Sliding window approach for analyzing fMRI time-series

Approach reported in this paper uses a sliding (rectangular) window on the original fMRI scans to produce the new scans. By selecting parameters of sliding windows, autocorrelation function (acf) among new scans can be reduced to a predicted level, and fMRI analysis will be performed on these new scans. Theoretical analysis showed that this level is 1/k (k is the window size). Simulations by using different window structures verified this conclusion and the graphic illustation provides an intuitive explanation.