Pre-conference workshops

Directed connectvity analysis of EEG/MEG signals

Miroslaw Wyczesany, PhD
Jagiellonian University in Krakow

This workshop will guide you through the analysis of directed brain communication based on EEG/MEG signals, focusing on:

 

• Automated, machine-learning cleaning procedures 

• Classification method for the separation of artifactual and brain components

• Source reconstruction of EEG/MEG signals

• Source-based connectivity analysis with Directed Transfer Function based on granger causality

This workshop will consist of a theoretical introduction and a practical hands-on programming session in MATLAB. Participants will analyze sample data, starting from the raw signal to the testing of research hypotheses. There will also be time for step-by-step recommendations on how to analyze your own data.

 

Advanced fMRI data analysis

Jakub Szewczyk, PhD
Donders Institute for Brain, Cognition, and Behaviour

This workshop will introduce you and deepen your understanding of advanced fMRI data analysis techniques, focusing on:

 

• Voxelwise Encoding Modelswith Ridge Regression: a method to predict neural activity patterns. This session will cover the principles of voxelwise encoding models, including how to select and apply the optimal regularization parameter for your data.

• Representational Similarity Analysis (RSA): a powerful method to compare patterns of neural activity across conditions. Understand how to construct and interpret similarity matrices, and how to use RSA to uncover the representational structure of cognitive processes in the brain.

 

This workshop will consist of a theoretical introduction and a practical hands-on programming session using Python/numpy/scikit-learn (so at least rudimentary knowledge of Python is recommended).

Workshop 3 (TBA)