Disruptions of Brain Networks and Sleep by Electroconvulsive Therapy

摘要 电休克治疗(ECT)是治疗精神障碍患者的有效干预手段。 具体地说，它是治疗难治性抑郁症(TRD)患者的既定治疗方法，缺乏 对至少两种药理抗抑郁药的反应。尽管有效率高达70%，但人们对此知之甚少。 关于电疗减轻精神症状或施加认知能力的电路水平机制 减损。ECT可诱发全身性癫痫发作，并引起功能网络内的神经可塑性改变。一个 迫切需要更好地理解ECT，因为它是在一般情况下执行的重复程序 麻醉及其益处受到治疗后认知障碍的限制。脑电图仪 (EEG)能够捕捉不同觉醒和最近状态下大脑活动的时间动态 高密度脑电技术的发展使得大规模功能脑网络的阐明成为可能。 记录睡眠时的脑电可以提供对睡眠结构的洞察。在这项研究中，“大脑网络的中断” 和电休克治疗的睡眠，我们将调查ECT对信息传输效率的影响 在与睡眠慢波有关的功能网络中，突触可塑性的脑电标志。它的新奇之处在于 这一建议源于我们对睡眠、清醒和睡眠期间脑电标记物的纵向评估 在治疗过程中ECT诱发癫痫发作。我们还将获得抑郁症严重程度的结果和 记忆是纵向测量的。无线可穿戴设备将解决以前的纵向障碍 门诊电休克患者睡眠微结构的研究基于图的高密度脑电信号的网络分析 信号允许对功能网络上的信息传输进行表征。这些信息措施是 在特定的子网络中进行本地调查，并在大型功能网络上进行全球调查。纵向 在整个ECT过程中对EEG的评估以及临床和认知结果将提供 独一无二的机会，以提高我们对发展的基础电路机制的理解 ECT过程中出现的认知障碍和抗抑郁作用。此外，我们的发现可能会揭示 其他针对精神疾病患者睡眠慢波活动的非侵入性干预。 总体而言，阐明电刺激对不同觉醒状态下信息处理的影响可能有 通过识别潜在的新生物标记物和治疗靶点来显示潜在的临床意义 为改善TRD患者的公共健康做出贡献。

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.