0427 Altered Brain-State Energy Landscape and Neurotransmitter Contributions in Chronic Insomnia: A Network Control Theory Study

Abstract Introduction Chronic insomnia (CI) is characterized by hyperarousal and abnormal large-scale brain dynamics, yet the energetic demands underlying transitions between brain states remain poorly understood. Network control theory provides a mechanistic framework for quantifying the minimum control energy required for the brain to maintain or transition between functional configurations. This study aimed to characterize the energy landscape of brain states in patients with CI and to examine its associations with symptom severity and neurotransmitter receptor architecture. Methods Forty-two adults with CI and forty-four matched healthy controls underwent diffusion tensor imaging, T1-weighted imaging, and resting-state functional MRI. Hidden Markov modeling identified recurrent functional states and quantified fractional occupancy and mean dwell time. Individual structural connectivity matrices served as system matrices for estimating control energy for state maintenance and transitions. Nineteen neurotransmitter receptor and transporter maps were incorporated to identify neurochemical contributors to altered energy patterns. Associations with insomnia severity and sleep quality were assessed. Results Two robust brain states were identified. State 1 was characterized by high activity in the default mode and frontoparietal control network, accompanied by reduced activation in the dorsal attention and somatomotor networks. State 2 was characterized by opposing patterns. CI participants showed significantly higher fractional occupancy (Z = 2.84, P = 0.006) and longer mean lifetime in State 1, alongside significantly reduced occupancy in State 2 (Z = 3.72, P < 0.001). The longer mean lifetime in State 1 was associated with lower habitual sleep efficiency (R2 = 0.10, P = 0.040). The transition energy from State 2 to State 1 was positively associated with sleep latency (R2 = 0.14, P = 0.024) and insomnia severity (R2 = 0.13, P = 0.028). Neurotransmitter analyses revealed strong contributions from GABAergic, dopaminergic, cholinergic, glutamatergic, serotonergic, and opioid systems to altered transition energies. Conclusion CI is characterized by a flattened brain-state energy landscape, reduced dynamical stability, and neurotransmitter-mediated abnormalities in the energy required for transitioning between functional states. These findings provide mechanistic evidence linking impaired brain-state controllability with clinical symptoms and highlight neurotransmitter systems that may shape neural dynamics in insomnia. Support (if any) This study was supported by the CYRUS TANG FUNDATION.