PC5 – Demo and discussion: Bayesian descriptions of information processing in the brain

Lecturer: Chris Mathys
Fields: Cognitive neuroscience, computational modelling

Content

In this meeting, I will do a software demo (of the HGF Toolbox) which illustrates the theoretical points made in the main talk. There will also be time to answer questions and to continue discussions started after main talk.

Literature

  • Mathys, C., Daunizeau, J., Friston, K. J., & Stephan, K. E. (2011). A Bayesian foundation for individual learning under uncertainty. Frontiers in Human Neuroscience, 5, 39. https://doi.org/10.3389/fnhum.2011.00039
  • Iglesias, S., Mathys, C., Brodersen, K. H., Kasper, L., Piccirelli, M., den Ouden, H. E. M., & Stephan, K. E. (2013). Hierarchical Prediction Errors in Midbrain and Basal Forebrain during Sensory Learning. Neuron, 80(2), 519–530. https://doi.org/10.1016/j.neuron.2013.09.009

Lecturer

Chris Mathys

Chris Mathys is Associate Professor of Cognitive Science at Aarhus University. He originally trained as a physicist and has a PhD in Information Technology from ETH Zurich.

Affiliation: Interacting Minds Centre, Aarhus University, Denmark
Homepage: https://chrismathys.com