Voxel-based Morphometry

Voxel-based Morphometry

Voxel based morphometry (VBM) is a neuroimaging analysis technique that allows investigation of focal differences in brain anatomy, using the statistical approach of statistical parametric mapping. In traditional morphometry, volume of the whole brain or its subparts is measured by drawing regions of interest (ROIs) on images from brain scanning and calculating the volume enclosed. However, this is time consuming and can only provide measures of rather large areas. Smaller differences in volume may be overlooked. VBM registers every brain to a template, which gets rid of most of the large differences in brain anatomy among people. Then the brain images are smoothed so that each voxel represents the average of itself and its neighbors. Finally, the image volume is compared across brains at every voxel.

One of the first VBM studies and one that came to attention in main stream media was a study on the hippocampus brain structure of London taxicab drivers. The VBM analysis showed the back part of the posterior hippocampus was on average larger in the taxi drivers compared to control subjects while the anterior hippocampus was smaller. London taxi drivers need good spatial navigational skills and scientists have usually associated hippocampus with this particular skill.

Another famous VBM paper was a study on the effect of age on gray and white matter and CSF of 465 normal adults. The VBM analysis showed global gray matter was decreased linearly with age, especially for men, whereas global white matter did not decline with age.

A key description of the methodology of voxel-based morphometry is Voxel-Based Morphometry—The Methods — one of the most cited articles in the journal NeuroImage. The usual approach for statistical analysis is mass-univariate (analysis of each voxel separately), but pattern recognition may also be used, e.g., for classifying patients from healthy.