The electroencephalographic features of the sleep onset process and their experimental manipulation with sleep deprivation and transcranial electrical stimulation protocols

Spatiotemporal EEG dynamics of the sleep onset process in preadolescence

BACKGROUND

During preadolescence the sleep electroencephalography undergoes massive qualitative and quantitative modifications. Despite these relevant age-related peculiarities, the specific EEG pattern of the wake-sleep transition in preadolescence has not been exhaustively described.

METHODS

The aim of the present study is to characterize regional and temporal electrophysiological features of the sleep onset (SO) process in a group of 23 preadolescents (9-14 years) and to compare the topographical pattern of slow wave activity and delta/beta ratio of preadolescents with the EEG pattern of young adults.

RESULTS

Results showed in preadolescence the same dynamics known for adults, but with peculiarities in the delta and beta activity, likely associated with developmental cerebral modifications: the delta power showed a widespread increase during the SO with central maxima, and the lower bins of the beta activity showed a power increase after SO. Compared to adults, preadolescents during the SO exhibited higher delta power only in the slowest bins of the band: before SO slow delta activity was higher in prefrontal, frontal and occipital areas in preadolescents, and, after SO the younger group had higher slow delta activity in occipital areas. In preadolescents delta/beta ratio was higher in more posterior areas both before and after the wake-sleep transition and, after SO, preadolescents showed also a lower delta/beta ratio in frontal areas, compared to adults.

CONCLUSION

Results point to a general higher homeostatic drive for the developing areas, consistently with plastic-related maturational modifications, that physiologically occur during preadolescence.

Embracing sleep-onset complexity

Sleep is crucial for many vital functions and has been extensively studied. By contrast, the sleep-onset period (SOP), often portrayed as a mere prelude to sleep, has been largely overlooked and remains poorly characterized. Recent findings, however, have reignited interest in this transitional period and have shed light on its neural mechanisms, cognitive dynamics, and clinical implications. This review synthesizes the existing knowledge about the SOP in humans. We first examine the current definition of the SOP and its limits, and consider the dynamic and complex electrophysiological changes that accompany the descent to sleep. We then describe the interplay between internal and external processing during the wake-to-sleep transition. Finally, we discuss the putative cognitive benefits of the SOP and identify novel directions to better diagnose sleep-onset disorders.

Sleep in Healthy and Pathological Aging

Human sleep physiology is strongly affected by age [...].

Mapping general anesthesia states based on electro-encephalogram transition phases

Cortical electro-encephalography (EEG) served as the clinical reference for monitoring unconsciousness during general anesthesia. The existing EEG-based monitors classified general anesthesia states as underdosed, adequate, or overdosed, lacking predictive power due to the absence of transition phases among these states. In response to this limitation, we undertook an analysis of the EEG signal during isoflurane-induced general anesthesia in mice. Adopting a data-driven approach, we applied signal processing techniques to track θ- and δ-band dynamics, along with iso-electric suppressions. Combining this approach with machine learning, we successfully developed an automated algorithm. The findings of our study revealed that the dampening of the δ-band occurred several minutes before the onset of significant iso-electric suppression episodes. Furthermore, a distinct γ-frequency oscillation was observed, persisting for several minutes during the recovery phase subsequent to isoflurane-induced overdose. As a result of our research, we generated a map summarizing multiple brain states and their transitions, offering a tool for predicting and preventing overdose during general anesthesia. The transition phases identified, along with the developed algorithm, have the potential to be generalized, enabling clinicians to prevent inadequate anesthesia and, consequently, tailor anesthetic regimens to individual patients.

Mental fatigue assessment by an arbitrary channel EEG based on morphological features and LSTM-CNN

In order to achieve more sensitive mental fatigue assessment (MFA) based on an arbitrary channel EEG, this study proposed a series of feature extraction methods that combine mathematical morphology (MM), as well as an LSTM-CNN architecture. Firstly, 37 subjects had their resting-state EEGs collected at rested wakefulness (RW) and after 24 h of sleep deprivation (SD) using a 30-channel EEG acquisition device, the RW and SD groups were regarded as the negative and positive groups of mental fatigue, respectively, and the EEG collection were further categorized into two conditions: eye-opened state (EO) and eye-closed state (EC). Then, since MM can reflect the morphological characteristics of EEG rhythms and their potentials relatively independently of the time-frequency analysis and phase calculation, the MM methods were found to better reflect the mental fatigue after SD statistically, whether for single features (ANOVA: p<0.000001), multiple features (clustering by K-means, t-test: p<0.01), or time series feature spaces (calculating CD, t-test: p<0.01) of a single channel. Finally, the LSTM-CNN enhanced the generalization ability when dealing with different single-channel EEG by combining GRUs with convolutional layers: comparing the AUCs of different architectures for MFA based on an arbitrary channel, LSTM-CNN (0.992) > LSTM network (0.94) > CNN (0.831) > MLP (0.754). Moreover, the use of MM also improved the accuracy of analyzed architectures, and the true/false positive rate (TPR/FPR) of the LSTM-CNN architecture for MFA based on an arbitrary channel reached 97.024 %/3.497 %, which provided a feasible solution for the arbitrary channel EEG-based MFA.

The effects of bifrontal anodal transcranial direct current stimulation (tDCS) on sleepiness and vigilance in partially sleep-deprived subjects: A multidimensional study

In recent years, transcranial electrical stimulation techniques have demonstrated their ability to modulate our levels of sleepiness and vigilance. However, the outcomes differ among the specific aspects considered (physiological, behavioural or subjective). This study aimed to observe the effects of bifrontal anodal transcranial direct current stimulation. Specifically, we tested the ability of this stimulation protocol to reduce sleepiness and increase vigilance in partially sleep-deprived healthy participants. Twenty-three subjects underwent a within-subject sham-controlled stimulation protocol. We compared sleepiness and vigilance levels before and after the two stimulation conditions (active versus sham) by using behavioural (reaction-time task), subjective (self-report scales) and physiological (sleep-onset latency and electroencephalogram power [n = 20] during the Maintenance of Wakefulness Test) measures. We showed the efficacy of the active stimulation in reducing physiological sleepiness and preventing vigilance drop compared with the sham stimulation. Consistently, we observed a reduction of perceived sleepiness following the active stimulation for both self-report scales. However, the stimulation effect on subjective measures was not statistically significant probably due to the underpowered sample size for these measures, and to the possible influence of motivational and environmental factors. Our findings confirm the ability of this technique to influence vigilance and sleepiness, pointing out the potential for new treatment developments based on transcranial electrical stimulation.

Time Course of Motor Activity Wake Inertia Dissipation According to Age

The time course of motor activity sleep inertia (maSI) dissipation was recently investigated through actigraphy in an everyday life condition from middle childhood to late adulthood. Motor activity sleep inertia was dissipated in 70 min, and the sleep inertia phenomenon was more evident in younger participants than in older participants. The aim of the current secondary analysis of previously published data was to examine, within the same sample, the time course of motor activity wake inertia (maWI) dissipation, i.e., the motor pattern in the transition phase from wakefulness to sleep, according to age. To this end, an overall sample of 374 participants (215 females), ranging in age between 9 and 70 years old, was examined. Each participant was asked to wear an actigraph around their non-dominant wrist for one week. The variation in the motor activity pattern of the wake–sleep transition according to age was examined through functional linear modeling (FLM). FLM showed that motor activity wake inertia dissipated around 20 min after bedtime. Moreover, a lower age was significantly associated with greater motor activity within the last two hours of wakefulness and the first twenty minutes after bedtime. Overall, this pattern of results seems to suggest that maWI dissipation is comparable to that of maSI.

The Regional EEG Pattern of the Sleep Onset Process in Older Adults

Healthy aging is characterized by macrostructural sleep changes and alterations of regional electroencephalographic (EEG) sleep features. However, the spatiotemporal EEG pattern of the wake-sleep transition has never been described in the elderly. The present study aimed to assess the topographical and temporal features of the EEG during the sleep onset (SO) in a group of 36 older participants (59–81 years). The topography of the 1 Hz bins’ EEG power and the time course of the EEG frequency bands were assessed. Moreover, we compared the delta activity and delta/beta ratio between the older participants and a group of young adults. The results point to several peculiarities in the elderly: (a) the generalized post-SO power increase in the slowest frequencies did not include the 7 Hz bin; (b) the alpha power revealed a frequency-specific pattern of post-SO modifications; (c) the sigma activity exhibited only a slight post-SO increase, and its highest bins showed a frontotemporal power decrease. Older adults showed a generalized reduction of delta power and delta/beta ratio in both pre- and post-SO intervals compared to young adults. From a clinical standpoint, the regional EEG activity may represent a target for brain stimulation techniques to reduce SO latency and sleep fragmentation.

Age-Related Effect of Sleepiness on Driving Performance: A Systematic-Review

Background: Several studies highlighted that sleepiness affects driving abilities. In particular, road traffic injuries due to excessive daytime sleepiness are about 10–20%. Considering that aging is related to substantial sleep changes and the number of older adults with driving license is increasing, the current review aims to summarize recent studies on this issue. Further, we intend to provide insights for future research. Methods: From the 717 records screened, ten articles were selected and systematically reviewed. Results: Among the selected articles, (a) five studies investigated sleepiness only by self-reported standardized measures; (b) two studies assessed sleepiness also using a behavioral task; (c) three studies obtained objective measures by electroencephalographic recordings. Conclusions: The available literature on the topic reports several limitations. Overall, many findings converge in evidencing that older drivers are less vulnerable to sleep loss and sleepiness-related driving impairments than young adults. These discrepancies in sleepiness vulnerability between age groups may be ascribed to differences in subjects’ lifestyles. Moreover, it has been hypothesized that older adults self-regulate their driving and avoid specific dangerous situations. We believe that an easy protocol to objectively evaluate the vigilance level in elderly and young adults is required, and further studies are needed.

The distinctive sleep pattern of the human calcarine cortex: a stereo-electroencephalographic study

STUDY OBJECTIVES

The aim of this study was to describe the spontaneous electroencephalographic (EEG) features of sleep in the human calcarine cortex, comparing them with the well-established pattern of the parietal cortex.

METHODS

We analyzed presurgical intracerebral EEG activity in calcarine and parietal cortices during non-rapid eye movement (NREM) and rapid eye movement (REM) sleep in seven patients with drug-resistant focal epilepsy. The time course of the EEG spectral power and NREM vs REM differences was assessed. Sleep spindles were automatically detected. To assess homeostatic dynamics, we considered the first vs second half of the night ratio in the delta frequency range (0.5-4 Hz) and the rise rate of delta activity during the first sleep cycle.

RESULTS

While the parietal area showed the classically described NREM and REM sleep hallmarks, the calcarine cortex exhibited a distinctive pattern characterized by: (1) the absence of sleep spindles; (2) a large similarity between EEG power spectra of NREM and REM; and (3) reduced signs of homeostatic dynamics, with a decreased delta ratio between the first and the second half of the night, a reduced rise rate of delta activity during the first NREM sleep cycle, and lack of correlation between these measures.

CONCLUSIONS

Besides describing for the first time the peculiar sleep EEG pattern in the human calcarine cortex, our findings provide evidence that different cortical areas may exhibit specific sleep EEG pattern, supporting the view of sleep as a local process and promoting the idea that the functional role of sleep EEG features should be considered at a regional level.

Sleep-Based Interventions in Alzheimer's Disease: Promising Approaches from Prevention to Treatment along the Disease Trajectory

The multifactorial nature of Alzheimer’s disease (AD) has led scientific researchers to focus on the modifiable and treatable risk factors of AD. Sleep fits into this context, given the bidirectional relationship with AD confirmed by several studies over the last years. Sleep disorders appear at an early stage of AD and continue throughout the entire course of the pathology. Specifically, sleep abnormalities, such as more fragmented sleep, increase in time of awakenings, worsening of sleep quality and primary sleep disorders raise with the severity and progression of AD. Intervening on sleep, therefore, means acting both with prevention strategies in the pre-clinical phase and with treatments during the course of the disease. This review explores sleep disturbances in the different stages of AD, starting from the pre-clinical stage. Particular attention is given to the empirical evidence investigating obstructive sleep apnea (OSA) disorder and the mechanisms overlapping and sharing with AD. Next, we discuss sleep-based intervention strategies in the healthy elderly population, mild cognitive impairment (MCI) and AD patients. We mention interventions related to behavioral strategies, combination therapies, and bright light therapy, leaving extensive space for new and raising evidence on continuous positive air pressure (CPAP) treatment effectiveness. Finally, we clarify the role of NREM sleep across the AD trajectory and consider the most recent studies based on the promising results of NREM sleep enhancement, which use innovative experimental designs and techniques.

The why and how of sleep-dependent synaptic down-selection

Sleep requires that we disconnect from the environment, losing the ability to promptly respond to stimuli. There must be at least one essential function that justifies why we take this risk every day, and that function must depend on the brain being offline. We have proposed that this function is to renormalize synaptic weights after learning has led to a net increase in synaptic strength in many brain circuits. Without this renormalization, synaptic activity would become energetically too expensive and saturation would prevent new learning. There is converging evidence from molecular, electrophysiological, and ultrastructural experiments showing a net increase in synaptic strength after the major wake phase, and a net decline after sleep. The evidence also suggests that sleep-dependent renormalization is a smart process of synaptic down-selection, comprehensive and yet specific, which could explain the many beneficial effects of sleep on cognition. Recently, a key molecular mechanism that allows broad synaptic weakening during sleep was identified. Other mechanisms still being investigated should eventually explain how sleep can weaken most synapses but afford protection to some, including those directly activated by learning. That synaptic down-selection takes place during sleep is by now established; why it should take place during sleep has a plausible explanation; how it happens is still work in progress.