The effects of simple procedural, cognitive procedural and declarative learning on sleep /

Sleep spindles have been found to increase following an intense period of learning on a combination of motor tasks. It is not clear whether these changes are task specific, or a result of learning in general. The current study investigated changes in sleep spindles and spectral power following learning on cognitive procedural (C-PM), simple procedural (S-PM) or declarative (DM) learning tasks. It was hypothesized that S-PM learning would result in increases in Sigma power during Non-REM sleep, whereas C-PM and DM learning would not affect Sigma power. It was also hypothesized that DM learning would increase Theta power during REM sleep, whereas S-PM and C-PM learning would not affect Theta power. Thirty-six participants spent three consecutive nights in the sleep laboratory. Baseline polysomnographic recordings were collected on night 2. Participants were randomly assigned to one of four conditions: C-PM, S-PM, DM or control (C). Memory task training occurred on night 3 followed by polysomnographic recording. Re-testing on respective memory tasks occurred one-week following training. EEG was sampled at 256Hz from 16 sites during sleep. Artifact-free EEG from each sleep stage was submitted to power spectral analysis. The C-PM group made significantly fewer errors, the DM group recalled more, and the S-PM improved on performance from test to re-test. There was a significant night by group interaction for the duration of Stage 2 sleep. Independent t-tests revealed that the S-PM group had significantly more Stage 2 sleep on the test night than the C group. The C-PM and the DM group did not differ from controls in the duration of Stage 2 sleep on test night. There was no significant change in the duration of slow wave sleep (SWS) or REM sleep. Sleep spindle density (spindles/minute) increased significantly from baseline to test night following S-PM learning, but not for C-PM, DM or C groups. This is the first study to have shown that the same pattern of results was found for spindles in SWS. Low Sigma power (12-14Hz) increased significantly during SWS following S-PM learning but not for C-PM, DM or C groups. This effect was maximal at Cz, and the largest increase in Sigma power was at Oz. It was also found that Theta power increased significantly during REM sleep following DM learning, but not for S-PM, C-PM or C groups. This effect was maximal at Cz and the largest change in Theta power was observed at Cz. These findings are consistent with the previous research that simple procedural learning is consolidated during Stage 2 sleep, and provide additional data to suggest that sleep spindles across all non-REM stages and not just Stage 2 sleep may be a mechanism for brain plasticity. This study also provides the first evidence to suggest that Theta activity during REM sleep is involved in memory consolidation.

A comparison of electrophysiological changes during the sleep onset period of psychophysiological insomniacs, psychiatric insomniacs and normal sleepers

The EEG of the sleep onset period of psychophysiological insomniacs, psychiatric insomniacs and controls was compared using power spectral analysis (FFT). Eighteen drug-free subjects were equally divided into three groups according to their responses in the Brock Sleep and Insomnia Questionnaire, the Minnesota Multiphasic Personality Inventory and the Sleep Disorders Questionnaire. Group 1 consisted of psychophysiological insomniacs, group 2 included insomniacs with an indication of psychiatric disturbances, and group 3 was a control group. EEG, EOG and EMG were recorded for two consecutive nights. Power spectral analysis (FFT) of EEG at C4 from the sleep onset period (defined as lights out to the first five minutes of stage 2) was performed on all standard frequency bands, delta: .5-4 Hz; theta: 4-8 Hz; alpha: 8-12 Hz; sigma: 12-15 Hz beta: 15-25 Hz. Psychophysiological insomniacs had less alpha during wakefulness than the other two groups and did not show the dramatic drop in alpha across the sleep onset period, which characterizes normal sleep. They also had less delta, especially during stage 2 on night 2. They also showed less delta in the last quartile of the chronological analysis of the sleep onset period. Psychiatric insomniacs showed lower relative beta power values overall while psychophysiological insomniacs showed higher relative beta power values during wakefulness. This microanalysis 11 confirms that the sleep onset period is generally similar for psychiatric insomniacs and normal sleepers. This may be due to the sample of psychiatric insomniacs being heterogeneous or may reflect a sleep onset system that is essentially intact. Psychophysiological insomniacs have higher cortical arousal during the sleep onset period than do the psychiatric insomniacs and the controls. Clear differences in the sleep onset period of psychophysiological insomniacs exist. The dramatic changes in power values in these two groups are not seen in the psychophysiological insomniacs, which may make the discrimination between wakefulness and sleep more difficult.

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.

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.

Sleep and information processing in individuals who have sustained a traumatic brain injury

Individuals who have sustained a traumatic brain injury (TBI) often complain of t roubl e sleeping and daytime fatigue but little is known about the neurophysiological underpinnings of the s e sleep difficulties. The fragile sleep of thos e with a TBI was predicted to be characterized by impairments in gating, hyperarousal and a breakdown in sleep homeostatic mechanisms. To test these hypotheses, 20 individuals with a TBI (18- 64 years old, 10 men) and 20 age-matched controls (18-61 years old, 9 men) took part in a comprehensive investigation of their sleep. While TBI participants were not recruited based on sleep complaint, the fmal sample was comprised of individuals with a variety of sleep complaints, across a range of injury severities. Rigorous screening procedures were used to reduce potential confounds (e.g., medication). Sleep and waking data were recorded with a 20-channel montage on three consecutive nights. Results showed dysregulation in sleep/wake mechanisms. The sleep of individuals with a TBI was less efficient than that of controls, as measured by sleep architecture variables. There was a clear breakdown in both spontaneous and evoked K-complexes in those with a TBI. Greater injury severities were associated with reductions in spindle density, though sleep spindles in slow wave sleep were longer for individuals with TBI than controls. Quantitative EEG revealed an impairment in sleep homeostatic mechanisms during sleep in the TBI group. As well, results showed the presence of hyper arousal based on quantitative EEG during sleep. In wakefulness, quantitative EEG showed a clear dissociation in arousal level between TBls with complaints of insomnia and TBls with daytime fatigue. In addition, ERPs indicated that the experience of hyper arousal in persons with a TBI was supported by neural evidence, particularly in wakefulness and Stage 2 sleep, and especially for those with insomnia symptoms. ERPs during sleep suggested that individuals with a TBI experienced impairments in information processing and sensory gating. Whereas neuropsychological testing and subjective data confirmed predicted deficits in the waking function of those with a TBI, particularly for those with more severe injuries, there were few group differences on laboratory computer-based tasks. Finally, the use of correlation analyses confirmed distinct sleep-wake relationships for each group. In sum, the mechanisms contributing to sleep disruption in TBI are particular to this condition, and unique neurobiological mechanisms predict the experience of insomnia versus daytime fatigue following a TBI. An understanding of how sleep becomes disrupted after a TBI is important to directing future research and neurorehabilitation.

The Role of Sleep in the Selective Reconsolidation of Declarative Memories

While sleep has been shown to be involved in memory consolidation and the selective enhancement of newly acquired memories of future relevance (Wilhelm, et al., 2011), limited research has investigated the role of sleep or future relevance in processes of memory reconsolidation. The current research employed a list-method directed forgetting procedure in which participants learned two lists of syllable pairs on Night 1 and received directed forgetting instructions on Night 2. On Night 2, one group (Labile; n = 15) received a memory reactivation treatment consisting of reminders designed to return memories of the learned lists to a labile state. A second group (Stable, n = 16) received similar reminders designed to leave memories of the learned lists in their stable state. No differences in forgetting were found across the two lists or groups. However, a negative correlation between frontal delta (1 – 4 Hz) electroencephalographic (EEG) power during Early Stage 2 non-rapid eye movement (NREM) sleep and forgetting of to-beremembered material was found exclusively in the Labile group (r = -.61, p < .05). Further, central theta (4 – 8 Hz ) EEG power during rapid eye movement (REM) sleep was found to correlate with directed forgetting exclusively in the Labile group (r = .81, p < .001) and total forgetting in the Stable group (r = .50, p < .05). These observed relationships support the proposed hypothesis suggesting that sleep processes are involved in the reconsolidation of labile memories, and that this reconsolidation may be selective for memories of future relevance. A role for sleep in the beneficial reprocessing of memories through the selective reconsolidation of labile memories in NREM sleep and the weakening of memories in REM sleep is discussed.

1970 Convocation Stage

View of the Convocation Stage during the May 26, 1970 ceremonies.

Electrophysiological analysis of the sleep onset period : a comparison between subjects with long term insomnia complaints associated with mild traumatic brain injury and matched controls /

The purpose of the current undertaking was to study the electrophysiological properties of the sleep onset period (SOP) in order to gain understanding into the persistent sleep difficulties of those who complain of insomnia following mild traumatic brain injury (MTBI). While many believe that symptoms of post concussion syndrome (PCS) following MTBI resolve within 6 to 12 months, there are a number of people who complain of persistent sleep difficulty. Two models were proposed which hypothesize alternate electrophysiological presentations of the insomnia complaints of those sustaining a MTBI: 1) Analyses of standard polysomnography (PSG) sleep parameters were conducted in order to determine if the sleep difficulties of the MTBI population were similar to that of idiopathic insomniacs (i.e. greater proportion ofREM sleep, reduced delta sleep); 2) Power spectral analysis was conducted over the SOP to determine if the sleep onset signature of those with MTBI would be similar to psychophysiological insomniacs (characterized by increased cortical arousal). Finally, exploratory analyses examined whether the sleep difficulties associated with MTBI could be explained by increases in variability of the power spectral data. Data were collected from 9 individuals who had sustained a MTBI 6 months to 5 years earlier and reported sleep difficulties that had arisen within the month subsequent to injury and persisted to the present. The control group consisted of 9 individuals who had experienced neither sleep difficulties, nor MTBI. Previous to spending 3 consecutive uninterrupted nights in the sleep lab, subjects completed questionnaires regarding sleep difficulties, adaptive functioning, and personality.

A dose-response investigation of the attentional blink during sleep restriction /

Recent dose-response sleep restriction studies, in which nightly sleep is curtailed to varying degrees (e.g., 3-, 5-, 7-hours), have found cumulative, dose-dependent changes in sleepiness, mood, and reaction time. However, brain activity has typically not been measured, and attentionbased tests employed tend to be simple (e.g., reaction time). One task addressing the behavioural and electrophysiological aspects of a specific attention mechanism is the Attentional Blink (AB), which shows that the report accuracy of a second target (T2) is impaired when it is presented soon after a first target (Tl). The aim of the present study was to examine behavioural and electrophysioiogical responses to the AB task to elucidate how sleep restriction impacts attentional capacity. Thirty-six young-adults spent four consecutive days and nights in a sleep laboratory where sleep, food, and activity were controlled. Nightly sleep began with a baseline sleep (8 hours), followed by two nights of sleep restriction (3,5 or 8 hours of sleep), and a recovery sleep (8 hours). An AB task was administered each day at 11 am. Results from a basic battery oftests (e.g., sleepiness, mood, reaction time) confirmed the effectiveness of the sleep restriction manipulation. In terms of the AB, baseline performance was typical (Le., T2 accuracy impaired when presented soon after Tl); however, no changes in any AB behavioural measures were observed following sleep restriction for the 3- or 5-hour groups. The only statistically significant electrophysiological result was a decrease in P300 amplitude (for Tl) from baseline to the second sleep restriction night for the 3-hour group. Therefore, following a brief, two night sleep restriction paradigm, brain functioning was impaired for the TI of the AB in the absence of behavioural deficit. Study limitations and future directions are discussed.

Information processing in sleep-onset insomnia : a test of the neurocognitive model /

The present thesis study is a systematic investigation of information processing at sleep onset, using auditory event-related potentials (ERPs) as a test of the neurocognitive model of insomnia. Insomnia is an extremely prevalent disorder in society resulting in problems with daytime functioning (e.g., memory, concentration, job performance, mood, job and driving safety). Various models have been put forth in an effort to better understand the etiology and pathophysiology of this disorder. One of the newer models, the neurocognitive model of insomnia, suggests that chronic insomnia occurs through conditioned central nervous system arousal. This arousal is reflected through increased information processing which may interfere with sleep initiation or maintenance. The present thesis employed event-related potentials as a direct method to test information processing during the sleep-onset period. Thirteen poor sleepers with sleep-onset insomnia and 1 2 good sleepers participated in the present study. All poor sleepers met the diagnostic criteria for psychophysiological insomnia and had a complaint of problems with sleep initiation. All good sleepers reported no trouble sleeping and no excessive daytime sleepiness. Good and poor sleepers spent two nights at the Brock University Sleep Research Laboratory. The first night was used to screen for sleep disorders; the second night was used to investigate information processing during the sleep-onset period. Both groups underwent a repeated sleep-onsets task during which an auditory oddball paradigm was delivered. Participants signalled detection of a higher pitch target tone with a button press as they fell asleep. In addition, waking alert ERPs were recorded 1 hour before and after sleep on both Nights 1 and 2.As predicted by the neurocognitive model of insomnia, increased CNS activity was found in the poor sleepers; this was reflected by their smaller amplitude P2 component seen during wake of the sleep-onset period. Unlike the P2 component, the Nl, N350, and P300 did not vary between the groups. The smaller P2 seen in our poor sleepers indicates that they have a deficit in the sleep initiation processes. Specifically, poor sleepers do not disengage their attention from the outside environment to the same extent as good sleepers during the sleep-onset period. The lack of findings for the N350 suggest that this sleep component may be intact in those with insomnia and that it is the waking components (i.e., Nl, P2) that may be leading to the deficit in sleep initiation. Further, it may be that the mechanism responsible for the disruption of sleep initiation in the poor sleepers is most reflected by the P2 component. Future research investigating ERPs in insomnia should focus on the identification of the components most sensitive to sleep disruption. As well, methods should be developed in order to more clearly identify the various types of insomnia populations in research contexts (e.g., psychophysiological vs. sleep-state misperception) and the various individual (personality characteristics, motivation) and environmental factors (arousal-related variables) that influence particular ERP components. Insomnia has serious consequences for health, safety, and daytime functioning, thus research efforts should continue in order to help alleviate this highly prevalent condition.

Aerobic exercise in adolescence : self-efficacy and stage of change

The purpose of this cross-sectional exploratory study was to examine the relationships among self-efficacy, stage of change, and exercise behaviour in a sample of younger (Grade 9) and older (Grade 12) adolescents. A secondary objective of this study was to apply the transtheoretical model of Stage of Change, as a measure of intention to change, in order to discover the applicability of the model to an adolescent cohort in relation to exercise behaviour. This five-stage model is a self-report measure of an individual's readiness to adopt a new behaviour (e.g., regular exercise). The transtheoretical model incorporates Bandura's self-efficacy factor, which is purported to be a predictive measure of exercise behaviour and a covariant of stage. Exercise behaviour was measured with the Physical Activity Scale, and the University of Rhode Island Change Assessment Scale (URleA) was used to measure the stage of change and self-efficacy variables. The results of this study indicated significant differences between younger and older adolescents, and between males and females in their exercise behaviour. No significant differences were found for grade and gender on stage of change as measured by either a single-item question or a continuous measure of stage. Although grade and gender subgroups were not significantly different in their self-efficacy, significant interaction was found in the grade*gender variable.

Evaluation of a stage II screening protocol for prostate cancer

In 2003, prostate cancer (PCa) is estimated to be the most commonly diagnosed cancer and third leading cause of cancer death in Canada. During PCa population screening, approximately 25% of patients with a normal digital rectal examination (DRE) and intermediate serum prostate specific antigen (PSA) level have PCa. Since all patients typically undergo biopsy, it is expected that approximately 75% of these procedures are unnecessary. The purpose of this study was to compare the degree of efficacy of clinical tests and algorithms in stage II screening for PCa while preventing unnecessary biopsies from occurring. The sample consisted of 201 consecutive men who were suspected of PCa based on the results of a DRE and serum PSA. These men were referred for venipuncture and transrectal ultrasound (TRUS). Clinical tests included TRUS, agespecific reference range PSA (Age-PSA), prostate specific antigen density (PSAD), and free-to-total prostate specific antigen ratio (%fPSA). Clinical results were evaluated individually and within algorithms. Cutoffs of 0.12 and 0.15 ng/ml/cc were employed for PSAD. Cutoffs that would provide a minimum sensitivity of 0.90 and 0.95, respectively were utilized for %fPSA. Statistical analysis included ROC curve analysis, calculated sensitivity (Sens), specificity (Spec), and positive likelihood ratio (LR), with corresponding confidence intervals (Cl). The %fPSA, at a 23% cutoff ({ Sens=0.92; CI, 0.06}, {Spec=0.4l; CI, 0.09}, {LR=1.56; CI, O.ll}), proved to be the most efficacious independent clinical test. The combination of PSAD (cutoff 0.15 ng/ml/cc) and %fPSA (cutoff 23%) ({Sens=0.93; CI, 0.06}, {Spec=0.38; CI, 0.08}, {LR=1.50; CI, 0.10}) was the most efficacious clinical algorithm. This study advocates the use of %fPSA at a cutoff of 23% when screening patients with an intermediate serum PSA and benign DRE.

Geological image processing of petrographic thin sections using the rotating polarizer stage

One of the fundamental problems with image processing of petrographic thin sections is that the appearance (colour I intensity) of a mineral grain will vary with the orientation of the crystal lattice to the preferred direction of the polarizing filters on a petrographic microscope. This makes it very difficult to determine grain boundaries, grain orientation and mineral species from a single captured image. To overcome this problem, the Rotating Polarizer Stage was used to replace the fixed polarizer and analyzer on a standard petrographic microscope. The Rotating Polarizer Stage rotates the polarizers while the thin section remains stationary, allowing for better data gathering possibilities. Instead of capturing a single image of a thin section, six composite data sets are created by rotating the polarizers through 900 (or 1800 if quartz c-axes measurements need to be taken) in both plane and cross polarized light. The composite data sets can be viewed as separate images and consist of the average intensity image, the maximum intensity image, the minimum intensity image, the maximum position image, the minimum position image and the gradient image. The overall strategy used by the image processing system is to gather the composite data sets, determine the grain boundaries using the gradient image, classify the different mineral species present using the minimum and maximum intensity images and then perform measurements of grain shape and, where possible, partial crystallographic orientation using the maximum intensity and maximum position images.

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.