Organized by Felix Ball, Emanuele Porcu, & Tömme Noesselt
In the last decade, Bayes modelling became a fundamental statistical tool in cognitive and medical science, and science in general. Today, many influential scientists apply Bayesian modelling to investigate processes underlying behavior and perception.
The 1st Modelling Symposium, held in Magdeburg and Berlin, Germany, provided a mix of theoretical and application-oriented introductions to Bayesian modelling. It provided the basis to conduct Bayesian statistics autonomously, and the basis for creating own Bayes models. Fortunately, we were able to invite two leading scientists (Jaqueline Scholl and Nils Kolling) from Oxford University as tutors.
Throughout the workshop, we covered topics such as non-bayesian methods, i.e. cognitive models (example: reinforcement learning),
Bayesian models of cognition, Bayesian data analysis such as hierarchical models, using Stan (via Matlab interface) to fit models etc.
She is a neuroscientist interested in understanding the psychological and neural mechanisms underlying motivated behavior. Specifically, how do humans learn what they value and how do they use this knowledge to make good decisions? She is furthermore interested in applying these concepts to understand psychiatric disorders, such as depression, and their treatments.
The primary aim of his research is the understanding of the neural mechanisms underlying reward-guided decision making, learning and exploration. He focuses particularly on the role of the frontal lobes of humans in generating choices based on rewards and other features of the environment.