Acknowledgements
“If I have seen further, it is by standing on the shoulders of giants.” - Isaac Newton (1675)
Acknowledgments
The course material would not be possible without the prior work of many others. In particular we would like to acknowledge:
- Simon Farrell, John Kruschke, Ben Lambert, Stephan Lewandowsky, Michael Lee, Richard McElreath, and Eric-Jan Wagenmakers for their excellent textbooks which have heavily shaped the course content and structure
- Woo-Young Ahn, Nate Haines, Jan Gläscher and Antonius Wiehler for their support in developing the initial version of these materials
Future content
We are hoping to further expand the content covered in this course. Examples for additional workshops include:
- Applying a wider family of computational models (delay discounting, intertemporal choice)
- Computational modeling of decision-making tasks using the
hBayesDM
package1 inR
- Practical examples of implementing model-based fMRI
So make sure to stay up-to-date with the website by starring ⭐ the GitHub repository!
Footnotes
Ahn, W. Y., Haines, N., & Zhang, L. (2017). Revealing neurocomputational mechanisms of reinforcement learning and decision-making with the hBayesDM package. Computational Psychiatry (Cambridge, Mass.), 1, 24.↩︎