Sleep deprivation exacerbates microglial reactivity and Aβ deposition in a TREM2-dependent manner in mice

Sleep loss is associated with cognitive decline in the aging population and is a risk factor for Alzheimer's disease (AD). Considering the crucial role of immunomodulating genes such as that encoding the triggering receptor expressed on myeloid cells type 2 (TREM2) in removing pathogenic amyloid-β (Aβ) plaques and regulating neurodegeneration in the brain, our aim was to investigate whether and how sleep loss influences microglial function in mice. We chronically sleep-deprived wild-type mice and the 5xFAD mouse model of cerebral amyloidosis, expressing either the humanized TREM2 common variant, the loss-of-function R47H AD-associated risk variant, or without TREM2 expression. Sleep deprivation not only enhanced TREM2-dependent Aβ plaque deposition compared with 5xFAD mice with normal sleeping patterns but also induced microglial reactivity that was independent of the presence of parenchymal Aβ plaques. We investigated lysosomal morphology using transmission electron microscopy and found abnormalities particularly in mice without Aβ plaques and also observed lysosomal maturation impairments in a TREM2-dependent manner in both microglia and neurons, suggesting that changes in sleep modified neuro-immune cross-talk. Unbiased transcriptome and proteome profiling provided mechanistic insights into functional pathways triggered by sleep deprivation that were unique to TREM2 and Aβ pathology and that converged on metabolic dyshomeostasis. Our findings highlight that sleep deprivation directly affects microglial reactivity, for which TREM2 is required, by altering the metabolic ability to cope with the energy demands of prolonged wakefulness, leading to further Aβ deposition, and underlines the importance of sleep modulation as a promising future therapeutic approach.

Electrophysiological correlates of behavioural changes in vigilance in vegetative state and minimally conscious state

The existence of normal sleep in patients in a vegetative state is still a matter of debate. Previous electrophysiological sleep studies in patients with disorders of consciousness did not differentiate patients in a vegetative state from patients in a minimally conscious state. Using high-density electroencephalographic sleep recordings, 11 patients with disorders of consciousness (six in a minimally conscious state, five in a vegetative state) were studied to correlate the electrophysiological changes associated with sleep to behavioural changes in vigilance (sustained eye closure and muscle inactivity). All minimally conscious patients showed clear electroencephalographic changes associated with decreases in behavioural vigilance. In the five minimally conscious patients showing sustained behavioural sleep periods, we identified several electrophysiological characteristics typical of normal sleep. In particular, all minimally conscious patients showed an alternating non-rapid eye movement/rapid eye movement sleep pattern and a homoeostatic decline of electroencephalographic slow wave activity through the night. In contrast, for most patients in a vegetative state, while preserved behavioural sleep was observed, the electroencephalographic patterns remained virtually unchanged during periods with the eyes closed compared to periods of behavioural wakefulness (eyes open and muscle activity). No slow wave sleep or rapid eye movement sleep stages could be identified and no homoeostatic regulation of sleep-related slow wave activity was observed over the night-time period. In conclusion, we observed behavioural, but no electrophysiological, sleep wake patterns in patients in a vegetative state, while there were near-to-normal patterns of sleep in patients in a minimally conscious state. These results shed light on the relationship between sleep electrophysiology and the level of consciousness in severely brain-damaged patients. We suggest that the study of sleep and homoeostatic regulation of slow wave activity may provide a complementary tool for the assessment of brain function in minimally conscious state and vegetative state patients.

Attention modulation regulates both motor and non-motor performance: a high-density EEG study in Parkinson's disease

We have previously shown that, in early stages of Parkinson's disease (PD), patients with higher reaction times are also more impaired in visual sequence learning, suggesting that movement preparation shares resources with the learning of visuospatial sequences. Here, we ascertained whether, in patients with PD, the pattern of the neural correlates of attentional processes of movement planning predict sequence learning and working memory abilities. High density Electroencephalography (EEG, 256 electrodes) was recorded in 19 patients with PD performing reaching movements in a choice reaction time paradigm. Patients were also tested with Digit Span and performed a visuomotor sequence learning task that has an important declarative learning component. We found that attenuation of alpha/beta oscillatory activity before the stimulus presentation in frontoparietal regions significantly correlated with reaction time in the choice reaction time task, similarly to what we had previously found in normal subjects. In addition, such activity significantly predicted the declarative indices of sequence learning and the scores in the Digit Span task. These findings suggest that some motor and non motor PD signs might have common neural bases, and thus, might have a similar response to the same behavioral therapy. In addition, these results might help in designing and testing the efficacy of novel rehabilitative approaches to improve specific aspects of motor performance in PD and other neurological disorders.

The effects of morning training on night sleep: a behavioral and EEG study

The consolidation of memories in a variety of learning processes benefits from post-training sleep, and recent work has suggested a role for sleep slow wave activity (SWA). Previous studies using a visuomotor learning task showed a local increase in sleep SWA in right parietal cortex, which was correlated with post-sleep performance enhancement. In these as in most similar studies, learning took place in the evening, shortly before sleep. Thus, it is currently unknown whether learning a task in the morning, followed by the usual daily activities, would also result in a local increase in sleep SWA during the night, and in a correlated enhancement in performance the next day. To answer this question, a group of subjects performed a visuomotor learning task in the morning and was retested the following morning. Whole night sleep was recorded with high-density EEG. We found an increase of SWA over the right posterior parietal areas that was most evident during the second sleep cycle. Performance improved significantly the following morning, and the improvement was positively correlated with the SWA increase in the second sleep cycle. These results suggest that training-induced changes in sleep SWA and post-sleep improvements do not depend upon the time interval between original training and sleep.