Multivariate prediction of cognitive performance from the sleep electroencephalogram

Sleep-spindles as a marker of attention and intelligence in dogs

The sleep spindle-generating thalamo-cortical circuitry supports attention capacity in awake humans and animals, but using sleep spindles to predict differences in attention has not been tried in either. Of the more commonly examined cognitive correlates of spindle occurrence and amplitude, post-sleep recall, and general intelligence, only post-sleep recall had been studied in dogs, rats and mice. Here, we examined a sample of companion dogs (N = 58) for whom polysomnographic recordings and several cognitive tests were performed on two occasions each, with a three-month break in-between. Five of the tests were used to extract a factor analogous to human g (general mental ability). A sixth test in the battery measured sustained attention. Both attention and g-factor scores were linked to higher slow spindle occurrence and absolute sigma power detected in polysomnographic recordings over the central electrode. These effects persisted across measurement occasions. Higher intrinsic spindle frequency was, in turn, linked to lower g-factor scores but displayed no relationship with attention scores. The overlap in localization and direction for the effects of slow spindle density (spindles/minute) and sigma power supports that they tap into the same underlying cognition-relevant aspects of spindling. Given earlier large sample and meta-analysis validations of sigma power as a reliable predictor of cognitive performance in humans, we thus conclude that the currently handled method for quantifying spindle density in dogs indeed measures cognition-relevant spindle activity by virtue of its agreement with the sigma power alternative.

Association Between EEG Power During Sleep and Attention Levels in Patients with Major Depressive Disorder

Purpose

Major depressive disorder (MDD) is associated with cognitive impairment through unclear mechanisms. We examined the relationship between sleep electroencephalogram (EEG) power and attention level in MDD.

Patients and Methods

Forty-seven untreated patients with MDD and forty-seven age- and sex-matched controls were included. We examined relative EEG power during non-rapid eye movement (NREM) sleep and rapid eye movement (REM) sleep by fast Fourier transform. The Attention Network Test (ANT) was performed to evaluate attention levels.

Results

Compared to controls, patients with MDD had lower theta power during NREM (P = 0.018) and REM (P = 0.002) sleep, while higher beta power (P = 0.050) during NREM sleep and delta power (P = 0.018) during REM sleep. Regarding attention level, patients with MDD had lower levels of accuracy (P = 0.021), longer mean reaction time (P < 0.001), poorer manifestations of the alerting effect (P = 0.038) and worse executive control (P = 0.048). Moreover, decreased theta power during NREM sleep was correlated with worsened accuracy (β = 0.329, P = 0.040), decreased theta power during REM sleep was correlated with worsened alerting effect (β = 0.355, P = 0.020), and increased delta power during REM sleep was correlated with longer mean reaction time (β = 0.325, P = 0.022) in patients with MDD. No association between ANT performance and other frequency bands was observed in patients with MDD.

Conclusion

Our findings suggest that patients with MDD manifest impaired selective attention function that is associated with decreased theta power during NREM/REM sleep and increased delta power during REM sleep.

Sleep alterations as a function of 88 health indicators

BACKGROUND

Alterations in sleep have been described in multiple health conditions and as a function of several medication effects. However, evidence generally stems from small univariate studies. Here, we apply a large-sample, data-driven approach to investigate patterns between in sleep macrostructure, quantitative sleep EEG, and health.

METHODS

We use data from the MrOS Sleep Study, containing polysomnography and health data from a large sample (N = 3086) of elderly American men to establish associations between sleep macrostructure, the spectral composition of the electroencephalogram, 38 medical disorders, 2 health behaviors, and the use of 48 medications.

RESULTS

Of sleep macrostructure variables, increased REM latency and reduced REM duration were the most common findings across health indicators, along with increased sleep latency and reduced sleep efficiency. We found that the majority of health indicators were not associated with objective EEG power spectral density (PSD) alterations. Associations with the rest were highly stereotypical, with two principal components accounting for 85-95% of the PSD-health association. PC1 consists of a decrease of slow and an increase of fast PSD components, mainly in NREM. This pattern was most strongly associated with depression/SSRI medication use and age-related disorders. PC2 consists of changes in mid-frequency activity. Increased mid-frequency activity was associated with benzodiazepine use, while decreases were associated with cardiovascular problems and associated medications, in line with a recently proposed hypothesis of immune-mediated circadian demodulation in these disorders. Specific increases in sleep spindle frequency activity were associated with taking benzodiazepines and zolpidem. Sensitivity analyses supported the presence of both disorder and medication effects.

CONCLUSIONS

Sleep alterations are present in various health conditions.