Multilevel Characterization of Approach and Avoidance Biases Linked to Social Stress

项目摘要 经历严重抑郁症的人通常会拒绝奖励，而是避免威胁（包括 不相关的）。尽管这些代价高昂的行为普遍存在，但他们的决策能力受到了损害。 潜在的神经生物学定义不明确。在这里，我结合联合收割机强大的鼠标模型，以提供一个多层次的 与抑郁症有关的接近和回避决定的特征。以前的研究强调了特定的 皮质纹状体边缘系统内的区域作为信号接近和回避表达。但我 我建议超越这种有限的方法，无偏见地分析小鼠整个大脑中的神经元活动 显示接近和回避决策偏差与抑郁症相关的表型。此外，我建议 在关键区域无偏地描绘转录模式，并在化学遗传学上测试关键细胞类型的作用。 我假设，除了已证实的领域，我们的结果将揭示被忽视的领域和细胞类型， 活动可能在与抑郁症相关的驾驶方法和避免偏见中至关重要。而且我们 转录分析将鉴定已证实的（即，和CREB）和新的转录调节因子驱动的 这些偏见。在目标1中，我采用了一个平台介导的回避任务，以分析接近和回避偏见 在暴露于慢性社会失败压力（CSDS）的小鼠中，这是一种用于研究抑郁症相关病理学的模型。我 第一次证明了对CSDS敏感的小鼠，类似于抑郁症患者，表现出持续的回避， 到先前宣布电击威胁的线索，以错过奖励为代价。相比之下，小鼠对 CSDS迅速减少他们的回避，以最大限度地获得奖励。为了进一步描述这些行为 在实验1.1中，我使用cFOS的全脑免疫染色作为相关神经元活动的代表。 接下来，为了利用神经元活动和基因表达模式，在实验1.2中，我将使用RNA测序， 来转录分析那些活动与接近和回避偏差最密切相关的区域。 同时，我会分析皮质纹状体内的杏仁核，杏仁核和前额叶皮层- 边缘系统，已被证明是信号的接近和避免，并敏感的不利 压力的后果。接下来，在实验1.3中，我将执行化学遗传学，以测试关键的因果作用， 区域和细胞类型的偏置方法或避免决定后CSDS。利用这次培训， K 00阶段，我将研究对压力敏感的决策回路的体内时空动力学， 将行为与钙成像和计算建模相结合。总体培训和研究计划 这里概述的内容将揭示对受压力影响的决策过程的新见解，并将极大地 支持我成功地过渡到博士后奖学金和随后的科学独立。

PROJECT SUMMARY People experiencing major depression often decline their approach to rewards, to instead avoid threats (including irrelevant ones). Despite the prevalence of these costly behaviors featuring decision-making impairments, their underlying neurobiology is poorly defined. Here, I combine powerful mouse models to provide a multilevel characterization of approach and avoidance decisions linked to depression. Previous studies highlight specific areas within the corticostriatal-limbic system as signaling approach and avoidance expression. However, I propose to go beyond this limited approach by unbiasedly profiling neuronal activity in the whole brain of mice showing approach and avoidance decisional biases linked to depression-related phenotypes. Further, I propose to unbiasedly profile transcriptional patterns in key areas and to chemogenetically test the role of key cell types. I hypothesize that, in addition to proven areas, our results will reveal overlooked areas and cell types whose activity might be crucial in driving approach and avoidance biases linked to depression. Moreover, our transcriptional analyses will identify proven (i.e., ∆FOSB & CREB) and novel transcriptional regulators driving these biases. In Aim 1, I adapted a platform-mediated avoidance task, to profile approach and avoidance biases in mice exposed to chronic social defeat stress (CSDS), a model used to study depression-related pathology. I first demonstrated that mice susceptible to the CSDS, similar to depressed patients, show persistent avoidance to a cue previously announcing a shock threat, at the cost of missing rewards. In contrast, mice resilient to the CSDS quickly decrease their avoidance to maximize gaining rewards. To further characterize these behavioral biases, in Experiment 1.1, I use brain-wide immunostaining of cFOS as a proxy for correlated neuronal activity. Next, to leverage neuronal activity and gene expression patterns, in Experiment 1.2, I will use RNA-sequencing to transcriptionally profile areas whose activity most strongly correlated with approach and avoidance biases. Simultaneously, I will profile the nucleus accumbens, amygdala, and prefrontal cortex within the corticostriatal- limbic system, which have been proven to signal approach and avoidance and to be sensitive to the adverse consequences of stress. Next, in Experiment 1.3, I will perform chemogenetics, to test the causal role of key areas and cell types in biasing approach or avoidance decisions after CSDS. Capitalizing on this training, in the K00 phase, I will study in vivo temporospatial dynamics of decision-making circuits sensitive to stress, by combining behavior with calcium-imaging and computational modeling. The overall training and research plans outlined here will reveal novel insights into decision-making processes impacted by stress, and will greatly support my successful transition to a postdoctoral fellowship and subsequent scientific independence.