Course content:
The course focuses on experimental design and analysis of MEG and EEG data. We will briefly introduce the basis of the MEG and EEG signal at a neural level, and how it is measured by the different sensor technologies applied in MEG and EEG. The data processing steps, before statistical analysis, will be explained. The application of general linear model analysis, parametric and nonparametric tests of MEG and EEG data will be explained, including correction for multiple comparisons. We will review experimental design considerations for developing MEG and EEG paradigms. The study of functional connectivity using MEG and EEG data will be introduced.
The students will attend lectures, implement different steps of the data preprocessing and analysis during the hands-on sessions, present and discuss results. It is possible to join the course remotely.
Instructions on how to apply: https://staff.ki.se/course-catalogue-and-vacancies-doctoral-courses
Course info: https://kiwas.ki.se/katalog/katalog/kurs/9783(deadline Nov 15. If you want to join after contact Christoph.pfeiffer@ki.se)