Nocturnal eye movements in patients with idiopathic rapid eye movement sleep behaviour disorder and patients with Parkinson’s disease

Christensen, Julie Anja Engelhard; Cesari, Matteo; Pizza, Fabio; Antelmi, Elena; Frandsen, Rune; Plazzi, Giuseppe; Jennum, Poul

doi:10.1111/jsr.13125

Cited by 5 publications

(5 citation statements)

References 34 publications

(49 reference statements)

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“…Similar abnormalities e.g. reduced sleep spindle density and morphology [13], [19], altered eye movements [14]- [16], and changes in macro and micro sleep stability [17], [18], [20] have been observed also in PD and PD+RBD patients.…”

Section: Introductionsupporting

confidence: 59%

“…Neuroanatomical abnormalities [5]- [7] in PD and iRBD affect the structure of sleep, which can be measured as changes in electrophysiological signals [8], [9]. Most notably, in comparison to controls, iRBD patients show a slowing the electroencephalography (EEG) [10], [11], a decrease in CAP rate and index [12], changed sleep spindle density [13], nocturnal eye movement frequency and morphology [14]- [16] and changes in both non-REM and REM sleep stability [17], [18]. Similar abnormalities e.g.…”

Section: Introductionmentioning

confidence: 99%

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Arousal characteristics in patients with Parkinson’s disease and isolated rapid eye movement sleep behavior disorder

Brink-Kjær

Cesari

Sixel‐Döring

et al. 2021

Sleep

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Study objectives Patients diagnosed with isolated rapid eye movement (REM) sleep behavior disorder (iRBD) and Parkinson’s disease (PD) have altered sleep stability reflecting neurodegeneration in brainstem structures. We hypothesize that neurodegeneration alters the expression of cortical arousals in sleep. Methods We analyzed polysomnography data recorded from 88 healthy controls (HC), 22 iRBD patients, 82 de novo PD patients without RBD and 32 with RBD (PD+RBD). These patients were also investigated at a 2-year follow-up. Arousals were analyzed using a previously validated automatic system, which used a central EEG lead, electrooculography, and chin electromyography. Multiple linear regression models were fitted to compare group differences at baseline and change to follow-up for arousal index (ArI), shifts in electroencephalographic signals associated with arousals, and arousal chin muscle tone. The regression models were adjusted for known covariates affecting the nature of arousal. Results In comparison to HC, patients with iRBD and PD+RBD showed increased ArI during REM sleep and their arousals showed a significantly lower shift in α-band power at arousals and a higher muscle tone during arousals. In comparison to HC, the PD patients were characterized by a decreased ArI in NREM sleep at baseline. ArI during NREM sleep decreased further at the 2-year follow-up, although not significantly Conclusions Patients with PD and iRBD present with abnormal arousal characteristics as scored by an automated method. These abnormalities are likely to be caused by neurodegeneration of the reticular activation system due to alpha-synuclein aggregation.

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Section: Introductionsupporting

confidence: 59%

Section: Introductionmentioning

confidence: 99%

Arousal characteristics in patients with Parkinson’s disease and isolated rapid eye movement sleep behavior disorder

Brink-Kjær

Cesari

Sixel‐Döring

et al. 2021

Sleep

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“…The oculomotor system may be affected in patients with neurodegenerative disorders, and could be affected in prodromal stages such as RBD as eye movement are partially controlled by brainstem neurons. In line with this, a significantly lower frequency of nocturnal eye movements during nocturnal wakefulness and significantly higher frequency of eye movements during N2 sleep was reported in patients with iRBD as well in patients with Parkinson’s disease and RBD ( Christensen et al, 2021 ).…”

Section: Rem Sleep Behavior Disordersupporting

confidence: 74%

Clinical neurophysiology of REM parasomnias: Diagnostic aspects and insights into pathophysiology

Bergmann,

Högl,

Stefani

2024

Clinical Neurophysiology Practice

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“…Furthermore, PSG-based diagnosis is currently based on the combination of RSWA and clinical history of dreamenactment or, alternatively, evidence of complex behaviors and/or vocalizations during REM sleep identified on PSG video recordings, per the American Academy of Sleep Medicine guidelines [6]. However, recent studies suggest that RBD may have a wider range of neurophysiological abnormalities beyond REM sleep that could be detected on PSG, such as loss of hypotonia during during non-REM (NREM) sleep [7], changes in resting state EEG [8], ] including micro-sleep event abnormalities [9], abnormal EEG oscillations in NREM [10], EOG abnormalities [11], and changes in autonomic activity, e.g. heart rate variability (HRV) [12].…”

Section: Motivationmentioning

confidence: 99%

SViT: A Spectral Vision Transformer for the Detection of REM Sleep Behavior Disorder

Gunter

Brink-Kjær

Mignot

et al. 2023

IEEE J. Biomed. Health Inform.

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REM sleep behavior disorder (RBD) is a parasomnia with dream enactment and presence of REM sleep without atonia (RSWA). RBD diagnosed manually via polysomnography (PSG) scoring, which is time intensive. Isolated RBD (iRBD) is also associated with a high probability of conversion to Parkinson's disease. Diagnosis of iRBD is largely based on clinical evaluation and subjective PSG ratings of REM sleep without atonia. Here we show the first application of a novel spectral vision transformer (SViT) to PSG signals for detection of RBD and compare the results to the more conventional convolutional neural network architecture. The vision-based deep learning models were applied to scalograms (30 or 300 second windows) of the PSG data (EEG, EMG and EOG) and the predictions interpreted. A total of 153 RBD (96 iRBD and 57 RBD with PD) and 190 controls were included in the study and 5-fold bagged ensemble was used. Model outputs were analyzed per-patient (averaged), with regards to sleep stage, and the SViT was interpreted using integrated gradients. Models had a similar per-epoch test F1 score. However, the vision transformer had the best per-patient performance, with an F1 score 0.87. Training the SViT on channel subsets, it achieved an F1 score of 0.93 on a combination of EEG and EOG. EMG is thought to have the highest diagnostic yield, but interpretation of our model showed that high relevance was placed on EEG and EOG, indicating these channels could be included for diagnosing RBD.

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Nocturnal eye movements in patients with idiopathic rapid eye movement sleep behaviour disorder and patients with Parkinson’s disease

Cited by 5 publications

References 34 publications

Arousal characteristics in patients with Parkinson’s disease and isolated rapid eye movement sleep behavior disorder

Arousal characteristics in patients with Parkinson’s disease and isolated rapid eye movement sleep behavior disorder

Clinical neurophysiology of REM parasomnias: Diagnostic aspects and insights into pathophysiology

SViT: A Spectral Vision Transformer for the Detection of REM Sleep Behavior Disorder

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