Open to Master’s and Research Master’s students from Psychology, and students from the specialisation Education and Child Studies: Applied Neuroscience in Human Development (Leiden University)
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
MRI Physics basics
Preprocessing of fMRI scans
Making statistical inferences
Functional brain connectivity
At the end of the course, the student can:
- Explain methods of FMRI image acquisition and the theory of physiological processes causing FMRI-measurable brain activation
- Discuss and explain FMRI data pre-processing including motion correction, filtering, and image registration
- Discuss and explain how multiple regression analysis is applied to FMRI data of individuals and groups of individuals
- Discuss and explain the multiple comparisons problem in FMRI data and how to correct for this using statistical thresholding techniques
- Discuss additional advanced FMRI methods including FMRI connectivity and FMRI prediction
For the timetable of this course please refer to MyTimetable
Students must register themselves for all course components (lectures, tutorials and practicals) they wish to follow. You can register up to 5 days prior to the start of the course.
You must register for each exam in My Studymap at least 10 days before the exam date. You cannot take an exam without a valid registration in My Studymap. Carefully read all information about the procedures and deadlines for registering for courses and exams.
Exchange students and external guest students will be informed by the education administration about the current registration procedure.
Mode of instruction
The course consists of:
7 2-hour lectures
7 2-hour work group sessions
1 or 2 1-hour sessions at the MRI scanner
No web-lectures available for this course. Lectures and work groups language: English.
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.
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. All students are required to take and pass the Scientific Integrity Test with a score of 100% in order to learn about the practice of integrity in scientific writing. Students are given access to the quiz via a module on Brightspace. Disciplinary measures will be taken when fraud is detected. Students are expected to be familiar with and understand the implications of this fraud policy.
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 provided manuals is 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.
S.A. Huettel, A.W. Song, G. McCarthy. (2009). Functional Magnetic Resonance Imaging 3rd Revised Edition. Sinauer Associates Inc.,U.S.
Reader of work group sessions
Ethan McCormick email@example.com
Anne Hafkemeijer firstname.lastname@example.org