Transdiagnostic Mechanisms of Mental Health: Insights from Computational Modelling

To what extent can computational models of learning truly capture the mechanisms of mental health? I will present computational insights into transdiagnostic dimensions, such as negative affective bias and control-seeking, that cut across traditional psychiatric diagnoses such as depression and eating disorders. However, the utility of this approach has been recently called into question. I will therefore go on to present a large online study that stress-tests the implicit assumptions of computational psychiatry, offering a critical perspective on current limitations and providing a roadmap for more robust modelling practices.

I am a Senior Lecturer in Mental Health at the University of York, UK. I was awarded a DPhil in Psychiatry from the University of Oxford in 2018 on the topic of eating disorders and compulsivity, supervised by Professor Phil Cowen and Dr Rebecca Park. From 2018-2022, I worked as a postdoctoral researcher in the Neuroscience and Mental Health Group at the Institute of Cognitive Neuroscience (UCL), under the guidance of Professor Oliver Robinson, focusing on the application of reinforcement learning models to anxiety.

My primary research focus is to use cognitive and computational psychiatry techniques to investigate the mechanisms that precipitate mental health concerns, such as eating disorders and anxiety. However, I have also dipped a toe into interoception, psychometrics, meta-science, and qualitative research. I have received funding from the Academy of Medical Sciences and the Wellcome Trust, and am an associate editor for the Journal ‘Royal Society Open Science’. I am a Council Member of the British Association of Psychopharmacology.

This seminar is hosted in person in the Seminar Room. To join online, please use the Zoom details below. 

• https://zoom.us/j/98611180818?pwd=qKFgYGOss76befRbH4zy0aRgjqNyOU.1
• Meeting ID: 986 1118 0818
• Passcode: 765845