NREM Sleep Oscillations and Brain Plasticity in Aging

The Interaction between Obstructive Sleep Apnea and Parkinson's Disease: Possible Mechanisms and Implications for Cognitive Function

Parkinson's disease (PD) is a relentlessly progressive neurodegenerative disorder associated with hallmark motor and nonmotor symptoms (NMS) such as sleep disturbances and cognitive dysfunction. While dopaminergic treatments have improved the motor aspects of PD, progression remains inevitable. Research has recently increasingly focused on strategies to modify disease progression and on nonmotor manifestations of PD, given their impact on patients' quality of life. Obstructive sleep apnea (OSA) is a treatable sleep disorder, common in the general population, associated with excessive daytime sleepiness and neurocognitive deficits. Neuroimaging has demonstrated structural and functional changes in OSA patients; in animal models, OSA causes brain inflammation and oxidative injury, including in key areas involved in PD pathophysiology such as locus coeruleus. The prevalence of OSA in PD has been variable in studies to date, and potential consequences and interrelationship between the two disorders have not been well studied. There is however emerging evidence that OSA is associated with increased NMS in PD, particularly cognitive dysfunction. This review focuses on the possible interrelationship between OSA and PD. Mechanisms promoting OSA in PD will be reviewed, as well as mechanisms whereby OSA can affect the neurodegenerative process in PD.

Changes in Cognitive Performance Are Associated with Changes in Sleep in Older Adults With Insomnia

The present study examined sleep features associated with cognition in older adults and examined whether sleep changes following insomnia treatment were associated with cognitive improvements. Polysomnography and cognition (recall, working memory, and reasoning) were assessed before and after an insomnia intervention (Brief Behavioral Treatment of Insomnia [BBTI] or information control [IC]) in 77 older adults with insomnia. Baseline wake-after-sleep-onset (WASO) was associated with recall. Greater NREM (nonrapid eye movement) delta power and lower NREM sigma power were associated with greater working memory and reasoning. The insomnia intervention did not improve performance. However, increased absolute delta power and decreased relative sigma power were associated with improved reasoning. Findings suggest that improvements in executive function may occur with changes in NREM architecture.

Sleep spindle and K-complex detection using tunable Q-factor wavelet transform and morphological component analysis

A novel framework for joint detection of sleep spindles and K-complex events, two hallmarks of sleep stage S2, is proposed. Sleep electroencephalography (EEG) signals are split into oscillatory (spindles) and transient (K-complex) components. This decomposition is conveniently achieved by applying morphological component analysis (MCA) to a sparse representation of EEG segments obtained by the recently introduced discrete tunable Q-factor wavelet transform (TQWT). Tuning the Q-factor provides a convenient and elegant tool to naturally decompose the signal into an oscillatory and a transient component. The actual detection step relies on thresholding (i) the transient component to reveal K-complexes and (ii) the time-frequency representation of the oscillatory component to identify sleep spindles. Optimal thresholds are derived from ROC-like curves (sensitivity vs. FDR) on training sets and the performance of the method is assessed on test data sets. We assessed the performance of our method using full-night sleep EEG data we collected from 14 participants. In comparison to visual scoring (Expert 1), the proposed method detected spindles with a sensitivity of 83.18% and false discovery rate (FDR) of 39%, while K-complexes were detected with a sensitivity of 81.57% and an FDR of 29.54%. Similar performances were obtained when using a second expert as benchmark. In addition, when the TQWT and MCA steps were excluded from the pipeline the detection sensitivities dropped down to 70% for spindles and to 76.97% for K-complexes, while the FDR rose up to 43.62 and 49.09%, respectively. Finally, we also evaluated the performance of the proposed method on a set of publicly available sleep EEG recordings. Overall, the results we obtained suggest that the TQWT-MCA method may be a valuable alternative to existing spindle and K-complex detection methods. Paths for improvements and further validations with large-scale standard open-access benchmarking data sets are discussed.

Hippocampal activity mediates the relationship between circadian activity rhythms and memory in older adults

Older adults experience parallel changes in sleep, circadian rhythms, and episodic memory. These processes appear to be linked such that disruptions in sleep contribute to deficits in memory. Although more variability in circadian patterns is a common feature of aging and predicts pathology, little is known about how alterations in circadian activity rhythms within older adults influence new episodic learning. Following 10 days of recording sleep-wake patterns using actigraphy, healthy older adults underwent fMRI while performing an associative memory task. The results revealed better associative memory was related to more consistent circadian activity rhythms, independent of total sleep time, sleep efficiency, and level of physical activity. Moreover, hippocampal activity during successful memory retrieval events was positively correlated with associative memory accuracy and circadian activity rhythm (CAR) consistency. We demonstrated that the link between consistent rhythms and associative memory performance was mediated by hippocampal activity. These findings provide novel insight into how the circadian rhythm of sleep-wake cycles are associated with memory in older adults and encourage further examination of circadian activity rhythms as a biomarker of cognitive functioning.

Acupuncture-brain interactions as hypothesized by mood scale recordings

Mood expressions encompassing positive scales like "activity, elation, contemplation, calmness" and negative scales like "anger, excitement, depression, fatigue" were applied for introducing a new tool to assess the effects of acupuncture on brain structures. Traditional acupuncture points defined in the literature for their effects on task negative and task positive brain structures were applied to chronic disease patients supposed to have dominant negative mood scales. Burn-out syndrome (n=10) and female chronic pain patients (n=22) showed a significant improvement on positive mood scales and a decline in negative mood scales after 10 acupuncture sessions. We observed a direct effect of acupuncture on brain structures in 5 burn-out syndrome patients showing an immediate, fast suppression of unusual slow high amplitude EEG waves in response to acupuncture needle rotation. These EEG waves described here for the first time in awake patients disappeared after 10 sessions but gradually returned after 1-1.5 years without acupuncture. This was accompanied with deterioration of positive mood scales and a return to negative mood scales. Both male (n=16) and female chronic pain patients reported a significant decrease of pain intensity after 10 sessions. Female patients only, however, showed a linear correlation between initial pain intensity and pain relief as well as a linear correlation between changes in pain intensity and mood scales accompanied by a drop of their heart rate during the acupuncture sessions. We hypothesized that mood scale recordings are a sensitive and specific new tool to reveal individual acupuncture-brain interaction.

Dysplasticity, metaplasticity, and schizophrenia: Implications for risk, illness, and novel interventions

In this paper, we review the history of the concept of neuroplasticity as it relates to the understanding of neuropsychiatric disorders, using schizophrenia as a case in point. We briefly review the myriad meanings of the term neuroplasticity, and its neuroscientific basis. We then review the evidence for aberrant neuroplasticity and metaplasticity associated with schizophrenia as well as the risk for developing this illness, and discuss the implications of such understanding for prevention and therapeutic interventions. We argue that the failure and/or altered timing of plasticity of critical brain circuits might underlie cognitive and deficit symptoms, and may also lead to aberrant plastic reorganization in other circuits, leading to affective dysregulation and eventually psychosis. This "dysplastic" model of schizophrenia can suggest testable etiology and treatment-relevant questions for the future.

Sleep spindle alterations in patients with Parkinson's disease

The aim of this study was to identify changes of sleep spindles (SS) in the EEG of patients with Parkinson's disease (PD). Five sleep experts manually identified SS at a central scalp location (C3-A2) in 15 PD and 15 age- and sex-matched control subjects. Each SS was given a confidence score, and by using a group consensus rule, 901 SS were identified and characterized by their (1) duration, (2) oscillation frequency, (3) maximum peak-to-peak amplitude, (4) percent-to-peak amplitude, and (5) density. Between-group comparisons were made for all SS characteristics computed, and significant changes for PD patients vs. control subjects were found for duration, oscillation frequency, maximum peak-to-peak amplitude and density. Specifically, SS density was lower, duration was longer, oscillation frequency slower and maximum peak-to-peak amplitude higher in patients vs. controls. We also computed inter-expert reliability in SS scoring and found a significantly lower reliability in scoring definite SS in patients when compared to controls. How neurodegeneration in PD could influence SS characteristics is discussed. We also note that the SS morphological changes observed here may affect automatic detection of SS in patients with PD or other neurodegenerative disorders (NDDs).

Combining time-frequency and spatial information for the detection of sleep spindles

EEG sleep spindles are short (0.5-2.0 s) bursts of activity in the 11-16 Hz band occurring during non-rapid eye movement (NREM) sleep. This sporadic activity is thought to play a role in memory consolidation, brain plasticity, and protection of sleep integrity. Many automatic detectors have been proposed to assist or replace experts for sleep spindle scoring. However, these algorithms usually detect too many events making it difficult to achieve a good tradeoff between sensitivity (Se) and false detection rate (FDr). In this work, we propose a semi-automatic detector comprising a sensitivity phase based on well-established criteria followed by a specificity phase using spatial and spectral criteria. In the sensitivity phase, selected events are those which amplitude in the 10-16 Hz band and spectral ratio characteristics both reject a null hypothesis (p < 0.1) stating that the considered event is not a spindle. This null hypothesis is constructed from events occurring during rapid eye movement (REM) sleep epochs. In the specificity phase, a hierarchical clustering of the selected candidates is done based on events' frequency and spatial position along the anterior-posterior axis. Only events from the classes grouping most (at least 80%) spindles scored by an expert are kept. We obtain Se = 93.2% and FDr = 93.0% in the first phase and Se = 85.4% and FDr = 86.2% in the second phase. For these two phases, Matthew's correlation coefficients are respectively 0.228 and 0.324. Results suggest that spindles are defined by specific spatio-spectral properties and that automatic detection methods can be improved by considering these features.

Sleep, cognition, and normal aging: integrating a half century of multidisciplinary research

Sleep is implicated in cognitive functioning in young adults. With increasing age, there are substantial changes to sleep quantity and quality, including changes to slow-wave sleep, spindle density, and sleep continuity/fragmentation. A provocative question for the field of cognitive aging is whether such changes in sleep physiology affect cognition (e.g., memory consolidation). We review nearly a half century of research across seven diverse correlational and experimental domains that historically have had little crosstalk. Broadly speaking, sleep and cognitive functions are often related in advancing age, though the prevalence of null effects in healthy older adults (including correlations in the unexpected, negative direction) indicates that age may be an effect modifier of these associations. We interpret the literature as suggesting that maintaining good sleep quality, at least in young adulthood and middle age, promotes better cognitive functioning and serves to protect against age-related cognitive declines.

Inter-expert and intra-expert reliability in sleep spindle scoring

OBJECTIVES

To measure the inter-expert and intra-expert agreement in sleep spindle scoring, and to quantify how many experts are needed to build a reliable dataset of sleep spindle scorings.

METHODS

The EEG dataset was comprised of 400 randomly selected 115s segments of stage 2 sleep from 110 sleeping subjects in the general population (57±8, range: 42-72 years). To assess expert agreement, a total of 24 Registered Polysomnographic Technologists (RPSGTs) scored spindles in a subset of the EEG dataset at a single electrode location (C3-M2). Intra-expert and inter-expert agreements were calculated as F1-scores, Cohen's kappa (κ), and intra-class correlation coefficient (ICC).

RESULTS

We found an average intra-expert F1-score agreement of 72±7% (κ: 0.66±0.07). The average inter-expert agreement was 61±6% (κ: 0.52±0.07). Amplitude and frequency of discrete spindles were calculated with higher reliability than the estimation of spindle duration. Reliability of sleep spindle scoring can be improved by using qualitative confidence scores, rather than a dichotomous yes/no scoring system.

CONCLUSIONS

We estimate that 2-3 experts are needed to build a spindle scoring dataset with 'substantial' reliability (κ: 0.61-0.8), and 4 or more experts are needed to build a dataset with 'almost perfect' reliability (κ: 0.81-1).

SIGNIFICANCE

Spindle scoring is a critical part of sleep staging, and spindles are believed to play an important role in development, aging, and diseases of the nervous system.

A time-frequency analysis of the dynamics of cortical networks of sleep spindles from MEG-EEG recordings

Sleep spindles are a hallmark of NREM sleep. They result from a widespread thalamo-cortical loop and involve synchronous cortical networks that are still poorly understood. We investigated whether brain activity during spindles can be characterized by specific patterns of functional connectivity among cortical generators. For that purpose, we developed a wavelet-based approach aimed at imaging the synchronous oscillatory cortical networks from simultaneous MEG-EEG recordings. First, we detected spindles on the EEG and extracted the corresponding frequency-locked MEG activity under the form of an analytic ridge signal in the time-frequency plane (Zerouali et al., 2013). Secondly, we performed source reconstruction of the ridge signal within the Maximum Entropy on the Mean framework (Amblard et al., 2004), yielding a robust estimate of the cortical sources producing observed oscillations. Lastly, we quantified functional connectivity among cortical sources using phase-locking values. The main innovations of this methodology are (1) to reveal the dynamic behavior of functional networks resolved in the time-frequency plane and (2) to characterize functional connectivity among MEG sources through phase interactions. We showed, for the first time, that the switch from fast to slow oscillatory mode during sleep spindles is required for the emergence of specific patterns of connectivity. Moreover, we show that earlier synchrony during spindles was associated with mainly intra-hemispheric connectivity whereas later synchrony was associated with global long-range connectivity. We propose that our methodology can be a valuable tool for studying the connectivity underlying neural processes involving sleep spindles, such as memory, plasticity or aging.

Sleep spindles in Parkinson's disease may predict the development of dementia

Sleep disturbances and cognitive impairment are common non-motor manifestations of Parkinson's disease (PD). Recent studies suggest that sleep spindles and slow waves play a role in brain plasticity mechanisms and are associated with cognitive performance. However, it remains unknown whether these sleep parameters could serve as markers of cognitive decline in PD. Therefore, we examined whether alterations in sleep spindles and slow waves at baseline visit were associated with increased likelihood of developing dementia at follow-up in PD. Sixty-eight nondemented PD patients (64.9 ± 8.8 years old; 46 men) participated in the study, along with 47 healthy individuals (65.0 ± 10.6 years old; 30 men). All participants underwent baseline polysomnographic recording and a comprehensive neuropsychological assessment. Sleep spindles (12-15 Hz) and slow waves (>75 μV and <4 Hz) were automatically detected on all-night non-rapid eye movement sleep electroencephalography. At follow-up (mean: 4.5 years later), 18 PD patients developed dementia (70.2 ± 7.6 years old; 13 men) and 50 remained dementia-free (63.0 ± 8.5 years old; 33 men). Sleep spindle density and amplitude were lower in PD patients who converted to dementia compared with both patients who remained dementia-free and controls, mostly in posterior cortical regions (p < 0.05). Dementia-free PD patients were intermediate between dementia patients and controls, with lower baseline sleep spindle density in all cortical areas compared with controls (p < 0.01). In demented PD patients, lower sleep spindle amplitude in parietal and occipital areas was associated with poorer visuospatial abilities. Although slow wave amplitude was lower in PD patients compared with controls (p < 0.0001), no difference was observed between those who developed or did not develop dementia. Results demonstrate non-rapid eye movement sleep electroencephalographic abnormalities in PD patients. Sleep spindle activity was particularly impaired in PD patients who developed dementia, with a more posterior topographic pattern. Sleep spindle alterations are associated with later development of dementia in PD, and thus may serve as an additional marker of cognitive decline in these patients.

Off-line consolidation of motor sequence learning results in greater integration within a cortico-striatal functional network

The consolidation of motor sequence learning is known to depend on sleep. Work in our laboratory and others have shown that the striatum is associated with this off-line consolidation process. In this study, we aimed to quantify the sleep-dependent dynamic changes occurring at the network level using a measure of functional integration. We directly compared changes in connectivity before and after sleep or the simple passage of daytime. As predicted, the results revealed greater integration within the cortico-striatal network after sleep, but not an equivalent daytime period. Importantly, a similar pattern of results was also observed using a data-driven approach; the increase in integration being specific to a cortico-striatal network, but not to other known functional networks. These findings reveal, for the first time, a new signature of motor sequence consolidation: a greater between-regions interaction within the cortico-striatal system.

Age differences in the variability and distribution of sleep spindle and rapid eye movement densities

The present study had two main objectives. The first objective was to compare the sleep architecture of young and older adults, with an emphasis on sleep spindle density and REM density. The second objective was to examine two aspects of age differences that have not been considered in previous studies: age differences in the variability of sleep measures as well as the magnitude of age differences in phasic events across the distribution of values (i.e., at each decile rather than a single measure of location such as the mean or median. A total of 24 young (mean age=20.75 ± 1.78 years) and 24 older (mean age=71.17 ± 6.15 years) adults underwent in-home polysomnography. Whole-night spindle density was significantly higher in young adults than older adults. The two age groups did not differ significantly in whole-night REM density, although significant increases in REM density across the night were observed in both age groups. These results suggest that spindle density is more affected by age than REM density. Although age differences were observed in the degree of absolute variability (older adults had significantly larger variances than young adults for sleep efficiency and time spent awake after sleep onset), a similar pattern was also observed within the two age groups: the four sleep measures with the lowest degrees of relative variability were the same and included time spent in REM and Stage 2 sleep, total sleep time, and sleep efficiency. The distributional analysis of age differences in sleep spindle density revealed that the largest age differences were initially observed in the middle of the distributions, but as the night progressed, they were seen at the upper end of the distributions. The results reported here have potential implications for the causes and functional implications of age-related changes in sleep architecture.

fMRI and sleep correlates of the age-related impairment in motor memory consolidation

Behavioral studies indicate that older adults exhibit normal motor sequence learning (MSL), but paradoxically, show impaired consolidation of the new memory trace. However, the neural and physiological mechanisms underlying this impairment are entirely unknown. Here, we sought to identify, through functional magnetic resonance imaging during MSL and electroencephalographic (EEG) recordings during daytime sleep, the functional correlates and physiological characteristics of this age-related motor memory deficit. As predicted, older subjects did not exhibit sleep-dependent gains in performance (i.e., behavioral changes that reflect consolidation) and had reduced sleep spindles compared with young subjects. Brain imaging analyses also revealed that changes in activity across the retention interval in the putamen and related brain regions were associated with sleep spindles. This change in striatal activity was increased in young subjects, but reduced by comparison in older subjects. These findings suggest that the deficit in sleep-dependent motor memory consolidation in elderly individuals is related to a reduction in sleep spindle oscillations and to an associated decrease of activity in the cortico-striatal network.

Does age worsen sleep-dependent memory consolidation?

Slow wave sleep (SWS) is known to favour episodic memory consolidation. Given that ageing is associated with a reduction in SWS and episodic memory impairment, our aim was to investigate whether memory continues to benefit from sleep in older adults. Episodic memory consolidation was tested in 20 young (22.1 ± 1.7 years) and 20 older volunteers (68.9 ± 5.3 years) who performed a visuospatial two-dimensional object-location task. Retention capacities were evaluated after 12 h of wakefulness or 12 h of sleep. Performances before and after the interval allowed us to calculate a forgetting rate. Sleep architecture was measured by polysomnography (older adults = 410 min; young adults: 467 min). Our results showed that the beneficial effect of sleep on memory consolidation was reduced in older adults compared to young adults. In older adults, sleep did not enhance memory consolidation significantly compared to wakefulness. Sleep prevented young adults from forgetting (-0.10% ± 2.1), while the forgetting rate in older adults was still important after a period of sleep (16.60% ± 4.2; P = 0.05). The sleep architecture of older adults was characterized by a decrease in sleep efficiency (-12%; P < 0.05), in total cycle time (-137 min; P < 0.05), in percentage of total cycle time (-21%; P < 0.05) and in rapid eye movement time (-41 min; P < 0.05) compared to young adults. However, no difference in slow wave sleep was observed (-1%; not significant) and no correlation was found with performance. Age-related changes in sleep parameters may have a negative impact on memory consolidation in older adults.

Exercise benefits for the aging brain depend on the accompanying cognitive load: insights from sleep electroencephalogram

Although exercise clearly offsets aging effects on the body, its benefits for the aging brain are likely to depend on the extent that physical activity (especially locomotion) facilitates multisensory encounters, curiosity, and interactions with novel environments; this is especially true for exploratory activity, which occupies much of wakefulness for most mammals in the wild. Cognition is inseparable from physical activity, with both interlinked to promote neuroplasticity and more successful brain aging. In these respects and for humans, exercising in a static, featureless, artificially lit indoor setting contrasts with exploratory outdoor walking within a novel environment during daylight. However, little is known about the comparative benefits for the aging brain of longer-term daily regimens of this latter nature including the role of sleep, to the extent that sleep enhances neuroplasticity as shown in short-term laboratory studies. More discerning analyses of sleep electroencephalogram (EEG) slow-wave activity especially 0.5-2-Hz activity would provide greater insights into use-dependent recovery processes during longer-term tracking of these regimens and complement slower changing waking neuropsychologic and resting functional magnetic resonance imaging (fMRI) measures, including those of the brain's default mode network. Although the limited research only points to ephemeral small sleep EEG effects of pure exercise, more enduring effects seem apparent when physical activity incorporates cognitive challenges. In terms of "use it or lose it," curiosity-driven "getting out and about," encountering, interacting with, and enjoying novel situations may well provide the brain with its real exercise, further reflected in changes to the dynamics of sleep.

Sleep cyclic alternating pattern and cognition in children: a review

Several studies have been recently focused on the relationship between sleep cyclic alternating pattern (CAP) and daytime cognitive performance, supporting the idea that the CAP slow components may play a role in sleep-related cognitive processes. Based on the results of these reports, it can be hypothesized that the analysis of CAP might be helpful in characterizing sleep microstructure patterns of different phenotypes of intellectual disability and a series of studies has been carried out that are reviewed in this paper. First the studies exploring the correlations between CAP and cognitive performance in normal adults and children are described; then, those analyzing the correlation between CAP and cognitive patterns of several developmental conditions with neurocognitive dysfunction (with or without mental retardation) are reported in detail in order to achieve a unitary view of the role of CAP in these conditions that allows to detect a particular "sleep microstructure phenotype" of children with neurologic/neuropsychiatric disorders.

Impaired prefrontal sleep spindle regulation of hippocampal-dependent learning in older adults

A hallmark feature of cognitive aging is a decline in the ability to form new memories. Parallel to these cognitive impairments are marked disruptions in sleep physiology. Despite recent evidence in young adults establishing a role for sleep spindles in restoring hippocampal-dependent memory formation, the possibility that disrupted sleep physiology contributes to age-related decline in hippocampal-dependent learning remains unknown. Here, we demonstrate that reduced prefrontal sleep spindles by over 40% in older adults statistically mediates the effects of old age on next day episodic learning, such that the degree of impaired episodic learning is explained by the extent of impoverished prefrontal sleep spindles. In addition, prefrontal spindles significantly predicted the magnitude of impaired next day hippocampal activation, thereby determining the influence of spindles on post-sleep learning capacity. These data support the hypothesis that disrupted sleep physiology contributes to age-related cognitive decline in later life, the consequence of which has significant treatment intervention potential.