resources

Teaching

The resources listed here are Open Educational Resources (OER) that are free to use, share, copy and edit, with attribution and following this license.

Bachelor courses

• Cognitive Neuroscience [practicals] (2023/24 onwards) - together with Javier Ortiz-Tudela
  • Repository of students’ podcasts on Cognitive Neuroscience

Master courses

• Methods in Cognitive Neuroscience (2023/24 onwards)
• Preregistration in Cognitive Neuroscience

Tutorials

• Introduction to Markdown (in Spanish)
• Introduction to ggplot (in Spanish)

Materials and code

Please, check the specific license of each resource before using it.

THINGS-Mooney database

The THINGS-Mooney database provides a set of “mooney-style” distorted images (created from the original license-free THINGS-plus images). Additionally, this repository contains a toolbox to create your own mooney-style images, plus subjective recognition scores for each mooney image collected on a large sample of participants (n = 947).

If you use this dataset in your research, please cite this repository as follows:

Linde-Domingo, J.*, Ortiz-Tudela, J.*, Voeller, J., & González-García, C. (2024). THINGS-Mooney database (v1.0.0). Zenodo. https://doi.org/10.5281/zenodo.14040189

(* denotes equal contribution)

Prediction Error estimator

This notebook demonstrates a toy model of Prediction Error (PE) estimation.

It visualizes how sensory information, priors, and their precisions interact to form a posterior belief.

The model is based on the principles of Bayesian inference and uses Kullback-Leibler (KL) divergence to quantify the difference between distributions.