Biology subjects

Van Someren, E.

Publications and source records attributed to Van Someren, E..

3 recordsLinked to original sources

bioRxiv2026

Active Bed Microclimate Regulation Modulates Sleep Architecture, Autonomic, and Central Nervous System Activity during Sleep

Skin temperature and bed microclimate are established modulators of human sleep, but most prior work has relied on passive thermal materials. We used a smart bed capable of heating or cooling the microclimate to investigate how six temperature settings affect sleep architecture, autonomic activity, and electroencephalographic (EEG) activity. Eighteen adults (9 male, 9 female; mean age 44.5 years) completed two overnight polysomnography sessions with bed temperature assigned via Latin-square counterbalancing across three-hour segments of high cooling, medium cooling, low cooling, off, low heating, and medium heating. Mixed-effects regression models evaluated manipulation checks on induced thermal changes, the probability of sleep versus wake, and the probability of each sleep stage (N1, N2, N3, REM), while secondary analyses assessed sleep deepening, heart rate, and EEG spectral power. Temperature manipulations significantly affected sleep and physiological outcomes. All five active settings shifted sleep toward greater depth, increasing the odds of slow-wave sleep (odds ratios 1.21 to 3.65, largest for high cooling) and reducing the odds of light non-rapid eye movement sleep relative to off. Heating accelerated early sleep deepening relative to cooling without significantly altering sleep onset latency, whereas cooling produced a graded reduction in heart rate. EEG analyses revealed distinct cortical signatures for heating and cooling conditions. These findings demonstrate that active bed microclimate regulation modulates sleep architecture, autonomic activity, and cortical activity during sleep. The nonlinear pattern of effects suggests thermal "sweet spots" that may vary across the night and individuals, supporting the development of individualized programmable temperature-regulation strategies for sleep optimization.

physiology↗

bioRxiv2024

Modelling of brain dynamics reveals reduced switching between brain states in insomnia disorder - a resting state fMRI study

Insomnia disorder is the most common sleep disorder, and neuroimaging research indicates that it is related to dysfunction in large-scale brain networks. Recently developed methods have enabled the investigation of the dynamic aspects of brain activity varying over time. In the present study, we used a novel data-driven approach to evaluate time-varying brain activity in adults with insomnia disorder compared to matched controls with no sleep problems. We acquired ten minutes resting state functional magnetic resonance images and T1-weighed images in all participants. We used Hidden Markov modelling for a data-driven definition of dynamic changes in whole-brain activity. The results showed that insomnia disorder is characterised by reduced switching rates between brain states. In line with the reduced switching, the HMM analyses suggested reduced prevalence of two whole-brain states - the default mode network and a fronto-parietal network - and an increase in just one brain state - a global activation state - in insomnia patients compared to controls. The findings suggest that insomnia disorder is characterised by less flexible transitions between brain states at wakeful rest, and thus highlight the importance of evaluating the spatiotemporal dynamics of brain activity to advance the understanding of the neural underpinnings of insomnia disorder.

neuroscience↗

bioRxiv2019

Reduced structural connectivity in Insomnia Disorder

Insomnia Disorder is the most prevalent sleep disorder and it involves both sleep difficulties and daytime complaints. The neural underpinnings of Insomnia Disorder are poorly understood. Existing neuroimaging studies are limited by their focus on local measures and specific regions of interests. To address this shortcoming, we applied a data-driven approach to assess differences in whole-brain structural connectivity between adults with Insomnia Disorder and matched controls without sleep complaints. We used diffusion tensor imaging and probabilistic tractography to assess whole-brain structural connectivity and examined group differences using Network-Based Statistics. The results revealed a significant difference in the structural connectivity of the two groups. Participants with Insomnia Disorder showed reduced connectivity in a subnetwork that was largely left lateralized, including mainly fronto-subcortical connections with the insula as a key region. By taking a whole-brain network perspective, our study succeeds at integrating previous inconsistent findings, and our results reveal that reduced structural connectivity of the left insula and the connections between frontal and subcortical regions are central neurobiological features of Insomnia Disorder. The importance of these areas for interoception, emotional processing, stress responses and the generation of slow wave sleep may help guide the development of neurobiology-based models of the highly prevalent condition of Insomnia Disorder.

neuroscience↗