Duplicate Detection of Spike Events: A Relevant Problem in Human Single-Unit Recordings
Single-unit recordings in the brain of behaving human subjects provide a unique opportunity to advance our understanding of neural mechanisms of cognition. These recordings are exclusively performed in medical centers during diagnostic or therapeutic procedures. The presence of medical instruments a...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-06-01
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| Series: | Brain Sciences |
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| Online Access: | https://www.mdpi.com/2076-3425/11/6/761 |
| _version_ | 1797530976786579456 |
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| author | Gert Dehnen Marcel S. Kehl Alana Darcher Tamara T. Müller Jakob H. Macke Valeri Borger Rainer Surges Florian Mormann |
| author_facet | Gert Dehnen Marcel S. Kehl Alana Darcher Tamara T. Müller Jakob H. Macke Valeri Borger Rainer Surges Florian Mormann |
| author_sort | Gert Dehnen |
| collection | DOAJ |
| description | Single-unit recordings in the brain of behaving human subjects provide a unique opportunity to advance our understanding of neural mechanisms of cognition. These recordings are exclusively performed in medical centers during diagnostic or therapeutic procedures. The presence of medical instruments along with other aspects of the hospital environment limit the control of electrical noise compared to animal laboratory environments. Here, we highlight the problem of an increased occurrence of simultaneous spike events on different recording channels in human single-unit recordings. Most of these simultaneous events were detected in clusters previously labeled as artifacts and showed similar waveforms. These events may result from common external noise sources or from different micro-electrodes recording activity from the same neuron. To address the problem of duplicate recorded events, we introduce an open-source algorithm to identify these artificial spike events based on their synchronicity and waveform similarity. Applying our method to a comprehensive dataset of human single-unit recordings, we demonstrate that our algorithm can substantially increase the data quality of these recordings. Given our findings, we argue that future studies of single-unit activity recorded under noisy conditions should employ algorithms of this kind to improve data quality. |
| first_indexed | 2024-03-10T10:37:34Z |
| format | Article |
| id | doaj.art-e0557bf648ac48ddbf13bda65518ae4f |
| institution | Directory Open Access Journal |
| issn | 2076-3425 |
| language | English |
| last_indexed | 2024-03-10T10:37:34Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Brain Sciences |
| spelling | doaj.art-e0557bf648ac48ddbf13bda65518ae4f2023-11-21T23:13:29ZengMDPI AGBrain Sciences2076-34252021-06-0111676110.3390/brainsci11060761Duplicate Detection of Spike Events: A Relevant Problem in Human Single-Unit RecordingsGert Dehnen0Marcel S. Kehl1Alana Darcher2Tamara T. Müller3Jakob H. Macke4Valeri Borger5Rainer Surges6Florian Mormann7Department of Epileptology, University of Bonn Medical Center, Venusberg-Campus 1, 53127 Bonn, GermanyDepartment of Epileptology, University of Bonn Medical Center, Venusberg-Campus 1, 53127 Bonn, GermanyDepartment of Epileptology, University of Bonn Medical Center, Venusberg-Campus 1, 53127 Bonn, GermanyComputational Neuroengineering, Department of Electrical and Computerengineering, TU Munich, 80333 Munich, GermanyComputational Neuroengineering, Department of Electrical and Computerengineering, TU Munich, 80333 Munich, GermanyDepartment of Neurosurgery, University of Bonn Medical Center, Venusberg-Campus 1, 53127 Bonn, GermanyDepartment of Epileptology, University of Bonn Medical Center, Venusberg-Campus 1, 53127 Bonn, GermanyDepartment of Epileptology, University of Bonn Medical Center, Venusberg-Campus 1, 53127 Bonn, GermanySingle-unit recordings in the brain of behaving human subjects provide a unique opportunity to advance our understanding of neural mechanisms of cognition. These recordings are exclusively performed in medical centers during diagnostic or therapeutic procedures. The presence of medical instruments along with other aspects of the hospital environment limit the control of electrical noise compared to animal laboratory environments. Here, we highlight the problem of an increased occurrence of simultaneous spike events on different recording channels in human single-unit recordings. Most of these simultaneous events were detected in clusters previously labeled as artifacts and showed similar waveforms. These events may result from common external noise sources or from different micro-electrodes recording activity from the same neuron. To address the problem of duplicate recorded events, we introduce an open-source algorithm to identify these artificial spike events based on their synchronicity and waveform similarity. Applying our method to a comprehensive dataset of human single-unit recordings, we demonstrate that our algorithm can substantially increase the data quality of these recordings. Given our findings, we argue that future studies of single-unit activity recorded under noisy conditions should employ algorithms of this kind to improve data quality.https://www.mdpi.com/2076-3425/11/6/761human single-unit recordingsartifact removalspike sorting |
| spellingShingle | Gert Dehnen Marcel S. Kehl Alana Darcher Tamara T. Müller Jakob H. Macke Valeri Borger Rainer Surges Florian Mormann Duplicate Detection of Spike Events: A Relevant Problem in Human Single-Unit Recordings Brain Sciences human single-unit recordings artifact removal spike sorting |
| title | Duplicate Detection of Spike Events: A Relevant Problem in Human Single-Unit Recordings |
| title_full | Duplicate Detection of Spike Events: A Relevant Problem in Human Single-Unit Recordings |
| title_fullStr | Duplicate Detection of Spike Events: A Relevant Problem in Human Single-Unit Recordings |
| title_full_unstemmed | Duplicate Detection of Spike Events: A Relevant Problem in Human Single-Unit Recordings |
| title_short | Duplicate Detection of Spike Events: A Relevant Problem in Human Single-Unit Recordings |
| title_sort | duplicate detection of spike events a relevant problem in human single unit recordings |
| topic | human single-unit recordings artifact removal spike sorting |
| url | https://www.mdpi.com/2076-3425/11/6/761 |
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