Action potential waveform variability limits multi-unit separation in freely behaving rats.
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 multiwire electrodes such as tetrodes. In this study we have tested the ability of single-wire electrodes t...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2012-01-01
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| Series: | PLoS ONE |
| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22719894/pdf/?tool=EBI |
| _version_ | 1818718861496680448 |
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| author | Peter Stratton Allen Cheung Janet Wiles Eugene Kiyatkin Pankaj Sah François Windels |
| author_facet | Peter Stratton Allen Cheung Janet Wiles Eugene Kiyatkin Pankaj Sah François Windels |
| author_sort | Peter Stratton |
| collection | DOAJ |
| description | 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 multiwire 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/ mm(3)). 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. |
| first_indexed | 2024-12-17T19:57:46Z |
| format | Article |
| id | doaj.art-7d8aca475d4749e6a3cbd33492b4e8e8 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-17T19:57:46Z |
| publishDate | 2012-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-7d8aca475d4749e6a3cbd33492b4e8e82022-12-21T21:34:33ZengPublic Library of Science (PLoS)PLoS ONE1932-62032012-01-0176e3848210.1371/journal.pone.0038482Action potential waveform variability limits multi-unit separation in freely behaving rats.Peter StrattonAllen CheungJanet WilesEugene KiyatkinPankaj SahFrançois WindelsExtracellular 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 multiwire 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/ mm(3)). 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.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22719894/pdf/?tool=EBI |
| spellingShingle | Peter Stratton Allen Cheung Janet Wiles Eugene Kiyatkin Pankaj Sah François Windels Action potential waveform variability limits multi-unit separation in freely behaving rats. PLoS ONE |
| title | Action potential waveform variability limits multi-unit separation in freely behaving rats. |
| title_full | Action potential waveform variability limits multi-unit separation in freely behaving rats. |
| title_fullStr | Action potential waveform variability limits multi-unit separation in freely behaving rats. |
| title_full_unstemmed | Action potential waveform variability limits multi-unit separation in freely behaving rats. |
| title_short | Action potential waveform variability limits multi-unit separation in freely behaving rats. |
| title_sort | action potential waveform variability limits multi unit separation in freely behaving rats |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22719894/pdf/?tool=EBI |
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