We demonstrate how to apply pilab linear discriminant contrast methods to a real fMRI dataset, including searchlight mapping over the full volume.

We estimate multivariate discriminability with linear discriminant contrast (also known as cross-validated Mahalanobis distance, crossnobis).

We simulate a basic fMRI dataset, and estimate cross-validated prediction performance for a convolved design.