Project 3: Modulating repetitive negative thinking related brain networks in young adults with depression

项目概要：项目3 - Tsuchiyagaito 重度抑郁症（MDD）是年轻人最常见的心理健康状况之一 (ages 18-25）发生在11%，并对长期结果有严重影响，如共病精神疾病， 疾病、失业和自杀，如果得不到有效治疗。重复性消极思维（RNT） 一种反复出现的思维过程，其效价是负的，难以控制。RNT始终与一个 更高的频率，持续时间和抑郁的严重程度，也预测了成年早期的自杀倾向。 尽管已经建立了有效的MDD治疗方法，但近三分之二的患者不会有反应， 并且用目前可用的方式治疗MDD留下多达90%的残留症状， 包括RNT。较高的RNT也与对两种抗抑郁药的反应较慢和结果较差有关。 药物治疗和心理治疗因此，RNT和潜在的神经回路将是理想的直接 有针对性的，它将促进相关的调节大脑功能。实时功能磁共振 成像神经反馈（rtfMRI-nf）训练是一种理想的，非侵入性的方法来翻译RNT相关的大脑 将网络转化为一个有针对性的疾病修饰过程。这项建议建立在我们以前的工作基础上， 确定了与RNT相关的脑功能连接，即，我们确定了 右岛叶前沟（rAI）与右上级颞沟（rSTS）之间呈正相关 MDD患者的RNT更高。在这个提议中，我们使用rtfMRI-nf来因果地关联 rAI-rSTS连接与RNT强度的关系。我们将进行一项随机、双盲、假对照 在n=110（n=100完成者，假设10%的损耗）年轻成人MDD个体（年龄18- 18岁）中进行rtfMRI-nf试验。 25)RNT症状。我们将评估rtfMRI-nf如何用于减弱RNT，从而减少 萧条我们的目标是调查减少rAI-rSTS连接性使RNT和 接受主动rtfMRI-nf治疗的年轻MDD患者的抑郁症状（n=55，50例完成者）与 假手术（神经反馈与人工产生的反馈信号; n=55，50完成者）组。具体目标 确定（1）真实的与假rtfMRI-nf对rAI-rSTS功能连接的急性影响;（2）以及 RNT和抑郁症一个探索性的目的是检查急性调节rAI-rSTS的程度， 连接导致RNT的变化以及抑郁症和亚急性rAI-rSTS连接改变一个 rtfMRI-nf后一周。首要目标是确定（1）RNT中涉及rAI-rSTS连接， 可以作为MDD的靶向疾病修饰过程进行调节，以及（2）通过调节rAI-rSTS 连接减少RNT，我们可以降低抑郁症的严重程度。该提案的系统方法 通过识别转诊断构建的神经靶点体现NIH RDoC计划的目标， 研究特定网络直接调制的脑-行为功能关系。

PROJECT SUMMARY: Project 3 – Tsuchiyagaito Major Depressive disorder (MDD) is among the most common mental health conditions in young adulthood (ages 18-25) occurring in 11%, and has serious effects on long-term outcomes such as comorbid mental disorders, unemployment and suicide, if not effectively treated. Repetitive negative thinking (RNT) is a recurrent thought process which is negative in valence and difficult to control. RNT is consistently linked to a higher frequency, duration, and severity of depression, and also predicts suicidality in early adulthood. Although effective treatments for MDD have been established, nearly two-thirds of patients will not respond, and treatment of MDD with currently available modalities leave as many as 90% with residual symptoms, including RNT. Higher RNT is also linked to a slower response and poorer outcome to both antidepressant medication and psychotherapy. Thus, RNT and the underlying neural circuit would be ideal to be directly targeted and it would boost the relevant regulatory brain functions. Real-time functional Magnetic Resonance Imaging neurofeedback (rtfMRI-nf) training is an ideal, non-invasive method to translate RNT-related brain networks into a targetable disease-modifying process. This proposal builds on our previous work, in which we identified the brain functional connectivity associated with RNT, i.e., we determined that the connectivity between the right anterior insular (rAI) and the right superior temporal sulcus (rSTS) was positively correlated with higher RNT in individuals with MDD. In this proposal, we use rtfMRI-nf to causally relate the dysfunction of rAI-rSTS connectivity with the intensity of RNT. We will conduct a randomized double-blind, sham-controlled trial of rtfMRI-nf in n=110 (n=100 completers, assuming a 10% attrition) young adult MDD individuals (ages 18- 25) with RNT symptoms. We will evaluate how rtfMRI-nf can be used to attenuate RNT, and thereby reduce depression. We aim to investigate the degree to which reducing rAI-rSTS connectivity alleviates RNT and depressive symptoms in young adults with MDD receiving active rtfMRI-nf (n=55, 50 completers) compared to sham (neurofeedback with artificially generated feedback signals; n=55, 50 completers) groups. Specific aims are to determine (1) an acute effect of real vs. sham rtfMRI-nf on rAI-rSTS functional connectivity; (2) and on RNT and depression. An exploratory aim will examine the degree to which acute modulation of rAI-rSTS connectivity leads to changes in RNT as well as depression and sub-acute rAI-rSTS connectivity change one week after rtfMRI-nf. The overarching goal is to establish that (1) rAI-rSTS connectivity is involved in RNT and can be modulated as a targetable disease-modifying process of MDD, and (2) by modulating rAI-rSTS connectivity to reduce RNT we can reduce depression severity. The systematic approach of this proposal embodies the goals of the NIH RDoC Initiative by identifying a neural target for a transdiagnostic construct, and studying the brain-behavioral function relationships with the direct modulation of a specific network.