Abstract
Nat Neurosci. 2025 Oct 28. doi: 10.1038/s41593-025-02091-1. Online ahead of print.
ABSTRACT
Sleep is a fundamental part of our lives; yet, how our brain falls asleep remains one of the most enduring mysteries of neuroscience. Here we report a new conceptual framework to analyze and model this phenomenon. The framework represents the changes in brain electroencephalogram activity during the transition into sleep as a trajectory in a normalized feature space. We use the framework to show that the brain's wake-to-sleep transition follows bifurcation dynamics with a distinct tipping point preceded by a critical slowing down. We validate the bifurcation dynamics in two independent datasets, which include more than 1,000 human participants. Finally, we demonstrate the framework's utility by predicting a person's progression into sleep in real time with seconds temporal resolution and over 0.95 average accuracy.
PMID:41152637 | DOI:10.1038/s41593-025-02091-1
UK DRI Authors
