Multilevel Characterization of Approach and Avoidance Biases Linked to Social Stress

项目概要 患有重度抑郁症的人通常会拒绝奖励，而是避免威胁（包括 无关的）。尽管这些以决策障碍为特征的代价高昂的行为普遍存在，但它们 基础神经生物学的定义不明确。在这里，我结合了强大的鼠标模型来提供多层次的 与抑郁症相关的接近和回避决策的特征。先前的研究强调了具体 皮质纹状体边缘系统内的区域作为信号传递和回避表达。然而，我 建议通过公正地分析小鼠整个大脑中的神经元活动来超越这种有限的方法 显示与抑郁相关表型相关的接近和回避决策偏差。此外，我建议 公正地分析关键区域的转录模式，并通过化学遗传学测试关键细胞类型的作用。 我假设，除了已证实的区域之外，我们的结果还将揭示被忽视的区域和细胞类型，这些区域和细胞类型 活动可能对于驱动与抑郁症相关的接近和回避偏见至关重要。此外，我们的 转录分析将识别经过验证的（即 ΔFOSB 和 CREB）和新型转录调节因子 这些偏见。在目标 1 中，我采用了平台介导的回避任务来分析方法和回避偏差 在暴露于慢性社交失败压力（CSDS）的小鼠中，这是一种用于研究抑郁相关病理学的模型。我 首先证明，与抑郁症患者类似，易受 CSDS 影响的小鼠表现出持续的回避行为 之前宣布休克威胁的提示，但代价是失去奖励。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。为了进一步表征这些行为 由于偏见，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 从转录角度分析其活动与接近和回避偏差最密切相关的区域。 同时，我将描绘皮质纹状体内的伏隔核、杏仁核和前额叶皮层。 边缘系统，已被证明可以发出接近和回避的信号，并对不利的情况敏感 压力的后果。接下来，在实验1.3中，我将进行化学遗传学，以测试关键的因果作用 CSDS 后偏向方法或回避决策中的区域和细胞类型。利用本次培训， K00阶段，我将研究对压力敏感的决策回路的体内时空动态，通过 将行为与钙成像和计算模型相结合。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颖见解，并将极大地促进 支持我成功过渡到博士后奖学金以及随后的科学独立。

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.