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Sleep Facts
Published in John A. Caldwell, J. Lynn Caldwell, Fatigue in Aviation, 2016
John A. Caldwell, J. Lynn Caldwell
A common modifier of sleep structure is sleep deprivation. When job requirements entail sleep loss either because of extended duty periods or shift work, the sleep that occurs in the first rest opportunity often contains far more slow-wave activity throughout the night while REM sleep is pushed either much later in the sleep episode or sometimes even into the next night of sleep. The brain shows a preference for recovering slow-wave sleep first and REM sleep afterwards, and this leads us to believe that slow-wave sleep probably conveys a greater survival advantage than REM sleep. However, the exact roles of the different stages of sleep have not been precisely determined.
Beyond the neural correlates of consciousness: using brain stimulation to elucidate causal mechanisms underlying conscious states and contents
Published in Journal of the Royal Society of New Zealand, 2021
Corinne A. Bareham, Matt Oxner, Tim Gastrell, David Carmel
It may seem counterintuitive to divide consciousness into these separate dimensions: Aren’t we aware of a large variety of stimuli when we are awake, and unaware of them when we are not awake? The distinction between wakefulness and awareness is useful, though, because the two do not always go hand-in-hand; in some states of consciousness, one may be high while the other is low. During sleep, for example, there is a distinction between rapid eye movement (REM) and non-REM (nREM) sleep. In nREM sleep, which comprises light and deep sleep stages, EEG activity is clearly distinguishable from that seen during wakefulness. (Deep nREM sleep is also known as ‘slow-wave sleep’ because it shows high-amplitude slow waves (0.5-4.5 Hz) that are not seen in other states.) Importantly, nREM sleep is where wakefulness and awareness match: it is characterised by a reduction in both as sleep becomes deeper. On the other hand, REM sleep (during which people make rapid bursts of eye movements) is a deep-sleep state in which the brain is highly active, and its EEG activity resembles that seen during wakefulness. During REM sleep, we often have vivid dreams – in other words, our wakefulness is low (we are asleep), but awareness is high (we experience feelings, have thoughts, and perceive images and sounds).
Moderate-intensity exercise performed in the evening does not impair sleep in healthy males
Published in European Journal of Sport Science, 2020
D. J. Miller, C. Sargent, G. D. Roach, A. T. Scanlan, G. E. Vincent, M. Lastella
Recent epidemiological data has challenged traditional sleep hygiene recommendations, highlighting a positive association between evening exercise and self-reported sleep quality and quantity (Buman, Phillips, Youngstedt, Kline, & Hirshkowitz, 2014). In a cross-sectional study examining sleep and exercise, Buman et al. (2014) found that evening exercise was not associated with disturbed sleep. Furthermore, experimental data suggests that evening exercise may result in increased slow wave sleep (Dworak et al., 2008), increased sleep efficiency and REM onset latency (Flausino, Da Silva Prado, de Queiroz, Tufik, & de Mello, 2012) and have no impact on subjective sleep quality (Myllymaki et al., 2011) or quantity (Alley, Mazzochi, Smith, Morris, & Collier, 2015; O’Connor, Breus, & Youngstedt, 1998). When interpreting such data, it is important to consider differences in exercise modality. Both aerobic exercise and resistance exercise are recommended for health benefits (e.g. decreased risk of hypertension, diabetes and depression; Warburton, Nicol, & Bredin, 2006), but the effect of these modalities on sleep when performed close to bedtime is not well understood. Acutely, aerobic exercise results in significantly increased heart rate and oxygen consumption compared to resistance exercise (Pontifex, Hillman, Fernhall, Thompson, & Valentini, 2009). Due to physiological differences between aerobic exercise and resistance exercise, it is possible that they may influence sleep differently when performed in the evening.
A validation study of the WHOOP strap against polysomnography to assess sleep
Published in Journal of Sports Sciences, 2020
Dean J. Miller, Michele Lastella, Aaron T. Scanlan, Clint Bellenger, Shona L. Halson, Gregory D. Roach, Charli Sargent
Sleep was measured simultaneously using the WHOOP strap (Generation 2.0 hardware, Generation 3 algorithm, CB Rank, Greater Boston, New England) and PSG. Prior to the study, clock time was manually synchronised on all devices (i.e., laboratory computers, mobile devices running the WHOOP smart phone application). To acquire WHOOP strap sleep data, the start and end times of each sleep opportunity were manually entered into the WHOOP smart phone application by the researchers. The manufacturer then provided data in 30-s epochs for wake, light sleep, SWS and REM for comparison with PSG. To measure sleep using PSG, a standard montage of electrodes were attached to the face and scalp of participants including three electroencephalography electrodes (i.e., C4-M1, F4-M1, O2-M1), two electro-oculograms (i.e., left/right outer canthus) and a submental electromyogram. PSG data were recorded directly to data acquisition, storage, and analysis systems (Grael, Compumedics; Victoria, Australia). PSG records were manually scored in 30-s epochs by an experienced registered polysomnographic technician in compliance with standard criteria (Iber et al., 2007). The following sleep variables were extracted from the PSG records and the WHOOP strap data: Total sleep time (TST): the sum of minutes spent in any stage of sleep (stages N1, N2, N3, REM);Wake: the sum of minutes spent awake;Light sleep: the sum of minutes spent in stage N1 or N2 sleep.Slow-wave sleep (SWS): the sum of minutes spent in stage N3 sleep.Rapid-eye-movement sleep (REM): the sum of minutes spent in stage R.