Following on from fMRI in 1000 words, which seemed to go down well, here’s the next step: how to analyze the data.
There are many software packages available for fMRI analysis, such as FSL, SPM, AFNI, and BrainVoyager. The following principles, however, apply to most. The first step is pre-processing, which involves:
Motion Correction – during the course of the experiment subjects often move their heads slightly; during realignment, all of the volumes are automatically adjusted to eliminate motion.
Smoothing – all MRI signals contain some degree of random noise. During smoothing, the image of the whole brain is blurred. This tends to smooth out random fluctuations. The degree of smoothing is given by the “Full Width to Half Maximum” (FWHM) of the smoother. Between 5 and 8 mm is most common.
Spatial Normalization – Everyone’s brain has a unique shape and size. In order to compare activations between two or more people, you need to eliminate these differences. Each subject’s brain is warped so that it fits with a standard template (the Montreal Neurological Institute or template is most popular.)
