Differences In Slow Wave Activity Research Articles

SLEEP MICROARCHITECTURE IN MILD COGNITIVE IMPAIRMENT: A HIGH‐DENSITY EEG STUDY

AbstractBackgroundSleep disturbance and sleep disorders are potential risk factors for dementia. Adults with mild cognitive impairment (MCI) are at increased risk of developing dementia and many report disturbed sleep. Altered sleep neurophysiology including deficits in sleep spindles and slow wave activity (SWA) during NREM sleep have been reported in MCI, though studies are sparse. These NREM EEG oscillations are crucial for overnight memory consolidation and optimal daytime functioning. Abnormal EEG activity during sleep in MCI may adversely impact sleep‐dependent memory processes and cognitive trajectory. This study is the first to examine sleep microarchitecture using high‐density EEG technology in MCI.MethodOlder adults with multi‐domain MCI (n = 19, mean age 68.5 years) and cognitively‐intact controls (n = 22, 69 years) had 256‐channel high‐density EEG recordings during overnight polysomnography and resting wakefulness. Declarative (word paired associates) and procedural (finger tapping) memory tasks were administered before and after sleep. Neuropsychological testing and brain MRI scans were also performed. After artefact processing, spectral analysis was performed for high‐density EEG recordings. Topographical power maps were calculated for standard frequency ranges for NREM sleep (N2 and N3 (slow wave sleep)). Maps were compared between groups using normalized power (z‐scores computed for each subject).ResultThe MCI group had worse declarative (% retention, MCI vs Controls: 84.2 ± 16.6 vs. 94.5 ± 7.8, p = 0.024) and procedural (% early improvement: 92.9 ± 11.0 vs. 103.0 ± 12.0%, p = 0.017) overnight memory consolidation than the controls. Topographic analysis of high‐density EEG data revealed a regional increase in SWA (1‐4.5Hz) EEG power during N3 in a cluster of 18 electrodes overlying the centroparietal cortex in the MCI group (cluster mean t‐value = 3.11, p = 0.0036, uncorrected) and a regional reduction in SWA in the left frontal (5 channels, t = ‐3.75, p<0.001) and right temporal areas (5 channels, t = ‐3.46, p = 0.001), Figure 1.ConclusionOvernight memory consolidation was impaired in this MCI population. Regional differences in SWA during deep sleep were present in distinct brain regions and may indicate pathology. Future analysis exploring associations between EEG abnormalities with underlying brain structures may provide mechanistic insights into the impact of altered sleep neurophysiology on cognitive outcomes in MCI.

33 Associations Between Long-Term Forgetting and Slow Wave Activity in Autosomal-Dominant Alzheimer’s Disease: Findings from the Colombia-Boston (COLBOS) Biomarker Study

Objective:Sleep contributes to memory retention and recall. Alzheimer’s disease (AD) patients experience decreased slow wave activity (SWA) during sleep. This decrease in SWA is associated with impaired memory consolidation (Lee et al., 2020). Long-term forgetting (LTF) over days or weeks has been linked to memory consolidation deficits and has been suggested as an early marker of AD that could be useful for identifying at-risk individuals for preclinical AD trials (Weston et al., 2018). Here, we examined associations between LTF and SWA in a sample of Presenilin-1 (PSEN1) E280A mutation carriers with autosomal dominant Alzheimer’s disease and non-carrier family members. Carriers of this mutation usually develop dementia in their forties (Fuller et al., 2019).Participants and Methods:Fourteen cognitively unimpaired PSEN1-E280A mutation carriers and sixteen age-matched non-carriers (mean age: 34.2 years) from the Colombia-Boston (COLBOS) biomarker study were included. Participants completed an overnight polysomnogram (PSG) and memory testing (NEUROPSI Word List) at 3-time points: 1) the night before PSG: immediate recall (Day1-ImmRecall) and a 20-minute delayed recall (Day1-DelayedRecall), 2) recall the following day (Day2-recall), and 3) recall one week later (Day7-recall). SWA was measured as the ratio 0. 6-1Hz/0.6-4Hz in frontopolar and frontotemporal regions and was calculated for sleep stages N2+N3 (slow wave sleep) based on an automated staging algorithm. Each participant’s LTF was calculated as the percent retention between Day 1 immediate recall and Day 7 recall (Butler, 2009). Mann-Whitney U tests were used to compare differences in recall, SWA, and LTF between groups. Spearman’s correlation was used to examine the associations between memory recall at different time points and SWA, as well as between LTF and SWA.Results:On Day 1, carriers had lower performance in immediate recall (p=0.02), compared to non-carriers, but there were no group differences in the 20-minute delayed recall. Carriers also recalled fewer words on Day 2 (p=0.03) and Day 7 (p=0.009) and had greater LTF (p=0.03). There were no group differences in SWA. In our overall sample, worse performance on word list delayed recall on Day 1, Day 2, and Day 7 was associated with less SWA across both frontotemporal (Day1: p=0.04, Day2: p=0.02, Day7: p=0.02) and frontopolar (all Ps<0.01) regions. In carriers, only worse performance on Day 1 delayed recall was associated with lower SWA in the frontopolar region (r= 0.535; p=0.049). Memory recall on other days was not associated with SWA in any brain regions. Additionally, greater LTF was associated with less SWA across both frontopolar (r= 0.507; p=0.005) and frontotemporal regions (r= 0.463 p= 0.01).Conclusions:Preliminary findings suggest that long-term forgetting is associated with less slow- wave activity in preclinical autosomal dominant Alzheimer’s disease. These results also suggest that SWA may be related to pre-sleep learning and subsequent overnight memory consolidation processes. LTF testing may be useful in selecting individuals for preclinical AD trials. Future research on the impact of slow wave activity on LTF may be useful in identifying ways to enhance short- and long-term memory consolidation in individuals at greater risk for dementia.

Overnight declarative memory consolidation and non-rapid eye movement sleep electroencephalographic oscillations in older adults with obstructive sleep apnea.

To compare overnight declarative memory consolidation and non-rapid eye movement (NREM) sleep electroencephalogram (EEG) oscillations in older adults with obstructive sleep apnea (OSA) to a control group and assess slow-wave activity (SWA) and sleep spindles as correlates of memory consolidation. Forty-six older adults (24 without OSA and 22 with OSA) completed a word-pair associate's declarative memory task before and after polysomnography. Recall and recognition were expressed as a percentage of the morning relative to evening scores. Power spectral analysis was performed on EEG recorded at frontal (F3-M2, F4-M1) and central (C3-M2, C4-M1) sites. We calculated NREM absolute slow oscillation (0.25-1 Hz) and delta (0.5-4.5 Hz) EEG power, and slow (11-13 Hz) spindle density (number of events per minute of N2 sleep) and fast (13-16 Hz) spindle density. There were no significant differences in overnight recall and recognition between OSA (mean age 58.7 ± 7.1 years, apnea-hypopnea index (AHI) 41.9 ± 29.7 events/hour) and non-OSA (age 61.1 ± 10.3 years, AHI 6.6 ± 4.2 events/hour) groups. The OSA group had lower fast spindle density in the frontal region (p = 0.007). No between-group differences in SWA were observed. In the Control group, overnight recognition positively correlated with slow spindle density in frontal (rho = 0.555, p = 0.020) and central regions (rho = 0.490, p = 0.046). Overnight recall was not related to SWA or spindle measures in either group. Older adults with OSA had deficits in fast sleep spindles but showed preserved overnight declarative memory consolidation. It is possible that compensatory mechanisms are being recruited by OSA patients to preserve declarative memory consolidation despite the presence of sleep spindle deficits.

Maturational trajectories of non-rapid eye movement slow wave activity and odds ratio product in a population-based sample of youth

BackgroundBrain maturation is reflected in the sleep electroencephalogram (EEG) by a decline in non-rapid eye movement (NREM) slow wave activity (SWA) throughout adolescence and a related decrease in sleep depth. However, this trajectory and its sex and pubertal differences lack replication in population-based samples. We tested age-related changes in SWA (0.4–4 Hz) power and odds ratio product (ORP), a standardized measure of sleep depth. MethodsWe analyzed the sleep EEG of 572 subjects aged 6-21 y (48% female, 26% racial/ethnic minority) and 332 subjects 5-12 y followed-up at 12-22 y. Multivariable-adjusted analyses tested age-related cross-sectional and longitudinal trajectories of SWA and ORP. ResultsSWA remained stable from age 6 to 10, decreased between ages 11 and 17, and plateaued from age 18 to 21 (p-cubic<0.001); females showed a longitudinal decline 23% greater than males by 13 y, while males experienced a steeper slope after 14 y and their longitudinal decline was 21% greater by 19 y. More mature adolescents (75% female) experienced a greater longitudinal decline in SWA than less mature adolescents by 14 y. ORP showed an age-related increasing trajectory (p-linear<0.001) with no sex or pubertal differences. ConclusionsWe provide population-level evidence for the maturational decline and sex and pubertal differences in SWA in the transition from childhood to adolescence, while introducing ORP as a novel metric in youth. Along with previous studies, the distinct trajectories observed suggest that age-related changes in SWA reflect brain maturation and local/synaptic processes during this developmental period, while those of ORP may reflect global/state control of NREM sleep depth.

Naps not as effective as a night of sleep at dissipating sleep pressure.

The two-process model of sleep posits that two processes interact to regulate sleep and wake: a homeostatic (Process S) and a circadian process (Process C). Process S compensates for sleep loss by increasing sleep duration and intensity. Process C gates the timing of sleep/wake favouring sleep during the circadian night in humans. In this study, we examined whether taking six naps throughout a 24-hr period would result in the same amount of dissipation of homeostatic pressure at the end of the day as a night of sleep, when time in bed is equivalent. Data from 46 participants (10-23years; mean=14.5 [± 2.9]; 25 females) were analysed. Slow-wave energy, normalized to account for individual differences in slow-wave activity, was used as a measure of sleep homeostasis. In the nap condition, slow-wave energy of six naps distributed equally during a 24-hr period was calculated. In the baseline condition, slow-wave energy was measured after 9-hr time in bed. A paired t-test was used to compare nap and baseline conditions. A linear regression was used to examine whether slow-wave energy varied as a function of age. Slow-wave energy was greater during baseline than the nap condition (p<.001). No association between age and slow-wave energy was found for baseline or nap conditions. Our findings indicate that multiple naps throughout the day are not as effective at dissipating sleep pressure as a night of sleep. This is likely due to the influence of the circadian system, which staves off sleep during certain times of the day.

Effects of obstructive sleep apnea on human spatial navigational memory processing in cognitively normal older individuals.

Obstructive sleep apnea (OSA) prevalence increases with age, but whether OSA-related sleep disruption could interrupt the processing of previously encoded wake information thought to normally occur during sleep in cognitively normal older adults remains unknown. Fifty-two older (age = 66.9 ± 7.7 years, 56% female), community-dwelling, cognitively normal adults explored a 3-D maze environment and then performed 3 timed trials before (evening) and after (morning) sleep recorded with polysomnography with a 20-minute morning psychomotor vigilance test. Twenty-two (22) participants had untreated OSA [apnea-hypopnea index (AHI4%) ≥ 5 events/h] where severity was mild on average [median (interquartile range); AHI4% = 11.0 (20.7) events/h] and 30 participants had an AHI4% < 5 events/h. No significant differences were observed in overnight percent change in completion time or in the pattern of evening presleep maze performance. However, during the morning postsleep trials, there was a significant interaction between OSA group and morning trial number such that participants with OSA performed worse on average with each subsequent morning trial, whereas those without OSA showed improvements. There were no significant differences in morning psychomotor vigilance test performance, suggesting that vigilance is unlikely to account for this difference in morning maze performance. Increasing relative frontal slow wave activity was associated with better overnight maze performance improvement in participants with OSA (r = .51, P = .02) but not in those without OSA, and no differences in slow wave activity were observed between groups. OSA alters morning performance in spatial navigation independent of a deleterious effect on morning vigilance or evening navigation performance. Relative frontal slow wave activity is associated with overnight performance change in older participants with OSA, but not those without.

Determinants of Slow-Wave Activity in Overweight and Obese Adults: Roles of Sex, Obstructive Sleep Apnea and Testosterone Levels.

Background: Slow-wave activity (SWA) in non-rapid eye movement (NREM) sleep, obtained by spectral analysis of the electroencephalogram, is a marker of the depth or intensity of NREM sleep. Higher levels of SWA are associated with lower arousability during NREM sleep and protect against sleep fragmentation. Multiple studies have documented that SWA levels are higher in lean women, compared to age-matched lean men, but whether these differences persist in obese subjects is unclear. Obstructive sleep apnea (OSA), a condition associated with obesity, is more prevalent in men than in women. Sex differences in SWA could therefore be one of the factors predisposing men to OSA. Furthermore, we hypothesized that higher levels of testosterone may be associated with lower levels of SWA.Objective: The aim of the current study was to identify sex differences in the determinants of SWA in young and middle-aged overweight and obese adults.Methods: We enrolled 101 overweight and obese but otherwise healthy participants from the community (44 men, 57 women) in this cross-sectional study. Participants underwent an overnight in-laboratory polysomnogram. The recordings were submitted to sleep staging and spectral analysis. Sex differences and the potential contribution of testosterone levels were evaluated after adjusting for age, body mass index and race/ethnicity.Results: OSA was present in 66% of men and in 44% of women. After adjustment for differences in age, race/ethnicity and BMI, the odds ratio for OSA in men vs. women was 3.17 (95% CI 1.14–9.43, p = 0.027). There was a graded inverse relationship between the apnea-hypopnea index (AHI) and SWA in men (β = −0.21, p = 0.018) but not in women (β = 0.10, p = 0.207). In a multivariate regression model, higher testosterone levels were independently associated with lower SWA in men after controlling for age, race/ethnicity and apnea-hypopnea index (β = −0.56, p = 0.025).Conclusion: Increasing severity of OSA was associated with significant decrease in sleep intensity in men but not in women. Higher testosterone levels were associated with lower sleep intensity in men. Men with higher testosterone levels may therefore have lower arousal thresholds and higher ventilatory instability in NREM sleep, and be at greater risk of OSA.

Sex-related differences in sleep slow wave activity in major depressive disorder: a high-density EEG investigation

BackgroundSleep disturbance plays an important role in major depressive disorder (MDD). Prior investigations have demonstrated that slow wave activity (SWA) during sleep is altered in MDD; however, results have not been consistent across studies, which may be due in part to sex-related differences in SWA and/or limited spatial resolution of spectral analyses. This study sought to characterize SWA in MDD utilizing high-density electroencephalography (hdEEG) to examine the topography of SWA across the cortex in MDD, as well as sex-related variation in SWA topography in the disorder.MethodsAll-night recordings with 256 channel hdEEG were collected in 30 unipolar MDD subjects (19 women) and 30 age and sex-matched control subjects. Spectral analyses of SWA were performed to determine group differences. SWA was compared between MDD and controls, including analyses stratified by sex, using statistical non-parametric mapping to correct for multiple comparisons of topographic data.ResultsAs a group, MDD subjects demonstrated significant increases in all-night SWA primarily in bilateral prefrontal channels. When stratified by sex, MDD women demonstrated global increases in SWA relative to age-matched controls that were most consistent in bilateral prefrontal regions; however, MDD men showed no significant differences relative to age-matched controls. Further analyses demonstrated increased SWA in MDD women was most prominent in the first portion of the night.ConclusionsWomen, but not men with MDD demonstrate significant increases in SWA in multiple cortical areas relative to control subjects. Further research is warranted to investigate the role of SWA in MDD, and to clarify how increased SWA in women with MDD is related to the pathophysiology of the disorder.

Regional differences in cortical electroencephalogram (EEG) slow wave activity and interhemispheric EEG asymmetry in the fur seal.

Slow wave sleep (SWS) in the northern fur seal (Callorhinus ursinus) is characterized by a highly expressed interhemispheric electroencephalogram (EEG) asymmetry, called 'unihemispheric' or 'asymmetrical' SWS. The aim of this study was to examine the regional differences in slow wave activity (SWA; power in the range of 1.2-4.0 Hz) within one hemisphere and differences in the degree of interhemispheric EEG asymmetry within this species. Three seals were implanted with 10 EEG electrodes, positioned bilaterally (five in each hemisphere) over the frontal, occipital and parietal cortex. The expression of interhemispheric SWA asymmetry between symmetrical monopolar recordings was estimated based on the asymmetry index [AI = (L-R)/(L+R), where L and R are the power in the left and right hemispheres, respectively]. Our findings indicate an anterior-posterior gradient in SWA during asymmetrical SWS in fur seals, which is opposite to that described for other mammals, including humans, with a larger SWA recorded in the parietal and occipital cortex. Interhemispheric EEG asymmetry in fur seals was recorded across the entire dorsal cerebral cortex, including sensory (visual and somatosensory), motor and associative (parietal or suprasylvian) cortical areas. The expression of asymmetry was greatest in occipital-lateral and parietal derivations and smallest in frontal-medial derivations. Regardless of regional differences in SWA, the majority (90%) of SWS episodes with interhemispheric EEG asymmetry meet the criteria for 'unihemispheric SWS' (one hemisphere is asleep while the other is awake). The remaining episodes can be described as episodes of bilateral SWS with a local activation in one cerebral hemisphere.

From apnea and insomnia in Iceland to season and slow wave sleep

Tacit assumptions and beliefs influence our research designs and interpretation of the data. Sometimes we have to admit that commonly held beliefs about sleep are based on scant data or no data at all. The current issue of the Journal of Sleep Research contains papers covering a wide range of issues relevant to sleep medicine and basic sleep research. Some of these papers challenge assumptions and common beliefs, others provide new insights. Apnea and insomnia are both highly prevalent and at first sight very distinct, disorders. Apnea is more common in men, and women suffer more frequently from insomnia. Recently, evidence that these disorders may co-exist has emerged. Bjornsdottir et al. (2012) have taken a closer look at the extent of co-existence in the general population in Iceland. Difficulties maintaining sleep were reported by 31% of women and 31% of men in the control group and 52% (men) and 62% (women) in the untreated obstructive sleep apnoea group. As reported by men, difficulties initiating sleep did not differ significantly between apnoea patients (12.6%) and controls (9.4%), but were much higher in women with apnea (27.3%) than in control women (27.3%). How to interpret these data? The authors point out that it may be that arousals associated with sleep apnea have a negative effect on sleep maintenance and sleep initiation. Therefore, it may be that sleep apnea is, at least in part, the underlying cause of the insomnia complaint, even though the degree of sleep apnea did not associate with insomnia complaints. Nevertheless, the data show that it is important to screen for insomnia in apnea patients, because the data also indicate that those apnea patients with insomnia report a greater reduction in quality of life than those apnea patients without insomnia. The current issue of the Journal also contains a report on differences in protein expression in serum samples of apnea patients (Jurado-Gamez et al., 2012). These differences were correlated with disease severity and were implicated primarily in lipid and vascular pathways. This, of course, fits neatly with the observation that sleep-disordered breathing is a risk factor for cardiovascular disease, and is a further step in understanding the pathogenesis underlying these associations. Svensson et al. (2012) also investigated some of the potential mechanisms underlying the associations between apnea and cardiovascular disease by assessing sleep, breathing and markers of inflammation in a population-based sample of 400 women in Sweden. A main finding of that study is that, after controlling for confounders such as central obesity, the percentage of sleep time with oxygen saturation below 90% appears to be the best predictor of inflammation. Of course, we sleep much longer during these long dark winter nights, and it is difficult to get up in the morning when it is freezing, snowing or just grey and drizzly? And should it not be expected that these effects of season are much greater on free days than during work days and much greater in Norway than in Ghana? Friborg et al. (2012) investigated these questions by asking a total of 330 participants in Norway and Ghana to complete a sleep diary for 1 week in August and January. Several surprising and unexpected findings emerged. Interaction between season and latitude were detected only during weekdays, not during weekends. No seasonal effect on sleep duration was detected. In the two countries, only aspects of sleep timing and insomnia were affected differentially by season. This is a relatively small study which raises many questions about the importance of variation in the duration of the natural photoperiod, the contribution of artificial light in the evening and social factors in the determination of sleep timing and quality which, to a large extent, are driven by circadian clocks. Individual differences in slow wave sleep (SWS) are considerable and stable within an individual. Several correlates of differences in slow wave activity have been reported recently (e.g. Buchmann et al., 2011), and it is often assumed that SWS is primarily for the brain. In the current issue, Mokhlesi et al. (2012) analyse data from more than 900 individuals who were referred to a sleep laboratory for suspected sleep apnea. Multiple regression analyses showed that age, gender, obesity and ethnicity, as well as sleep apnea severity, are all predictors of SWS. Some of these effects are comparable to or greater than the effects of total sleep deprivation. The challenge will now be to link the mechanisms by which individual differences in SWS relate to differences in the risk for developing, for example, diabetes or hypertension.

Anatomical markers of sleep slow wave activity derived from structural magnetic resonance images

Sleep studies often observe differences in slow wave activity (SWA) during non-rapid eye movement sleep between subjects. This study investigates to what extent these absolute differences in SWA can be explained with differences in grey matter volume, white matter volume or the thickness of skull and outer liquor rooms. To do this, we selected the 10-min interval showing maximal SWA of 20 young adult subjects and correlated these values lobe-wise with grey matter, skull and liquor thickness and globally with white matter as well as segments of the corpus callosum. Whereas grey matter, skull thickness and liquor did not correlate significantly with maximal slow wave activity, there were significant correlations with the anterior parts of the corpus callosum and with one other white matter region. In contrast, electroencephalogram power of higher frequencies correlates positively with grey matter volumes and cortical surface area. We discuss the possible role of white matter tracts on the synchronization of slow waves across the cortex.

S2067 ICC and Slow Wave Propagation in the Small Intestine of Diabetic Rats

in less than 20 min, with minimal human interaction, and with acceptable accuracy (~90% positive predictive value) compared with manually-generated maps. The electrode array positions and maps were anatomically registered on subject-specific stomach models across multiple recording sites and subjects. The 3D visualization of electrophysiology data was achieved. DISCUSSION: A computational pipeline for analyzing and anatomically-registering HR mapping data is presented. Although subject-specific results were employed and preferred, it would be possible to apply generic model templates to increase efficiency. This approach facilitates anatomically-accurate descriptions of regional differences in slow wave activity, and allows a more intuitive presentation of slow wave activity. This approach will also enable the establishment of a database of slow wave activity to allow quantitative comparisons between subjects and pathologies. In future, it will also allow the accurate anatomical localization of gastric dysrhythmic foci.