Cargando…
Classification of naturally evoked compound action potentials in peripheral nerve spatiotemporal recordings
Peripheral neural signals have the potential to provide the necessary motor, sensory or autonomic information for robust control in many neuroprosthetic and neuromodulation applications. However, developing methods to recover information encoded in these signals is a significant challenge. We introd...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6668407/ https://www.ncbi.nlm.nih.gov/pubmed/31366940 http://dx.doi.org/10.1038/s41598-019-47450-8 |
_version_ | 1783440209441980416 |
---|---|
author | Koh, Ryan G. L. Nachman, Adrian I. Zariffa, José |
author_facet | Koh, Ryan G. L. Nachman, Adrian I. Zariffa, José |
author_sort | Koh, Ryan G. L. |
collection | PubMed |
description | Peripheral neural signals have the potential to provide the necessary motor, sensory or autonomic information for robust control in many neuroprosthetic and neuromodulation applications. However, developing methods to recover information encoded in these signals is a significant challenge. We introduce the idea of using spatiotemporal signatures extracted from multi-contact nerve cuff electrode recordings to classify naturally evoked compound action potentials (CAP). 9 Long-Evan rats were implanted with a 56-channel nerve cuff on the sciatic nerve. Afferent activity was selectively evoked in the different fascicles of the sciatic nerve (tibial, peroneal, sural) using mechano-sensory stimuli. Spatiotemporal signatures of recorded CAPs were used to train three different classifiers. Performance was measured based on the classification accuracy, F(1)-score, and the ability to reconstruct original firing rates of neural pathways. The mean classification accuracies, for a 3-class problem, for the best performing classifier was 0.686 ± 0.126 and corresponding mean F(1)-score was 0.605 ± 0.212. The mean Pearson correlation coefficients between the original firing rates and estimated firing rates found for the best classifier was 0.728 ± 0.276. The proposed method demonstrates the possibility of classifying individual naturally evoked CAPs in peripheral neural signals recorded from extraneural electrodes, allowing for more precise control signals in neuroprosthetic applications. |
format | Online Article Text |
id | pubmed-6668407 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-66684072019-08-06 Classification of naturally evoked compound action potentials in peripheral nerve spatiotemporal recordings Koh, Ryan G. L. Nachman, Adrian I. Zariffa, José Sci Rep Article Peripheral neural signals have the potential to provide the necessary motor, sensory or autonomic information for robust control in many neuroprosthetic and neuromodulation applications. However, developing methods to recover information encoded in these signals is a significant challenge. We introduce the idea of using spatiotemporal signatures extracted from multi-contact nerve cuff electrode recordings to classify naturally evoked compound action potentials (CAP). 9 Long-Evan rats were implanted with a 56-channel nerve cuff on the sciatic nerve. Afferent activity was selectively evoked in the different fascicles of the sciatic nerve (tibial, peroneal, sural) using mechano-sensory stimuli. Spatiotemporal signatures of recorded CAPs were used to train three different classifiers. Performance was measured based on the classification accuracy, F(1)-score, and the ability to reconstruct original firing rates of neural pathways. The mean classification accuracies, for a 3-class problem, for the best performing classifier was 0.686 ± 0.126 and corresponding mean F(1)-score was 0.605 ± 0.212. The mean Pearson correlation coefficients between the original firing rates and estimated firing rates found for the best classifier was 0.728 ± 0.276. The proposed method demonstrates the possibility of classifying individual naturally evoked CAPs in peripheral neural signals recorded from extraneural electrodes, allowing for more precise control signals in neuroprosthetic applications. Nature Publishing Group UK 2019-07-31 /pmc/articles/PMC6668407/ /pubmed/31366940 http://dx.doi.org/10.1038/s41598-019-47450-8 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Koh, Ryan G. L. Nachman, Adrian I. Zariffa, José Classification of naturally evoked compound action potentials in peripheral nerve spatiotemporal recordings |
title | Classification of naturally evoked compound action potentials in peripheral nerve spatiotemporal recordings |
title_full | Classification of naturally evoked compound action potentials in peripheral nerve spatiotemporal recordings |
title_fullStr | Classification of naturally evoked compound action potentials in peripheral nerve spatiotemporal recordings |
title_full_unstemmed | Classification of naturally evoked compound action potentials in peripheral nerve spatiotemporal recordings |
title_short | Classification of naturally evoked compound action potentials in peripheral nerve spatiotemporal recordings |
title_sort | classification of naturally evoked compound action potentials in peripheral nerve spatiotemporal recordings |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6668407/ https://www.ncbi.nlm.nih.gov/pubmed/31366940 http://dx.doi.org/10.1038/s41598-019-47450-8 |
work_keys_str_mv | AT kohryangl classificationofnaturallyevokedcompoundactionpotentialsinperipheralnervespatiotemporalrecordings AT nachmanadriani classificationofnaturallyevokedcompoundactionpotentialsinperipheralnervespatiotemporalrecordings AT zariffajose classificationofnaturallyevokedcompoundactionpotentialsinperipheralnervespatiotemporalrecordings |