The first talk in the series is going to be by Prof. Ondřej Zíka (University College Dublin). It will take place on 27. October 2025 at 2 p.m. You can find more information on the event here, and below.
Abstract: Intolerance of uncertainty (IoU) is a prominent driver of internalizing psychopathology, especially anxiety. However, IoU is commonly only assessed using self-report measures. Here, we first focus on deriving a physiological marker of uncertainty sensitivity, which we subsequently use to predict longitudinal six-month changes in internalizing symptoms. At baseline, we employ the fear reversal paradigm while we record skin conductance. Using a combination of hierarchical Bayesian modeling and reinforcement learning we derive computational parameters including the learning rate, associability and uncertainty sensitivity. We then combine these computational parameters with fluctuations in anxiety symptoms over six months (e.g., standard deviation, autocorrelation) to predict changes in trait anxiety levels over the same period. During this talk, I will present preliminary results of these analyses and highlight some of the ongoing challenges and future plans.
Ondřej Zíka is an assistant professor at University College Dublin where he heads the Uncertain Mind lab. He completed his PhD in Clinical Neurosciences at Oxford University and later worked as postdoc at the Max Planck Insitute for Human Development, Berlin, Karolinska Institute, Stockholm and as an independent fellow at Bielefeld University. His research interests evolve around understanding how uncertainty impacts human decisions and how it relates to aspects of mental health (anxiety, eating disorders) and development. He is also interested in ways in which we can combine AI with longitudinal and multimodal approaches to improve prevention and diagnosis of mental health conditions. To study these topics, he uses a range of experimental and computational methods (reinforcement learning, Bayesian models) together with physiology (eye-tracking, skin conductance) and neuroimaging (M/EEG, fMRI).