Impact of acute sleep restriction on cerebral glucose metabolism during recovery non-rapid eye movement sleep among individuals with primary insomnia and good sleeper controls

Towards the neurobiology of insomnia: A systematic review of neuroimaging studies

Insomnia disorder signifies a major public health concern. The development of neuroimaging techniques has permitted to investigate brain mechanisms at a structural and functional level. The present systematic review aims at shedding light on functional, structural, and metabolic substrates of insomnia disorder by integrating the available published neuroimaging data. The databases PubMed, PsycARTICLES, PsycINFO, CINAHL and Web of Science were searched for case-control studies comparing neuroimaging data from insomnia patients and healthy controls. 85 articles were judged as eligible. For every observed finding of each study, the effect size was calculated from standardised mean differences, statistic parameters and figures, showing a marked heterogeneity that precluded a comprehensive quantitative analysis. From a qualitative point of view, considering the findings of significant group differences in the reported regions across the articles, this review highlights the major involvement of the anterior cingulate cortex, thalamus, insula, precuneus and middle frontal gyrus, thus supporting some central themes in the debate on the neurobiology of and offering interesting insights into the psychophysiology of sleep in this disorder.

EEG spectral analysis in insomnia disorder: A systematic review and meta-analysis

Insomnia disorder (ID) has become the second-most common mental disorder. Despite burgeoning evidence for increased high-frequency electroencephalography (EEG) activity and cortical hyperarousal in ID, the detailed spectral features of this disorder during wakefulness and different sleep stages remain unclear. Therefore, we adopted a meta-analytic approach to systematically assess existing evidence on EEG spectral features in ID. Hedges's g was calculated by 148 effect sizes from 24 studies involving 977 participants. Our results demonstrate that, throughout wakefulness and sleep, patients with ID exhibited increased beta band power, although such increases sometimes extended into neighboring frequency bands. Patients with ID also exhibited increased theta and gamma power during wakefulness, as well as increased alpha and sigma power during rapid eye movement (REM) sleep. In addition, ID was associated with decreased delta power and increased theta, alpha, and sigma power during NREM sleep. The EEG measures of absolute and relative power have similar sensitivity in detecting spectral features of ID during wakefulness and REM sleep; however, relative power appeared to be a more sensitive biomarker during NREM sleep. Our study is the first statistics-based review to quantify EEG power spectra across stages of sleep and wakefulness in patients with ID.

Fidelity of Information Processing on a Psychomotor Vigilance Task Predicts Changes in Self-Reported Sleepiness Ratings

INTRODUCTION

Daytime sleepiness is a common problem. Although sleepiness is primarily assessed at the self-report unit of analysis, factors that contribute to an individual's experience and report of sleepiness remain poorly understood. While sleepiness is known to impact vigilance performance, the impact of vigilance performance on sleepiness reports is less well understood. We aimed to explore how performance on a psychomotor vigilance task (PVT) relates to changes in self-reported sleepiness in a rested condition.

METHODS

Participants were 66 adults (Mdn=23, range 18-49 years old), 47% female, 88% white, with a wide range of insomnia symptoms. Participants rated their sleepiness on a scale from 1 (not sleepy) to 10 (extremely sleepy) at the start (pre) and the end (post) of a 10-minute computerized PVT. Ordinal regression determined whether mean reciprocal reaction time, a measure of overall performance, or the log-transformed signal-to-noise ratio (LSNR), a measure of fidelity of information processing, predicted post-sleepiness, adjusting for pre-sleepiness, insomnia, and potential confounds.

RESULTS

Lower LSNR predicted greater change in sleepiness (pre-to-post PVT) and higher post-sleepiness even after adjusting for pre-sleepiness, mean reciprocal reaction time, insomnia, and other potential confounds (p<0.05).

DISCUSSION

When adjusting for insomnia symptoms and potential confounds, participants with lower fidelity of information processing reported higher sleepiness than they had reported at the start of the PVT. Possible mechanisms and explanations are discussed in relation to a 3-factor model of sleep-wake states. This line of research may contribute to innovative approaches to assessing and treating sleepiness.