EEG group tutorial II: Data processing and plotting

Data processing and plotting

Electroencephalography (EEG) is a non-invasive neuroimaging technique that measures the brain waves or the electrical activity in the cortex via small metal discs or electrodes placed on the surface of the scalp. When EEG is time-locked to a specific event or stimulus (e.g., word, sound, image), we get ERPs. We look at the timing, size and other properties of different ERP components as an index of different neurocognitive processes.

In this tutorial, participants will work with a pre-existing dataset and will go through the different steps involved in the processing of EEG data and plotting ERPs.

After a brief introduction to EEG methodology, we will work with a pre-existing dataset and go through the different steps involved in processing raw EEG data and converting it to ERP waves. We will cover two pipelines, one manual pipeline using EEGLAB and one automatic pipeline using MATLAB and Python scripts. The course does not cover statistical analysis of EEG data but can include a short overview of this step if time allows.

Pre-requisites

• Participants are expected to have taken part in EEG tutorial I or have a basic understanding of EEG methodology and how EEG data is collected.
• Basic knowledge of MATLAB and Python is beneficial but not necessary.
• Participants should have their own computers with MATLAB, Python and EEGLAB installed (instructions will be sent prior to the meeting).
   

For info and applications, contact sara.farshchi@humlab.lu.se