Mapping the neural and computational traces of lack of controllability and their relevance for depression

Stress is an established risk factor of depression, but we lack a mechanistic understanding of how stress leads to depression. Crucially, the impact of stress is dependent on whether it is perceived to be controllable (i.e., avoidable).

In animal models, uncontrollable stress refers to unavoidable aversive stimulation and it induces passive behaviors and reduces dopamine release in relevant decision-making neural circuits. However, current paradigms to study controllability in humans are suboptimal for neuroimaging.

Here, we will use a new paradigm to characterize the behavioral and neuronal effects of uncontrollable aversive stimulation in healthy volunteers and develop behavioral markers of lack of control in depressed patients.

First, we will use PET and fMRI to study how uncontrollable aversive stimulation affects dopamine release and functional connectivity.

We will also use cognitive testing to study the effects of uncontrollable aversive stimulation on decision-making abilities. Second, we will use a smartphone app to collect data on decision-making abilities in depressed patients.

We will identify groups of depressed patients based on the clusters of variation in decision-making abilities in depression and relate these to clinical outcomes.

This project will elucidate the behavioral and neuronal effects of uncontrollable aversive stimulation in healthy participants and promote our understanding of how abnormal decision-making processes relate to depression.