Data from: Choosing wavelet methods, filters, and lengths for functional brain network construction

Zitong Zhang, Qawi K. Telesford, Chad Giusti, Kelvin O. Lim & Danielle S. Bassett
Wavelet methods are widely used to decompose fMRI, EEG, or MEG signals into time series representing neurophysiological activity in fixed frequency bands. Using these time series, one can estimate frequency-band specific functional connectivity between sensors or regions of interest, and thereby construct functional brain networks that can be examined from a graph theoretic perspective. Despite their common use, however, practical guidelines for the choice of wavelet method, filter, and length have remained largely undelineated. Here,...
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