Program

Day 1: Collaborative Meeting Day – Evidence Accumulation in Cognitive Neuroscience (sponsored by NWO)

11:00 Birte Forstmann – Introduction to model-based cognitive neuroscience and approaches to analysis.
13:00
Andrew Heathcote
– Introduction to Cognitive Race Models, including simulating and exploring the diffusion decision model (DDM), the linear ballistic accumulator (LBA), and the lognormal race model.
15:00 
Mini-talks (all lecturers present): We invite all participants to give a short (max 3 min & max 3 slides) talk about their recent work or about research questions to which they would like to apply model-based neuroscience techniques.

Day 2: Workshop Day 1

10:00 Bayesian estimation of evidence-accumulation models, including Bayes theorem, priors and posteriors, and sampling single subjects (Andrew Heathcote )
13:00 Introduction to model-based fMRI (Steven Miletic)
16:30 Mini-presentations continued.

Day 3: Workshop Day 2

10:00  Bayesian estimation and model based sampling, including more on sampling single subjects, model selection, and introduction to hierarchical models (Andrew Heathcote and Dora Matzke)
13:00 Introduction to model-based EEG (Michael Nunez)
16:30  Keynote 1: Rafal Bogacz – Models of Reinforcement Learning.

Day 4: Workshop Day 3

10:00  Bayesian estimation of evidence accumulation models continued, including sampling hierarchical models, model comparison, and plausible values (Andrew Heathcote)
13:30  Keynote 2: Brandon Turner – Methods of joint modelling.
15:00 Joint modelling of brain and behaviour tutorial (Brandon Turner and Reilly Innes)
16:30  Mini-presentations continued.

Day 5: Collaborative Meeting Day – Reinforcement Learning in Cognitive Neuroscience (sponsored by NWO)

10:00 Keynote 3: Peter Dayan – Model based and model free reinforcement learning.
11:30  Panel Discussion – Presenters of the Summer School will engage in a discussion on recent advances, potential limitations, future directions and applications of model-based cognitive neuroscience.
13:30  Introduction to fitting joint learning and evidence-accumulation models (Andrew Heathcote & Steven Miletic)
16:00 Closing remarks.

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