Cargando…
Small Size of Recorded Neuronal Structures Confines the Accuracy in Direct Axonal Voltage Measurements
Patch-clamp instruments including amplifier circuits and pipettes affect the recorded voltage signals. We hypothesized that realistic and complete in silico representation of recording instruments together with detailed morphology and biophysics of small recorded structures will reveal signal distor...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Society for Neuroscience
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8342265/ https://www.ncbi.nlm.nih.gov/pubmed/34257077 http://dx.doi.org/10.1523/ENEURO.0059-21.2021 |
_version_ | 1783734034787991552 |
---|---|
author | Oláh, Viktor János Tarcsay, Gergely Brunner, János |
author_facet | Oláh, Viktor János Tarcsay, Gergely Brunner, János |
author_sort | Oláh, Viktor János |
collection | PubMed |
description | Patch-clamp instruments including amplifier circuits and pipettes affect the recorded voltage signals. We hypothesized that realistic and complete in silico representation of recording instruments together with detailed morphology and biophysics of small recorded structures will reveal signal distortions and provide a tool that predicts native, instrument-free electrical signals from distorted voltage recordings. Therefore, we built a model that was verified by small axonal recordings. The model accurately recreated actual action potential (AP) measurements with typical recording artefacts and predicted the native electrical behavior. The simulations verified that recording instruments substantially filter voltage recordings. Moreover, we revealed that instrumentation directly interferes with local signal generation depending on the size of the recorded structures, which complicates the interpretation of recordings from smaller structures, such as axons. However, our model offers a straightforward approach that predicts the native waveforms of fast voltage signals and the underlying conductances even from the smallest neuronal structures. |
format | Online Article Text |
id | pubmed-8342265 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Society for Neuroscience |
record_format | MEDLINE/PubMed |
spelling | pubmed-83422652021-08-06 Small Size of Recorded Neuronal Structures Confines the Accuracy in Direct Axonal Voltage Measurements Oláh, Viktor János Tarcsay, Gergely Brunner, János eNeuro Research Article: New Research Patch-clamp instruments including amplifier circuits and pipettes affect the recorded voltage signals. We hypothesized that realistic and complete in silico representation of recording instruments together with detailed morphology and biophysics of small recorded structures will reveal signal distortions and provide a tool that predicts native, instrument-free electrical signals from distorted voltage recordings. Therefore, we built a model that was verified by small axonal recordings. The model accurately recreated actual action potential (AP) measurements with typical recording artefacts and predicted the native electrical behavior. The simulations verified that recording instruments substantially filter voltage recordings. Moreover, we revealed that instrumentation directly interferes with local signal generation depending on the size of the recorded structures, which complicates the interpretation of recordings from smaller structures, such as axons. However, our model offers a straightforward approach that predicts the native waveforms of fast voltage signals and the underlying conductances even from the smallest neuronal structures. Society for Neuroscience 2021-08-02 /pmc/articles/PMC8342265/ /pubmed/34257077 http://dx.doi.org/10.1523/ENEURO.0059-21.2021 Text en Copyright © 2021 Oláh et al. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed. |
spellingShingle | Research Article: New Research Oláh, Viktor János Tarcsay, Gergely Brunner, János Small Size of Recorded Neuronal Structures Confines the Accuracy in Direct Axonal Voltage Measurements |
title | Small Size of Recorded Neuronal Structures Confines the Accuracy in Direct Axonal Voltage Measurements |
title_full | Small Size of Recorded Neuronal Structures Confines the Accuracy in Direct Axonal Voltage Measurements |
title_fullStr | Small Size of Recorded Neuronal Structures Confines the Accuracy in Direct Axonal Voltage Measurements |
title_full_unstemmed | Small Size of Recorded Neuronal Structures Confines the Accuracy in Direct Axonal Voltage Measurements |
title_short | Small Size of Recorded Neuronal Structures Confines the Accuracy in Direct Axonal Voltage Measurements |
title_sort | small size of recorded neuronal structures confines the accuracy in direct axonal voltage measurements |
topic | Research Article: New Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8342265/ https://www.ncbi.nlm.nih.gov/pubmed/34257077 http://dx.doi.org/10.1523/ENEURO.0059-21.2021 |
work_keys_str_mv | AT olahviktorjanos smallsizeofrecordedneuronalstructuresconfinestheaccuracyindirectaxonalvoltagemeasurements AT tarcsaygergely smallsizeofrecordedneuronalstructuresconfinestheaccuracyindirectaxonalvoltagemeasurements AT brunnerjanos smallsizeofrecordedneuronalstructuresconfinestheaccuracyindirectaxonalvoltagemeasurements |