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Corticomuscular coherence and atonia index in controls, patients with idiopathic RBD, and combined RBD with Parkinsonism.
Source publication
REM sleep behavior disorder (RBD) could be a predictor of Parkinsonism even before development of typical motor symptoms. This study aims to characterize clinical features and corticomuscular and corticocortical coherence (CMC and CCC, respectively) during sleep in RBD patients with or without Parkinsonism. We enrolled a total of 105 subjects, incl...
Contexts in source publication
Context 1
... CMC was evaluated in each stage and is summarized in Table 3. During NREM2 stage, CMC values in RBD+P group were not significantly different from those in the control and iRBD groups ( Figure 1A). ...Context 2
... CMC was evaluated in each stage and is summarized in Table 3. During NREM2 stage, CMC values in RBD+P group were not significantly different from those in the control and iRBD groups ( Figure 1A). ...Context 3
... MAI was significantly decreased during both NREM2 and REM sleeps in the RBD+P group compared with iRBD group (Table 3). The iRBD group showed a lower MAI than controls during both NREM2 and REM stages, and the MAI decrease was greater in the RBD+P group than in the control and iRBD groups ( Figure 1E,F). ...Similar publications
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Citations
... The position of DBS electrodes is shown in figure 1B. Average power spectra across cohorts demonstrated exaggerated basal ganglia beta power (13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) in patients with PD across sleep stages, which was more prominent in the GPi than STN, and more prominent during REM and wakefulness compared with NREM sleep ( figure 1C). Here, we put our focus on REM sleep. ...
... 12 26 Lesions in the sublaterodorsal nucleus could result in reduced inhibition of spinal motor neurons, therefore leading to RSWA. 27 In addition to the brainstem, abnormal activation of the motor cortex during REM sleep also contributes to RBD. 28 Given the restored motor flexibility in patients with PD during RBD, it is proposed that the basal ganglia loop could be bypassed during RBD movement. 6 7 The theory was further supported by several subsequent studies. ...
Background
Rapid eye movement (REM) sleep behaviour disorder (RBD) is one of the most common sleep problems and represents a key prodromal marker in Parkinson’s disease (PD). It remains unclear whether and how basal ganglia nuclei, structures that are directly involved in the pathology of PD, are implicated in the occurrence of RBD.
Method
Here, in parallel with whole-night video polysomnography, we recorded local field potentials from two major basal ganglia structures, the globus pallidus internus and subthalamic nucleus, in two cohorts of patients with PD who had varied severity of RBD. Basal ganglia oscillatory patterns during RBD and REM sleep without atonia were analysed and compared with another age-matched cohort of patients with dystonia that served as controls.
Results
We found that beta power in both basal ganglia nuclei was specifically elevated during REM sleep without atonia in patients with PD, but not in dystonia. Basal ganglia beta power during REM sleep positively correlated with the extent of atonia loss, with beta elevation preceding the activation of chin electromyogram activities by ~200 ms. The connectivity between basal ganglia beta power and chin muscular activities during REM sleep was significantly correlated with the clinical severity of RBD in PD.
Conclusions
These findings support that basal ganglia activities are associated with if not directly contribute to the occurrence of RBD in PD. Our study expands the understanding of the role basal ganglia played in RBD and may foster improved therapies for RBD by interrupting the basal ganglia-muscular communication during REM sleep in PD.
... Jung and co-workers investigated CMC in patients with RBD and found significantly higher CMC value in patients with RBD compared to controls, suggesting an increased cortical locomotor drive (Jung et al., 2012). Similarly, CMC and corticocortical coherence (CCC) were higher in patients with iRBD compared to controls (Choi et al., 2021). ...
Parasomnias are due to a transient unstable state dissociation during entry into sleep, within sleep, or during arousal from sleep, and manifest with abnormal sleep related behaviors, perceptions, emotions, dreams, and autonomic nervous system activity.
Rapid eye movement (REM) parasomnias include REM sleep behavior disorder (RBD), isolated recurrent sleep paralysis and nightmare disorder. Neurophysiology is key for diagnosing these disorders and provides insights into their pathophysiology.
RBD is very well characterized from a neurophysiological point of view, also thank to the fact that polysomnography is needed for the diagnosis. Diagnostic criteria are provided by the American Academy of Sleep Medicine and video-polysomnography guidelines for the diagnosis by the International REM Sleep Behavior Disorder Study Group. Differences between the two sets of criteria are presented and discussed. Availability of polysomnography in RBD provides data on sleep electroencephalography (EEG), electrooculography (EOG) and electromyography (EMG). Sleep EEG in RBD shows e.g. changes in delta and theta power, in sleep spindles and K complexes. EMG during REM sleep is essential for RBD diagnosis and is an important neurodegeneration biomarker. RBD patients present alterations also in wake EEG, autonomic function, evoked potentials, and transcranial magnetic stimulation.
Clinical neurophysiological data on recurrent isolated sleep paralysis and nightmare disorder are scant. The few available data provide insights into the pathophysiology of these disorders, demonstrating a state dissociation in recurrent isolated sleep paralysis and suggesting alterations in sleep macro- and microstructure as well as autonomic changes in nightmare disorder.
... Impedances of electrodes were kept under 10 kΩ and the sampling rate was 200 Hz. A more detailed description of PSG data acquisition can be found in our previous paper (Choi et al., 2021). The sleep EEG was segmented into 30-s epochs, and each epoch was scored as one of five sleep stages (wake, N1, N2, N3, REM), as inspected by experts following the AASM manual (version 2.6; Berry et al., 2020). ...
Introduction
Sleep is an essential function to sustain a healthy life, and sleep dysfunction can cause various physical and mental issues. In particular, obstructive sleep apnea (OSA) is one of the most common sleep disorders and, if not treated in a timely manner, OSA can lead to critical problems such as hypertension or heart disease.
Methods
The first crucial step in evaluating individuals’ quality of sleep and diagnosing sleep disorders is to classify sleep stages using polysomnographic (PSG) data including electroencephalography (EEG). To date, such sleep stage scoring has been mainly performed manually via visual inspection by experts, which is not only a time-consuming and laborious process but also may yield subjective results. Therefore, we have developed a computational framework that enables automatic sleep stage classification utilizing the power spectral density (PSD) features of sleep EEG based on three different learning algorithms: support vector machine, k-nearest neighbors, and multilayer perceptron (MLP). In particular, we propose an integrated artificial intelligence (AI) framework to further inform the risk of OSA based on the characteristics in automatically scored sleep stages. Given the previous finding that the characteristics of sleep EEG differ by age group, we employed a strategy of training age-specific models (younger and older groups) and a general model and comparing their performance.
Results
The performance of the younger age-specific group model was similar to that of the general model (and even higher than the general model at certain stages), but the performance of the older age-specific group model was rather low, suggesting that bias in individual variables, such as age bias, should be considered during model training. Our integrated model yielded an accuracy of 73% in sleep stage classification and 73% in OSA screening when MLP algorithm was applied, which indicates that patients with OSA could be screened with the corresponding accuracy level only with sleep EEG without respiration-related measures.
Discussion
The current outcomes demonstrate the feasibility of AI-based computational studies that when combined with advances in wearable devices and relevant technologies could contribute to personalized medicine by not only assessing an individuals’ sleep status conveniently at home but also by alerting them to the risk of sleep disorders and enabling early intervention.
... 124 These findings have been recently confirmed and extended by an independent study in which muscle atonia index, CMC, and cortico-cortical coherence revealed specific findings both in PDRBD and in iRBD groups. 125 Lastly, some studies assessed psychophysiologic parameters, eg, through the active and passive oddball P300 paradigm. 126 In iRBD, no difference was noted between patients and matched controls, at least at early-middle stages of the disease. ...
Rapid eye movement (REM) sleep behavior disorder (RBD) is the result of the loss of physiological inhibition of muscle tone during REM sleep, characterized by dream-enacting behavior and widely recognized as a prodromal manifestation of alpha-synucleinopathies. Indeed, patients with isolated RBD (iRBD) have an extremely high estimated risk to develop a neurodegenerative disease after a long follow up. Nevertheless, in comparison with PD patients without RBD (PDnoRBD), the occurrence of RBD in the context of PD (PDRBD) seems to identify a unique, more malignant phenotype, characterized by a more severe burden of disease in terms of both motor and non-motor symptoms and increased risk for cognitive decline. However, while some medications (eg, melatonin, clonazepam, etc.) and non-pharmacological options have been found to have some therapeutic benefits on RBD there is no available treatment able to modify the disease course or, at least, slow down the neurodegenerative process underlying phenoconversion. In this scenario, the long prodromal phase may allow an early therapeutic window and, therefore, the identification of multimodal biomarkers of disease onset and progression is becoming increasingly crucial. To date, several clinical (motor, cognitive, olfactory, visual, and autonomic features) neurophysiological, neuroimaging, biological (biofluids or tissue biopsy), and genetic biomarkers have been identified and proposed, also in combination, as possible diagnostic or prognostic markers, along with a potential role for some of them as outcome measures and index of treatment response. In this review, we provide an insight into the present knowledge on both existing and future biomarkers of iRBD and highlight the difference with PDRBD and PDnoRBD, including currently available treatment options.
Study Objectives
This study aims to analyze phase-amplitude coupling (PAC) patterns during rapid eye movement (REM) sleep in patients with isolated REM sleep behavior disorder (iRBD), compared with demography-matched healthy control (HC) participants.
Methods
At baseline, electroencephalogram data from 13 iRBD patients and 10 HCs during REM sleep were analyzed. During follow-up, 4 patients (converters) later converted to alpha-synucleinopathies. Phasic and tonic REM states were determined by eye movement in 3-second epochs. PAC was compared between the groups, and correlations with clinical indicators were investigated. Additionally, the contribution of each electrode to PAC components was assessed.
Results
Patients with iRBD exhibited increased delta (1-3 Hz)-gamma (30-50 Hz) PAC only during the phasic REM state, but not during the tonic state, compared to the HCs (p < 0.05). Elevated PAC in patients negatively correlated with the REM atonia index (p = 0.011) and olfactory function (p = 0.038). Increase PACs were predominent in the fronto-temporo-occipital regions (corrected p < 0.05). Furthermore, patients showed reduced gamma-amplitude contributions of the parietal region (corrected p < 0.05). This reduction exhibited a progressively decreasing trend from HC to non-converters, and further to converters (p for trend = 0.044).
Conclusions
Our findings suggest PAC patterns during REM sleep could provide pathophysiological insights for iRBD. The widespread increase of PAC and reduced gamma-amplitude contribution in the parietal region suggest PAC during phasic REM sleep as potential biomarkers for disease progression in iRBD.
Olfactory impairment and rapid eye movement sleep behaviour disorder (RBD) are prodromal symptoms of Parkinson's disease (PD) that may be associated with each other. This review aims to investigate the significance of olfaction in the diagnosis and prognosis of patients with RBD and to assess moderating factors affecting olfactory performance. We searched articles on olfaction in RBD and PD in five electronic databases. We identified 32 studies for the systematic review and used 28 of those, including 2858 participants for meta-analysis. Results revealed significant deficits in odour identification (g=−1.80; 95% CI: −2.17 to −1.43), threshold (g=−1.29; 95% CI: −1.67 to −0.91), discrimination (g=−1.08; 95% CI: −1.28 to −0.87) and overall olfactory function (g=−1.64; 95% CI: −1.94 to −1.35) in patients with RBD. Except for the Unified Parkinson's Disease Rating Scale Part III scores, none of the known moderating variables (including age, sex, disease duration and years of education) accounted for the olfactory function heterogeneity in patients with RBD. We identified similar olfactory impairments in patients with RBD and patients with PD (either with or without underlying RBD). These findings suggest that olfactory impairment may be a sensitive and stable diagnostic biomarker of RBD and appears to be useful for identifying patients with idiopathic RBD at high risk for early conversion to PD.
