is classic in terms of statistics, as opposed to more recent methods based on the Bayesian inference which provides the posterior probability that the voxel is activated given the data [112]. All of these methods discussed so far are model-driven in a sense that they require specific assumptions about the time courses of the processes contributing to the measured signals and/or a priori statistical distributions of the signal and the noise. To remove such model dependence, a data-driven method has been implemented using independent component analysis (ICA) [113, 114].
