Digital filter design for electrophysiological data – a practical approach

Filtering is a ubiquitous step in the preprocessing of electroencephalographic (EEG) and magnetoencephalographic (MEG) data. Besides the intended effect of the attenuation of signal components considered as noise, filtering can also result in various unintended adverse filter effects (distortions such as smoothing) and filter artifacts.We give some practical guidelines for the evaluation of filter responses (impulse and frequency response) and...