Transdiagnostic mental health symptom dimensions predict use of flexible model-based inference in complex environments.

Symptoms of common mental health problems often pertain to complex inference and decision problems (for example around future social interactions). Such patterns may reflect the breakdown of the fundamental computational processes that ordinarily underpin these behaviours, with the use of flexible goal-directed decision-making being a prime candidate. Here, we used a validated, naturalistic threat inference task to assess the use of goal-directed decision-making in complex interactive decision problems. Participants (n = 1025) completed this task alongside a battery of self-report measures of mental health symptoms and neurodevelopmental characteristics. Participants higher in inattentive/neurodevelopmental symptoms were better able to predict the predator's behaviour, while those higher in externalising symptoms made more incorrect inferences. Variability in behaviour was better explained by these specific symptom dimensions than by more general factors. Using computational modelling, we show that these associations are mediated by the degree to which individuals use goal-directed decision-making to make inferences about the predator's behaviour. Our results suggest that symptoms and traits that manifest in real-world environments may result from alterations in the use of complex computational mechanisms.