A microanalysis of EMG and EEG changes during the sleep onset period (SOP) : a theoretical investigation with practical applications /

The present study has both theoretical and practical aspects. The theoretical intent of the study was to closely examine the relationship between muscle activity (EMG) and EEG state during the process of falling asleep. Sleep stages during sleep onset (SO) have been generally defined with regards to brain wave activity (Recht schaff en & Kales (1968); and more precisely by Hori, Hayashi, & Morikawa (1994)). However, no previous study has attempted to quantify the changes in muscle activity during this same process. The practical aspect of the study examined the reliability ofa commercially developed wrist-worn alerting device (NovAlert™) that utilizes changes in muscle activity/tension in order to alert its user in the event that he/she experiences reduced wakefulness that may result in dangerous consequences. Twelve female participants (aged 18-42) sp-ent three consecutive nights in the sleep lab ("Adaptation", "EMG", and "NOVA" nights). Each night participants were given 5, twenty-minute nap opportunities. On the EMG night, participants were allowed to fall asleep freely. On the NOV A night, participants wore the Nov Alert™ wrist device that administered a Psychomotor Vigilance Test (PVT) when it detected that muscle activity levels had dropped below baseline. Nap sessions were scored using Hori's 9-stage scoring system (Hori et aI, 1994). Power spectral analyses (FFT) were also performed. Effects ofthe PVT administration on EMG and EEG frequencies were also examined. Both chin and wrist EMG activity showed reliable and significant decline during the early stages ofHori staging (stages HO to H3 characterized by decreases in alpha activity). All frequency bands studied went through significant changes as the participants progressed through each ofHori's 9 SO stages. Delta, theta, and sigma activity increased later in the SO continuum while a clear alpha dominance shift was noted as alpha activity shifted from the posterior regions of the brain (during Hori stages HO to H3) to the anterior portions (during Hori stages H7 to H9). Administration of the PVT produced significant increases in EMG activity and was effective in reversing subjective drowsiness experienced during the later stages of sleep onset. Limitations of the alerting effects of the PVTs were evident following 60 to 75 minutes of use in that PVTs delivered afterwards were no longer able to significantly increase EMG levels. The present study provides a clearer picture of the changes in EMG and EEG during the sleep onset period while testing the efficacy of a commercially developed alerting device. EMG decreases were found to begin during Hori stage 0 when EEG was - dominated by alpha wave activity and were maximal as Hori stages 2 to 5 were traversed (coincident with alpha and beta activity). This signifies that EMG decrements and the loss of resting alpha activity are closely related. Since decreased alpha has long been associated with drowsiness and impending sleep, this investigation links drops in muscle tone with sleepiness more directly than in previous investigations. The EMG changes were reliably demonstrated across participants and the NovAlert™ detected the EMG decrements when Hori stage 3 was entered. The alerting vibrations produced by the NovAlert™ occurred early enough in the SO process to be of practical importance as a sleepiness monitoring and alerting device.

An electrophysiological examination of intentional and inadvertent sleep onset : the effect of intention on the sleep onset process

The main purpose ofthis study was to examine the effect ofintention on the sleep onset process from an electrophysiological point ofview. To test this, two nap conditions, the Multiple Sleep Latency Test (MSLT) and the Repeated Test of Sustained Wakefulness (RTSW) were used to compare intentional and inadvertent sleep onset. Sixteen female participants (aged 19-25) spent two non-consecutive nights in the sleep lab; however, due to physical and technical difficulties only 8 participants produced compete sets of data for analysis. Each night participants were given six nap opportunities. For three ofthese naps they were instructed to fall asleep (MSLT), for the remaining three naps they were to attempt to remain awake (RTSW). These two types of nap opportunities represented the conditions ofintentional (MSLT) and inadvertent (RTSW) sleep onset. Several other sleepiness, performance, arousal and questionnaire measures were obtained to evaluate and/or control for demand characteristics, subjective effort and mental activity during the nap tests. The nap opportunities were scored using a new 9 stage scoring system developed by Hori et al. (1994). Power spectral analyses (FFT) were also performed on the sleep onset data provided by the two nap conditions. Longer sleep onset latencies (approximately 1.25 minutes) were obseIVed in the RTSW than the MSLT. A higher incidence of structured mental activity was reported in the RTSW and may have been reflected in higher Beta power during the RTSW. The decent into sleep was more ragged in the RTSW as evidenced by an increased number shifts towards higher arousal as measured using the Hori 9 stage sleep scoring method. 1ll The sleep onset process also appears to be altered by the intention to remain awake, at least until the point ofinitial Stage 2 sleep (i.e. the first appearance of spindle activity). When only examining the final 4.3 minutes ofthe sleep onset process (ending with spindle activity), there were significant interactions between the type ofnap and the time until sleep onset for Theta, Alpha and Beta power. That is to say, the pattern of spectral power measurements in these bands differed across time as a function ofthe type ofnap. The effect ofintention however, was quite small (,,2 < .04) when compared to the variance which could be accounted for by the passage oftime (,,2 == .10 to .59). These data indicate that intention alone cannot greatly extend voluntary wakefulness if a person is sleepy. This has serious implications for people who may be required to perform dangerous tasks while sleepy, particularly for people who are in a situation that does not allow them the opportunity to engage in behavioural strategies in order to maintain their arousal.

The role of daytime napping in sleepiness and cognitive function in 24-70 year olds /

Daytime napping improves well-being and performance for young adults. The benefits of napping in older adults should be investigated because they have fragmented nocturnal sleep, cognitive declines, and more opportunity to nap. In addition, experience with napping might influence the benefits of napping. Study 1 examined the role of experience with napping in young adults. Habitual (n = 23) and non-habitual nappers (n = 16) were randomly assigned to a 20-minute nap or a 20- minute reading condition. Both groups slept the same according to macro architecture. However, microarchitecture showed greater theta, alpha, and beta power during Stage 1, and greater delta, alpha, and sigma power during Stage 2 for habitual nappers, for the most part indicating better sleep. Both groups felt less sleepy after the nap. P2 latency, reflecting information processing, decreased after the nap for habitual nappers, and after the control condition for non-habitual nappers. In sum, both groups who slept felt better, but only the habitual nappers who napped gained a benefit in terms of information processing. Based on this outcome, experience with napping was investigated in Study 2. Study 2 examined the extent to which daytime napping enhanced cognition in older adults, especially frontal lobe function. Cognitive deficits in older adults may be due to sleep loss and age-related decline in brain functioning. Longer naps were expected to provide greater improvement, particularly for older adults, by reducing sleep pressure. Thirty-two adults, aged 24-70 years, participated in a repeated measures dose-response manipulation of sleep pressure. Twenty- and sixty-minute naps were compared to a no-nap condition in three age groups. Mood, subjective sleepiness, reaction time, working memory, 11 novelty detection, and waking electro physiological measures were taken before and after each condition. EEG was also recorded during each nap or rest condition. Napping reduced subjective sleepiness, improved working memory (serial addition / subtraction task), and improved attention (reduced P2 amplitude). Physiological sleepiness (i.e., waking theta power) increased following the control condition, and decreased after the longer nap. Increased beta power after the short nap, and seen with older adults overall, may have reflected increased mental effort. Older adults had longer latencies and smaller amplitudes for several event-related potential components, and higher beta and gamma power. Following the longer nap, gamma power decreased for older adults, but increased for young adults. Beta and gamma power may represent enhanced alertness or mental effort. In addition, Nl amplitude showed that benefits depend on the preceding nap length as well as age. Since the middle group had smaller Nl amplitudes following the short nap and rest condition, it is possible that they needed a longer nap to maintain alertness. Older adults did not show improvements to Nl amplitude following any condition; they may have needed a nap longer than 60 minutes to gain benefits to attention or early information processing. Sleep characteristics were not related to benefits of napping. Experience with napping was also investigated. Subjective data confirmed habitual nappers were happier to nap, while non-habitual nappers were happier to stay awake, reflecting self-identified napping habits. Non-habitual nappers were sleepier after a nap, and had faster brain activity (i.e., heightened vigilance) at sleep onset. These reasons may explain why non-habitual nappers choose not to nap.

Electron Transfer Involving the Phylloquinone (A1) Cofactor of Photosystem I Examined with Time Resolved Absorbance and Electron Paramagnetic Resonance Spectroscopy

The dependence of the electron transfer (ET) rate on the Photosystem I (PSI) cofactor phylloquinone (A1) is studied by time-resolved absorbance and electron paramagnetic resonance (EPR) spectroscopy. Two active branches (A and B) of electron transfer converge to the FX cofactor from the A1A and A1B quinone. The work described in Chapter 5 investigates the single hydrogen bond from the amino acid residue PsaA-L722 backbone nitrogen to A1A for its effect on the electron transfer rate to FX. Room temperature transient EPR measurements show an increase in the rate for the A1A- to FX for the PsaA-L722T mutant and an increased hyperfine coupling to the 2-methyl group of A1A when compared to wild type. The Arrhenius plot of the A1A- to FX ET in the PsaA-L722T mutant suggests that the increased rate is probably the result of a slight change in the electronic coupling between A1A- and FX. The reasons for the non-Arrhenius behavior are discussed. The work discussed in Chapter 6 investigates the directionality of ET at low temperature by blocking ET to the iron-sulfur clusters FX, FA and FB in the menB deletion mutant strain of Synechocyctis sp. PCC 6803, which is unable to synthesize phylloquinone, by incorporating the high midpoint potential (49 mV vs SHE) 2,3-dichloro-1,4-naphthoquinone (Cl2NQ) into the A1A and A1B binding sites. Various EPR spectroscopic techniques were implemented to differentiate between the spectral features created from A and B- branch electron transfer. The implications of this result for the directionality of electron transfer in PS I are discussed. The work discussed in Chapter 7 was done to study the dependence of the heterogeneous ET at low temperature on A1 midpoint potential. The menB PSI mutant contains plastiquinone-9 in the A1 binding site. The solution midpoint potential of the quinone measures 100 mV more positive then wild-type phylloquinone. The irreversible ET to the terminal acceptors FA and FB at low temperature is not controlled by the forward step from A1 to FX as expected due to the thermodynamic differences of the A1 cofactor in the two active branches A and B. Alternatives for the ET heterogeneity are discussed.