Journal
JOURNAL OF NEUROSCIENCE METHODS
Volume 164, Issue 1, Pages 1-18Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jneumeth.2007.03.025
Keywords
spike sorting; template matching; overlapping spikes; multi-electrode arrays; electrophysiology
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Funding
- NINDS NIH HHS [R01 NS025074, R37 NS025074-19, R37 NS025074] Funding Source: Medline
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In multiple cell recordings identifying the number of neurons and assigning each action potential to a particular source, commonly referred to as 'spike sorting', is a highly non-trivial problem. Density grid contour clustering provides a computationally efficient way of locating high-density regions of arbitrary shape in low-dimensional space. When applied to waveforms projected onto their first two principal components, the algorithm allows the extraction of templates that provide high-dimensional reference points that can be used to perform accurate spike sorting. Template matching using subtractive waveform decomposition can locate these templates in waveform samples despite the influence of noise, spurious threshold crossing and waveform overlap. Tests with a large synthetic dataset incorporating realistic challenges faced during spike sorting (including overlapping and phase-shifted spikes) reveal that this strategy can consistently yield results with less than 6% false positives and false negatives (and less than 2% for high signal-to-noise ratios) at processing speeds exceeding those previously reported for similar algorithms by more than an order of magnitude. (C) 2007 Elsevier B.V. All rights reserved.
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