EEG and computational aspects of how aging affects sleep slow waves

Abstract

Sleep slow-waves have been reported to vary with age in human subjects, as well as in mouse, but the underlying mechanisms remain unclear. Here, we perform a precise quantification of the effect of aging on the shape and dynamics of sleep slow waves, in a large cohort of human subjects recorded with the electro-encephalogram (EEG) during sleep. The fine-structure analysis of slow waves reveals that they slow-down, increase of variability and decrease in amplitude with age. We next investigate a computational model of the genesis of slow-wave activity and model the aging by a global decrease of the strength of the external excitatory drive to the network. This simple model reproduces some of the main features observed in the EEG, suggesting that changes of long-range excitatory connection strength may explain the evolution of slow-waves with age.