White Matter Microstructural Properties are Related to Inter-Individual Differences in Cognitive Instability after Sleep Deprivation

Locus coeruleus microstructural integrity is associated with vigilance vulnerability to sleep deprivation

Insufficient sleep compromises cognitive performance, diminishes vigilance, and disrupts daily functioning in hundreds of millions of people worldwide. Despite extensive research revealing significant variability in vigilance vulnerability to sleep deprivation, the underlying mechanisms of these individual differences remain elusive. Locus coeruleus (LC) plays a crucial role in the regulation of sleep-wake cycles and has emerged as a potential marker for vigilance vulnerability to sleep deprivation. In this study, we investigate whether LC microstructural integrity, assessed by fractional anisotropy (FA) through diffusion tensor imaging (DTI) at baseline before sleep deprivation, can predict impaired psychomotor vigilance test (PVT) performance during sleep deprivation in a cohort of 60 healthy individuals subjected to a rigorously controlled in-laboratory sleep study. The findings indicate that individuals with high LC FA experience less vigilance impairment from sleep deprivation compared with those with low LC FA. LC FA accounts for 10.8% of the variance in sleep-deprived PVT lapses. Importantly, the relationship between LC FA and impaired PVT performance during sleep deprivation is anatomically specific, suggesting that LC microstructural integrity may serve as a biomarker for vigilance vulnerability to sleep loss.

White matter structural topologic efficiency predicts individual resistance to sleep deprivation

BACKGROUND

Sleep deprivation (SD) is commonplace in modern society and there are large individual differences in the vulnerability to SD. We aim to identify the structural network differences based on diffusion tensor imaging (DTI) that contribute to the individual different vulnerability to SD.

METHODS

The number of psychomotor vigilance task (PVT) lapses was used to classify 49 healthy subjects on the basis of whether they were vulnerable or resistant to SD. DTI and graph theory approaches were used to investigate the topologic organization differences of the brain structural connectome between SD-vulnerable and -resistant individuals. We measured the level of global efficiency and clustering in rich club and non-rich club organizations.

RESULTS

We demonstrated that participants vulnerable to SD had less global efficiency, network strength, and local efficiency but longer shortest path length compared with participants resistant to SD. Lower efficiency was mainly distributed in the right insula, bilateral thalamus, bilateral frontal, temporal, and temporal lobes. Furthermore, a disrupted subnetwork was observed that consisted of widespread connections. Moreover, the vulnerable group showed significantly decreased strength of the rich club compared with the resistant group. The strength of rich club connectivity was found to be correlated negatively with PVT performance (r = -0.395, p = 0.005). We further tested the reliability of the results.

CONCLUSION

The findings revealed that individual differences in resistance to SD are related to disrupted topologic efficiency connectome pattern, and our study may provide potential connectome-based biomarkers for the early detection of the vulnerable degree to SD.

Transcutaneous auricular vagus stimulation (taVNS) improves human working memory performance under sleep deprivation stress

Many human activities require high cognitive performance over long periods, while impairments induced by sleep deprivation influence various aspects of cognitive abilities, including working memory (WM), attention, and processing speed. Based on previous research, vagal nerve stimulation can modulate cognitive abilities, attention, and arousal. Two experiments were conducted to assess the efficacy of transcutaneous auricular vagus nerve stimulation (taVNS) to relieve the deleterious effects of sleep deprivation. In the first experiment, 35 participants completed N-back tasks at 8:00 a.m. for two consecutive days in a within-subject study. Then, the participants received either taVNS or earlobe stimulation (active control) intervention in two sessions at random orders after 24 h of sustained wakefulness. Then, they completed the N-back tasks again. In the second experiment, 30 participants completed the psychomotor vigilance task (PVT), and 32 completed the N-back tasks at 8:00 a.m. on the first and second days. Then, they received either taVNS or earlobe stimulation at random orders and finished the N-back and PVT tasks immediately after one hour. In Experiment 1, taVNS could significantly improve the accuracy rate of participants in spatial 3-back tasks compared to active control, which was consistent with experiment 2. However, taVNS did not specifically enhance PVT performance. Therefore, taVNS could be a powerful intervention for acute sleep deprivation as it can improve performance on high cognitive load tasks and is easy to administer.

Functional Connectivity of White Matter and Its Association with Sleep Quality

Purpose

Functional magnetic resonance imaging (fMRI) has been widely adopted to investigate the neural activity in gray matter (GM) in the field of sleep research, but the neural activity in white matter (WM) has received much less attention. The current study set out to test our hypothesis that WM functional abnormality is associated with poor sleep quality.

Participants and Methods

K-means clustering analysis was performed on 78 healthy adults drawn from the Human Connectome Project dataset to extract stable WM functional networks (WM-FNs) and GM-FNs. The differences in functional connectivity within WM-FNs and between WM- and GM-FNs, as well as the power spectrum between good sleep quality group (Pittsburgh Sleep Quality Index (PSQI) <6, daytime dysfunction = 0) and poor sleep quality group (PSQI >6, daytime dysfunction >0) were examined between groups with good and poor sleep quality. Additionally, linear relationships between sleep quality and altered functional characteristics of WM-FNs were evaluated.

Results

Functional connectivity between middle and superficial WM-FNs, short- and long-range functional connectivity between WM- and GM-FNs were decreased in poor sleepers and negatively correlated with PSQI score. The mean amplitudes of right sensorimotor WM networks at whole, high and low frequency bands were higher in poor sleepers and were positively correlated with PSQI score.

Conclusion

WM functional abnormality is associated with poor sleep quality. The neurobiological mechanisms that underlie the functional alterations of WM-FNs in poor sleepers need to be investigated in future studies.

Altered isotropic volume fraction in gray matter after sleep deprivation and its association with visuospatial memory: A neurite orientation dispersion and density imaging study

Background and aims

Diffusion magnetic resonance imaging (dMRI) studies have revealed microstructural abnormalities in white matter resulting from sleep deprivation (SD). This study aimed to adopt neurite orientation dispersion and density imaging (NODDI) to investigate the effect of SD on gray matter (GM) microstructural properties and its association to visuospatial memory (VSM).

Methods

Twenty-four healthy women underwent two sessions of dMRI scanning and visuospatial ability assessment by Complex Figure Test (CFT), once during rested wakefulness (RW) and once after 24 h of SD. We calculated NODDI metrics, including intracellular volume fraction (ICVF), orientation dispersion index (ODI), and isotropic volume fraction (ISO). Differences in NODDI-related metrics between RW and SD were determined using a voxel-wise paired t-test. We identified an association between NODDI metrics and CFT results using Spearman's correlation coefficient.

Results

Sleep deprivation worsened subjects' performance in the delayed-CFT trial. We observed no significant difference in ICVF and ODI between RW and SD. After SD, subjects showed decreases in ISO, primarily in the prefrontal cortex and temporal lobe, while exhibiting ISO increases in the anterior and posterior cerebellar lobe and cerebellar vermis. Furthermore, ISO change in the left superior, middle and inferior frontal gyrus was significantly correlated with completion time change in delayed-CFT trial performance.

Conclusion

Our results suggested that SD hardly affected the density and spatial organization of neurites in GM, but the extra-neurite water molecule diffusion process was affected (perhaps resulting from neuroinflammation), which contributed to VSM dysfunction.

Impact of spaceflight stressors on behavior and cognition: A molecular, neurochemical, and neurobiological perspective

The response of the human body to multiple spaceflight stressors is complex, but mounting evidence implicate risks to CNS functionality as significant, able to threaten metrics of mission success and longer-term behavioral and neurocognitive health. Prolonged exposure to microgravity, sleep disruption, social isolation, fluid shifts, and ionizing radiation have been shown to disrupt mechanisms of homeostasis and neurobiological well-being. The overarching goal of this review is to document the existing evidence of how the major spaceflight stressors, including radiation, microgravity, isolation/confinement, and sleep deprivation, alone or in combination alter molecular, neurochemical, neurobiological, and plasma metabolite/lipid signatures that may be linked to operationally-relevant behavioral and cognitive performance. While certain brain region-specific and/or systemic alterations titrated in part with neurobiological outcome, variations across model systems, study design, and the conspicuous absence of targeted studies implementing combinations of spaceflight stressors, confounded the identification of specific signatures having direct relevance to human activities in space. Summaries are provided for formulating new research directives and more predictive readouts of portending change in neurobiological function.

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.

Brain Structure Alterations in Hemifacial Spasm: A Diffusion Tensor Imaging Study

This study examined white matter integrity in patients with left-sided hemifacial spasm (HFS) using diffusion tensor imaging (DTI). Thirty-six patients with left-sided HFS (mean age 53.24 ± 8.16 years) and 36 healthy volunteers (mean age 53.92 ± 7.73 years) were recruited. Tract-based spatial statistics (TBSS) analysis revealed significantly increased fractional anisotropy (FA) of bilateral superior longitudinal fasciculus in HFS patients (P < 0.05, family-wise error corrected), with trends for radial diffusivity to decrease. We inferred that the results may be associated with poor sleep quality, impairment in visuospatial construction, and activity-dependent increases in myelination in HFS patients. Furthermore, the FA value of left superior longitudinal fasciculus showed a positive correlation with HFS duration (r = 0.352, P = .041) and spasm severity (r = 0.416, P = .014). However, the alteration of medial diffusivity and axial diffusivity were not found in bilateral superior longitudinal fasciculus between groups. These findings suggest FA changes of superior longitudinal fasciculus reflected by TBSS analysis may provide valuable insights into the diagnosis of HFS.

Nighttime Sleep Characteristics and White Matter Integrity in Young Adults

PURPOSE

Sleep is essential for life and plays a key role for optimal physiology, brain functioning, and health. Evidence suggests a relation between sleep and cerebral white matter integrity. Human studies report that sleep duration shows a U-shaped association with brain functioning. We hypothesized that participants with longer or shorter sleep time in the nighttime period show altered microstructural white matter integrity.

PARTICIPANTS AND METHODS

Seventy-three young adult participants were evaluated. Sleep-wake cycle parameters were assessed objectively using actigraphy. Diffusion tensor imaging studies were performed to assess white matter integrity using fractional anisotropy and mean, axial, and radial diffusivities. Relations between white matter microstructure indexes and sleep parameters were investigated through tract-based spatial statistics. Participants were grouped according to their nocturnal total sleep time: 27 in the Reference sleep group (6.5-8.0 h), 23 in the Short sleep group (<6.5 h) and 23 in the Long sleep group (>8.0 h).

RESULTS

Compared with the Reference sleep group, participants in the Long sleep group showed lower fractional anisotropy (p < 0.05) and higher radial diffusivity (p < 0.05) values in white matter tracts linked to sleep regulation (corona radiata, body of the corpus callosum, superior longitudinal fasciculus, and anterior thalamic radiation).

CONCLUSION

This pattern of reduced fractional anisotropy and increased radial diffusivity in the Long sleep group indicates an association between sleep duration and lower integrity of myelin sheaths. Because myelin is continuously remodeled in the brain, nighttime sleep characteristics appear to be a key player for its quality and maintenance.

Classifying Vulnerability to Sleep Deprivation Using Resting-State Functional MRI Graph Theory Metrics

Sleep deprivation (SD) has become very common in contemporary society, where people work around the clock. SD-induced cognitive deficits show large inter-individual differences and are trait-like with known neural correlates. However, few studies have used neuroimaging to predict vulnerability to SD. Here, resting state functional magnetic resonance imaging (fMRI) data and psychomotor vigilance task (PVT) data were collected from 60 healthy subjects after resting wakefulness and after one night of SD. The number of PVT lapses was then used to classify participants on the basis of whether they were vulnerable or resilient to SD. We explored the viability of graph-theory-based degree centrality to accurately classify vulnerability to SD. Compared with during resting wakefulness, widespread changes in degree centrality (DC) were found after SD, indicating significant reorganization of sleep homeostasis with respect to activity in resting state brain network architecture. Support vector machine (SVM) analysis using leave-one-out cross-validation achieved a correct classification rate of 84.75% [sensitivity 82.76%, specificity 86.67%, and area under the receiver operating characteristic curve (AUC) 0.94] for differentiating vulnerable subjects from resilient subjects. Brain areas that contributed most to the classification model were mainly located within the sensorimotor network, default mode network, and thalamus. Furthermore, we found a significantly negative correlation between changes in PVT lapses and DC in the thalamus after SD. These findings suggest that resting-state network measures combined with a machine learning algorithm could have broad potential applications in screening vulnerability to SD.

Gradually Increased Interhemispheric Functional Connectivity During One Night of Sleep Deprivation

BACKGROUND

It is well known that circadian rhythms and sleep homeostasis contribute to a pronounced trough in sleepiness and behavioral performance at night. However, the underlying neuroimaging mechanisms remain unclear. How brain-function connectivity is modulated during sleep deprivation (SD) has been rarely examined.

METHODS

By increasing the number of scanning sessions during SD, the current study used voxel-mirrored homotopic connectivity (VMHC) to investigate dynamic changes in interhemispheric communication during one night of SD. Every 2 hours from 10 pm to 06 am (session 1, 10 pm; session 2, 12 am; session 3, 2 am; session 4, 4 am; session 5, 6 am), functional magnetic resonance-imaging data and Stanford Sleepiness Scale (SSS) scores were collected from 36 healthy participants with intermediate chronotype. Dynamic changes in SSS scores and VMHC were determined using one-way repeated-measure ANOVA with the false discovery-rate method to correct for multiple comparisons.

RESULTS

Significant time effects for VMHC were found mainly in the bilateral thalamus, bilateral superior temporal gyrus, and bilateral precentral gyrus. SSS scores and VMHC in these areas were both found to be monotonously increased during SD. Furthermore, significant positive associations were found between SSS valu and VMHC values in the left superior temporal and right superior gyri.

CONCLUSION

These findings might represent the dynamic modulation of circadian rhythm merely or the interaction effects of both circadian rhythm and sleep homeostasis on interhemispheric connectivity within the thalamus, default-mode network, and sensorimotor network. Our study provides more comprehensive information on how SD regulates brain connectivity between hemispheres and adds new evidence of neuroimaging correlates of increased sleepiness after SD.

Disrupted structural covariance network in first episode schizophrenia patients: Evidence from a large sample MRI-based morphometric study

BACKGROUND

Recent progress in neuroscience research has provided evidence that schizophrenia is a disease that involves dysconnectivity of brain networks. Widespread gray matter loss was commonly observed but how these gray matter abnormalities are characterized at the large-scale network-level in schizophrenia, especially patients with first-episode (FE-SCZ) remains unclear.

METHODS

In this study, gray matter structural network aberrations were investigated by applying structural covariance network analysis to 193 first episode schizophrenia patients and 178 age and gender-matched healthy controls (HCs). The mean gray matter volume in seed regions relating to eight specific networks (visual, auditory, sensorimotor, speech, semantic, default-mode, executive control, and salience) were extracted, and voxel-wise analyses of covariance were conducted to compare the association between whole-brain gray matter volume and each seed region for FE-SCZ and HCs.

RESULTS

The auditory network was less extended in FE-SCZ compared with HCs, with a significant decrease in the structural association between the Hesch's gyrus and the middle frontal gyrus and the superior frontal gyrus. Hyperconnectivity was observed in executive control network with a significant increase in the structural association between the dorsal lateral prefrontal cortex and the superior frontal gyrus and supplementary motor area.

CONCLUSION

Our research shows that seed based structural covariance analysis can well characterize multiple large-scale networks, the observed changes might underly the hallucinations and cognitive impairments observed in FE-SCZ. Given that these patients were experiencing their first episode of schizophrenia, our findings suggest that such structural network deficits are present at an early stage in this disorder.

Sleep deprivation and its association with diseases- a review

Sleep deprivation, a consequence of multiple health problems or a cause of many major health risks, is a significant public health concern in this era. In the recent years, numerous reports have been added to the literature to provide explanation and to answer previously unanswered questions on this important topic but comprehensive updates and reviews in this aspect remain scarce. The present study identified 135 papers that investigated the association between sleep deprivation and health risks, including cardiovascular, respiratory, neurological, gastrointestinal, immunology, dermatology, endocrine, and reproductive health. In this review, we aimed to provide insight into the association between sleep deprivation and the development of diseases. We reviewed the latest updates available in the literature and particular attention was paid to reports that detailed all possible causal relationships involving both extrinsic and intrinsic factors that may be relevant to this topic. Various mechanisms by which sleep deprivation may affect health were presented and discussed, and this review hopes to serve as a platform for ideas generation for future research.

Alteration of Brain Gray Matter Density After 24 h of Sleep Deprivation in Healthy Adults

It has been reported that one night of acute sleep deprivation (SD) could induce brain structural changes at the synaptic and neuronal levels in animal studies, and could lead to white matter microstructure and cortical thickness change in human neuroimaging studies. In this study, we focused on changes of brain gray matter density (GMD) after one night of acute SD, which has not been explored previously. Twenty-three normal young participants completed the experiment. Each participant underwent twice T1-weighted structural image scanning with one at 08:00 after normal sleep [resting wakeful (RW)] and the other at 08:00 after 24 h of SD. Using voxel-based morphometry (VBM) analysis by FSL-VBM software, we compared GMD between RW and SD. In addition, the gray matter volume (GMV) and cortical thickness (CT) were also calculated based on volumetric and surface measures with FreeSurfer software. The psychomotor vigilance test (PVT) and the Karolinska Sleepiness Scale (KSS) were performed and evaluated for correlation analysis with GMD, GMV, and CT of the significant regions. Our results showed that the GMD in the right frontal pole (FP), right superior frontal gyrus (SFG), and right middle frontal gyrus significantly increased and GMV and CT in the right temporal pole (TP) significantly decreased after 24 h of acute SD. SD-induced changes in GMD in the right middle frontal gyrus were positively correlated with the changes of KSS scores (Spearman’s correlation r = 0.625, p = 0.0014, Bonferroni correction with p < 0.05/25). Taken together, our findings suggested that one night of acute SD could induce substantial brain structure changes and the alterations in GMD in the right middle frontal gyrus (MFG) might be implicated in sleepiness after SD.

Gray matter volume changes following antipsychotic therapy in first-episode schizophrenia patients: A longitudinal voxel-based morphometric study

Despite evidence of structural brain abnormalities in schizophrenia, the current study aimed to explore the effects of antipsychotic treatment on gray matter (GM) volume using structural magnetic resonance imaging (MRI) and investigate the relationship between brain structure and treatment response. The GM volumes of 33 patients with first-episode schizophrenia were calculated with voxel-based morphometry (VBM), with 33 matched healthy controls. Longitudinal volume changes within subjects after 4-month antipsychotic treatment were also evaluated. Correlation between volumetric changes and clinical symptoms derived from the Positive and Negative Syndrome Scale (PANSS) were further investigated. Compared with healthy controls, decreased GM volumes in the frontal gyrus were observed in schizophrenia patients. After 4-month treatment, patients showed significantly decreased GM volume primarily in the bilateral frontal, temporal and left parietal brain regions. In addition, the GM volume changes of the left postcentral gyrus was positively correlated with negative symptoms improvement, and the correlation analysis revealed the total PANSS scores changes were associated with GM volume changes in the right inferior frontal gyrus and the right superior temporal gyrus. Besides, non-responders had reduced GM volume in the bilateral middle frontal gyrus and the right superior frontal gyrus compared with responders and healthy controls. Our results suggest that the abnormality in the right frontal gyrus exists in the early stage of schizophrenia. Moreover, the relationship between antipsychotics and structural changes was identified. The GM volume might have the potential to reflect the symptom improvement in schizophrenia patients. And MRI may assist in predicting the antipsychotic treatment response in first-episode schizophrenia patients.

Voxel-based morphometry results in first-episode schizophrenia: a comparison of publicly available software packages

Investigations of brain structure in schizophrenia using magnetic resonance imaging (MRI) have identified variations in regional grey matter (GM) volume throughout the brain but the results are mixed. This study aims to investigate whether the inconsistent voxel-based morphometry (VBM) findings in schizophrenia are due to the use of different software packages. T1 MRI images were obtained from 86 first-episode schizophrenia (FESZ) patients and 86 age- and gender-matched Healthy controls (HCs). VBM analysis was carried out using FMRIB software library (FSL) 5.0 and statistical parametric mapping 8 (SPM8). All images were processed using the default parameter settings as provided by these software packages. FSL-VBM revealed widespread GM volume reductions in FESZ patients compared with HCs, however, for SPM-VBM, only increased and circumscribed GM volume changes were found, both software revealed increased GM volume within cerebellum. Significant correlations between Positive and Negative Syndrome Scale (PANSS) and GM volume were mainly found in frontal regions. Algorithms of GM tissue segmentation, image registration and statistical strategies might contribute to these disparate results.

How a Good Sleep Predicts Life Satisfaction: The Role of Zero-Sum Beliefs About Happiness

Sleep, although a vital aspect of human functioning, has received scant attention in happiness research. This research examines the effect of sleep quality on life satisfaction, and one possible mechanism that bridges the two. One cognitive factor that might tie the relationship between sleep and life satisfaction is a belief about the (in) finite nature of happiness (zero-sum belief about happiness; ZBH), a mindset that occurs more under conditions of scarcity. Given the interconnections among experiences prompted by various types of scarcity (e.g., financial and calorie), we predicted that deprived cognitive resource caused by poor sleep may activate the ZBH, thereby hurting one's life satisfaction. As expected, we found that sleep quality predicted the participants' life satisfaction, even controlling for baseline variables. More importantly, this relationship was partially mediated by ZBH. This study opens interesting questions on a relatively unexamined role of non-social predictors, such as sleep, in well-being.