The impact of denoising on independent component analysis of functional magnetic resonance imaging data

► Preprocessing utility in ICA has not previously been demonstrated. ► We prove the strong necessity for preprocessing in preparation for ICA. ► Low-pass filtering parameters are needed to improve ICA. ► Simple Gaussian smoothing is as efficient than more complex denoising methods. ► Noise reduction seems to have the most effect on increasing component independence.