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

Effects of one night of sleep deprivation on whole brain intrinsic connectivity distribution using a graph theory neuroimaging approach

Neuroimaging studies have revealed disturbances in brain functional connectivity (FC) after one night of sleep deprivation (SD). These researches explored the alterations of FC using classical regions of interest (ROI)-based analysis or functional connectivity density. However, these methods need for a priori information about the selected ROIs and a specific correlation threshold to define a connection between two ROIs or voxels, which may bring inconsistent results. In the present study, we adopted a data-driven, whole brain voxel-based graph-theoretical approach, intrinsic connectivity distribution (ICD) analysis, to examine changes of brain connectivity after SD in 52 normal young subjects without any prior knowledge. The cross-hemisphere ICD (ch-ICD) analysis was also performed to discover the effect of SD on cerebral lateralization. We found that sleep-deprived subjects showed significant reduced ICD in default mode network (DMN) and limbic network, and increased ICD in sensorimotor network. Furthermore, after SD, the ICD in the right precuneus showed significant correlation with psychomotor vigilance test (PVT) performance following the stepwise regression analysis after Bonferroni correction (ICD = 0.43 - 0.62∗10 % fast reaction time + 0.31∗the standard deviation of reaction time, p = 0.0012). Follow-up seed-based FC analyses in the right precuneus revealed decreased FC to regions in DMN, visual network, ventral attentional network and frontal-parietal network. Nevertheless, no striking difference of ch-ICD was found following SD. In conclusion, these findings suggested that DMN, especially precuneus may be hubs of FC disturbances associated with vigilance after SD, and may provide new insights into the intervention for SD.

Abnormal dynamic functional connectivity after sleep deprivation from temporal variability perspective

Sleep deprivation (SD) is very common in modern society and regarded as a potential causal mechanism of several clinical disorders. Previous neuroimaging studies have explored the neural mechanisms of SD using magnetic resonance imaging (MRI) from static (comparing two MRI sessions [one after SD and one after resting wakefulness]) and dynamic (using repeated MRI during one night of SD) perspectives. Recent SD researches have focused on the dynamic functional brain organization during the resting-state scan. Our present study adopted a novel metric (temporal variability), which has been successfully applied to many clinical diseases, to examine the dynamic functional connectivity after SD in 55 normal young subjects. We found that sleep-deprived subjects showed increased regional-level temporal variability in large-scale brain regions, and decreased regional-level temporal variability in several thalamus subregions. After SD, participants exhibited enhanced intra-network temporal variability in the default mode network (DMN) and increased inter-network temporal variability in numerous subnetwork pairs. Furthermore, we found that the inter-network temporal variability between visual network and DMN was negative related with the slowest 10% respond speed (β = -.42, p = 5.57 × 10^-4 ) of the psychomotor vigilance test after SD following the stepwise regression analysis. In conclusion, our findings suggested that sleep-deprived subjects showed abnormal dynamic brain functional configuration, which provides new insights into the neural underpinnings of SD and contributes to our understanding of the pathophysiology of clinical disorders.

Sleep Quality Modulates the Association between Dynamic Functional Network Connectivity and Cognitive Function in Healthy Older Adults

Aging is associated with changes in sleep, brain activity, and cognitive function, as well as the association among these factors; however, the precise nature of these changes has not been elucidated. This study systematically investigated the modulatory effect of sleep on the relationship between brain functional network connectivity (FNC) and cognitive function in older adults. In total, 107 community-dwelling healthy older adults were recruited and assigned into poor sleep and good sleep groups based on the Pittsburgh Sleep Quality Index. The static functional network connectivity (sFNC), the temporal variability of dynamic FNC (dFNC) from variance (dFNC-var), and the dFNC from clustering state (dFNC-state) were calculated. Corresponding cognition-predictive models were constructed for each sleep group. dFNC but not sFNC, was able to significantly predict the cognitive function in older adults. Specifically, sleep played a modulatory role in the association between dFNC and cognitive function, with sleep-specific variations at both microscopic (i.e., specific edges) and macroscopic levels (i.e., specific states) of dFNC.

Altered functional connectivity strength in chronic insomnia associated with gut microbiota composition and sleep efficiency

BACKGROUND

There is limited evidence on the link between gut microbiota (GM) and resting-state brain activity in patients with chronic insomnia (CI). This study aimed to explore the alterations in brain functional connectivity strength (FCS) in CI and the potential associations among altered FCS, GM composition, and neuropsychological performance indicators.

MATERIALS AND METHODS

Thirty CI patients and 34 age- and gender-matched healthy controls (HCs) were recruited. Each participant underwent resting-state functional magnetic resonance imaging (rs-fMRI) for the evaluation of brain FCS and was administered sleep-, mood-, and cognitive-related questionnaires for the evaluation of neuropsychological performance. Stool samples of CI patients were collected and subjected to 16S rDNA amplicon sequencing to assess the relative abundance (RA) of GM. Redundancy analysis or canonical correspondence analysis (RDA or CCA, respectively) was used to investigate the relationships between GM composition and neuropsychological performance indicators. Spearman correlation was further performed to analyze the associations among alterations in FCS, GM composition, and neuropsychological performance indicators.

RESULTS

The CI group showed a reduction in FCS in the left superior parietal gyrus (SPG) compared to the HC group. The correlation analysis showed that the FCS in the left SPG was correlated with sleep efficiency and some specific bacterial genera. The results of CCA and RDA showed that 38.21% (RDA) and 24.62% (CCA) of the GM composition variation could be interpreted by neuropsychological performance indicators. Furthermore, we found complex relationships between Alloprevotella, specific members of the family Lachnospiraceae, Faecalicoccus, and the FCS alteration, and neuropsychological performance indicators.

CONCLUSION

The brain FCS alteration of patients with CI was related to their GM composition and neuropsychological performance indicators, and there was also an association to some extent between the latter two, suggesting a specific interaction pattern among the three aspects: brain FCS alteration, GM composition, and neuropsychological performance indicators.

Alterations of Subcortical Brain Structures in Paradoxical and Psychophysiological Insomnia Disorder

Insomnia disorder (ID) is a common illness associated with mood and cognitive impairments. Subtyping ID is an ongoing debate in sleep medicine, but the underlying mechanisms of each subtype is poorly understood. Growing evidence suggests that subcortical brain structures play the key roles in pathophysiology of ID and its subtypes. Here, we aimed to investigate structural alteration of subcortical regions in patients with two common ID subtypes i.e., paradoxical and psychophysiological insomnia. Fifty-five patients and 49 healthy controls were recruited for this study and T1-weighted images and subjective and objective sleep parameters (i.e., Pittsburgh Sleep Quality Index and polysomnography) were collected from participants. Subcortical structures including the hippocampus, amygdala, caudate, putamen, globus pallidus, nucleus accumbens, and thalamus were automatically segmented in FSL. Volume and shape (using surface vertices) of each structure were compared between the groups, controlled for covariates, and corrected for multiple comparisons. In addition, correlations of sleep parameters and surface vertices or volumes were calculated. The caudate's volume was smaller in patients than controls. Compared with controls, we found regional shrinkage in the caudate, nucleus accumbens, posterior putamen, hippocampus, thalamus, and amygdala in paradoxical insomnia and shrinkage in the amygdala, caudate, hippocampus, and putamen in psychophysiological insomnia. Interestingly, comparing two patients groups, shape alteration in the caudate, putamen, and nucleus accumbens in paradoxical insomnia and shrinkage in the thalamus, amygdala, and hippocampus in psychophysiological insomnia were observed. Both subjective and objective sleep parameters were associated with these regional shape alterations in patients. Our results support the differential role of subcortical brain structures in pathophysiology of paradoxical and psychophysiological insomnia.