Application of non-linear filters based on the median filter to experimental and simulated multiunit neural recordings

Two non-linear, high-pass filters based on the median filter are proposed and tested as substitutes for linear filtering in applications involving multiunit neural recordings. The first, the median-based high-pass (MH) filter, operates by subtracting the output from the input of the median filter; it is aimed at preserving the shape of the impulses. The second, the negative median-based high-pass (NMH) filter, sets at zero the positive values in the output of the MH filter; it is aimed at transforming the impulses into monophasic waves placed on a flat baseline. When applied to experimental recordings and to a template action potential, the two median-based filters clearly outperformed two corresponding procedures based on a linear filter (moving-average filter). They did not produce appreciable distortions of the impulses, whereas their two counterparts induced or enlarged lateral lobes, as is the rule for linear high-pass filters. The recording display was much improved and impulse identification was made easier. When the two filters were applied to simulated recordings and the mean output was estimated by averaging and cross-correlation, a certain degree of performance deterioration was assessed in conditions of sustained activity and/or noise, with a resulting growing similarity to the mean output of the two corresponding, moving-average-based filters.