Abstract

There is concrete evidence that weightlessness and microgravity may affect sleep
quality. However, most of the studies failed to provide an integrative understanding of
sleep disorders. This study proposes a novel, multi-modal, data-driven model for
identifying the detrimental factors that are crucial for sleep quality. Its aim is to quantify
the impact of weightlessness on cortical functional connectivity and metabolic blood
biomarkers. It also investigates the efficacy of the Reactive Sledge Jump as a
countermeasure.The study involves healthy volunteers assigned either to a control or
to a sledge group. The data include polysomnographic recordings and blood
biomarkers. Reconstruction of the cortical resting-state networks through the sLORETA
methodology is performed. Then, functional connectivity is obtained, and regression
models are developed to explain the variance of the sleep macro-architecture
characteristics.The study results indicate that neither the bed rest nor the
countermeasure affect sleep macro-architecture or the biomarkers under
consideration. There are statistically significant functional connectivity alterations within
the alpha band. There are significant correlations among all the three biomarkers and
sleep quality characteristics. Glucose and prolactin values can predict the sleep onset
latency, whereas insulin and group (countermeasure or control) predict the number of
awakenings. Finally, the biomarker values are significantly correlated with functional
connectivity interactions.Our findings provide evidence that sleep disorders occur firstly
at a cortical level following a non-uniform pattern. These disorders are evident as
cortical connectivity disruptions before their clinical manifestation as biomarkers’
alterations or deterioration in terms of sleep characteristics. The proposed
methodology highlights the significance of a personalized, multi-parametric evaluation
of sleep quality which is able to identify sleep disorders prior to their clinical onset.