Sleep, Noninvasive Brain Stimulation, and the Aging Brain: Challenges and Opportunities

The multifactorial nature of healthy brain ageing: Brain changes, functional decline and protective factors

As the global population faces a progressive shift towards a higher median age, understanding the mechanisms underlying healthy brain ageing has become of paramount importance for the preservation of cognitive abilities. The first part of the present review aims to provide a comprehensive look at the anatomical changes the healthy brain endures with advanced age, while also summarizing up to date findings on modifiable risk factors to support a healthy ageing process. Subsequently, we describe the typical cognitive profile displayed by healthy older adults, conceptualizing the well-established age-related decline as an impairment of four main cognitive factors and relating them to their neural substrate previously described; different cognitive trajectories displayed by typical Alzheimer's Disease patients and successful agers with a high cognitive reserve are discussed. Finally, potential effective interventions and protective strategies to promote cognitive reserve and defer cognitive decline are reviewed and proposed.

PTH levels, sleep quality, and cognitive function in primary hyperparathyroidism

BACKGROUND

Cognitive function in patients with primary hyperparathyroidism (PHPT) may be affected and be identified to have been linked to the level of parathyroid hormone (PTH). Previous studies have suggested that patients with PHPT present poor sleep quality, which might interact with cognitive decline. The purpose of this study was to determine whether sleep quality mediates the association between PTH level and cognitive function and investigate whether surgery improves sleep quality and cognition in PHPT patients.

METHODS

Between June 2019 and August 2022, we recruited 146 patients diagnosed with PHPT (n = 146). We collected clinical data from medical records and evaluated sleep quality and cognition preoperatively and 2 months postoperatively by using the Pittsburgh Sleep Quality Index and Min-Mental State Examination. We examined the mediation effects of sleep disturbance and latency on correlations between PTH level and cognitive impairment by using the Bootstrap method.

RESULTS

The sleep quality and cognitive function were correlated with PTH level before surgery. Sleep latency or sleep disturbance exhibited a partial mediating effect on the association between PTH level and MMSE scores in PHPT patients (p < 0.05). In PHPT patients, there was a significant decline in PTH levels and an improvement in cognitive function post-surgery compared to pre-surgery, but no significant differences in sleep quality.

CONCLUSION

Sleep disturbance and sleep latency may mediate the association between PTH level and cognitive impairment in PHPT before surgery. The surgery could reduce PTH levels and improve cognition, but might not improve sleep quality in PHPT patients.

A unique color-coded visualization system with multimodal information fusion and deep learning in a longitudinal study of Alzheimer's disease

PURPOSE

Automated diagnosis and prognosis of Alzheimer's Disease remain a challenging problem that machine learning (ML) techniques have attempted to resolve in the last decade. This study introduces a first-of-its-kind color-coded visualization mechanism driven by an integrated ML model to predict disease trajectory in a 2-year longitudinal study. The main aim of this study is to help capture visually in 2D and 3D renderings the diagnosis and prognosis of AD, therefore augmenting our understanding of the processes of multiclass classification and regression analysis.

METHOD

The proposed method, Machine Learning for Visualizing AD (ML4VisAD), is designed to predict disease progression through a visual output. This newly developed model takes baseline measurements as input to generate a color-coded visual image that reflects disease progression at different time points. The architecture of the network relies on convolutional neural networks. With 1123 subjects selected from the ADNI QT-PAD dataset, we use a 10-fold cross-validation process to evaluate the method. Multimodal inputs* include neuroimaging data (MRI, PET), neuropsychological test scores (excluding MMSE, CDR-SB, and ADAS to avoid bias), cerebrospinal fluid (CSF) biomarkers with measures of amyloid beta (ABETA), phosphorylated tau protein (PTAU), total tau protein (TAU), and risk factors that include age, gender, years of education, and ApoE4 gene.

FINDINGS/RESULTS

Based on subjective scores reached by three raters, the results showed an accuracy of 0.82 ± 0.03 for a 3-way classification and 0.68 ± 0.05 for a 5-way classification. The visual renderings were generated in 0.08 msec for a 23 × 23 output image and in 0.17 ms for a 45 × 45 output image. Through visualization, this study (1) demonstrates that the ML visual output augments the prospects for a more accurate diagnosis and (2) highlights why multiclass classification and regression analysis are incredibly challenging. An online survey was conducted to gauge this visualization platform's merits and obtain valuable feedback from users. All implementation codes are shared online on GitHub.

CONCLUSION

This approach makes it possible to visualize the many nuances that lead to a specific classification or prediction in the disease trajectory, all in context to multimodal measurements taken at baseline. This ML model can serve as a multiclass classification and prediction model while reinforcing the diagnosis and prognosis capabilities by including a visualization platform.

Optimizing transcranial magnetic stimulation for spaceflight applications

As space agencies aim to reach and build installations on Mars, the crews will face longer exposure to extreme environments that may compromise their health and performance. Transcranial magnetic stimulation (TMS) is a painless non-invasive brain stimulation technique that could support space exploration in multiple ways. However, changes in brain morphology previously observed after long-term space missions may impact the efficacy of this intervention. We investigated how to optimize TMS for spaceflight-associated brain changes. Magnetic resonance imaging T1-weighted scans were collected from 15 Roscosmos cosmonauts and 14 non-flyer participants before, after 6 months on the International Space Station, and at a 7-month follow-up. Using biophysical modeling, we show that TMS generates different modeled responses in specific brain regions after spaceflight in cosmonauts compared to the control group. Differences are related to spaceflight-induced structural brain changes, such as those impacting cerebrospinal fluid volume and distribution. We suggest solutions to individualize TMS to enhance its efficacy and precision for potential applications in long-duration space missions.

Circadian disruption and sleep disorders in neurodegeneration

Disruptions of circadian rhythms and sleep cycles are common among neurodegenerative diseases and can occur at multiple levels. Accumulating evidence reveals a bidirectional relationship between disruptions of circadian rhythms and sleep cycles and neurodegenerative diseases. Circadian disruption and sleep disorders aggravate neurodegeneration and neurodegenerative diseases can in turn disrupt circadian rhythms and sleep. Importantly, circadian disruption and various sleep disorders can increase the risk of neurodegenerative diseases. Thus, harnessing the circadian biology findings from preclinical and translational research in neurodegenerative diseases is of importance for reducing risk of neurodegeneration and improving symptoms and quality of life of individuals with neurodegenerative disorders via approaches that normalize circadian in the context of precision medicine. In this review, we discuss the implications of circadian disruption and sleep disorders in neurodegenerative diseases by summarizing evidence from both human and animal studies, focusing on the bidirectional links of sleep and circadian rhythms with prevalent forms of neurodegeneration. These findings provide valuable insights into the pathogenesis of neurodegenerative diseases and suggest a promising role of circadian-based interventions.

Repetitive transcranial magnetic stimulation in primary sleep disorders

Repetitive transcranial magnetic stimulation (rTMS) is a widely used non-invasive neuromodulatory technique. When applied in sleep medicine, the main hypothesis explaining its effects concerns the modulation of synaptic plasticity and the strength of connections between the brain areas involved in sleep disorders. Recently, there has been a significant increase in the publication of rTMS studies in primary sleep disorders. A multi-database-based search converges on the evidence that rTMS is safe and feasible in chronic insomnia, obstructive sleep apnea syndrome (OSAS), restless legs syndrome (RLS), and sleep deprivation-related cognitive deficits, whereas limited or no data are available for narcolepsy, sleep bruxism, and REM sleep behavior disorder. Regarding efficacy, the stimulation of the dorsolateral prefrontal cortex bilaterally, right parietal cortex, and dominant primary motor cortex (M1) in insomnia, as well as the stimulation of M1 leg area bilaterally, left primary somatosensory cortex, and left M1 in RLS reduced subjective symptoms and severity scale scores, with effects lasting for up to weeks; conversely, no relevant effect was observed in OSAS and narcolepsy. Nevertheless, several limitations especially regarding the stimulation protocols need to be considered. This review should be viewed as a step towards the further contribution of individually tailored neuromodulatory techniques for sleep disorders.

Etiology and Clinical Significance of Network Hyperexcitability in Alzheimer's Disease: Unanswered Questions and Next Steps

Cortical network hyperexcitability related to synaptic dysfunction in Alzheimer's disease (AD) is a potential target for therapeutic intervention. In recent years, there has been increased interest in the prevalence of silent seizures and interictal epileptiform discharges (IEDs, or seizure tendency), with both entities collectively termed "subclinical epileptiform activity" (SEA), on neurophysiologic studies in AD patients. SEA has been demonstrated to be common in AD, with prevalence estimates ranging between 22-54%. Converging lines of basic and clinical evidence imply that modifying a hyperexcitable state results in an improvement in cognition. In particular, though these results require further confirmation, post-hoc findings from a recent phase II clinical trial suggest a therapeutic effect with levetiracetam administration in patients with AD and IEDs. Here, we review key unanswered questions as well as potential clinical trial avenues. Specifically, we discuss postulated mechanisms and treatment of hyperexcitability in patients with AD, which are of interest in designing future disease-modifying therapies. Criteria to prompt screening and optimal screening methodology for hyperexcitability have yet to be defined, as does timing and personalization of therapeutic intervention.

Targeting neural correlates of placebo effects

Harnessing the placebo effects would prompt critical ramifications for research and clinical practice. Noninvasive brain stimulation (NIBS) techniques, such as transcranial magnetic stimulation and multifocal transcranial electric stimulation, could manipulate the placebo response by modulating the activity and excitability of its neural correlates. To identify potential stimulation targets, we conducted a meta-analysis to investigate placebo-associated regions in healthy volunteers, including studies with emotional components and painful stimuli. Using biophysical modeling, we identified NIBS solutions to manipulate placebo effects by targeting either a single key region or multiple connected areas. Moving to a network-oriented approach, we then ran a quantitative network mapping analysis on the functional connectivity profile of clusters emerging from the meta-analysis. As a result, we suggest a multielectrode optimized montage engaging the connectivity patterns of placebo-associated functional brain networks. These NIBS solutions hope to provide a starting point to actively control, modulate or enhance placebo effects in future clinical studies and cognitive enhancement studies.

Sleep-dependent upscaled excitability, saturated neuroplasticity, and modulated cognition in the human brain

Sleep strongly affects synaptic strength, making it critical for cognition, especially learning and memory formation. Whether and how sleep deprivation modulates human brain physiology and cognition is not well understood. Here we examined how overnight sleep deprivation vs overnight sufficient sleep affects (a) cortical excitability, measured by transcranial magnetic stimulation, (b) inducibility of long-term potentiation (LTP)- and long-term depression (LTD)-like plasticity via transcranial direct current stimulation (tDCS), and (c) learning, memory, and attention. The results suggest that sleep deprivation upscales cortical excitability due to enhanced glutamate-related cortical facilitation and decreases and/or reverses GABAergic cortical inhibition. Furthermore, tDCS-induced LTP-like plasticity (anodal) abolishes while the inhibitory LTD-like plasticity (cathodal) converts to excitatory LTP-like plasticity under sleep deprivation. This is associated with increased EEG theta oscillations due to sleep pressure. Finally, we show that learning and memory formation, behavioral counterparts of plasticity, and working memory and attention, which rely on cortical excitability, are impaired during sleep deprivation. Our data indicate that upscaled brain excitability and altered plasticity, due to sleep deprivation, are associated with impaired cognitive performance. Besides showing how brain physiology and cognition undergo changes (from neurophysiology to higher-order cognition) under sleep pressure, the findings have implications for variability and optimal application of noninvasive brain stimulation.

Sleep EEG-Based Approach to Detect Mild Cognitive Impairment

Mild Cognitive Impairment (MCI) is an early stage of dementia, which may lead to Alzheimer's disease (AD) in older adults. Therefore, early detection of MCI and implementation of treatment and intervention can effectively slow down or even inhibit the progression of the disease, thus minimizing the risk of AD. Currently, we know that published work relies on an analysis of awake EEG recordings. However, recent studies have suggested that changes in the structure of sleep may lead to cognitive decline. In this work, we propose a sleep EEG-based method for MCI detection, extracting specific features of sleep to characterize neuroregulatory deficit emergent with MCI. This study analyzed the EEGs of 40 subjects (20 MCI, 20 HC) with the developed algorithm. We extracted sleep slow waves and spindles features, combined with spectral and complexity features from sleep EEG, and used the SVM classifier and GRU network to identify MCI. In addition, the classification results of different feature sets (including with sleep features from sleep EEG and without sleep features from awake EEG) and different classification methods were evaluated. Finally, the MCI classification accuracy of the GRU network based on features extracted from sleep EEG was the highest, reaching 93.46%. Experimental results show that compared with the awake EEG, sleep EEG can provide more useful information to distinguish between MCI and HC. This method can not only improve the classification performance but also facilitate the early intervention of AD.

Tau Toxicity in Neurodegeneration

Tau is a microtubule-associated protein widely distributed in the central nervous system (CNS). The main function of tau is to promote the assembly of microtubules and stabilize their structure. After a long period of research on neurodegenerative diseases, the function and dysfunction of the microtubule-associated protein tau in neurodegenerative diseases and tau neurotoxicity have attracted increasing attention. Tauopathies are a series of progressive neurodegenerative diseases caused by pathological changes in tau, such as abnormal phosphorylation. The pathological features of tauopathies are the deposition of abnormally phosphorylated tau proteins and the aggregation of tau proteins in neurons. This article first describes the normal physiological function and dysfunction of tau proteins and then discusses the enzymes and proteins involved in tau phosphorylation and dephosphorylation, the role of tau in cell dysfunction, and the relationships between tau and several neurodegenerative diseases. The study of tau neurotoxicity provides new directions for the treatment of tauopathies.

Toward noninvasive brain stimulation 2.0 in Alzheimer's disease

Noninvasive brain stimulation techniques (NiBS) have gathered substantial interest in the study of dementia, considered their possible role in help defining diagnostic biomarkers of altered neural activity for early disease detection and monitoring of its pathophysiological course, as well as for their therapeutic potential of boosting residual cognitive functions. Nevertheless, current approaches suffer from some limitations. In this study, we review and discuss experimental NiBS applications that might help improve the efficacy of future NiBS uses in Alzheimer's Disease (AD), including perturbation-based biomarkers for early diagnosis and disease tracking, solutions to enhance synchronization of oscillatory electroencephalographic activity across brain networks, enhancement of sleep-related memory consolidation, image-guided stimulation for connectome control, protocols targeting interneuron pathology and protein clearance, and finally hybrid-brain models for in-silico modeling of AD pathology and personalized target selection. The present work aims to stress the importance of multidisciplinary, translational, model-driven interventions for precision medicine approaches in AD.

Low Frequency Transcranial Alternating Current Stimulation Accelerates Sleep Onset Process

GOAL

The aim of this study is to find a kind of low frequency oscillation transcranial alternating current stimulation, which is directly applied to the scalp epidermal, to stimulate the cerebral cortex with a large spatial range of electric field oscillation across the brain hemisphere, and then trigger the start of the Top-Down processing of sleep homeostasis, in the daytime nap.

METHODS

Thirty healthy subjects, to take naps, underwent an intervention of electrical stimulation at 5 Hz, applied to the dorsal lateral prefrontal cortex. The subjects in the experiments were strictly controlled, and opened their eyes when stimulation was transmitted. Subsequently, after 15 min transcranial alternating current stimulation, subjects entered the experimental procedure of sleep. Electroencephalograph was taken at baseline and during sleep. Behavioral indicators were also added to the experiment.

RESULTS

We found that the total power of Electroencephalograph activity in the theta band, as well as low-frequency power at 1-7 Hz, was significantly entrained and increased, and that alpha activity was attenuated faster and spindle activity active earlier. Even more, the transition from awake to Non-rapid eye movement stages occurs earlier. Alertness also decreased when the subjects woke up after brief sleep.

CONCLUSION

The intervention of low frequency brain rhythmic transcranial alternating current stimulation may induce accelerated effect on sleep onset process, thereby possibly alleviating the problems related to sleep disorders such as difficulty to reach the real sleep state quickly after lying down.

Neuronal biomarkers of Parkinson's disease are present in healthy aging

The prevalence of Parkinson's disease (PD) increases with aging and both processes share similar cellular mechanisms and alterations in the dopaminergic system. Yet it remains to be investigated whether aging can also demonstrate electrophysiological neuronal signatures typically associated with PD. Previous work has shown that phase-amplitude coupling (PAC) between the phase of beta oscillations and the amplitude of gamma oscillations as well as beta bursts features can serve as electrophysiological biomarkers for PD. Here we hypothesize that these metrics are also present in apparently healthy elderly subjects. Using resting state multichannel EEG measurements, we show that PAC between beta oscillation and broadband gamma activity (50-150 Hz) is elevated in a group of elderly (59-77 years) compared to young volunteers (20-35 years) without PD. Importantly, the increase of PAC is statistically significant even after ruling out confounds relating to changes in spectral power and non-sinusoidal shape of beta oscillation. Moreover, a trend for a higher percentage of longer beta bursts (> 0.2 s) along with the increase in their incidence rate is also observed for elderly subjects. Using inverse modeling, we further show that elevated PAC and longer beta bursts are most pronounced in the sensorimotor areas. Moreover, we show that PAC and longer beta bursts might reflect distinct mechanisms, since their spatial patterns only partially overlap and the correlation between them is weak. Taken together, our findings provide novel evidence that electrophysiological biomarkers of PD may already occur in apparently healthy elderly subjects. We hypothesize that PAC and beta bursts characteristics in aging might reflect a pre-clinical state of PD and suggest their predictive value to be tested in prospective longitudinal studies.

MEMS inductor fabrication and emerging applications in power electronics and neurotechnologies

MEMS inductors are used in a wide range of applications in micro- and nanotechnology, including RF MEMS, sensors, power electronics, and Bio-MEMS. Fabrication technologies set the boundary conditions for inductor design and their electrical and mechanical performance. This review provides a comprehensive overview of state-of-the-art MEMS technologies for inductor fabrication, presents recent advances in 3D additive fabrication technologies, and discusses the challenges and opportunities of MEMS inductors for two emerging applications, namely, integrated power electronics and neurotechnologies. Among the four top-down MEMS fabrication approaches, 3D surface micromachining and through-substrate-via (TSV) fabrication technology have been intensively studied to fabricate 3D inductors such as solenoid and toroid in-substrate TSV inductors. While 3D inductors are preferred for their high-quality factor, high power density, and low parasitic capacitance, in-substrate TSV inductors offer an additional unique advantage for 3D system integration and efficient thermal dissipation. These features make in-substrate TSV inductors promising to achieve the ultimate goal of monolithically integrated power converters. From another perspective, 3D bottom-up additive techniques such as ice lithography have great potential for fabricating inductors with geometries and specifications that are very challenging to achieve with established MEMS technologies. Finally, we discuss inspiring and emerging research opportunities for MEMS inductors.

Sleep-Based Interventions in Alzheimer's Disease: Promising Approaches from Prevention to Treatment along the Disease Trajectory

The multifactorial nature of Alzheimer’s disease (AD) has led scientific researchers to focus on the modifiable and treatable risk factors of AD. Sleep fits into this context, given the bidirectional relationship with AD confirmed by several studies over the last years. Sleep disorders appear at an early stage of AD and continue throughout the entire course of the pathology. Specifically, sleep abnormalities, such as more fragmented sleep, increase in time of awakenings, worsening of sleep quality and primary sleep disorders raise with the severity and progression of AD. Intervening on sleep, therefore, means acting both with prevention strategies in the pre-clinical phase and with treatments during the course of the disease. This review explores sleep disturbances in the different stages of AD, starting from the pre-clinical stage. Particular attention is given to the empirical evidence investigating obstructive sleep apnea (OSA) disorder and the mechanisms overlapping and sharing with AD. Next, we discuss sleep-based intervention strategies in the healthy elderly population, mild cognitive impairment (MCI) and AD patients. We mention interventions related to behavioral strategies, combination therapies, and bright light therapy, leaving extensive space for new and raising evidence on continuous positive air pressure (CPAP) treatment effectiveness. Finally, we clarify the role of NREM sleep across the AD trajectory and consider the most recent studies based on the promising results of NREM sleep enhancement, which use innovative experimental designs and techniques.