Increased cerebral blood flow in the right frontal lobe area during sleep precedes self-awakening in humans

Sleeping with time in mind? A literature review and a proposal for a screening questionnaire on self-awakening

Some people report being able to spontaneously "time" the end of their sleep. This ability to self-awaken challenges the idea of sleep as a passive cognitive state. Yet, current evidence on this phenomenon is limited, partly because of the varied definitions of self-awakening and experimental approaches used to study it. Here, we provide a review of the literature on self-awakening. Our aim is to i) contextualise the phenomenon, ii) propose an operating definition, and iii) summarise the scientific approaches used so far. The literature review identified 17 studies on self-awakening. Most of them adopted an objective sleep evaluation (76%), targeted nocturnal sleep (76%), and used a single criterion to define the success of awakening (82%); for most studies, this corresponded to awakening occurring in a time window of 30 minutes around the expected awakening time. Out of 715 total participants, 125 (17%) reported to be self-awakeners, with an average age of 23.24 years and a slight predominance of males compared to females. These results reveal self-awakening as a relatively rare phenomenon. To facilitate the study of self-awakening, and based on the results of the literature review, we propose a quick paper-and-pencil screening questionnaire for self-awakeners and provide an initial validation for it. Taken together, the combined results of the literature review and the proposed questionnaire help in characterising a theoretical framework for self-awakenings, while providing a useful tool and empirical suggestions for future experimental studies, which should ideally employ objective measurements.

A Review of Cerebral Hemodynamics During Sleep Using Near-Infrared Spectroscopy

Investigating cerebral hemodynamic changes during regular sleep cycles and sleep disorders is fundamental to understanding the nature of physiological and pathological mechanisms in the regulation of cerebral oxygenation during sleep. Although sleep neuroimaging methods have been studied and have been well-reviewed, they have limitations in terms of technique and experimental design. Neurologists are convinced that Near-infrared spectroscopy (NIRS) provides essential information and can be used to assist the assessment of cerebral hemodynamics, and numerous studies regarding sleep have been carried out based on NIRS. Thus, a brief historical overview of the sleep studies using NIRS will be helpful for the biomedical students, academicians, and engineers to better understand NIRS from various perspectives. In this study, the existing literature on sleep studies is reviewed, and an overview of the NIRS applications is synthesized and provided. The paper first reviews the application scenarios, as well as the patterns of fluctuation of NIRS, which includes the investigation in regular sleep and sleep-disordered breathing. Various factors such as different sleep stages, populations, and degrees of severity were considered. Furthermore, the experimental design and signal processing, as well as the regulation mechanisms involved in regular and pathological sleep, are investigated and discussed. The strengths and weaknesses of the existing NIRS applications are addressed and presented, which can direct further NIRS analysis and utilization.

Passive BCI based on drowsiness detection: an fNIRS study

We use functional near-infrared spectroscopy (fNIRS) to discriminate the alert and drowsy states for a passive brain-computer interface (BCI). The passive brain signals for the drowsy state are acquired from the prefrontal and dorsolateral prefrontal cortex. The experiment is performed on 13 healthy subjects using a driving simulator, and their brain activity is recorded using a continuous-wave fNIRS system. Linear discriminant analysis (LDA) is employed for training and testing, using the data from the prefrontal, left- and right-dorsolateral prefrontal regions. For classification, eight features are tested: mean oxyhemoglobin, mean deoxyhemoglobin, skewness, kurtosis, signal slope, number of peaks, sum of peaks, and signal peak, in 0~5, 0~10, and 0~15 second time windows, respectively. The results show that the best performance for classification is achieved using mean oxyhemoglobin, the signal peak, and the sum of peaks as features. The average accuracies in the right dorsolateral prefrontal cortex (83.1, 83.4 and 84.9% in the 0~5, 0~10 and 0~15 second time windows, respectively) show that the proposed method has an effective utility for detection of drowsiness for a passive BCI.

Self-awakening improves alertness in the morning and during the day after partial sleep deprivation

The ability to awaken at a predetermined time without an alarm is known as self-awakening. Self-awakening improves morning alertness by eliminating sleep inertia; however, the effects of self-awakening on daytime alertness and alertness that has deteriorated as a result of sleep loss are unknown. The aim of this study was to determine the effects of self-awakening on both morning and daytime alertness after partial sleep deprivation. Fifteen healthy males without the habit of self-awakening participated in a cross-over trial including forced awakening and self-awakening conditions. In each condition, participants' sleep was restricted to 5 h per night in their homes for 4 consecutive days. They completed a psychomotor vigilance task and subjective ratings of sleepiness immediately upon awakening each morning. On the fourth day, participants completed subjective ratings of sleepiness, a psychomotor vigilance task and sleep latency tests in the laboratory seven times at 1-h intervals during the day. The response speed on the psychomotor vigilance task, in the morning and during the day, was higher in the self-awakening than the forced awakening condition. Our results showed that self-awakening improved alertness (assessed by response speeds) by reducing sleep inertia and alleviated daytime sleepiness heightened by partial sleep deprivation.