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An iterative deconvolution model to extract the temporal firing properties of the auditory nerve fibers in human eCAPs

The electrically evoked compound action potential (eCAP) has been widely studied for its clinical value for the evaluation of the surviving auditory nerve (AN) cells. However, many unknowns remain about the temporal firing properties of the AN fibers that underlie the eCAP in CI recipients. These te...

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Autores principales: Dong, Yu, Stronks, H. Christiaan, Briaire, Jeroen J., Frijns, Johan H.M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8374234/
https://www.ncbi.nlm.nih.gov/pubmed/34434763
http://dx.doi.org/10.1016/j.mex.2021.101240
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author Dong, Yu
Stronks, H. Christiaan
Briaire, Jeroen J.
Frijns, Johan H.M.
author_facet Dong, Yu
Stronks, H. Christiaan
Briaire, Jeroen J.
Frijns, Johan H.M.
author_sort Dong, Yu
collection PubMed
description The electrically evoked compound action potential (eCAP) has been widely studied for its clinical value for the evaluation of the surviving auditory nerve (AN) cells. However, many unknowns remain about the temporal firing properties of the AN fibers that underlie the eCAP in CI recipients. These temporal properties may contain valuable information about the condition of the AN. Here, we propose an iterative deconvolution model for estimating the human evoked unitary response (UR) and for extracting the compound discharge latency distribution (CDLD) from eCAP recordings, under the assumption that all AN fibers have the same UR. In this model, an eCAP is modeled by convolving a parameterized UR and a parameterized CDLD model. Both the UR and CDLD are optimized with an iterative deconvolution fitting error minimization routine to minimize the error between the modeled eCAP and the recorded eCAP. • This method first estimates the human UR from eCAP recordings. The human eCAP is unknown at the time of this writing. The UR is subsequently used to extract the underlying temporal neural excitation pattern (the CDLD) that reflects the contributions from individual AN fibers in human eCAPs. • By calculating the CDLD, the synchronicity of AN fibers can be evaluated.
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spelling pubmed-83742342021-08-24 An iterative deconvolution model to extract the temporal firing properties of the auditory nerve fibers in human eCAPs Dong, Yu Stronks, H. Christiaan Briaire, Jeroen J. Frijns, Johan H.M. MethodsX Method Article The electrically evoked compound action potential (eCAP) has been widely studied for its clinical value for the evaluation of the surviving auditory nerve (AN) cells. However, many unknowns remain about the temporal firing properties of the AN fibers that underlie the eCAP in CI recipients. These temporal properties may contain valuable information about the condition of the AN. Here, we propose an iterative deconvolution model for estimating the human evoked unitary response (UR) and for extracting the compound discharge latency distribution (CDLD) from eCAP recordings, under the assumption that all AN fibers have the same UR. In this model, an eCAP is modeled by convolving a parameterized UR and a parameterized CDLD model. Both the UR and CDLD are optimized with an iterative deconvolution fitting error minimization routine to minimize the error between the modeled eCAP and the recorded eCAP. • This method first estimates the human UR from eCAP recordings. The human eCAP is unknown at the time of this writing. The UR is subsequently used to extract the underlying temporal neural excitation pattern (the CDLD) that reflects the contributions from individual AN fibers in human eCAPs. • By calculating the CDLD, the synchronicity of AN fibers can be evaluated. Elsevier 2021-01-22 /pmc/articles/PMC8374234/ /pubmed/34434763 http://dx.doi.org/10.1016/j.mex.2021.101240 Text en © 2021 The Author(s). Published by Elsevier B.V. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Method Article
Dong, Yu
Stronks, H. Christiaan
Briaire, Jeroen J.
Frijns, Johan H.M.
An iterative deconvolution model to extract the temporal firing properties of the auditory nerve fibers in human eCAPs
title An iterative deconvolution model to extract the temporal firing properties of the auditory nerve fibers in human eCAPs
title_full An iterative deconvolution model to extract the temporal firing properties of the auditory nerve fibers in human eCAPs
title_fullStr An iterative deconvolution model to extract the temporal firing properties of the auditory nerve fibers in human eCAPs
title_full_unstemmed An iterative deconvolution model to extract the temporal firing properties of the auditory nerve fibers in human eCAPs
title_short An iterative deconvolution model to extract the temporal firing properties of the auditory nerve fibers in human eCAPs
title_sort iterative deconvolution model to extract the temporal firing properties of the auditory nerve fibers in human ecaps
topic Method Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8374234/
https://www.ncbi.nlm.nih.gov/pubmed/34434763
http://dx.doi.org/10.1016/j.mex.2021.101240
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