• Britz Juliane

• Britz Juliane

The EEG (Electroencephalogram) is the oldest window into the human mind and non-invasively tracks the electrical activity generated by the brain with high temporal resolution, thus providing important information about mental operations.

This goal of this course is to give a comprehensive overview over the field of EEG research with a particular focus on event-related activity. It will cover the physical and physiological basics of EEG, fundamentals of digital signal processing and recording techniques. Students will present papers using state-of-the-art analysis techniques as well as “classics” in the EEG literature; an important aspect of these paper presentations are the particular questions we can answer with EEG as well as the methodological challenges and their solutions.

The class will be a hybrid format comprising lectures on the physical bases of EEG / ERPs and presentations and discussion of papers on different methodologies.

By the end of the class, students will have a fundamental understanding of the physics and physiology of EEG, be able to read and evaluate papers covering broad scope of analysis methods.

This class addresses Master (and PhD) students with an interest in EEG, particularly those working with EEG data for their thesis.

Contents and organization of the class

In this class (block course), we will cover the physical bases of the EEG and learn how the EEG is generated in the brain, how it is measured on the surface of the scalp and how its sources can be reconstructed from scalp recordings.

We will further cover some basic concepts of Digital Signal Processing and apply them to the EEG signal to extract those aspects of the EEG that are important to researchers in Cognitive Neuroscience. We will further see the distinction between spontaneous and evoked activity.

In the first two blocks (November 5 & 12) we cover the theoretical bases. In the third and fourth blocks (November 19, December 3), students will present selected papers covering the theoretical topics addressed in the first block and – if applicable – present their own EEG projects.

Please contact me prior to the beginning of class if you have an EEG project lined up for your Master’s.

Evaluation will be based on the presentations.

The class will be held in presence and presence is mandatory in both sessions to allow active exchange between participants.

Learning objectives

After the “EEG” class, students will have a fundamental knowledge about the generation, measurement, analysis and interpretation of EEG signals in cognitive neuroscience.

They will know

• how the EEG is generated in the brain
• how the EEG is measured on the surface of the scalp
• how the EEG signal is preprocessed to extract signal features of interest
• the difference between spontaneous and evoked activity
• basic concepts in Digital Signal Processing: filtering, down-sampling, aliasing, Fourier-Transform, time-frequency decomposition, Independent Component Analysis
• how EEG sources are reconstructed
• classic and state-of-the-art EEG analysis methods applied to spontaneous and evoked activity

In addition, students will be able to read and present relevant papers from the field.

They will be able to

• read and understand relevant publications using various EEG measures
• present classic and state-of-the-art publication on various EEG measures
• critically reflect on EEG publications by phrasing pertinent questions about them

Please contact me prior to the beginning of class if you have an EEG project lined up for your Master’s.

• Syllabus - PLEASE READ BEFORE INSCRIBING

Evaluation of an oral paper presentation (in groups)

Evaluation of an oral paper presentation (in groups)

Evaluation of an oral paper presentation (in groups)

Evaluation of an oral paper presentation (in groups)