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Investigation of brain networks for personalized rTMS in healthy subjects and patients with major depressive disorder: A translational study

磁刺激 默认模式网络 背外侧前额叶皮质 神经科学 心理学 重性抑郁障碍 脑刺激 扣带回前部 萧条(经济学) 前额叶皮质 物理医学与康复 医学 功能磁共振成像 认知 刺激 经济 宏观经济学
作者
Aditya Singh
标识
DOI:10.53846/goediss-8452
摘要

Depression is a complex psychiatric disorder with emotional dysregulation at its core. The first line of treatment includes cognitive behaviour therapy and pharmacological antidepressants. However, up to one third of patients with depression fail to respond to these treatment interventions. The past decades have seen an increasing use of repetitive Transcranial Magnetic Stimulation (rTMS) in clinical studies, as an alternative treatment for depression. Several large-scale, multicentre randomized controlled trials have led the Food and Drugs Administration (FDA), USA to approve two rTMS protocols for clinical application in the treatment of depression - 10 Hz rTMS and intermittent Theta Burst Stimulation (iTBS). However, only 30-50% of patients receiving rTMS respond to the treatment. The large variability in response to rTMS likely stems from multiple reasons, one being the targeting method currently employed for delivering rTMS at the left dorsolateral prefrontal cortex (DLPFC). Previous functional connectivity studies have shown that stimulation at left DLPFC targets with larger negative correlation to the subgenual anterior cingulate cortex (sgACC) may result in greater therapeutic response than those with lower negative correlation. However, current use of rTMS ignores functional connectivity in choosing the left DLPFC target, thus largely discarding functional architectural differences of the brain across subjects. Furthermore, despite widespread clinical use of rTMS, the basic network mechanisms behind these rTMS protocols remain elusive. This work presents a novel personalization method of left DLPFC target selection based on their negative functional connectivity to the sgACC. The default mode network (DMN) is a large-scale brain network commonly involved in self-referential thought processing and plays an essential role in the pathophysiology of depression. I use the novel personalization method and identical study designs to delineate DMN mechanisms from a single session of 10 Hz rTMS and iTBS in healthy subjects. Arguably, an understanding of basic mechanisms of clinically relevant rTMS protocols in healthy subjects will help improve the current therapeutic effect of rTMS, and possibly expand the therapeutic role of rTMS. My work shows, for the first time, strong but different modulations of DMN connectivity by single personalized sessions of 10 Hz rTMS and iTBS. Such modulations can be predicted using the personality trait harm avoidance (HA). Given that initial results show that the method is robust and reproducible, its adaptation to patient cohorts is likely to result in improved therapeutic benefits. Therefore, the novel method of personalization is translated to clinical setting by using accelerated iTBS (aiTBS) in patients with depression. Additionally, a comparison is made between effects resulting from personalized and nonpersonalized (10-20 EEG system F3 position) aiTBS in patients with depression. By evaluating the DMN, and heart rate variability, I show precise modulatory effects of personalized aiTBS, which is not seen in the standard aiTBS group. The work presented here introduces an important method to reduce variability and increase precision in rTMS modulation by personalizing the left DLPFC target selection. Even though DMN and cardiac effects already point towards the advantage of personalization, the still preliminary analysis fails to show significant differences in treatment response. Lack of greater therapeutic benefits viii from personalized aiTBS in this ongoing study probably stems from a still limited sample size. In case personalization proves clinically advantageous to standard iTBS by the final sample size, this work can sediment the first step towards systems medicine in the field of psychiatry.

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