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Imaging the Evolving Neural Circuit Dynamics of Depression

抑郁症神经回路动力学的成像

基本信息

批准号：
8955225
负责人：
Melissa Rhoads Warden
金额：
$ 232.5万
依托单位：
CORNELL UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-09-30 至 2020-05-31
项目状态：
已结题

项目摘要

DESCRIPTION (provided by applicant): Major depressive disorder affects an estimated 20% of the United States population and is one of the nation's leading causes of lost productivity, resulting in an estimated 200 million lost workdays each year. In order to design targeted and effective treatments for depression it is essential to understand the neural mechanisms underlying the entry into, maintenance of, and exit from the depressed state. The goals of this proposal are to discover the functional cellular-level neural signatures of depression by monitoring and decoding the network activity of large populations of identified single neurons. Leveraging the power of the most recently developed technologies for probing brain function, we will examine baseline neural activity patterns in a population of neurons during normal behavior, follow the evolution of these patterns in this same population of neurons during the induction and maintenance of a depression-like state, determine whether antidepressant therapies bring the network back to a baseline state or an alternate state, and attempt to normalize these pathological neural dynamics with fast, circuit-based, optogenetic intervention. Specifically, we will record the neural activity of genetically or topologically identified network of neurons using the genetically encoded calcium indicator GCaMP6f and a fluorescence microendoscope designed for use during free behavior. Neural activity will be monitored before, during, and after the induction of a depression-like state (with chronic mild stress) during behaviors that probe processes relevant to depression and during the resting state. Neuronal population data will be analyzed to identify network states associated with depression. We will then use targeted optogenetic stimulation to move the network dynamics back towards the baseline patterns seen before the induction of depression, a novel application of simultaneous optical control and readout. The research proposed here is extremely well suited to the goals of the New Innovator program. New technological approaches will be developed and used to ask questions about disease-related changes in neural circuit function that are not possible to address with existing methods, and new approaches to the circuit-specific treatment of depression will be tested with an eye towards translation to human patients. My scientific background in systems neurophysiology, computational neuroscience, and optogenetics combined with my demonstrated productivity in the field of depression research is the precise combination of skills and interests needed to execute this paradigm-shifting work.

描述（由申请人提供）：严重抑郁症影响了估计20%的美国人口，是美国生产力损失的主要原因之一，每年估计造成2亿个工作日的损失。为了设计有针对性和有效的治疗抑郁症，有必要了解进入，维持和退出抑郁状态的神经机制。该提案的目标是通过监测和解码大量已识别的单个神经元的网络活动来发现抑郁症的功能性细胞水平神经特征。利用最新开发的探测大脑功能的技术的力量，我们将检查正常行为期间神经元群体中的基线神经活动模式，在诱导和维持抑郁样状态期间，跟踪同一神经元群体中这些模式的演变，确定抗抑郁治疗是否使网络回到基线状态或替代状态，并试图通过快速的、基于电路的光遗传学干预来使这些病理性神经动力学正常化。具体来说，我们将使用遗传编码的钙指示剂GCaMP6f和设计用于自由行为期间的荧光显微内窥镜记录遗传或拓扑识别的神经元网络的神经活动。在诱导抑郁样状态（慢性轻度应激）之前、期间和之后，在探索抑郁相关过程的行为期间和静息状态期间监测神经活动。将分析神经元群体数据以识别与抑郁症相关的网络状态。然后，我们将使用有针对性的光遗传学刺激，将网络动力学移回诱导抑郁症之前的基线模式，这是同时进行光学控制和读出的一种新应用。这里提出的研究非常适合新创新者计划的目标。新的技术方法将被开发和使用，以询问与疾病相关的神经回路功能变化的问题，这些问题是现有方法无法解决的，并且将测试抑郁症回路特异性治疗的新方法，着眼于向人类患者的转化。我在系统神经生理学，计算神经科学和光遗传学方面的科学背景，加上我在抑郁症研究领域的生产力，是执行这种范式转变工作所需的技能和兴趣的精确组合。