Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4336327 | Journal of Neuroscience Methods | 2008 | 7 Pages |
Abstract
The isolation of single units in extracellular recordings involves filtering. Removing lower frequencies allows a constant threshold to be applied in order to identify and extract action potential events. However, standard methods such as Butterworth bandpass filtering perform this frequency excision at a cost of grossly distorting waveform shapes. Here, we apply wavelet decomposition and reconstruction as a filter for electrophysiology data and demonstrate its ability to better preserve spike shape. For the majority of cells, this approach also improves spike signal-to-noise ratio (SNR) and increases cluster discrimination. Additionally, the described technique is fast enough to be applied real-time.
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Authors
Alexander B. Wiltschko, Gregory J. Gage, Joshua D. Berke,