Electrophysiological correlates of dream recall during REM sleep: evidence from multiple awakenings and within-subjects design

Purpose: In the current study, we aimed to investigate the EEG correlates of dream recall (DR) monitoring both the homeostatic and state-trait like factors. We assessed the influence of the time of night on the EEG correlates of DR from REM sleep. Specifically, we tested the continuity-hypothesis (on the theta EEG band) and the activation-hypothesis (on the delta and beta bands). Methods: Twenty-seven subjects underwent polysomnography with multiple provoked awakenings during REM sleep. Only the subjects showing combinations of dream recall (REC) and non-REC (NREC) conditions in both first (1st– 2nd sleep cycle) and second (3rd– 4th sleep cycle) part of the night were included in the analyses. The final sample was composed of 10 subjects (mean age 24± 0.70). EEG power spectra of the 5-min of REM sleep preceding each awakening were computed by a fast Fourier transform. The following frequency bands were considered: delta (0.50– 4.75 Hz), theta (5.00– 7.75 Hz), and beta (16.00– 24.75 Hz). We also calculated the delta/beta power ratio as an integrated EEG index of activation. Results: The 2× 2 within-subjects ANOVA recall × time revealed: a) no significant effect for time and no interaction; b) significant differences over the occipital area in the beta band; c) significant differences over the parietal area for the activation index values. Overall, the results indicated that DR is associated with higher activation regardless of homeostatic pressure across the night of sleep. Conclusion: In line with recent findings, we have shown that DR is predicted by desynchronized EEG activity during REM sleep, providing clear evidence in favor of the activation-hypothesis. We have also confirmed that the EEG pattern of DR can be ascribed to state-like factors. Further studies should assess whether homeostatic modulation may interact with some dream features and the related EEG predictors

The Influence of Sleep Quality, Vigilance, and Sleepiness on Driving-Related Cognitive Abilities: A Comparison between Young and Older Adults

Background: Driving performance is strongly vulnerable to drowsiness and vigilance fluctuations. Excessive sleepiness may alter concentration, alertness, and reaction times. As people age, sleep undergoes some changes, becoming fragmented and less deep. However, the effects of these modifications on daily life have not been sufficiently investigated. Recently, the assessment of sleepiness became mandatory in Europe for people at risk who need the driving license release. Moreover, considering the expectation that people around the world are rapidly aging, it is necessary to investigate the relationships between senescence sleep changes, vigilance levels, and driving-related cognitive skills. Method: 80 healthy subjects (40 young adults and 40 elders) participated in the study. Sleep quality, sleepiness, and vigilance levels were assessed through the Pittsburgh Sleep Quality Index, the Karolinska Sleepiness Scale, the Epworth Sleepiness Scale, and the Psychomotor Vigilance Task (PVT). Driving-related cognitive abilities were assessed through Vienna Test System TRAFFIC, investigating selective attention, tachistoscopic perception, and risk assumption. Results: 2 × 2 between-subject ANOVAs showed less habitual sleep efficiency and worse performances in PVT in the older group. Unexpectedly, younger subjects show higher selfrated sleepiness. Moreover, older adults have lower performance in attention and perception tests, but they appear to be more cautious in situations involving traffic. Finally, the multiple regressions show age to be the only robust predictor of cognitive driving-related abilities. Conclusions: This is the first study that investigates the relationships among sleepiness/vigilance and specific drivingrelated cognitive skills on a sufficiently large sample. Nevertheless, the study should be considered preliminary and does not allow us to understand how specific changes in sleep architecture impact performances in the elders’ everyday life and, specifically, on driving skills