In this project, we have studied resting-state networks using Empirical Mode Decomposition (EMD) to obtain energy-period information and compared results with the Maximal Overlap Discrete Wavelet Transform (MODWT) and the Short-Time Fourier Transform (STFT). We chose the STFT and MODWT for comparison with EMD, because the STFT is based on Fourier basis functions, the MODWT allows more adaptivity but still is model-based by wavelet functions, and EMD is model-free, adaptive and entirely data-driven. EMD showed the strongest relationship to frequency and energy content for different clusters of resting-state networks.
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