Literature DB >> 18597853

Wavelet filtering before spike detection preserves waveform shape and enhances single-unit discrimination.

Alexander B Wiltschko1, Gregory J Gage, Joshua D Berke.   

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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Year:  2008        PMID: 18597853      PMCID: PMC2602872          DOI: 10.1016/j.jneumeth.2008.05.016

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  15 in total

1.  Spike sorting based on discrete wavelet transform coefficients.

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Journal:  J Neurosci Methods       Date:  2000-09-15       Impact factor: 2.390

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3.  Unsupervised spike detection and sorting with wavelets and superparamagnetic clustering.

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  30 in total

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9.  Local dynamics of gap-junction-coupled interneuron networks.

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10.  Fast oscillations in cortical-striatal networks switch frequency following rewarding events and stimulant drugs.

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Journal:  Eur J Neurosci       Date:  2009-07-31       Impact factor: 3.386

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