Alzheimer's disease pathogenesis:The role of disturbed sleep in attenuated brain plasticity and neurodegenerative processes

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by cognitive impairments. The classical symptoms of the disease include gradual deterioration of memory and language. Epidemiological studies indicate that around 25-40% of AD patients have sleep-wake cycle disturbances. Importantly, a series of studies suggested that the relationship between AD and sleep disturbance may be complex and bidirectional. Indeed, accumulation of the extracellular neuronal protein amyloid-beta (A beta) leads to altered sleep-wake behavior in both mice and humans. At the same time, disturbances of the normal sleep-wake cycle may facilitate AD pathogenesis. This paper will review the mechanisms underlying this potential interrelated connection including locus coeruleus damage, reductions in orexin neurotransmission, alterations in melatonin levels, and elevated cytokine levels. In addition, we will also highlight how both the development of AD and sleep disturbances lead to changes in intracellular signaling pathways involved in regulating neuronal plasticity and connectivity, particularly extremes in cofilin phosphorylation. Finally, current pharmacological and nonpharmacological therapeutic approaches will be discussed

Linking light exposure and subsequent sleep:A field polysomnography study in humans

Study objectives: To determine the effect of light exposure on subsequent sleep characteristics under ambulatory field conditions. Methods: Twenty healthy participants were fitted with ambulatory PSG and wrist-actigraphs to assess light exposure, rest-activity, sleep quality, timing and architecture. Laboratory salivary dim-light melatonin onset (DLMO) was analyzed to determine endogenous circadian phase. Results: Later circadian clock phase was associated with lower intensity (R2=0.34, χ2(1)=7.19, p <0.01), later light exposure (quadratic, controlling for daylength, R2=0.47, χ2(3)=32.38, p <0.0001), and to later sleep timing (R2=0.71, χ2(1)=20.39, p<0.0001). Those with later first exposure to more than 10 lux of light had more awakenings during subsequent sleep (controlled for daylength, R2=0.36, χ2(2)=8.66, p<0.05). Those with later light exposure subsequently had a shorter latency to first REM sleep episode (R2=0.21, χ2(1)=5.77, p<0.05). Those with less light exposure subsequently had a higher percentage of REM sleep (R2=0.43, χ2(2)=13.90, p<0.001) in a clock phase modulated manner. Slow wave sleep accumulation was observed to be larger after preceding exposure to high maximal intensity and early first light exposure (p<0.05). Conclusions: The quality and architecture of sleep is associated with preceding light exposure. We propose that light exposure timing and intensity does not only modulate circadian-driven aspects of sleep but also homeostatic sleep pressure. These novel ambulatory PSG findings are the first to highlight the direct relationship between light and subsequent sleep, combining knowledge of homeostatic and circadian regulation of sleep by light. Upon confirmation by interventional studies, this hypothesis could change current understanding of sleep regulation and its relationship to prior light exposure

Perinatal fluoxetine exposure disrupts the circadian response to a phase-shifting challenge in female rats

Funding Information: This research was funded by the Dobberke foundation, grant number UPS/BP/4151 2016-27.Peer reviewedPublisher PD

The reverse translation of a quantitative neuropsychiatric framework into preclinical studies:Focus on social interaction and behavior

Following the Research Domain Criteria (RDoC) concept, major brain circuits are conserved in evolution and malfunctioning of a brain circuit will lead to specific behavioral symptoms. Reverse translation of patient-based findings from Alzheimer’s disease (AD), schizophrenia (SZ) and major depression (MD) patients to preclinical models accordingly can be a starting point for developing a deeper understanding of the functional circuit biology and contribute to the validation of new hypotheses for therapeutic intervention in patients. In the context of the EU funded PRISM project, a preclinical test battery of tasks has been selected and aligned with the clinical test battery. It allows for assessment of social functioning, sensory processing, attention and working memory and is designed for validation of biological substrates from human molecular landscaping of social withdrawal. This review will broadly summarize the available literature on tasks for studying social behavior in rodents and outline the development of a preclinical test battery for the PRISM project by reverse translation

Daily light exposure patterns reveal phase and period of the human circadian clock

Light is the most potent time cue that synchronizes (entrains) the circadian pacemaker to the 24-h solar cycle. This entrainment process is an interplay between an individual's daily light perception and intrinsic pacemaker period under free-running conditions. Establishing individual estimates of circadian phase and period can be time-consuming. We show that circadian phase can be accurately predicted (SD = 1.1 h for dim light melatonin onset, DLMO) using 9 days of ambulatory light and activity data as an input to Kronauer's limit-cycle model for the human circadian system. This approach also yields an estimated circadian period of 24.2 h (SD = 0.2 h), with longer periods resulting in later DLMOs. A larger amount of daylight exposure resulted in an earlier DLMO. Individuals with a long circadian period also showed shorter intervals between DLMO and sleep timing. When a field-based estimation of tau can be validated under laboratory studies in a wide variety of individuals, the proposed methods may prove to be essential tools for individualized chronotherapy and light treatment for shift work and jetlag applications. These methods may improve our understanding of fundamental properties of human circadian rhythms under daily living conditions

Validation of ‘Somnivore’, a Machine Learning Algorithm for Automated Scoring and Analysis of Polysomnography Data

Manual scoring of polysomnography data is labor-intensive and time-consuming, and most existing software does not account for subjective differences and user variability. Therefore, we evaluated a supervised machine learning algorithm, SomnivoreTM, for automated wake–sleep stage classification. We designed an algorithm that extracts features from various input channels, following a brief session of manual scoring, and provides automated wake-sleep stage classification for each recording. For algorithm validation, polysomnography data was obtained from independent laboratories, and include normal, cognitively-impaired, and alcohol-treated human subjects (total n = 52), narcoleptic mice and drug-treated rats (total n = 56), and pigeons (n = 5). Training and testing sets for validation were previously scored manually by 1–2 trained sleep technologists from each laboratory. F-measure was used to assess precision and sensitivity for statistical analysis of classifier output and human scorer agreement. The algorithm gave high concordance with manual visual scoring across all human data (wake 0.91 ± 0.01; N1 0.57 ± 0.01; N2 0.81 ± 0.01; N3 0.86 ± 0.01; REM 0.87 ± 0.01), which was comparable to manual inter-scorer agreement on all stages. Similarly, high concordance was observed across all rodent (wake 0.95 ± 0.01; NREM 0.94 ± 0.01; REM 0.91 ± 0.01) and pigeon (wake 0.96 ± 0.006; NREM 0.97 ± 0.01; REM 0.86 ± 0.02) data. Effects of classifier learning from single signal inputs, simple stage reclassification, automated removal of transition epochs, and training set size were also examined. In summary, we have developed a polysomnography analysis program for automated sleep-stage classification of data from diverse species. Somnivore enables flexible, accurate, and high-throughput analysis of experimental and clinical sleep studies

Neurodegeneration and brain cancer: a longitudinal field study of rest-activity and sleep

This thesis investigates rest-activity and sleep profiles in neurodegeneration and brain cancer. Study 1 comprised longitudinal field assessments of rest-activity, sleep and memory in controls and memory-impairment individuals with: subjective memory complaint (SMC), amnestic mild cognitive impairment (aMCI), mild and moderate Alzheimer’s disease (AD). Four questions were addressed: (1) is SMC a prodromal stage of AD? (2) do characteristics of SMC predict future decline? (3) does cholinergic medication (ChEI) impact rest-activity and sleep of moderate AD patients? and (4) are there factors predicting response to ChEI? Study 2 assessed rest-activity and melatonin rhythms in a brain cancer patient (JJB), and post-mortem analysis of brain tissue assessed infiltration of cancer cells on the circadian clock (SCN). Both studies used questionnaires, cognitive tests, electroencephalography and actigraphy simultaneously at patients’ homes. In Study 1, the SMC group showed a reduced activity amplitude to be correlated with increasing memory impairment severity, lower sleep quality and efficiency. Increased sleep fragmentation was observed in all memory-impaired groups, although not correlated to impairment severity. Increased fragmentation of rest-activity rhythm correlated with increasing memory impairment severity in all groups except SMC. Following ChEI medication with donepezil, moderate AD patients showed increased sleep fragmentation, probably due to potentiation of available acetylcholine known to maintain arousal. Higher daytime-activity and lower activity in the rest-phase, when drug-naïve, predicted improved cognition following ChEIs. In Study 2, cancer cell infiltration of the patient’s SCN was confirmed. However, a robust circadian rest-activity period with a misaligned melatonin phase, was recorded, indicating that the effects of partial SCN lesions in humans are complex and this result was possibly in part are due to the masking effect of social behaviour.</p

Neurodegeneration and brain cancer: a longitudinal field study of rest-activity and sleep

This thesis investigates rest-activity and sleep profiles in neurodegeneration and brain cancer. Study 1 comprised longitudinal field assessments of rest-activity, sleep and memory in controls and memory-impairment individuals with: subjective memory complaint (SMC), amnestic mild cognitive impairment (aMCI), mild and moderate Alzheimer’s disease (AD). Four questions were addressed: (1) is SMC a prodromal stage of AD? (2) do characteristics of SMC predict future decline? (3) does cholinergic medication (ChEI) impact rest-activity and sleep of moderate AD patients? and (4) are there factors predicting response to ChEI? Study 2 assessed rest-activity and melatonin rhythms in a brain cancer patient (JJB), and post-mortem analysis of brain tissue assessed infiltration of cancer cells on the circadian clock (SCN). Both studies used questionnaires, cognitive tests, electroencephalography and actigraphy simultaneously at patients’ homes. In Study 1, the SMC group showed a reduced activity amplitude to be correlated with increasing memory impairment severity, lower sleep quality and efficiency. Increased sleep fragmentation was observed in all memory-impaired groups, although not correlated to impairment severity. Increased fragmentation of rest-activity rhythm correlated with increasing memory impairment severity in all groups except SMC. Following ChEI medication with donepezil, moderate AD patients showed increased sleep fragmentation, probably due to potentiation of available acetylcholine known to maintain arousal. Higher daytime-activity and lower activity in the rest-phase, when drug-naïve, predicted improved cognition following ChEIs. In Study 2, cancer cell infiltration of the patient’s SCN was confirmed. However, a robust circadian rest-activity period with a misaligned melatonin phase, was recorded, indicating that the effects of partial SCN lesions in humans are complex and this result was possibly in part are due to the masking effect of social behaviour.This thesis is not currently available in ORA

Cerebellar Atlas Data

A collection of manually labeled cerebellar atlases. For details please see and cite: Jörn Diedrichsen, Joshua H. Balsters, Jonathan Flavell, Emma Cussans, Narender Ramnani, A probabilistic MR atlas of the human cerebellum, NeuroImage, Volume 46, Issue 1, 15 May 2009, Pages 39-46, ISSN 1053-8119, http://dx.doi.org/10.1016/j.neuroimage.2009.01.045