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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 illustration provides an intuitive explanation.