Common resting state fRMI preprocessing steps are done in the Fourier domain, in particular temporal filtering. These can introduce temporal artifacts that can be exaggerated by using data time-series that are not power of 2 in length. We show that using non-power of 2 data can affect the shape of the temporal filter being applied and can increase unwanted correlations from aliased physiologic noise for example and introduce increased autocorrelations in the data.
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