A whole-brain model of the aging brain during slow wave sleep.

Abstract

Age-related brain changes affect sleep and are reflected in properties of sleep slow-waves, however the precise mechanisms behind these changes are still not completely understood. Here, we adapt a previously established whole-brain model relating structural connectivity changes to resting state dynamics, and extend it to a slow-wave sleep brain state. In particular, starting from a representative connectome at the beginning of the aging trajectory, we have gradually reduced the inter-hemispheric connections, and simulated sleep-like slow-wave activity. We show that the main empirically observed trends, namely a decrease in duration and increase in variability of the slow waves are captured by the model. Furthermore, comparing the simulated EEG activity to the source signals, we suggest that the empirically observed decrease in amplitude of the slow waves is caused by the decrease in synchrony between brain regions.Significance Statement Aging is characterized by changes in slow wave (SW) sleep features, yet the precise mechanisms driving these alterations remain elusive. Employing a connectome-based model, we implement the established age- related reductions in inter-hemispheric connectivity, successfully replicating the SW changes in the simulated activity. Our simulation of EEG activity also suggests that observed decreases in SW amplitude stems from diminished synchrony between brain regions. Our results support the notion that alterations in SW characteristics result from reductions in cortical excitatory drive-here facilitated by the inter-hemispheric connections. Our model serves as a robust foundation for extensions to population studies and interventional work in animal models of aging aimed at disentangling the contributions of network alterations, changes to local neural mass properties, and neuromodulation.