Disruptions of Brain Networks and Sleep by Electroconvulsive Therapy

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ABSTRACT Electroconvulsive therapy (ECT) is an effective intervention for treating patients with psychiatric disorders. Specifically, it is an established treatment for patients with Treatment-Resistant Depression (TRD) with a lack of responsiveness to at least two pharmacologic antidepressants. Despite an efficacy of up to 70%, little is known about the circuit-level mechanisms through which ECT alleviates psychiatric symptoms or exerts cognitive impairments. ECT induces generalized seizures and causes neuroplastic changes within functional networks. A better understanding of ECT is urgently needed given that it is a repetitive procedure performed under general anesthesia and its benefits are limited by cognitive impairment following treatment. Electroencephalography (EEG) enables capturing the temporal dynamics of brain activity in different states of arousal and recent developments in high-density EEG technology allow for elucidation of large-scale functional brain networks. Recording EEG during sleep provides insights about sleep structure. In this study, “Disruptions of Brain networks and Sleep by Electroconvulsive Therapy,” we will investigate the impact of ECT on information transfer efficiency in functional networks in relation to sleep slow waves, an EEG marker of synaptic plasticity. The novelty of this proposal stems from our focus on the longitudinal assessment of EEG markers during sleep, wakefulness, and ECT-induced seizures over the course of therapy. We will also acquire depression severity outcomes and memory measures longitudinally. Wireless wearable devices will address previous barriers to the longitudinal study of sleep microstructure in the outpatient ECT settings. Graph-based network analyses of high-density EEG signals allow characterization of information transfer over functional networks. These information measures are investigated locally in specific subnetworks and globally over large-scale functional networks. Longitudinal assessments of EEG throughout the course of ECT alongside clinical and cognitive outcomes will provide a unique opportunity to improve our understanding of the circuit mechanisms underlying the development of cognitive impairments and antidepressant effects incurred during ECT. Furthermore, our findings may shed light on other non-invasive interventions targeting sleep slow wave activity in patients with psychiatric illnesses. Overall, elucidating the impact of ECT on information processing in different states of arousal may have promising clinical implications through identification of potential new biomarkers and therapeutic targets leading to the improvement of public health for TRD patients.