Resources for fMRI data analysis

Steve Simon


I was asked to provide feedback on a grant that will use functional magnetic resonance imaging (fMRI) as one component of the research. This technique is used to quantify brain activity by measuring changes in blood flow in various regions of the brain. It effectively produces information in the three dimensions of the brain structure, plus a dimension of time. The technology today can produce images localized to a cube with dimensions of approximately 2-4 mm, and these can be measured every 1-4 seconds. Each individual cubic region is called a voxel, a contraction of the words “volume” and “pixel.”

The general goal of fMRI in research is to contrast brain activity in certain regions of the brain (such as the prefrontal cortex) between two or more groups of subjects and/or with two or more different sensory stimuli.

The data produced in an fMRI study is especially challenging from a statistical perspective. A quick Medline search yielded a whole host of papers listing exotic statistical methods. Here are some examples (I’m just reproducing the titles):

The analysis of fMRI data requires extensive graphics processing and filtering. There are spatial and temporal autocorrelations that need to be accounted for. Some proprietary software for fMRI data analysis include

There are two R libraries for analysis of fMRI data:

At the SPM website, you can find a nice introduction to some of the data analysis issues in a paper

Another resource discussing data analysis issues is:

There are several books out on fMRI analysis, and the one that looked like it has the most statistical content is

I may be asked to produce a power calculation, and a good reference for this is:

You can find an earlier version of this page on my old website.