Course content

Event related potentials (ERP's) and time-frequency analyses combined with clustering techniques such as principal and independent component analyses (PCA/ICA) will be taught and practised in the course.
High-density EEG recordings are often challenging to analyse. Conventional ERP analysis typically focuses on a small number of channels and identifies differences between trial types in certain time windows. Although this method can be used with high-density data, it does not take full advantage of the spatiotemporal information present in the data. One way of analysing electrical recordings made at the scalp is based on the assumption that EEG signals may be interpreted as a mixture of the activity of a number of underlying sources in the brain. Source separation consists of identifying different sources in the brain, where each source is described in terms of a varying course of activity and a consistent distribution across the scalp. In other words, a statistically independent source can be represented as both a time-invariant scalp-surface map and a time course of the strength of expression of that spatial map in accounting for the overall EEG at that point in time. Further, a blind (unbiased) separation of sources in terms of PCA and ICA will be used allowing us to extract more general stuctures of brain activity.

Learning outcome

1. Students will learn to collect electroencephalogram (EEG) signals from the brain.
2. Students will learn to recognize common EEG artifacts caused by movements such as eye blinks, facial muscle contractions and head movement.
3. Students should be able to perform a traditional (ERP/VEP) peak analysis and map the result in a 3D head model.
4. Students will perform a source analysis including single and dual source dipole fitting.
5. Students will be able to coregister the seeded source modelling with fMRI using individual anatomy.
6. Students will test an experimental hypothesis about the development of the visual system in young infants.
7. Students will be able to present their findings in a scientific report.

Learning methods and activities

Lectures (16h), tutorial exercises (16h), data collection (16h), self study (130h) and a scientific report will be central activities in the course. The course will only be run with a minimum of three and a maximum of eight students. The course will be organised as an intensive course comprising six working days distributed over two weeks which can either be run consecutively or spread over shorter periods.

Compulsory assignments

• Laboratory work

Recommended previous knowledge

Rugg, M.D. & Coles, M.G.H (1996). Electrophysiology of Mind: Event-related brain potentials and cognition. Oxford: Psychology series (25). Luck S.J. (2005). An Introduction to the Event-Related Potential Technique. Cambridge: MIT Press.

Required previous knowledge

Master`s degree or similar in one of the relevant subject areas. Interested undergraduate students with relevant backgrounds will be assessed on an individual basis.

Course materials

Various tutorials and practice data will be provided during the course.