Onzième exposition à Nîmes, 1909. Catalogue explicatif des ouvrages de peinture, sculpture, dessin, architecture etc. admis à l'exposition...

[Exposition [11e. 1909. Nîmes]]

Continental margin architecture : the palynological signature of glacioeustasy /

Palynomorphs from two siliciclastic margins were examined to gain insights into continental margin architecture. Sea level change is thought to be one of the primary controls on continental margin architecture. Because Late Neogene glacioeustasy has been well studied marine sediments deposited during the Late Neogene were examined to test this concept. Cores from the outer shelf and upper slope were taken from the New Jersey margin in the western North Atlantic Ocean and from the Sunda Shelf margin in the South China Sea. Continental margin architecture is often described in a sequence stratigraphic context. One of the main goals of both coring projects was to test the theoretical sequence stratigraphic models developed by a research group at Exxon (e.g. Wilgus et al., 1988). Palynomorphs provide one of the few methods of inferring continental margin architecture in monotonous, siliciclastic marine sediments where calcareous sediments are rare (e.g. New Jersey margin). In this study theoretical models of the palynological signature expected in sediment packages deposited during the various increments of a glacioeustatic cycle were designed. These models were based on the modem palynomorph trends and taphonomic factors thought to control palynomorph distribution. Both terrestrial (pollen and spores) and marine (dinocysts) palynomorphs were examined. The palynological model was then compared with New Jersey margin and Sunda Shelf margin sediments. The predicted palynological trends provided a means of identifying a complete cycle of glacioeustatic change (Oxygen Isotope Stage 5e to present) in the uppermost 80 meters of sediment on the slope at the New Jersey margin. Sediment availability, not sea meters of sediment on the slope at the New Jersey margin. Sediment availability, not sea level change, is thought to be the major factor controlling margin architecture during the late Pleistocene here at the upper slope. This is likely a function of the glacial scouring of the continents which significantly increases sediment availability during glacial stages. The subaerially exposed continental shelf during the lowstand periods would have been subject to significant amounts of erosion fi:om the proglacial rivers flowing fi-om the southern regions of the ice-sheet. The slope site is non-depositional today and was also non-depositional during the last full interglacial period. The palynomorph data obtained fi-om the South China Sea indicate that the major difference between the New Jersey Margin sites and the Sunda Shelf margin sites is the variation in sediment supply and the rate of sediment accumulation. There was significantly less variation in sediment supply between glacial and interglacial periods and less overall sediment accumulation at the Sunda Shelf margin. The data presented here indicate that under certain conditions the theoretical palynological models allow the identification of individual sequence stratigraphic units and therefore, allow inferences regarding continental margin architecture. The major condition required in this approach is that a complete and reliable database of the contemporaneous palynomorphs be available.

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.

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.

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.

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.