Reduced switching between brain states in insomnia

Insomnia disorder is the most common sleep disorder affecting millions of people. Brain research has linked insomnia to dysfunction in large-scale brain networks, not only during sleep but also in wakeful rest. Yet, the underlying brain dynamics remain little understood. In the present study, we directly addressed this using a data-driven framework for evaluating time-varying large-scale brain activity. We used functional magnetic imaging to compare participants with insomnia disorder to matched controls with no sleep complaints. Using Hidden Markov modeling (HMM) for a completely data-driven characterization of the brain dynamics of whole-brain activity, we found that insomnia disorder is characterized by significantly reduced switching rates between large-scale brain states. In particular, HMM was used to compare insomnia patients to controls, which showed that their brains spent significantly less time in two whole-brain states-the default mode network and a fronto-parietal network-complemented by increased time spent in a global activation state. Overall, the findings reveal the brain dynamics of insomnia to show that insomnia disorder is characterized by less flexible transitions between brain states at wakeful rest. This highlights the importance of evaluating the spatiotemporal dynamics of brain activity to advance the understanding of the neural underpinnings of insomnia disorder.