Abstract
Senescence affects various aspects of sleep, and it remains unclear how sleep-related neuronal network activity is altered by senescence. Here, we recorded local field potential signals from multiple brain regions covering the forebrain in young (10-week-old) and aged (2-year-old) mice. Interregional LFP correlations across these brain regions could not detect pronounced differences between awake and sleep states in both young and aged mice. Multivariate analyses with machine learning algorithms with uniform manifold approximation and projection and robust continuous clustering demonstrated that LFP correlational patterns at multiple frequency bands, ranging from delta to high gamma bands, in aged mice less represented awake/sleep states than those in young mice. By housing aged mice in an enriched environment, the LFP patterns were changed to more precisely represent awake/sleep states. Our results demonstrate senescence-induced changes in neuronal activity at the network level and provide insight into the prevention of pathological symptoms associated with sleep disturbance in senescence.