Motion correction algorithms of the brain mapping community create spurious functional activations

Abstract

This paper describes several experiments that prove that standard motion correction methods may induce spurious activations in some motion-free fMRI studies. This artefact stems from the fact that activated areas behave like biasing outliers for the least square based measure usually driving such registration methods. This effect is demonstrated first using a motion-free simulated time series including artificial activation-like signal changes. Several additional simulations explore the influence of activation on registration accuracy for a wide-range of simulated misregistrations. The effect is finally highlighted on an actual time series obtained from a 3T magnet. All the experiments are performed using four different realignment methods, which allows us to show that the problem is overcome by methods based on robust similarity measures like mutual information.