List Type ◽  
Dynamic Functional Connectivity ◽  
Whole Brain ◽  
Brain Level

AbstractDynamic Functional Connectivity (dFC) in the resting state (rs) is considered as a correlate of cognitive processing. Describing dFC as a flow across morphing connectivity configurations, our notion of dFC speed quantifies the rate at which FC networks evolve in time. Here we probe the hypothesis that variations of rs dFC speed and cognitive performance are selectively interrelated within specific functional subnetworks.In particular, we focus on Sleep Deprivation (SD) as a reversible model of cognitive dysfunction. We found that whole-brain level (global) dFC speed significantly slows down after 24h of SD. However, the reduction in global dFC speed does not correlate with variations of cognitive performance in individual tasks, which are subtle and highly heterogeneous. On the contrary, we found strong correlations between performance variations in individual tasks –including Rapid Visual Processing (RVP, assessing sustained visual attention)– and dFC speed quantified at the level of functional subnetworks of interest. Providing a compromise between classic static FC (no time) and global dFC (no space), modular dFC speed analyses allow quantifying a different speed of dFC reconfiguration independently for sub-networks overseeing different tasks. Importantly, we found that RVP performance robustly correlates with the modular dFC speed of a characteristic frontoparietal module.HighlightsSleep Deprivation (SD) slows down the random walk in FC space implemented by Dynamic Functional Connectivity (dFC) at rest.Whole-brain level slowing of dFC speed does not selectively correlate with fine and taskspecific changes in performanceWe quantify dFC speed separately for different link-based modules coordinated by distinct regional “meta-hubs”Modular dFC speed variations capture subtle and task-specific variations of cognitive performance induced by SD.Author summaryWe interpreted dynamic Functional Connectivity (dFC) as a random walk in the space of possible FC networks performed with a quantifiable “speed”.Here, we analyze a fMRI dataset in which subjects are scanned and cognitively tested both before and after Sleep Deprivation (SD), used as a reversible model of cognitive dysfunction. While global dFC speed slows down after a sleepless night, it is not a sufficiently sensitive metric to correlate with fine and specific cognitive performance changes. To boost the capacity of dFC speed analyses to account for fine and specific cognitive decline, we introduce the notion of modular dFC speed. Capitalizing on an edge-centric measure of functional connectivity, which we call Meta-Connectivity, we isolate subgraphs of FC describing relatively independent random walks (dFC modules) and controlled by distinct “puppet masters” (meta-hubs). We then find that variations of the random walk speed of distinct dFC modules now selectively correlate with SD-induced variations of performance in the different tasks. This is in agreement with the fact that different subsystems – distributed but functionally distinct– oversee different tasks.The high sensitivity of modular dFC analyses bear promise of future applications to the early detection and longitudinal characterization of pathologies such as Alzheimer’s disease.

scholarly journals 0143 Vigilance Declines Following Sleep Deprivation are Associated with Two Previously Identified Dynamic Connectivity States

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A56-A57
Author(s):  
J Teng ◽  
J Ong ◽  
A Patanaik ◽  
J Zhou ◽  
M Chee ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Sleep Deprivation ◽  
Sustained Attention ◽  
Resting State ◽  
Resting State Fmri ◽  
Fmri Data ◽  
Dynamic Functional Connectivity ◽  
Arousal State ◽  
Total Sleep Deprivation ◽  
Dynamic Connectivity

Abstract Introduction Dynamic functional connectivity (DFC) analysis of resting-state fMRI data has been successfully used to track fluctuations in arousal in the human brain. Changes in DFC have also been reported with acute sleep deprivation. Here, we demonstrate that dynamic connectivity states (DCS) previously related to arousal are reproducible, and are associated with individual differences in sustained attention declines after one night of total sleep deprivation. Methods 32 participants underwent two counterbalanced resting-state fMRI scans: during rested wakefulness (RW) and following total sleep deprivation (SD). They also completed the Psychomotor Vigilance Test (PVT), a sustained attention task that is highly sensitive to the effects of sleep loss. SD vulnerability was computed as the decrease in response speed (∆RS) and increase in lapses (∆lapse) in SD compared with RW. Dynamic functional connectivity analysis was conducted on rs-fMRI data. Connectivity matrices were clustered to obtain 5 prototypical DCS. We calculated the proportion of time participants spent in each of these DCS, as well as how often participants transitioned between DCSs. Relationships between SD vulnerability and connectivity metrics were then correlated. Results We recovered two DCS that were highly similar (ρ = .89-.91) to arousal-related DCS observed in previous work (high arousal state (HAS); low arousal state (LAS)). After sleep deprivation, the proportion of time spent in the LAS increased significantly (t29=3.16, p=.0039), while there was no significant change in HAS (t29=-1.43, p=.16). We observed significantly more state transitions in RW compared with SD. Change in LAS and HAS across sleep conditions correlated significantly with SD vulnerability (ΔLASxΔRS: r=-0.64, p<.0001; ΔLASxΔlapse: r=0.43, p=.018; ΔHASxΔRS; r=0.43, p=.019; ΔHASxΔlapse; r=-0.39, p=.033). Finally, Δ%transitions was correlated with ΔRS but not Δlapse. Conclusion This study adds to the evidence that two specific reproducible DCS are robust markers of arousal and attention, and may be useful indicators of SD vulnerability. Support This work was supported by the National Medical Research Council, Singapore (STaR/0015/2013), and the National Research Foundation Science of Learning (NRF2016-SOL002-001).

scholarly journals Decreased Functional Connectivity Between the Right Precuneus and Middle Frontal Gyrus Is Related to Attentional Decline Following Acute Sleep Deprivation

2020 ◽  
Vol 14 ◽  
Author(s):  
Bozhi Li ◽  
Liwei Zhang ◽  
Ying Zhang ◽  
Yang Chen ◽  
Jiaxi Peng ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Sleep Deprivation ◽  
Resting State ◽  
Specific Effect ◽  
Region Of Interest ◽  
Brain Regions ◽  
Middle Frontal Gyrus ◽  
Acute Sleep Deprivation ◽  
The Right ◽  
The Relationship

ObjectivesAcute sleep deprivation (SD) seriously affects cognitive functions, such as attention, memory, and response inhibition. Previous neuroimaging studies have demonstrated a close relationship between the functional activities of the precuneus (PC) and the function of alert attention. However, the specific effect of the PC on attention decline after acute SD has not been elucidated. In this study, we used resting-state functional magnetic resonance imaging (fMRI) to study the relationship between the changes of the PC functional connectivity and alertness decline after total SD.MethodsThirty healthy, right-handed adult men participated in the experiment. Alert attention and functional connectivity were assessed by the Psychomotor Vigilance Test and a resting-state fMRI scan before and after total SD. The region of interest to region of interest (“ROI-to-ROI”) correlation was employed to analyze the relationship between the PC and other brain regions after acute SD.ResultsParticipants showed decreased alert attention after total SD. In addition, SD induced decreased functional connectivity between the right PC and the right middle frontal gyrus (MFG). Moreover, there was a significant correlation between the decreased PC functional connectivity and alertness decline after total SD.ConclusionOur findings suggest that the interruption of the connection between the right PC and the right MFG is related to the observed decline in alert attention after acute SD. These results provide evidence further elucidating the cognitive impairment model of SD.

scholarly journals Relation of Decreased Functional Connectivity Between Left Thalamus and Left Inferior Frontal Gyrus to Emotion Changes Following Acute Sleep Deprivation

2021 ◽  
Vol 12 ◽  
Author(s):  
Bo-zhi Li ◽  
Ya Cao ◽  
Ying Zhang ◽  
Yang Chen ◽  
Yu-hong Gao ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Sleep Deprivation ◽  
Inferior Frontal Gyrus ◽  
Brain Regions ◽  
Left Inferior Frontal Gyrus ◽  
Middle Temporal ◽  
Functional Connections ◽  
Left Thalamus ◽  
Acute Sleep Deprivation ◽  
Left Middle

Objective: The thalamus is a key node for sleep-wake pathway gate switching during acute sleep deprivation (ASD), and studies have shown that it plays a certain role in emotion changes. However, there are no studies on the association between the thalamus and emotion changes in ASD. In this study, we used resting-state functional magnetic resonance imaging (R-fMRI) to explore whether changes in the functional connections between the thalamus and other brain regions are related to emotion changes and further explored the function of the thalamus under total ASD conditions.Method: Thirty healthy, right-handed adult men underwent emotional assessment according to the Profile of Mood States Scale and R-fMRI scans before and after ASD. The correlations between changes in functional connectivity between the thalamus and other brain regions and emotion changes were then studied.Results: Positive emotions and psychomotor performance were reduced, and negative emotions were increased following ASD. The functional connections between the left thalamus and left middle temporal gyrus, left inferior frontal gyrus, right thalamus, right inferior temporal gyrus, left middle temporal pole gyrus, right calcarine, left cuneus, left rectus and left medial superior frontal gyrus were significantly altered. Decreased functional connectivity between left thalamus and left inferior frontal gyrus related to emotion changes following ASD.Conclusion: This study finds that functional changes in the thalamus are associated with emotion changes during ASD, suggesting that the left thalamus probably plays an essential role in emotion changes under ASD conditions.

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