Multidimensional brain connectome features of depression and anxiety

项目总结 负责情绪调节的大脑区域之间的沟通中断(边缘和 高级认知皮质区域)可能是情绪失调的关键原因 以情绪和焦虑症为特征。然而，这些指标中最有启发性的指标 沟通尚未达成一致。此外，由于技术障碍，还有 目前还没有对人类边缘次区域连接性的细粒度测量。一个网络- 基于的方法可用于探索边缘和皮质次区域的连通性(即 连接体)，揭示了核心下的离散或共享的神经机制 情绪和焦虑症的症状。在拟议的研究中，我们将(1)描述Small 健康对照和大脑血管疾病患者边缘亚区和全脑连接的研究 通过优化和使用新的7-特斯拉磁共振成像，研究抑郁症和广泛性焦虑症 提高空间分辨率和全脑覆盖的协议；(2)基于识别网络的 抑郁症和焦虑症的生物标志物--发展和表征多模式 由结构、功能和动态拓扑图组成的综合大脑网络使用 新的计算多层方法；以及(3)通过诊断检查连接体如何 在三个研究小组中都体现了组织性。通过描绘特定的边缘区域 参与大脑连接体，这将促进我们对如何 连接体的改变在精神障碍中表现出来。此外，这项工作结合了 脑活动和同步化的高分辨率测量(功能磁共振)，以及 脑白质结构和解剖连接(弥散磁共振成像)。他们加在一起 研究将有助于识别异常网络特征及其对核心的贡献 抑郁和焦虑的症状。最后，跨诊断方法将揭示共享 以及抑郁和焦虑的独特网络机制，这可能会提供 改进了诊断和治疗选择。 这一职业发展奖将允许关键的免费培训目标 重点是：(1)获得实际的临床经验，以确定临床需求和 进行翻译研究；(2)开发技术先进的MRI序列 开发技能；(3)用先进的网络科学方法提炼计算技能。这个 由该奖项提供的拟议研究和培训将使我能够启动一个独立的 开发神经成像方法的研究计划，以研究大脑网络扰动 情绪和焦虑症。

PROJECT SUMMARY Disrupted communication between brain regions responsible for emotion regulation (limbic and higher cognitive cortical regions) may critically underlie the emotional dysregulation that characterizes mood and anxiety disorders. However, the most instructive metric of such communication has yet to be agreed upon. In addition, due to technical barriers, there are currently no fine-grained measurements of limbic subregion connectivity in humans. A network- based approach can be used to explore limbic and cortical subregion connectivity (i.e. connectome), shedding light on the discrete or shared neural mechanisms underlying core symptoms in mood and anxiety disorders. In the proposed study we will (1) characterize small limbic subregions and whole-brain connectomes in healthy controls and individuals with major depressive and generalized anxiety disorder, by optimizing and employing a novel 7-Tesla MRI protocol with improved spatial resolution with whole brain coverage; (2) discern network based biomarkers of depression and anxiety by developing and characterizing a multi-modal integrative brain network consisting of structural, functional and dynamic topographies using a new computational multilayer approach; and (3) transdiagnostically examine how connectome organization manifests across the three study groups. By portraying specific limbic subregion involvement in the brain connectome, this would advance our understanding of how connectome alternations manifest in psychiatric disorders. Furthermore, this work combines high-resolution measures of brain activity and synchronization (functional MRI), with maps of the brain’s white matter architecture and anatomical connections (diffusion MRI). Their combined study will facilitate identification of aberrant network features and their contributions to core symptoms in depression and anxiety. Lastly, the transdiagnostic approach will uncover shared and unique network mechanisms of depression and anxiety that could potentially provide improved diagnostics and treatment selection. This Career Development Award will allow for the critical complimentary training goals centering on: (1) gaining practical clinical experience towards identifying clinical needs and conducting translational research; (2) development of technical advanced MRI sequence development skills; (3) refine computational skills in advanced network science methods. The proposed research and training afforded by this award will allow me to launch an independent research program developing neuroimaging methods to study brain network perturbations in mood and anxiety disorders.