When we designed this course, we assumed participants have general (but not advanced) background knowledge in the areas listed below. Due to time constraints we are not able to teach these topics during this course, they usually are (and if not should be) covered in general academic training in the neurosciences.
- neuroanatomy, neurophysiology
- statistics: hypothesis testing using the general linear model
- basic physics
- basic math (algebra)
We do expect you have a basic knowledge on how to operate a modern PC with a common user interface such as Windows, Macintosh or Linux. For example, you might have to copy files from one location (such as an external pen drive) to another (your computer's harddrive) or install a simple program. When you do not have basic computer skills, we suggest you acquire them before visiting our course. You will not get very far with fMRI analysis without basic computer skills, not in our course practicals and not in your real work.
When you want to prepare for the course, we suggest the following reading. It is not a requirement, you will hopefully be able to understand most of the course material without it, but it might help.
- An excellent overview paper on fMRI analysis:
- Karl J. Friston. Models of Brain Function in Neuroimaging. Annu. Rev. Psychol. 2005. 56:57–87
The content for most of the theoretical image analysis lectures is based on the theory in the following book chapters. After the course it might be worthwile to read them to refresh things or for further study.
- Statistical Parametrical Mapping: the Analysis of Functional Brain Images. Authors: K.J. Friston, J.T. Ashburner, S. Kiebel, T.E. Nichols and W.D. Penny
- Important chapters on spatial preprocessing: Part 2, chapters 4, 5 and 6
- Statistical analysis: Part 3, chapters 8, 9 and 12, 15. Part 4, chapter 18, 20