Multilevel Characterization of Approach and Avoidance Biases Linked to Social Stress

About This Grant

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.