Slow Wave Sleep and EEG Delta Spectral Power are Associated with Cognitive Function in Parkinson's Disease

Brain metabolites are associated with sleep architecture and cognitive functioning in older adults

Sleep deficits are a possible risk factor for development of cognitive decline and dementia in older age. Research suggests that neuroinflammation may be a link between the two. This observational, cross-sectional study evaluated relationships between sleep architecture, neuroinflammation and cognitive functioning in healthy older adults. Twenty-two adults aged ≥60 years underwent whole-brain magnetic resonance spectroscopic imaging (in vivo method of visualizing increased brain temperatures as a proxy for neuroinflammation), supervised laboratory-based polysomnography, and comprehensive neurocognitive testing. Multiple regressions were used to assess relationships between magnetic resonance spectroscopic imaging-derived brain temperature and metabolites related to inflammation (choline; myo-inositol; N-acetylaspartate), sleep efficiency, time and % N3 sleep and cognitive performance. Choline, myo-inositol and N-acetylaspartate were associated with sleep efficiency and cognitive performance. Higher choline and myo-inositol in the bilateral frontal lobes were associated with slower processing speed and lower sleep efficiency. Higher choline and myo-inositol in bilateral frontoparietal regions were associated with better cognitive performance. Higher N-acetylaspartate around the temporoparietal junction and adjacent white matter was associated with better visuospatial function. Brain temperature was not related to cognitive or sleep outcomes. Our findings are consistent with the limited literature regarding neuroinflammation and its relationships with sleep and cognition in older age, which has implicated ageing microglia and astrocytes in circadian dysregulation, impaired glymphatic clearance and increased blood-brain barrier integrity, with downstream effects of neurodegeneration and cognitive decline. Inflammatory processes remain difficult to measure in the clinical setting, but magnetic resonance spectroscopic imaging may serve as a marker of the relationship between neuroinflammation, sleep and cognitive decline in older adults.

Diffusion Tensor Imaging-Along the Perivascular-Space Index Is Associated with Disease Progression in Parkinson's Disease

BACKGROUND

The glymphatic clearance pathway is a waste clearance system that allows for removal of soluble proteins such as amyloid β (Aβ) from the brain. Higher Aβ levels are associated with cognitive dysfunction in Parkinson's disease (PD). Diffusion tensor imaging-along the perivascular space (DTI-ALPS) is an imaging measure proposed to indirectly measure glymphatic function.

OBJECTIVES

Evaluate differences in DTI-ALPS-index between PD and healthy controls (HC) and characterize relationships between this proposed measure of glymphatic clearance, cognition, and disease severity in PD.

METHODS

PD (n = 32) and HC (n = 23) participants underwent brain imaging to assess DTI-ALPS. PD participants were classified as PD-normal cognition (PD-NC; n = 20) or PD-mild cognitive impairment (PD-MCI; n = 12) based on a Level II comprehensive cognitive assessment. A subgroup of PD participants (n = 21) returned for annual assessments for up to 4 years after baseline. Longitudinal outcomes included changes in performance on the comprehensive cognitive assessment and changes in the Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS).

RESULTS

PD participants had lower DTI-ALPS-index compared to HC. PD participants classified as PD-MCI had significantly lower DTI-ALPS-index compared to PD-NC. Lower DTI-ALPS-index at baseline was associated with longitudinal cognitive decline and worse longitudinal disease severity.

CONCLUSIONS

Glymphatic clearance, as measured with DTI-ALPS, has potential to serve as a marker of longitudinal disease progression. Interventions targeting glymphatic function should be explored for potential to slow cognitive decline in PD. © 2024 International Parkinson and Movement Disorder Society.

Objective sleep enhancement in Parkinson's disease: A sham-controlled trial of low-frequency repetitive transcranial magnetic stimulation over the right dorsolateral prefrontal cortex

INTRODUCTION

Parkinson's disease (PD) is often accompanied by sleep disturbances, impacting patients' quality of life. While repetitive transcranial magnetic stimulation (rTMS) shows promise in improving self-reported sleep quality, its effects on objective sleep architecture in PD remain understudied. Sleep disturbances, including rapid eye movement (REM) and slow-wave sleep disturbances, correlate with cognitive decline and motor symptoms. This study investigated the effect of low-frequency rTMS targeting the right dorsolateral prefrontal cortex (DLPFC) modifying objective sleep architecture and explored symptom improvement mechanisms in PD patients.

METHODS

In this randomized, double-blind, sham-controlled trial, 67 PD patients received 10 consecutive days of 1-Hz rTMS over the right DLPFC. Polysomnography assessed sleep microstructure, while electroencephalogram recordings evaluated power spectral density and sleep spindle activity. Clinical scales measured sleep quality, motor symptoms, and cognition at baseline, post-treatment, and 3 months post-rTMS.

RESULTS

The rTMS group exhibited improvements in sleep quality, motor symptoms, and cognition post-treatment, persisting at the 3-month follow-up. There was a notable increase in the REM sleep proportion post-rTMS. The rTMS group exhibited elevated low-frequency (0.5-2 Hz) slow-wave electroencephalogram spectral density during non-REM sleep. Cognitive enhancement correlated with increased lower delta power, while motor symptom progression correlated with spindle frequency and slow-wave sleep percentage changes.

CONCLUSION

Low-frequency rTMS targeting the right DLPFC holds promise for improving clinical symptoms and modulating sleep architecture in PD. These findings suggest a link between symptom improvement and sleep structure enhancement, highlighting the need for further investigation into the therapeutic potential of rTMS in PD management.

Is the insomnia phenotype the common denominator in LUTS during transition periods? An expert NOPIA research group review

AIMS

As people age, sleep stages and characteristics transition over time, but sleep deficits can profoundly impact health and cognitive functioning. Chronic sleep deprivation is linked to impaired attention and productivity, weakened immunity, increased risk of cardiovascular disease, obesity, and mental health disorders. Insomnia, obstructive sleep apnea syndrome, hormonal changes, nocturia, neurological disorders, and life events interfere with sleep patterns and some are linked to lower urinary tract symptoms (LUTS). This NOPIA symposium on Lifelong LUTS aimed to analyze the literature on associations between sleep and LUTS, generate ideas for future research, and explore whether there is support for the concept of lifelong LUTS in relation to changes in sleep throughout the lifespan.

METHODS

An international panel of experts took part in an online meeting addressing the role of lifelong LUTS in relationship to sleep and the brain organized by the NOPIA research group. The manuscript summarizes existing literature, hypotheses, future research ideas, and clinical recommendations.

RESULTS

Insomnia, sleep fragmentation, hyperarousal, and sensory processing disorders emerged as potential factors in the relationship between sleep and LUTS. Insomnia is often a persistent factor and may have been the initial symptom; however, it is often unrecognized and/or unaddressed in healthcare settings. By recognizing insomnia as a primary driver of various health issues, including nocturia, transitional care aims to address root causes and underlying problems earlier to initiate appropriate treatment.

CONCLUSIONS

A multidisciplinary approach with collaboration between healthcare professionals from various disciplines, such as urology, sleep medicine, gynecology, pediatrics, and geriatrics, is needed and should include validated measurements such as the insomnia severity index and sleep and voiding diaries. Ensuring ongoing follow-up and monitoring through transitional care is crucial for individuals with persistent sleep problems and LUTS, allowing issues that arise or fluctuate over the lifespan to be addressed.

Slow-wave sleep and REM sleep without atonia predict motor progression in Parkinson's disease

BACKGROUND

Growing evidence supports the potential role of sleep in the motor progression of Parkinson's disease (PD). Slow-wave sleep (SWS) and rapid eye movement (REM) sleep without atonia (RWA) are important sleep parameters. The association between SWS and RWA with PD motor progression and their predictive value have not yet been elucidated.

METHODS

We retro-prospectively analyzed clinical and polysomnographic data of 136 patients with PD. The motor symptoms were assessed using Unified Parkinson's Disease Rating Scale Part III (UPDRS III) at baseline and follow-up to determine its progression. Partial correlation analysis was used to explore the cross-sectional associations between slow-wave energy (SWE), RWA and clinical symptoms. Longitudinal analyses were performed using Cox regression and linear mixed-effects models.

RESULTS

Among 136 PD participants, cross-sectional partial correlation analysis showed SWE decreased with the prolongation of the disease course (P = 0.046), RWA density was positively correlated with Hoehn & Yahr (H-Y) stage (tonic RWA, P < 0.001; phasic RWA, P = 0.002). Cox regression analysis confirmed that low SWE (HR = 1.739, 95% CI = 1.038-2.914; P = 0.036; FDR-P = 0.036) and high tonic RWA (HR = 0.575, 95% CI = 0.343-0.963; P = 0.032; FDR-P = 0.036) were predictors of motor symptom progression. Furthermore, we found that lower SWE predicted faster rate of axial motor progression (P < 0.001; FDR-P < 0.001) while higher tonic RWA density was associated with faster rate of rigidity progression (P = 0.006; FDR-P = 0.024) using linear mixed-effects models.

CONCLUSIONS

These findings suggest that SWS and RWA might represent markers of different motor subtypes progression in PD.

Slow-wave sleep dysfunction in mild parkinsonism is associated with excessive beta and reduced delta oscillations in motor cortex

Increasing evidence suggests slow-wave sleep (SWS) dysfunction in Parkinson's disease (PD) is associated with faster disease progression, cognitive impairment, and excessive daytime sleepiness. Beta oscillations (8-35 Hz) in the basal ganglia thalamocortical (BGTC) network are thought to play a role in the development of cardinal motor signs of PD. The role cortical beta oscillations play in SWS dysfunction in the early stage of parkinsonism is not understood, however. To address this question, we used a within-subject design in a nonhuman primate (NHP) model of PD to record local field potentials from the primary motor cortex (MC) during sleep across normal and mild parkinsonian states. The MC is a critical node in the BGTC network, exhibits pathological oscillations with depletion in dopamine tone, and displays high amplitude slow oscillations during SWS. The MC is therefore an appropriate recording site to understand the neurophysiology of SWS dysfunction in parkinsonism. We observed a reduction in SWS quantity (p = 0.027) in the parkinsonian state compared to normal. The cortical delta (0.5-3 Hz) power was reduced (p = 0.038) whereas beta (8-35 Hz) power was elevated (p = 0.001) during SWS in the parkinsonian state compared to normal. Furthermore, SWS quantity positively correlated with delta power (r = 0.43, p = 0.037) and negatively correlated with beta power (r = -0.65, p < 0.001). Our findings support excessive beta oscillations as a mechanism for SWS dysfunction in mild parkinsonism and could inform the development of neuromodulation therapies for enhancing SWS in people with PD.

Excessive cortical beta oscillations are associated with slow-wave sleep dysfunction in mild parkinsonism

Increasing evidence associates slow-wave sleep (SWS) dysfunction with neurodegeneration. Using a within-subject design in the nonhuman primate model of Parkinson's disease (PD), we found that reduced SWS quantity in mild parkinsonism was accompanied by elevated beta and reduced delta power during SWS in the motor cortex. Our findings support excessive beta oscillations as a mechanism for SWS dysfunction and will inform development of neuromodulation therapies for enhancing SWS in PD.

Original research: initial development of a pragmatic tool to estimate cognitive decline risk focusing on potentially modifiable factors in Parkinson's disease

Introduction

Cognitive decline is common in Parkinson's disease (PD). Calculating personalized risk of cognitive decline in PD would allow for appropriate counseling, early intervention with available treatments, and inclusion in disease-modifying trials.

Methods

Data were from the Parkinson's Progression Markers Initiative de novo cohort. Baseline scores were calculated for Lifestyle for Brain Health (LIBRA) and the Montreal Parkinson Risk of Dementia Scale (MoPaRDS) per prior literature and preliminary Parkinson's disease Risk Estimator for Decline In Cognition Tool (pPREDICT) by attributing a point for fourteen posited risk factors. Baseline and 5-year follow-up composite cognitive scores (CCSs) were calculated from a neuropsychological battery and used to define cognitive decliners (PD-decline) versus maintainers (PD-maintain).

Results

The PD-decline group (n = 44) had higher LIBRA (6.76 ± 0.57, p < 0.05), MoPaRDS (2.45 ± 1.41, p < 0.05) and pPREDICT (4.52 ± 1.66, p < 0.05) scores compared to the PD-maintain group (n = 263; LIBRA 4.98 ± 0.20, MoPaRDS 1.68 ± 1.16, pPREDICT 3.38 ± 1.69). Area-under-the-curve (AUC) for LIBRA was 0.64 (95% confidence interval [CI], 0.55-0.73), MoPaRDS was 0.66 (95% CI, 0.58-0.75) and for pPREDICT was 0.68 (95% CI, 0.61-0.76). In linear regression analyses, LIBRA (p < 0.05), MoPaRDS (p < 0.05) and pPREDICT (p < 0.05) predicted change in CCS. Only age stratified by sex (p < 0.05) contributed significantly to the model for LIBRA. Age and presence of hallucinations (p < 0.05) contributed significantly to the model for MoPaRDS. Male sex, older age, excessive daytime sleepiness, and moderate-severe motor symptoms (all p < 0.05) contributed significantly to the model for pPREDICT.

Conclusion

Although MoPaRDS is a PD-specific tool for predicting cognitive decline relying on only clinical features, it does not focus on potentially modifiable risk factors. LIBRA does focus on potentially modifiable risk factors and is associated with prediction of all-cause dementia in some populations, but pPREDICT potentially demonstrates improved performance in cognitive decline risk calculation in individuals with PD and may identify actionable risk factors. As pPREDICT incorporates multiple potentially modifiable risk factors that can be obtained easily in the clinical setting, it is a first step in developing an easily assessable tool for a personalized approach to reduce dementia risk in people with PD.

Wake and non-rapid eye movement sleep dysfunction is associated with colonic neuropathology in Parkinson's disease

Study Objectives

The body-first Parkinson's disease (PD) hypothesis suggests initial gut Lewy body pathology that propagates to the pons before reaching the substantia nigra, and subsequently progresses to the diencephalic and cortical levels. This disease course may also be the most likely in PD with rapid eye movement sleep behavior disorder (RBD).

Objectives

We aimed to explore the potential association between colonic phosphorylated alpha-synuclein histopathology (PASH) and diencephalic or cortical dysfunction evidenced by non-rapid eye movement (NREM) sleep and wakefulness polysomnographic markers.

Methods

In a study involving 43 patients with PD who underwent clinical examination, rectosigmoidoscopy, and polysomnography, we detected PASH on colonic biopsies using whole-mount immunostaining. We performed a visual semi-quantitative and automated quantification of spindle and slow wave features of NREM sleep, and the wake dominant frequency, and then determined Braak and Arizona stage classifications for PD severity based on sleep and wake electroencephalographic features.

Results

The visual analysis aligned with the automated quantified spindle characteristics and the wake dominant frequency. Altered NREM sleep and wake parameters correlated with markers of PD severity, colonic PASH, and RBD diagnosis. Colonic PASH frequency also increased in parallel to presumed PD Braak and Arizona stage classifications.

Conclusions

Colonic PASH in PD is strongly associated with widespread brain sleep and wake dysfunction, pointing toward likely extensive diffusion of the pathological process in the presumptive body-first PD phenotype. Visual and automated analyses of polysomnography signals provide useful markers to gauge covert brain dysfunction in PD.

Statement of Significance

The presence of gut synucleinopathy in Parkinson's disease can be linked to the body-first hypothesis in its pathophysiology. This study, performed in a cohort of 43 patients with Parkinson's disease that underwent clinical assessment, rectosigmoidoscopy and polysomnography, provides evidence that colonic neuropathology in Parkinson's disease is associated with widespread brain dysfunction, as evaluated by wake and non-rapid eye movement sleep polysomnographic markers. Our results support the assumption of an extensive diffusion of the pathological process to diencephalic and neocortical structures in the presumptive body-first phenotype. They also suggest the use of routine polysomnography in phenotyping patients with Parkinson's disease. Future studies should investigate the brain diffusion pattern and its sleep markers in the hypothesized brain-first phenotype of Parkinson's disease.

Preoperative slow-wave sleep is associated with postoperative delirium after heart valve surgery: A prospective pilot study

Postoperative delirium (POD) is a very common neurological complication after valve surgery. Some studies have shown that preoperative sleep disorder is associated with POD, but the correlation between preoperative slow wave sleep (SWS) and POD remains unclear. Therefore, this study aims to identify the correlation between preoperative slow wave sleep and postoperative delirium in patients with heart valve disease. This was a prospective, observational study of elective valve surgery patients admitted to the Heart Medical Center between November 2021 and July 2022. Polysomnography (PSG) was used to monitor sleep architecture from 9:30 p.m. for 1 night before surgery to 6:30 a.m. on the day of surgery. Patients were assessed for postoperative delirium from postoperative day 1 to extubation or day 5 by using the Richmond Agitation/Sedation Scale (RASS) and the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). A total of 60 elective valve surgery patients were enrolled in this study. Prolonged N1 (11.44%) and N2 (58.62%) sleep, decreased N3 sleep (8.75%) and REM sleep (18.24%) within normal limits were the overall sleep architecture. Compared with patients without POD, patients with POD had less slow wave sleep 1 night before surgery (5.77% vs 10.88%, p < 0.001). After adjusting for confounding factors, slow wave sleep (OR: 0.647, 95% CI 0.493-0.851, p = 0.002) was found to be a protective factor for postoperative delirium. The preoperative SWS is a predictive factor of the POD in patients undergoing valve surgery. But further studies with larger sample sizes are still needed to elucidate the relationship between preoperative slow wave sleep and postoperative delirium.

Quantitative sleep electroencephalogram and cognitive performance in Parkinson's disease with and without rapid eye movement sleep behavior disorder

Introduction

Parkinson's disease (PD) patients with REM sleep behavior disorder (RBD) are at greater risk for cognitive decline and RBD has been associated with alterations in sleep-related EEG oscillations. This study evaluates differences in sleep quantitative EEG (qEEG) and cognition in PD participants with (PD-RBD) and without RBD (PD-no-RBD).

Methods

In this cross-sectional study, polysomnography (PSG)-derived qEEG and a comprehensive level II neuropsychological assessment were compared between PD-RBD (n = 21) and PD-no-RBD (n = 31). Following artifact rejection, qEEG analysis was performed in the frontal and central leads. Measures included Scalp-slow wave (SW) density, spindle density, morphological properties of SW and sleep spindles, SW-spindle phase-amplitude coupling, and spectral power analysis in NREM and REM. The neurocognitive battery had at least two tests per domain, covering five cognitive domains as recommended by the Movement Disorders Society Task Force for PD-MCI diagnosis. Differences in qEEG features and cognitive performance were compared between the two groups. Stepwise linear regression was performed to evaluate predictors of cognitive performance. Multiple comparisons were corrected using the Benjamini-Hochberg method.

Results

Spindle density and SW-spindle co-occurrence percent were lower in participants with PD-RBD compared to PD-no-RBD. The PD-RBD group also demonstrated higher theta spectral power during REM. Sleep spindles and years of education, but not RBD, were predictors of cognitive performance.

Conclusion

PD participants with RBD have alterations in sleep-related qEEG compared to PD participants without RBD. Although PD-RBD participants had worse cognitive performance compared to PD-no-RBD, regression models suggest that lower sleep spindle density, rather than presence of RBD, predicts worse comprehensive cognitive score. Future studies should include longitudinal evaluation to determine whether sleep-related qEEG alterations are associated with more rapid cognitive decline in PD-RBD.

Deep-learning detection of mild cognitive impairment from sleep electroencephalography for patients with Parkinson's disease

Parkinson's disease which is the second most prevalent neurodegenerative disorder in the United States is a serious and complex disease that may progress to mild cognitive impairment and dementia. The early detection of the mild cognitive impairment and the identification of its biomarkers is crucial to support neurologists in monitoring the progression of the disease and allow an early initiation of effective therapeutic treatments that will improve the quality of life for the patients. In this paper, we propose the first deep-learning based approaches to detect mild cognitive impairment in the sleep Electroencephalography for patients with Parkinson's disease and further identify the discriminative features of the disease. The proposed frameworks start by segmenting the sleep Electroencephalography time series into three sleep stages (i.e., two non-rapid eye movement sleep-stages and one rapid eye movement sleep stage), further transforming the segmented signals in the time-frequency domain using the continuous wavelet transform and the variational mode decomposition and finally applying novel convolutional neural networks on the time-frequency representations. The gradient-weighted class activation mapping was also used to visualize the features based on which the proposed deep-learning approaches reached an accurate prediction of mild cognitive impairment in Parkinson's disease. The proposed variational mode decomposition-based model offered a superior accuracy, sensitivity, specificity, area under curve, and quadratic weighted Kappa score, all above 99% as compared with the continuous wavelet transform-based model (that achieved a performance that is almost above 92%) in differentiating mild cognitive impairment from normal cognition in sleep Electroencephalography for patients with Parkinson's disease. In addition, the features attributed to the mild cognitive impairment in Parkinson's disease were demonstrated by changes in the middle and high frequency variational mode decomposition components across the three sleep-stages. The use of the proposed model on the time-frequency representation of the sleep Electroencephalography signals will provide a promising and precise computer-aided diagnostic tool for detecting mild cognitive impairment and hence, monitoring the progression of Parkinson's disease.

Original research: longitudinal evaluation of cognitively demanding daily function using performance-based functional assessment highlights heterogeneous trajectories in cognitive and functional abilities in people with Parkinson's disease

Background

Longitudinal assessment of functional abilities in Parkinson's disease (PD) is needed to determine the efficacy of cognitive interventions in providing meaningful improvements in daily life. Additionally, subtle changes in instrumental activities of daily living may precede a clinical diagnosis of dementia and could aid earlier detection of and intervention for cognitive decline.

Objective

The primary goal was to validate the longitudinal application of the University of California San Diego Performance-Based Skills Assessment (UPSA). An exploratory secondary goal was to determine whether UPSA may identify individuals at higher risk of cognitive decline in PD.

Methods

Seventy participants with PD completed the UPSA with at least one follow-up visit. Linear mixed effects modeling was used to identify associations between baseline UPSA score and cognitive composite score (CCS) over time. Descriptive analysis of four heterogeneous cognitive and functional trajectory groups and individual case examples was performed.

Results

Baseline UPSA score predicted CCS at each timepoint for functionally impaired and unimpaired groups (p < 0.01) but did not predict the rate change in CCS over time (p = 0.83). Participants displayed heterogenous trajectories in both UPSA and CCS during the follow-up period. Most participants maintained both cognitive and functional performance (n = 54), though some displayed cognitive and functional decline (n = 4), cognitive decline with functional maintenance (n = 4), and functional decline with cognitive maintenance (n = 8).

Conclusion

The UPSA is a valid measure of cognitive functional abilities over time in PD. Given the heterogeneity of functional and cognitive trajectories, this performance-based assessment did not predict cognitive decline with this relatively short follow-up. Further work is needed to understand longitudinal functional assessments in PD-associated cognitive impairment.

Quantitative Sleep Electroencephalogram in Parkinson's Disease: A Case-Control Study

BACKGROUND

Sleep disorders are common in Parkinson's disease (PD) and include alterations in sleep-related EEG oscillations.

OBJECTIVE

This case-control study tested the hypothesis that patients with PD would have a lower density of Scalp-Slow Wave (SW) oscillations and higher slow-to-fast frequencies ratio in rapid eye movement (REM) sleep than non-PD controls. Other sleep-related quantitative EEG (qEEG) features were also examined, including SW morphology, sleep spindles, and Scalp-SW spindle phase-amplitude coupling.

METHODS

Polysomnography (PSG)-derived sleep EEG was compared between PD participants (n = 56) and non-PD controls (n = 30). Following artifact rejection, sleep qEEG analysis was performed in frontal and central leads. Measures included SW density and morphological features of SW and sleep spindles, SW-spindle phase-amplitude coupling, and spectral power analysis in Non-REM (NREM) and REM. Differences in qEEG features between PD and non-PD controls were compared using two-tailed Welch's t-tests, and correction for multiple comparisons was performed per the Benjamini-Hochberg method.

RESULTS

SW density was lower in PD than in non-PD controls (F = 13.5, p' = 0.003). The PD group also exhibited higher ratio of slow REM EEG frequencies (F = 4.23, p' = 0.013), higher slow spindle peak frequency (F = 24.7, p' <  0.002), and greater SW-spindle coupling angle distribution non-uniformity (strength) (F = 7.30, p' = 0.034).

CONCLUSION

This study comprehensively evaluates sleep qEEG including SW-spindle phase amplitude coupling in PD compared to non-PD controls. These findings provide novel insights into how neurodegenerative disease disrupts electrophysiological sleep rhythms. Considering the role of sleep oscillatory activity on neural plasticity, future studies should investigate the influence of these qEEG markers on cognition in PD.

Characteristics of sleep structure in Parkinson's disease patients with hallucinations based on polysomnography

Hallucination is a common non-motor symptom in patients with Parkinson's disease (PD). Additionally, sleep disorders are associated with an increased risk of hallucinations in PD patients. This study aimed to examine the association between hallucination and objective sleep parameters in PD patients. We retrospectively recruited 278 PD patients who underwent polysomnography and clinical assessments and classified them into non-hallucination and hallucination groups. Hallucinations were observed in 77 older PD patients who had more severe motor symptoms and higher scores on the Non-Motor Symptoms Questionnaire (NMSQ), Hamilton Depression Scale (HAMD) and Hamilton Anxiety Scale (HAMA) but lower scores on the Montreal Cognitive Assessment (MOCA) and PD Sleep Scale (PDSS) than PD patients without hallucinations. Analysis of the polysomnographic variables in patients with hallucinations showed that they exhibited a decrease in total sleep time, sleep efficiency (SE), rapid eye movement (REM) sleep time and slow wave sleep (SWS, N3) time and percentage but a significant increase in wake time after sleep onset (WASO), periodic limb movement index (PLMI) scores, and stage 2 NREM (N2)percentage. Logistic regression analysis revealed that higher NMSQ scores, lower MOCA scores, lower SE, and a lower percentage of N3 sleep were associated with hallucinations in PD patients. Our results suggested that PD patients with hallucinations had worse sleep quality and differences in sleep architecture (measured by polysomnography).

Neurofeedback for the Education of Children with ADHD and Specific Learning Disorders: A Review

Neurofeedback (NF) is a type of biofeedback in which an individual’s brain activity is measured and presented to them to support self-regulation of ongoing brain oscillations and achieve specific behavioral and neurophysiological outcomes. NF training induces changes in neurophysiological circuits that are associated with behavioral changes. Recent evidence suggests that the NF technique can be used to train electrical brain activity and facilitate learning among children with learning disorders. Toward this aim, this review first presents a generalized model for NF systems, and then studies involving NF training for children with disorders such as dyslexia, attention-deficit/hyperactivity disorder (ADHD), and other specific learning disorders such as dyscalculia and dysgraphia are reviewed. The discussion elaborates on the potential for translational applications of NF in educational and learning settings with details. This review also addresses some issues concerning the role of NF in education, and it concludes with some solutions and future directions. In order to provide the best learning environment for children with ADHD and other learning disorders, it is critical to better understand the role of NF in educational settings. The review provides the potential challenges of the current systems to aid in highlighting the issues undermining the efficacy of current systems and identifying solutions to address them. The review focuses on the use of NF technology in education for the development of adaptive teaching methods and the best learning environment for children with learning disabilities.

Trihexyphenidyl increases delta activity in non-rapid eye movement sleep without impairing cognitive function in rodent models

Both human and rodent studies suggest the link between non-rapid eye movement (NREM) sleep and cognition. Recent study indicated that selective activation of cholinergic neurons in basal forebrain inhibits electroencephalogram (EEG) delta power and shortens NREM sleep. In the current study, we aimed to test the pharmacological effect of trihexyphenidyl (THP), a selective muscarinic M1 receptor antagonist, on EEG power spectra and sleep with or without the selective activation of basal forebrain cholinergic neurons. THP (1, 2, and 3 mg/kg) was administrated intraperitoneally in natural sleep phase. Basal forebrain cholinergic neurons expressing modified G protein-coupled muscarinic receptors (hM3Dq) were activated by intraperitoneal injection of clozapine-N-oxide in ChAT-IRES-Cre mice. EEG and electromyogram (EMG) signals were recorded in freely moving mice to analyze EEG power spectrum and sleep hypnogram. Y-maze and novel object recognition tests were used for testing cognition. THP 1 mg/kg significantly increased EEG delta power and facilitated NREM sleep in wildtype mice, while THP 3 mg/kg was required in ChAT-IRES-Cre mice treated with clozapine-N-oxide. THP with dosage up to 8 mg/kg did not induce cognitive impairments in wildtype mice. EEG delta power of NREM sleep is often used as an indicator of sleep depth or sleep quality, which tightly link with sleep-dependent cognition. Taken together, the data collected from rodents hinted that, THP could possibly be used as the NREM sleep facilitator in humans.

The top 100 most cited papers in insomnia: A bibliometric analysis

OBJECTIVE

The number of citations to a paper represents the weight of that work in a particular area of interest. Several highly cited papers are listed in the bibliometric analysis. This study aimed to identify and analyze the 100 most cited papers in insomnia research that might appeal to researchers and clinicians.

METHODS

We reviewed the Web of Science (WOS) Core Collection database to identify articles from 1985 to 24 March 2022. The R bibliometric package was used to further analyze citation counts, authors, year of publication, source journal, geographical origin, subject, article type, and level of evidence. Word co-occurrence in 100 articles was visualized using VOS viewer software.

RESULTS

A total of 44,654 manuscripts were searched on the Web of Science. Between 2001 and 2021, the top 100 influential manuscripts were published, with a total citation frequency of 38,463. The top countries and institutions contributing to the field were the U.S. and Duke University. Morin C.M. was the most productive author, ranking first in citations. Sleep had the highest number of manuscripts published in the top 100 (n = 31), followed by Sleep Medicine Reviews (n = 9). The most cited manuscript (Bastien et al., Sleep Medicine, 2001; 3,384 citations) reported clinical validation of the Insomnia Severity Index (ISI) as a brief screening indicator for insomnia and as an outcome indicator for treatment studies. Co-occurrence analyses suggest that psychiatric disorders combined with insomnia and cognitive behavioral therapy remain future research trends.

CONCLUSION

This study provides a detailed list of the most cited articles on insomnia. The analysis provides researchers and clinicians with a detailed overview of the most cited papers on insomnia over the past two decades. Notably, COVID-19, anxiety, depression, CBT, and sleep microstructure are potential areas of focus for future research.

The therapeutic properties of ketogenic diets, slow-wave sleep, and circadian synchrony

PURPOSE OF REVIEW

To summarize emerging connections between sleep, ketogenic diets, and health.

RECENT FINDINGS

Mechanisms involved in the therapeutic benefits of ketogenic diets continue to be elucidated. Concurrently, the importance of sleep quality and circadian rhythms in their effects on metabolic and cognitive health is increasingly appreciated. Advances in the understanding of the actions of adenosine, nicotinamide adenine dinucleotide, and slow-wave sleep underscore connections between these areas of research.

SUMMARY

Many molecular pathways activated during ketogenic diets are known to modulate sleep-wake cycles, circadian rhythms, and sleep stages. Ketogenic diets often have beneficial effects on sleep at the same time as having beneficial effects on particular medical conditions. Enhancement of slow-wave sleep and rejuvenation of circadian programming may be synergistic with or causally involved in the benefits of ketogenic diets.

Reduced Regional NREM Sleep Slow-Wave Activity Is Associated With Cognitive Impairment in Parkinson Disease

Growing evidence implicates a distinct role of disturbed slow-wave sleep in neurodegenerative diseases. Reduced non-rapid eye movement (NREM) sleep slow-wave activity (SWA), a marker of slow-wave sleep intensity, has been linked with age-related cognitive impairment and Alzheimer disease pathology. However, it remains debated if SWA is associated with cognition in Parkinson disease (PD). Here, we investigated the relationship of regional SWA with cognitive performance in PD. In the present study, 140 non-demented PD patients underwent polysomnography and were administered the Montréal Cognitive Assessment (MoCA) to screen for cognitive impairment. We performed spectral analysis of frontal, central, and occipital sleep electroencephalography (EEG) derivations to measure SWA, and spectral power in other frequency bands, which we compared to cognition using linear mixed models. We found that worse MoCA performance was associated with reduced 1–4 Hz SWA in a region-dependent manner (F_{2, 687} =11.67, p < 0.001). This effect was driven by reduced regional SWA in the lower delta frequencies, with a strong association of worse MoCA performance with reduced 1–2 Hz SWA (F_{2, 687} =18.0, p < 0.001). The association of MoCA with 1–2 Hz SWA (and 1–4 Hz SWA) followed an antero-posterior gradient, with strongest, weaker, and absent associations over frontal (rho = 0.33, p < 0.001), central (rho = 0.28, p < 0.001), and occipital derivations, respectively. Our study shows that cognitive impairment in PD is associated with reduced NREM sleep SWA, predominantly in lower delta frequencies (1–2 Hz) and over frontal regions. This finding suggests a potential role of reduced frontal slow-wave sleep intensity in cognitive impairment in PD.