Background Suicide is a major public health concern, and a barrier to reducing the suicide rate is the lack of objective predictors of risk. The present study considers whether quantitative sleep electroencephalography (EEG) may be a neurobiological correlate of suicidal ideation. Methods Participants included 84 (45 female, mean age=26.6) adults diagnosed with major depressive disorder (MDD). The item that measures thoughts of death or suicide on the Quick Inventory of Depressive Symptomatology (QIDS) was used to classify 47 participants as low suicidal ideation (24 females, mean age=26.1) and 37 as high suicidal ideation (21 females, mean age=27.3). Data were obtained from archival samples collected at the University of Michigan and University of Texas Southwestern Medical Center between 2004 and 2012. Sleep EEG was quantified using power spectral analysis, and focused on alpha, beta, and delta frequencies. Results Results indicated that participants with high compared to low suicidal ideation experienced 1) increased fast frequency activity, 2) decreased delta activity, and 3) increased alpha-delta sleep after adjusting for age, sex, depression, and insomnia symptoms. Limitations Limitations include the exclusion of imminent suicidal intent, a single suicidal ideation item, and cross-sectional archival data. Conclusions This is one of the first studies to provide preliminary support that electrophysiological brain activity during sleep is associated with increased suicidal ideation in MDD, and may point toward central nervous system (CNS) hyperarousal during sleep as a neurobiological correlate of suicidal ideation.
SUMMARYIndividuals with major depressive disorder typically exhibit sleep electroencephalograpy abnormalities which have been shown to vary by sex. Recent research has shown that depressed males display deficits in slow wave sleep and delta electroencephalograph (EEG) activity that are not apparent in depressed females. This may suggest that males and females with depression vary with respect to their homeostatic regulation of sleep. Utilizing archival data, the present study examined the effects of a 3-h sleep delay, which represents a mild sleep challenge, on slow wave activity in healthy controls and individuals with depression. All participants slept in the laboratory for three sequential nights. On the third night in the laboratory, the participants' bedtime was delayed by 3 h. Slow wave activity was calculated utilizing power spectral analysis and compared across groups. Following the sleep delay, males with depression exhibited the lowest slow wave activity compared to all other groups. These results may suggest that males with depression are at a greater risk for homeostatic dysregulation than females, and may require specialized intervention. IN TROD UCTI ONSleep disturbance is one of the central symptoms reported by most individuals with major depressive disorder (MDD; Mendlewicz, 2009). Years of research looking at differences in sleep between healthy subjects and those diagnosed with MDD have greatly increased our understanding of the qualitative difference in sleep in those with MDD. With regard to the most common differences in visually scored sleep variables, research has shown consistently that individuals with MDD have more proportionate time awake, a measure of sleep efficiency, shorter time to enter REM sleep (REM latency), greater amount of REM sleep, increased amounts of rapid eye movements (REM density) and decreases in slow wave sleep compared to healthy controls. Understanding these qualitative differences has been an essential first step; however, newer methodology, including quantitative electroencephalograph (EEG) analysis, may allow us to assess more clearly the differences in sleep regulation in MDD. Borb ely and Wirz-Justice (1982) suggested that the sleep disturbances occurring in individuals with MDD, including delayed sleep onset and difficulty maintaining sleep, were a result of a reduced drive for sleep (process S). This model also suggests that those with MDD would present reduced slow wave sleep during the first portion of the night, when slow wave activity is typically at its highest. Kupfer et al. (1986) demonstrated that there was indeed a reduction in slow wave EEG activity in NREM sleep (SWA) in those with MDD; however, they also noted that there was only a very small relationship between time awake and reduced delta activity in those with MDD. Utilizing quantitative EEG analyses, Armitage et al. (1992Armitage et al. ( , 1995Armitage et al. ( , 1997Armitage et al. ( , 2000a have also shown that individuals with MDD exhibit an abnormal distribution of SWA across the nigh...
Study Objectives Sleep spindles, a defining feature of stage N2 sleep, are maximal at central electrodes and are found in the frequency range of the EEG (sigma 11-16Hz) that is known to be heritable. However, relatively little is known about the heritability of spindles. Two recent studies investigating the heritability of spindles reported moderate heritability, but with conflicting results depending on scalp location and spindle type. The present study aimed to definitively assess the heritability of sleep spindle characteristics. Methods We utilized the polysomnography data of 58 monozygotic and 40 dizygotic same-sex twin pairs to identify heritable characteristics of spindles at C3/C4 in stage N2 sleep including density, duration, peak-to-peak amplitude, and oscillation frequency. We implemented and tested a variety of spindle detection algorithms and used two complementary methods of estimating trait heritability. Results We found robust evidence to support strong heritability of spindles regardless of detector method (h 2>0.8). However not all spindle characteristics were equally heritable, and each spindle detection method produced a different pattern of results. Conclusions The sleep spindle in stage N2 sleep is highly heritable, but the heritability differs for individual spindle characteristics and depends on the spindle detector used for analysis.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.