Testing a Hypothesis of Non-REM Sleep Reinforcement and REM Sleep Refinement for the Benefits of Post-Learning Sleep on Memory Retrieval
AuthorMacDonald, Kevin John
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AbstractIt is well established that post-learning sleep benefits later memory retrieval, but there is still much to learn about the processes involved and the nature of these benefits. Sleep is composed of stages of non-REM (NREM) and REM sleep: NREM sleep, especially slow wave activity of NREM sleep, and REM sleep have been implicated in memory performance benefits, but the specific contributions of each state remain unclear. This thesis presents a hypothesis proposing that post-learning NREM sleep supports memory accessibility, benefitting the likelihood of successful memory retrieval, and that post-learning REM sleep supports memory fidelity, allowing for more accurate retrieval when retrieval is successful. This hypothesis was tested over studies examining the effects of an afternoon nap (Chapter 2), targeted memory reactivation during NREM slow wave sleep (Chapter 3), and both targeted memory reactivation during NREM slow wave sleep and selective deprivation of REM sleep (Chapter 4) on measures of memory accessibility and memory fidelity in visuospatial memory tasks. In each study, measures of sleep architecture and electroencephalographic power in sleep were examined as predictors of memory performance. Several identified associations and interactions further inform an understanding of how NREM sleep and REM sleep may benefit memory performance. Most notably, these studies consistently found greater slow wave activity of NREM sleep to be specifically associated with better maintenance of memory accessibility. These studies did not identify a clear effect of REM sleep. It is hoped that the hypothesis and findings presented stimulate additional inquires that will further our understanding of the individual and combined contributions of NREM and REM sleep.
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Relationships Between Sleep Quality, Sleep Hygiene, and Psychological Distress In University Student-AthletesGladney, Chris; Gladney, Chris; Applied Health Sciences ProgramPost-secondary student-athletes are one of the most vulnerable populations that experience poor sleep quality, which has detrimental effects on psychological distress due to the strong relationship between sleep quality and psychological distress. Research suggests that by improving sleep hygiene behaviours an individual can improve sleep quality, which will improve psychological distress. Few studies have examined sleep quality, sleep hygiene and psychological distress together among a post-secondary population and none have investigated a student-athlete population. The present study examined if sleep hygiene mediates the relationship between sleep quality and psychological distress among post-secondary student-athletes. A sample of 94 student-athletes completed the Kessler Psychological Distress Scale, Pittsburgh Sleep Quality Index, and Sleep Hygiene Practice Scale (Buyess et al., 1989; Kessler et al., 2002; Lin, Cheng, Yang, & Hsu, 2007). A mediation model was used to examine the relationships between the variables using the global scores. Bootstrapping was conducted to increase power of the model, which resulted in confidence interval levels that did not include zero indicating the indirect effect is significant and sleep hygiene mediates the relationship between sleep quality and psychological distress. This study can implicate future studies regarding sleep hygiene interventions changing the lifestyle habits and behaviours affecting their sleep hygiene, which is shown to impact sleep quality and psychological distress. In conclusion, Sleep hygiene mediated the relationship between sleep quality and psychological distress.
An electrophysiological examination of intentional and inadvertent sleep onset : the effect of intention on the sleep onset processMurphy, Tim.; Department of Psychology (Brock University, 1995-07-09)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.
Subjective, behavioural and electrophysiological measurements of the time-course and intensity of sleep inertia after a full night of sleep /Stewart, Craig P.; Department of Psychology (Brock University, 2000-07-14)Several recent studies have described the period of impaired alertness and performance known as sleep inertia that occurs upon awakening from a full night of sleep. They report that sleep inertia dissipates in a saturating exponential manner, the exact time course being task dependent, but generally persisting for one to two hours. A number of factors, including sleep architecture, sleep depth and circadian variables are also thought to affect the duration and intensity. The present study sought to replicate their findings for subjective alertness and reaction time and also to examine electrophysiological changes through the use of event-related potentials (ERPs). Secondly, several sleep parameters were examined for potential effects on the initial intensity of sleep inertia. Ten participants spent two consecutive nights and subsequent mornings in the sleep lab. Sleep architecture was recorded for a fiiU nocturnal episode of sleep based on participants' habitual sleep patterns. Subjective alertness and performance was measured for a 90-minute period after awakening. Alertness was measured every five minutes using the Stanford Sleepiness Scale (SSS) and a visual analogue scale (VAS) of sleepiness. An auditory tone also served as the target stimulus for an oddball task designed to examine the NlOO and P300 components ofthe ERP waveform. The five-minute oddball task was presented at 15-minute intervals over the initial 90-minutes after awakening to obtain six measures of average RT and amplitude and latency for NlOO and P300. Standard polysomnographic recording were used to obtain digital EEG and describe the night of sleep. Power spectral analyses (FFT) were used to calculate slow wave activity (SWA) as a measure of sleep depth for the whole night, 90-minutes before awakening and five minutes before awakening.