Effects of transcranial direct current stimulation on performance and recovery sleep during acute sleep deprivation: a pilot study

Pre-treatment subjective sleep quality as a predictive biomarker of tDCS effects in preclinical Alzheimer's disease patients: Secondary analysis of a randomised clinical trial

BACKGROUND

Despite transcranial direct current stimulation (tDCS) has demonstrated encouraging potential for modulating the circadian rhythm, little is known about how well and sustainably tDCS might improve the subjective sleep quality in older adults. This study sought to determine how tDCS affected sleep quality and cognition, as well as how well pre-treatment sleep quality predicted tDCS effects on domain-specific cognitive functions in patients with mild neurocognitive disorder due to Alzheimer's disease (NCD-AD).

METHODS

This clinical trial aimed to compare the effectiveness of tDCS and cognitive training in mild NCD-AD patients (n =  201). Over the course of four weeks, patients were randomized to receive either tDCS plus working memory training, or sham tDCS plus working memory training, or tDCS plus controlled cognitive training. The Pittsburgh Sleep Quality Index (PSQI) was used to measured subjective sleep quality. The Alzheimer's disease assessment scale-cognitive subscale (ADAS-Cog) was used to evaluate domain-specific cognitive functions.

RESULTS

Recurrent tDCS treatments enhanced subjective sleep quality and cognition considerably. The poor sleepers (i.e., PSQI >  5) who received tDCS treatment had more cognitive benefits (p =  0.031, Cohen's d =  0.605) and sleep improvements (p <  0.001, Cohen's d =  1.209) in comparison to cognitive training. Pre-treatment subjective sleep quality was linked to tDCS-induced improvement in memory function.

CONCLUSION

During the course of two months, repeated tDCS could considerably enhance subjective sleep quality. For the cognitive benefits of the treatments, the status of pre-treatment subjective sleep quality is crucial. More thorough research is necessary to explore an efficient approach to managing comorbidities for preclinical AD patients.

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.

Sleep deprivation-induced memory impairment: exploring potential interventions

Sleep's crucial role in memory consolidation is well-established, with neuroimaging and sleep stage analysis revealing the intricate processes involved. Sleep deprivation significantly impairs memory performance and the ability to form new memories, highlighting the need for effective countermeasures. This article concludes that while sleep deprivation significantly impairs memory, the emerging insights into the gut-brain axis offer a promising frontier for developing novel interventions that can mitigate these effects. The review discusses various interventions, ranging from pharmaceutical compounds like donepezil, memantine, and tolcapone, to innovative physical therapy techniques such as transcranial magnetic stimulation (TMS), deep brain stimulation (DBS), and transcranial direct current stimulation (tDCS). Additionally, the emerging role of the gut-brain axis in sleep deprivation-induced memory impairment is examined, shedding light on the complex interplay between gut microbiota and cognitive functions. This comprehensive review explores the multifaceted relationship between sleep deprivation and memory impairment, delving into the neurobiological mechanisms underlying these processes and examining potential interventions.

The Use of Cognitive Paired Associative Stimulation (C-PAS) in Investigating and Remediating the Effects of Sleep Deprivation on Working Memory in Humans: The Importance of State-Dependency

Purpose of Review

Sleep deprivation is a global health issue, and the resultant cognitive deficits can be debilitating. A series of studies reported success with individually neuronavigated transcranial magnetic stimulation (TMS), coupled with online task performance, in substantially reducing performance deficits in working memory in healthy adults caused by 2 days of total sleep depression. This paradigm of coupling TMS with online task performance has been referred to as Cognitive Paired Associative Stimulation (C-PAS). This review describes those studies and the research since using various TMS paradigms to remediate working memory deficits in sleep deprivation.

Recent Findings

Three such studies were found, but none replicated the earlier findings. However, in each case, there were differences in study design that might explain the negative findings and inform future methodological choices and to underline the need to combine TMS with brain imaging guidance.

Summary

Online task performance during TMS, as done in the C-PAS paradigm, appears to be essential to demonstrating lasting remediation of working memory deficits induced by sleep deprivation. This observation highlights the importance of state-dependency in determining the effects of TMS. Further work needs to be done to clarify the potential role of C-PAS in alleviating the effects of sleep deprivation and studying cognitive processes affected by sleep.

Single sessions of transcranial direct current stimulation and transcranial random noise stimulation exert no effect on sleepiness in patients with narcolepsy and idiopathic hypersomnia

Background

Hypersomnia poses major challenges to treatment providers given the limitations of available treatment options. In this context, the application of non-invasive brain stimulation techniques such as transcranial electrical stimulation (tES) may open up new avenues to effective treatment. Preliminary evidence suggests both acute and longer-lasting positive effects of transcranial direct current stimulation (tDCS) on vigilance and sleepiness in hypersomniac patients. Based on these findings, the present study sought to investigate short-term effects of single sessions of tDCS and transcranial random noise stimulation (tRNS) on sleepiness in persons suffering from hypersomnia.

Methods

A sample of 29 patients suffering from narcolepsy or idiopathic hypersomnia (IH) was recruited from the Regensburg Sleep Disorder Center and underwent single sessions of tES (anodal tDCS, tRNS, sham) over the left and right dorsolateral prefrontal cortex on three consecutive days in a double-blind, sham-controlled, pseudorandomized crossover trial. The primary study endpoint was the mean reaction time measured by the Psychomotor Vigilance Task (PVT) before and directly after the daily tES sessions. Secondary endpoints were additional PVT outcome metrics as well as subjective outcome parameters (e.g., Karolinska Sleepiness Scale; KSS).

Results

There were no significant treatment effects neither on objective (i.e., PVT) nor on subjective indicators of sleepiness.

Conclusion

We could not demonstrate any clinically relevant effects of single sessions of tDCS or tRNS on objective or subjective measures of sleepiness in patients with hypersomnia. However, we cannot exclude that repeated sessions of tES may affect vigilance or sleepiness in hypersomniac patients.

Altered functional connectivity after acute sleep deprivation reveals potential locations for noninvasive brain stimulation techniques

BACKGROUNDS

Non-invasive brain stimulation (NIBS) techniques are emerging as efficacious treatments for sleep deprivation (SD). However, the stimulation location of NIBS (e.g. transcranial magnetic stimulation and transcranial direct current stimulation) on intervening acute SD is limited in previous studies. In this study, we aimed to investigate potentially effective targets of NIBS on intervening acute SD.

METHODS

We firstly performed a meta-analysis of 95 functional magnetic resonance imaging studies to find SD-related brain regions as regions of interest (ROI). Subsequently, we used resting-state functional connectivity analysis in 32 young individuals suffering from 24 h SD to identify brain surface regions associated with the ROIs. Finally, we applied 10-20 system coordinates to locate scalp sites for NIBS corresponding to the brain surface regions.

RESULTS

We identified the bilateral dorsolateral prefrontal cortex, bilateral inferior frontal gyrus, left supplementary motor area, precentral, right precuneus, bilateral inferior parietal gyrus, right middle temporal gyrus, and superior frontal gyrus as potential targets of NIBS for intervening SD. The 10-20 system coordinates corresponding to these brain surface regions were identified as potential sites for NIBS.

CONCLUSIONS

In conclusion, we identified several potential targets which could provide alternative stimulation locations for the use of NIBS on young patients suffering from acute SD.

Lack of correlation between hippocampal substructure atrophy and attention dysfunction in deficit schizophrenia

Hippocampal abnormalities are an established finding in the neuroimaging study of schizophrenia. However, no studies have examined the possibility of regional hippocampal abnormalities specific to deficit schizophrenia (DS) and associations with the unique symptoms of this schizophrenia subtype. This study compared 33 DS and 39 non-deficit schizophrenia (NDS) patients and 38 healthy subjects for hippocampal subfield volumetry. Clinical symptoms were assessed by PANSS, cognition by the neurocognitive battery on the day of the MRI scan. The automatic hippocampal segmentation were preprocesses use FreeSurfer 7.2.0. Unfortunately, the associations between neurocognitive scores and hippocampal subfield volumes in the DS group were not significant after the Bonferroni correction. Our results did not support a causal relationship between hippocampal subregional atrophy and cognitive deficits in DS.

Choroidal structural analysis in ultra-high risk and first-episode psychosis

Both structural and functional alterations in the retina and the choroid of the eye, as parts of the central nervous system, have been shown in psychotic disorders, especially in schizophrenia. In addition, genetic and imaging studies indicate vascular and angiogenesis anomalies in the psychosis spectrum disorders. In this ocular imaging study, choroidal structure and vascularity were investigated using enhanced depth imaging (EDI) optical coherence tomography (OCT) in first-episode psychosis (FEP), ultra-high risk for psychosis (UHR-P), and age- and gender- matched healthy controls (HCs). There were no significant differences between groups in central choroidal thickness, stromal choroidal area (SCA), luminal choroidal area (LCA) and total subfoveal choroidal area. The LCA/SCA ratio (p<0.001) and the choroidal vascularity index (CVI) (p<0.001) were significantly different between FEP, UHR-P and HCs. CVI and LCA/SCA ratio were significantly higher in patients with FEP compared to help-seeking youth at UHR-P. CVI and LCA/SCA ratio were not different between UHR-P and HCs. However, CVI was higher in UHR-P compared to HCs after excluding the outliers for the sensitivity analysis (p = 0.002). Current findings suggest that choroidal thickness is normal, but there are abnormalities in choroidal microvasculature in prodromal and first-episode psychosis. Further longitudinal studies are needed to investigate oculomics, especially CVI, as a promising biomarker for the prediction of conversion to psychosis in individuals at clinical high-risk.

The effects of bifrontal anodal transcranial direct current stimulation (tDCS) on sleepiness and vigilance in partially sleep-deprived subjects: A multidimensional study

In recent years, transcranial electrical stimulation techniques have demonstrated their ability to modulate our levels of sleepiness and vigilance. However, the outcomes differ among the specific aspects considered (physiological, behavioural or subjective). This study aimed to observe the effects of bifrontal anodal transcranial direct current stimulation. Specifically, we tested the ability of this stimulation protocol to reduce sleepiness and increase vigilance in partially sleep-deprived healthy participants. Twenty-three subjects underwent a within-subject sham-controlled stimulation protocol. We compared sleepiness and vigilance levels before and after the two stimulation conditions (active versus sham) by using behavioural (reaction-time task), subjective (self-report scales) and physiological (sleep-onset latency and electroencephalogram power [n = 20] during the Maintenance of Wakefulness Test) measures. We showed the efficacy of the active stimulation in reducing physiological sleepiness and preventing vigilance drop compared with the sham stimulation. Consistently, we observed a reduction of perceived sleepiness following the active stimulation for both self-report scales. However, the stimulation effect on subjective measures was not statistically significant probably due to the underpowered sample size for these measures, and to the possible influence of motivational and environmental factors. Our findings confirm the ability of this technique to influence vigilance and sleepiness, pointing out the potential for new treatment developments based on transcranial electrical stimulation.

Repetitive transcranial magnetic stimulation in primary sleep disorders

Repetitive transcranial magnetic stimulation (rTMS) is a widely used non-invasive neuromodulatory technique. When applied in sleep medicine, the main hypothesis explaining its effects concerns the modulation of synaptic plasticity and the strength of connections between the brain areas involved in sleep disorders. Recently, there has been a significant increase in the publication of rTMS studies in primary sleep disorders. A multi-database-based search converges on the evidence that rTMS is safe and feasible in chronic insomnia, obstructive sleep apnea syndrome (OSAS), restless legs syndrome (RLS), and sleep deprivation-related cognitive deficits, whereas limited or no data are available for narcolepsy, sleep bruxism, and REM sleep behavior disorder. Regarding efficacy, the stimulation of the dorsolateral prefrontal cortex bilaterally, right parietal cortex, and dominant primary motor cortex (M1) in insomnia, as well as the stimulation of M1 leg area bilaterally, left primary somatosensory cortex, and left M1 in RLS reduced subjective symptoms and severity scale scores, with effects lasting for up to weeks; conversely, no relevant effect was observed in OSAS and narcolepsy. Nevertheless, several limitations especially regarding the stimulation protocols need to be considered. This review should be viewed as a step towards the further contribution of individually tailored neuromodulatory techniques for sleep disorders.

Sleep patterns correlates with the efficacy of tDCS on post-stroke patients with prolonged disorders of consciousness

BACKGROUND

The subclassification of prolonged disorders of consciousness (DoC) based on sleep patterns is important for the evaluation and treatment of the disease. This study evaluates the correlation between polysomnographic patterns and the efficacy of transcranial direct current stimulation (tDCS) in patients with prolonged DoC due to stroke.

METHODS

In total, 33 patients in the vegetative state (VS) with sleep cycles or without sleep cycles were randomly assigned to either active or sham tDCS groups. Polysomnography was used to monitor sleep changes before and after intervention. Additionally, clinical scale scores and electroencephalogram (EEG) analysis were performed before and after intervention to evaluate the efficacy of tDCS on the patients subclassified according to their sleep patterns.

RESULTS

The results suggest that tDCS improved the sleep structure, significantly prolonged total sleep time (TST) (95%CI: 14.387-283.527, P = 0.013) and NREM sleep stage 2 (95%CI: 3.157-246.165, P = 0.040) of the VS patients with sleep cycles. It also significantly enhanced brain function of patients with sleep cycles, which were reflected by the increased clinical scores (95%CI: 0.340-3.440, P < 0.001), the EEG powers and functional connectivity in the brain and the 6-month prognosis. Moreover, the changes in NREM sleep stage 2 had a significant positive correlation with each index of the β band.

CONCLUSION

This study reveals the importance of sleep patterns in the prognosis and treatment of prolonged DoC and provides new evidence for the efficacy of tDCS in post-stroke patients with VS patients subclassified by sleep pattern. Trial registration URL: https://www.

CLINICALTRIALS

gov . Unique identifier: NCT03809936. Registered 18 January 2019.

Automatic diagnosis of sleep apnea from biomedical signals using artificial intelligence techniques: Methods, challenges, and future works

Apnea is a sleep disorder that stops or reduces airflow for a short time during sleep. Sleep apnea may last for a few seconds and happen for many while sleeping. This reduction in breathing is associated with loud snoring, which may awaken the person with a feeling of suffocation. So far, a variety of methods have been introduced by researchers to diagnose sleep apnea, among which the polysomnography (PSG) method is known to be the best. Analysis of PSG signals is very complicated. Many studies have been conducted on the automatic diagnosis of sleep apnea from biological signals using artificial intelligence (AI), including machine learning (ML) and deep learning (DL) methods. This research reviews and investigates the studies on the diagnosis of sleep apnea using AI methods. First, computer aided diagnosis system (CADS) for sleep apnea using ML and DL techniques along with its parts including dataset, preprocessing, and ML and DL methods are introduced. This research also summarizes the important specifications of the studies on the diagnosis of sleep apnea using ML and DL methods in a table. In the following, a comprehensive discussion is made on the studies carried out in this field. The challenges in the diagnosis of sleep apnea using AI methods are of paramount importance for researchers. Accordingly, these obstacles are elaborately addressed. In another section, the most important future works for studies on sleep apnea detection from PSG signals and AI techniques are presented. Ultimately, the essential findings of this study are provided in the conclusion section.

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Predicting and mitigating fatigue effects due to sleep deprivation: A review

The deleterious effects of insufficient sleep have been well-established in the literature and can lead to a wide range of adverse health outcomes. Some of the most replicated findings demonstrate significant declines in cognitive functions such as vigilance and executive attention, psychomotor and cognitive speed, and working memory. Consequently, these decrements often lead individuals who are in a fatigued state to engage in substandard performance on everyday tasks. In the interest of curtailing these effects, prior work has attempted to identify mechanisms that predict fatigue onset and develop techniques to mitigate its negative consequences. Nonetheless, these results are often confounded by variables such as an individual’s resistance to fatigue, sleep history, and unclear distinctions about whether certain performance decrements are present due to fatigue or due to other confounding factors. Similar areas of research have provided approaches to produce models for the prediction of cognitive performance decrements due to fatigue through the use of multi-modal recording and analysis of fatigue-related responses. Namely, gathering and combining response information from multiple sources (i.e., physiological and behavioral) at multiple timescales may provide a more comprehensive representation of what constitutes fatigue onset in the individual. Therefore, the purpose of this review is to discuss the relevant literature on the topic of fatigue-related performance effects with a special emphasis on a variety of physiological and behavioral response variables that have shown to be sensitive to changes in fatigue. Furthermore, an increasing reliance on sleep loss, meant to assist in meeting the demands of modern society, has led to an upsurge in the relevance of identifying dependable countermeasures for fatigued states. As such, we will also review methods for the mitigation of performance effects due to fatigue and discuss their usefulness in regulating these effects. In sum, this review aims to inspire future work that will create opportunities to detect fatigue and mitigate its effects prior to the onset of cognitive impairments.