We have introduced a new method to determine the optimal time-dependent window-size for calculating sliding-window correlations between two non-stationary time series. The time-dependent window-size is calculated from the local information of intrinsic mode functions of each time series computed using empirical mode decomposition. Results from simulation demonstrate that the running-correlation computed with a time-dependent window-size is able to capture local transients without creating unstable fluctuations. By incorporating the optimal window-size in a whole-brain dynamic functional connectivity analysis, we are able to view differences in whole-brain temporal dynamics between normal control subjects and PD subjects more precisely.
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