Distinct Computational Mechanisms of Uncertainty Processing Explain Opposing Exploratory Behaviors in Anxiety and Apathy

Background: Decision making in uncertain environments can lead to varied outcomes, and how we process those outcomes may depend on our emotional state. Understanding how individuals interpret the sources of uncertainty is crucial for understanding adaptive behavior and mental well-being. Uncertainty can be broadly categorized into 2 components: volatility and stochasticity. Volatility describes how quickly conditions change. Stochasticity, on the other hand, refers to outcome randomness. We investigated how anxiety and apathy influenced people's perceptions of uncertainty and how uncertainty perception shaped explore-exploit decisions. Methods: Participants (N = 1001, nonclinical sample) completed a restless 3-armed bandit task that was analyzed using both latent state and process models. Results: Individuals with anxiety perceived uncertainty as resulting more from volatility, leading to increased exploration and learning rates, especially after reward omission. Conversely, individuals with apathy viewed uncertainty as more stochastic, resulting in decreased exploration and learning rates. The perceived volatility to stochasticity ratio mediated the anxiety-exploration relationship post adverse outcomes. Dimensionality reduction showed exploration and uncertainty estimation to be distinct but related latent factors shaping a manifold of adaptive behavior that is modulated by anxiety and apathy. Conclusions: These findings reveal distinct computational mechanisms for how anxiety and apathy influence decision making, providing a framework for understanding cognitive and affective processes in neuropsychiatric disorders.