Spindle Oscillations in Sleep Disorders: A Systematic Review

Abstract

Measurement of sleep microarchitecture and neural oscillations is an increasingly popular technique for quantifying EEG sleep activity. Many studies have examined sleep spindle oscillations in sleep-disordered adults; however reviews of this literature are scarce. As such, our overarching aim was to critically review experimental studies examining sleep spindle activity between adults with and without different sleep disorders. Articles were obtained using a systematic methodology with a priori criteria. Thirty-seven studies meeting final inclusion criteria were reviewed, with studies grouped across three categories: insomnia, hypersomnias, and sleep-related movement disorders (including parasomnias). Studies of patients with insomnia and sleep-disordered breathing were more abundant relative to other diagnoses. All studies were cross-sectional. Studies were largely inconsistent regarding spindle activity differences between clinical and nonclinical groups, with some reporting greater or less activity, while many others reported no group differences. Stark inconsistencies in sample characteristics (e.g., age range and diagnostic criteria) and methods of analysis (e.g., spindle bandwidth selection, visual detection versus digital filtering, absolute versus relative spectral power, and NREM2 versus NREM3) suggest a need for greater use of event-based detection methods and increased research standardization. Hypotheses regarding the clinical and empirical implications of these findings, and suggestions for potential future studies, are also discussed.

Intra‐individual stability of NREM sleep quantitative EEG measures in obstructive sleep apnea

“…Traditional clinical sleep parameters are insufficient to predict clinical daytime impairments in OSA, like driving risk (Vakulin et al, 2016). While research evaluating the correlation between these brain biomarkers and daytime impairments in patients with OSA is limited, there is strong evidence showing that spindle oscillations are impaired (Weiner & Dang-Vu, 2016) and that SWA is reduced in OSA (Himanen et al, 2004) This study demonstrated clinically significant intra-individual stability of EEG biomarkers in the delta and sigma bands across 2 nights in patients with OSA. This may be of use to future studies wishing to evaluate qEEG as a biomarker from a single night of recording.…”

“…A recent study examining the relationship between sleep quantitative (q)EEG and cognitive performance in OSA participants found that reduced SWA during NREM sleep correlates with poorer performance on a driving simulator task (Vakulin et al., ). Spindle frequency activity or sigma power in NREM sleep is decreased in OSA (Ondze, Espa, Dauvilliers, Billiard, & Besset, ; Weiner & Dang‐Vu, ). While no studies have directly measured the relationship between spindle frequency activity and memory in OSA, recent studies have shown increased spindle activity in OSA participants receiving continuous positive airway pressure (CPAP) therapy (Lafortune et al., ; Saunamäki, Huupponen, Loponen, & Himanen, ; Yetkin & Aydogan, ).…”

“…Spindle frequency activity or sigma power in NREM sleep is decreased in OSA (Ondze, Espa, Dauvilliers, Billiard, & Besset, 2003;Weiner & Dang-Vu, 2016). While no studies have directly measured the relationship between spindle frequency activity and memory in OSA, recent studies have shown increased spindle activity in OSA participants receiving continuous positive airway pressure (CPAP) therapy (Lafortune et al, 2014;Saunamäki, Huupponen, Loponen, & Himanen, 2017;Yetkin & Aydogan, 2018).…”

The Accuracy, Night-to-Night Variability, and Stability of Frontopolar Sleep Electroencephalography Biomarkers

“…Further research is required to compare the automated sleep spindle detection by this approach with automated routines applied to more conventional EEG spindle detection sites, 38 and to evaluate the changes in this measure as it relates to age, sex, and neurodegeneration. [3][4][5]39 A limitation of this study was the relatively dichotomous age representation of our healthy controls with very few participants in this cohort being between the ages of 40 and 60 years. Cognizant of the limitation, we excluded those older than 70 years when establishing the sleep spindle reference values.…”

“…2 Emerging evidence also suggests that sleep architecture and sleep continuity (ie, sleep biomarkers) may be beneficial in monitoring brain health in the setting of management of neurodegenerative disorders. For example, sleep spindle characteristics during non-rapid eye movement (NREM) sleep have been associated with cognitive decline in patients with Parkinson disease, [3][4][5] and reduced slow wave sleep has been associated with increased beta amyloid (directly linked to Alzheimer disease) concentrations in the cerebrospinal fluid. 6 Because sleep spindles and slow wave sleep are believed to be associated with the metabolic clearance systems of the brain, 7 it is now argued that the routine monitoring of change in these measures are useful in evaluating the risk for, or progression of neurodegeneration.…”