Sleep restriction and age effects on waking alpha EEG activity in adolescents

Aperiodic components and aperiodic-adjusted alpha-band oscillations in children with ADHD

This study aimed to investigate the aperiodic properties and aperiodic-adjusted alpha-band oscillations in children with ADHD, focusing on the influence of different scalp regions and lateralization on these neural correlates. Sixty-two ADHD children and 52 typical developing children aged 6-12 years were enrolled. EEG recordings were made with eyes closed for a minimum of 6 min. The 'FOOOF' was used to compute aperiodic parameters (exponent and offset), and aperiodic-adjusted alpha-band features including center frequency (CF), adjusted power (AP), and bandwidth (BW). Mixed-design ANOVAs were conducted with two between-subjects levels (ADHD and control groups) and two within-subjects' factors (lateralization and scalp region). ANCOVAs were conducted after accounting for sex and age. The ADHD group showed a significantly lower exponent compared to the control group, and this difference was not influenced significantly by factors like lateralization, scalp region, or sex. There were no notable distinctions between the groups for other measures. We noticed alpha-band CF tends to increase with age, while only frontal AP shows a significant positive correlation with age. Significant main effects of sex and lateralization were observed for offset, along with an interaction effect between sex and lateralization for CF. Our findings indicate that children aged 6-12 with ADHD have a markedly lower exponent, suggesting that this measure could potentially serve as a biomarker for ADHD. Future studies should consider factors such as age, sex, lateralization, and scalp region when investigating aperiodic and aperiodic-adjusted features.

The evaluation of cEEGrids for fatigue detection in aviation

Operator fatigue poses a major concern in safety-critical industries such as aviation, potentially increasing the chances of errors and accidents. To better understand this risk, there is a need for noninvasive objective measures of fatigue. This study aimed to evaluate the performance of cEEGrids, a type of ear-EEG, for fatigue detection by analyzing the alpha and theta power before and after sleep restriction in four sessions on two separate days, employing a within-participants design. Results were compared to traditional, highly validated methods: the Karolinska Sleepiness Scale (KSS) and Psychomotor Vigilance Task (PVT). After sleep restriction and an office workday, 12 participants showed increased alpha band power in multiple electrode channels, but no channels correlated with KSS scores and PVT response speed. These findings indicate that cEEGrids can detect differences in alpha power following mild sleep loss. However, it should be noted that this capability was limited to specific channels, and no difference in theta power was observed. The study shows the potential and limitations of ear-EEG for fatigue detection as a less invasive alternative to cap-EEG. Further design and electrode configuration adjustments are necessary before ear-EEG can be implemented for fatigue detection in the field.

Earlier Bedtime and Its Effect on Adolescent Sleep Duration

BACKGROUND AND OBJECTIVES

Sleep duration decreases by ∼10 minutes per year throughout adolescence. A circadian phase delay and changes in homeostatic sleep regulation enable adolescents to stay up later. We determine if teens are able to increase sleep duration by advancing bedtime and whether this ability changes with age.

METHODS

A younger cohort of 77 participants ranging in age from 9.9 to 16.2 years were studied annually for 3 years. An older cohort of 67 participants ranging in age from 15.0 to 20.6 years was studied only once. Annually, participants kept each of 3 different time in bed (TIB) schedules (7, 8.5, and 10 hours) for 4 consecutive nights. Participants kept their habitual weekday rise times; TIB was altered by advancing bedtimes. We report polysomnography-measured sleep durations from the fourth night of the TIB schedule.

RESULTS

Despite increases in sleep onset latency and wake after sleep onset, sleep duration increased with TIB as bedtime was advanced. Average (SE) sleep duration increased from 402.8 (1.6) minutes with 7 hours to 470.6 (2.1) minutes with 8.5 hours to 527.5 (3.0) minutes with 10 hours TIB. Sleep duration decreased with age (1.55 [0.48] minutes/year), but the TIB effect on sleep duration did not (TIB by age interaction, P = .42).

CONCLUSIONS

Adolescents can substantially increase sleep duration by advancing bedtime, and this ability does not change between ages 10 and 21 years. Additional research is needed to determine how to translate these findings from experiment-controlled sleep schedules to real-world sleep duration increases.