Power line artifacts are the bane of animal and human electrophysiology. A number of methods are available to help attenuate or eliminate them, but each has its own set of drawbacks. In this brief note I present a simple method that combines the advantages of spectral and spatial filtering, while minimizing their downsides. A perfect-reconstruction filterbank is used to split the data into two parts, one noise-free and the other contaminated by line artifact. The artifact-contaminated stream is processed by a spatial filter to project out line components, and added to the noise-free part to obtain clean data. This method is applicable to multichannel data such as electroencephalography (EEG), magnetoencephalography (MEG), or multichannel local field potentials (LFP). I briefly review past methods, pointing out their drawbacks, describe the new method, and evaluate the outcome using synthetic and real data.
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Alain de Cheveigné (2019) studied this question.
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