Test-retest reliability estimation of functional MRI data.

Abstract

Functional magnetic resonance imaging (fMRI) data are commonly used to construct activation maps for the human brain. It is important to quantify the reliability of such maps. We have developed statistical models to provide precise estimates for reliability from several runs of the same paradigm over time. Specifically, our method extends the premise of maximum likelihood (ML) developed by Genovese et al. (Magn Reson Med 1997;38:497-507) by incorporating spatial context into the estimation process. Experiments indicate that our methodology provides more conservative estimates of true positives compared to those obtained by Genovese et al. The reliability estimates can be used to obtain voxel-specific reliability measures for activated as well as inactivated regions in future experiments. We derive statistical methodology to determine optimal thresholds for region- and context-specific activations. Empirical guidelines are also provided on the number of repeat scans to acquire in order to arrive at accurate reliability estimates. We report the results from experiments involving a motor paradigm performed on a single subject several times over a period of 2 months.