In terms of defining and diagnosing psychiatric and neurological conditions, there has been an increased focus on a transdiagnostic characterisation of different disorders that capture similar symptoms in different conditions (Huys et al., 2016; Montague et al., 2012). The study by Will et al (2017) utilises this relatively new approach to understanding associations between the brain and clinical conditions. They combine parameters from their computational model of self-esteem and self-report questionnaires of several symptoms including depression and anxiety. This allows them to identify an interpersonal vulnerability dimension across different conditions that modulated functional connectivity from medial prefrontal areas. Moving forward, this approach of harnessing well characterized frameworks of reinforcement and associative learning, along with transdiagnostic descriptions of psychiatric symptoms, promises to uncover new insights into clinically relevant psychological and neural mechanisms.
