Action potential waveform variability limits multi-unit separation in freely behaving rats

Stratton, Peter, Cheung, Allen, Wiles, Janet H., Kiyatkin, E., Sah, Pankaj and Windels, Francois (2012) Action potential waveform variability limits multi-unit separation in freely behaving rats. PLoS One, 7 6: e38482.1-e38482.16.

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Author Stratton, Peter
Cheung, Allen
Wiles, Janet H.
Kiyatkin, E.
Sah, Pankaj
Windels, Francois
Title Action potential waveform variability limits multi-unit separation in freely behaving rats
Journal name PLoS One   Check publisher's open access policy
ISSN 1932-6203
Publication date 2012-06
Sub-type Article (original research)
DOI 10.1371/journal.pone.0038482
Volume 7
Issue 6
Start page e38482.1
End page e38482.16
Total pages 16
Place of publication San Francisco, CA, United States
Publisher Public Library of Science
Collection year 2013
Language eng
Formatted abstract Extracellular multi-unit recording is a widely used technique to study spontaneous and evoked neuronal activity in awake behaving animals. These recordings are done using either single-wire or mulitwire electrodes such as tetrodes. In this study we have tested the ability of single-wire electrodes to discriminate activity from multiple neurons under conditions of varying noise and neuronal cell density. Using extracellular single-unit recording, coupled with iontophoresis to drive cell activity across a wide dynamic range, we studied spike waveform variability, and explored systematic differences in single-unit spike waveform within and between brain regions as well as the influence of signal-to-noise ratio (SNR) on the similarity of spike waveforms. We also modelled spike misclassification for a range of cell densities based on neuronal recordings obtained at different SNRs. Modelling predictions were confirmed by classifying spike waveforms from multiple cells with various SNRs using a leading commercial spike-sorting system. Our results show that for single-wire recordings, multiple units can only be reliably distinguished under conditions of high recording SNR (≥4) and low neuronal density (≈20,000/ mm3). Physiological and behavioural changes, as well as technical limitations typical of awake animal preparations, reduce the accuracy of single-channel spike classification, resulting in serious classification errors. For SNR <4, the probability of misclassifying spikes approaches 100% in many cases. Our results suggest that in studies where the SNR is low or neuronal density is high, separation of distinct units needs to be evaluated with great caution.
Open Access Mandate Compliance Yes - Open Access (Publisher DOI)
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Article # e38482

 
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Created: Thu, 12 Jul 2012, 14:05:57 EST by Debra McMurtrie on behalf of Queensland Brain Institute