Detecting cortical activations from fMRI data using a recursive STAP algorithm

Space-time adaptive processing (STAP), previously developed in the field of sensor array processing and applied to radar signal processing, has already been shown to exhibit potential when applied on a small scale to multidimensional functional magnetic resonance imaging (fMRI) data. In this study, a recursive version of the STAP algorithm, the method of steepest descent, is introduced for application to fMRI data. It is believed to be more suitable for adaptation to larger data sets than is the previous STAP implementation using matrix inversion. Computer simulations incorporating actual MRI noise indicate that it exhibits an improvement over the previous matrix inversion method in detecting activations.