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fMRI Data and Statistics


Important Note

  • All Semester II bachelor and master psychology courses and examinations (2020-2021) will be offered in an on-line format.

  • If it is safe and possible to do so, supplementary course meetings may be planned on-campus. However, attendance at these meetings will not be required to successfully complete Semester II courses.

  • All obligatory work groups and examinations will be offered on-line during Central European Time, which is local time in the Netherlands.

  • Information on the mode of instruction and the assessment method per course will be offered in Brightspace, considering the possibilities that are available at that moment. The information in Brightspace is leading during the Corona crisis, even if this does not match the information in the Prospectus.

Entry requirements

  • Only open to Master’s and Research Master’s students from Psychology

  • People with no previous experience of UNIX should spend a few hours, before the course starts, working through at least the first 5 sections of a basic unix tutorial


The use of fMRI has become a very important technique for functional brain imaging. The special nature of the data collected by this method requires very specific, often recently developed, statistical methods for data analysis. In this course several statistical methods for analysing fMRI data will be discussed. The course takes place in 7 sessions. On most days, in the first two hours theoretical issues will be addressed. In the last two hours students are trained in the analysis of data in practical situations.

Topics which will be discussed are:

  • Why and when fMRI

  • BOLD response

  • preprocessing

  • design for a single-subject experiment

  • making statistical inferences

  • statistical analysis of fMRI data by GLM

  • task-fMRI and functional brain connectivity

  • group analyses.

Course objectives

Upon completion of this course, students will:

  • Understand theory of fMRI data acquisition and fMRI statistics; and

  • Learn image processing of fMRI data as basic preparation for analysis in fMRI-research.


For the timetables of your lectures, work groups and exams, please select your study programme in: Psychology timetables




Students must register for the course once. Master’s course registration


Students are not automatically enrolled for an examination. They can register via uSis from 100 to 10 calendar days before the date. Students who are not registered will not be permitted to take the examination. Registering for exams

Mode of instruction

The course consists of:

  • 6 2-hour lectures, attendance is mandatory

  • 7 2-hour work group sessions, attendance is mandatory

  • 1 or 2 1-hour sessions at the MRI scanner, attendance is not mandatory

No web-lectures available for this course. Lectures and work groups language: English.

Assessment method

The final grade is based on a written exam, consisting of 8-10 open questions about both theory (e.g. theory of statistics) and practical fMRI (e.g. the various analysis steps when computing fMRI activation maps). Language: English.

You will be informed via Brightspace about the manner of inspection and discussion of the examination.

Study material for the exam

All that is discussed at the lectures and at the practical sessions, all information on the course slides and in the manualsis exam material. The book (below) is needed to understand the exam material. The book also contains non-exam material.

The Institute of Psychology follows the policy of the Faculty of Social and Behavioural Sciences to systematically check student papers for plagiarism with the help of software. Disciplinary measures will be taken when fraud is detected. Students are expected to be familiar with and understand the implications of this fraud policy.

Reading list

  • S.A. Huettel, A.W. Song, G. McCarthy. (2009). Functional Magnetic Resonance Imaging 3rd Revised Edition. Sinauer Associates Inc.,U.S.

  • Lecture notes

  • Reader of work group sessions

Contact information

Serge Rombouts

Anne Hafkemeijer