Mr Eddie Xiao

I am generally interested in computational models of learning and decision-making, and how the brain copes with various forms of uncertainty. My PhD project examined the neurocomputational mechanisms underlying vigilant scanning. Increased vigilance is an adaptive response to uncertain environments and unexpected events, as it promotes information gathering. However, excessive vigilance, potentially driven by the misestimation of uncertainty and/or hyperarousal, is detrimental to mental health. It is therefore important to understand how these processes are altered in anxiety and other stress-related disorders.

For data collection, I work with eye-tracking, mouse-tracking, and EEG, which I use to study attention allocation and prediction error signalling. In addition, I apply Bayesian and non-Bayesian models to quantify individual differences, and I am particularly interested in joint modelling (e.g., of choice and reaction time data, or of choice and gaze data). I am also keen on triangulating across studies or measurement modalities (e.g., replications across in-person and online studies, and combining EEG with pupillometry).

My past projects and ongoing collaborative projects pertain to:
1) The Cambridge Research into Autism and Anxiety (CamRAA): studying the common and unique cognitive differences in learning under uncertainty for autistic and anxious individuals
2) How effort-based decision-making is affected by anhedonia and apathy, and whether progress feedback reduces effort aversion.