Imaging the Evolving Neural Circuit Dynamics of Depression

 描述(申请人提供)：据估计，美国约有20%的人口患有严重的抑郁症，这是美国生产力下降的主要原因之一，每年造成约2亿个工作日的损失。为了设计有针对性的、有效的抑郁症治疗方法，了解抑郁症进入、维持和退出抑郁状态的神经机制是至关重要的。这项建议的目标是通过监测和解码大量已识别的单一神经元的网络活动来发现抑郁症的功能性细胞水平的神经特征。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一组神经元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这些模式在同一组神经元中的演变，确定抗抑郁治疗是将网络恢复到基线状态还是交替状态，并尝试通过快速、基于电路的光遗传干预使这些病理神经动力学正常化。具体地说，我们将使用遗传编码的钙指示剂GCaMP6f和设计用于自由行为的荧光显微内窥镜来记录遗传或拓扑识别的神经元网络的神经活动。神经活动将在诱导类似抑郁状态之前、期间和之后进行监测，在探索与抑郁相关的过程的行为期间和在休息状态期间。将对神经元群体数据进行分析，以确定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刺激，将网络动力学恢复到诱导抑郁之前的基线模式，这是一种同时进行光学控制和读出的新应用。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并用于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，而针对抑郁症的回路特异性治疗的新方法将被测试，着眼于对人类患者的翻译。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，再加上我在抑郁症研究领域所展示的生产力，正是执行这项范式转换工作所需的技能和兴趣的精确结合。

 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.