Examination arrangement

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

Knowledge:
The candidate...
- will have knowledge to carry out a traditional ERP/VEP-component analysis and to represent the results in a 3D head model.
- will have knowledge to recognize ordinary EEG artifacts caused by movements such as eye blinking, facial movements and head movements.

Skills:
The candidate...
- will have adequate skills in collecting electroencephalogram (EEG) signals from the brain.
- will have adequate skills to carry out a source analysis which both includes single and double montage of source dipoles.

General qualifications:
The candidate...
- will be able to record source modelling with fMRI through individual brain anatomy.
- will be able to test an experimental hypothesis concerning the visual system in humans.
- will be able to present their research results in a scientific report.

Learning methods and activities

Lectures (16h), seminars (16h), tutorial exercises (16h) and dissemination of research results in a scientific report will be central activities in the course. The course will only be run with a minimum of five PhD candidates and a maximum of fifteen candidates. The course will be organised as an intensive course comprising nine working days distributed over two weeks. Interested undergraduate students with relevant backgrounds will be assessed on an individual basis. PhD candidates have priority.

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 equivalent in one of the relevant subject areas. Interested undergraduate students with relevant backgrounds will be assessed on an individual basis. PhD candidates have priority.

Course materials

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