Brain Imaging


Course Objective

The course is short, so our goal is to give you an idea of the awesome
possibilities and annoying pitfalls of functional brain imaging, but
most importantly, to give you a solid foundation for further learning.
At the end of the course, you will be able to devise a valid fMRI
experiment, and perform the basic analysis on the resulting data using
state-of-the-art open science and open source tools.

Course Content

In this course we will teach you the ins and outs of brain imaging, that
is, fMRI. We will teach you everything from the basics of signal
analysis, to experimental design, to statistics. Some of the newest
cutting-edge techniques, including pattern classification analysis,
connectivity modeling, and resting state network analysis, are also

Teaching Methods

Every week, there will be one lecture, and one practical/'werkcollege'.
The course is broadly divided into two parts; the first half of the
course serves to teach you the very basics of signal analysis and
experimentation. We believe this basis is necessary to later start to
think independently and academically about research in your future
field. In this first phase of the course the weekly lecture will treat
theory while the practicals will allow you to wet your toes with this
material. This way we try to combine theory and practice.
In the second half of the course, you will already know a lot about what
Brain Imaging entails. Then, we will switch gears a bit, and teach you
what's going on in the neuroimaging field right now. That means that
during the weekly lecture we will use research articles to illustrate
the state of the art. In the practicals we'll move towards letting you
perform an entire fMRI analysis yourselves. In this second part of the
course we'll also focus more and more on recent articles that show us
the state-of-the-art in neuroimaging.

Method of Assessment

Final Exam, open-end questions 40%
Practical assignments 50%
Quizzes 10%

Entry Requirements

Fluency in the Python programming language, for instance through
following the "Programming in python" course offered in the psychology


Handbook of Functional MRI Data Analysis, Poldrack et al, Cambridge
We will further use articles describing current research.

Additional Information

Prior knowledge of Python programming and statistics is recommended.

General Information

Course Code P_MBRIMAG
Credits 6 EC
Period P4
Course Level 400
Language of Tuition English
Faculty Fac. of Behavioural and Movement Science
Course Coordinator dr. T.H.J. Knapen
Examiner dr. T.H.J. Knapen
Teaching Staff dr. T.H.J. Knapen
D.M. van Es MSc

Practical Information

You need to register for this course yourself

Teaching Methods Seminar, Lecture