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A Python Code for Simulating Single Tactile Receptors and the Spiking Responses of Their Afferents

This work presents a pieces of Python code to rapidly simulate the spiking responses of large numbers of single cutaneous tactile afferents with millisecond precision. To simulate the spike responses of all the major types of cutaneous tactile afferents, we proposed an electromechanical circuit mode...

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Detalles Bibliográficos
Autores principales: Ouyang, Qiangqiang, Wu, Juan, Shao, Zhiyu, Wu, Miao, Cao, Zhiyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6478814/
https://www.ncbi.nlm.nih.gov/pubmed/31057386
http://dx.doi.org/10.3389/fninf.2019.00027
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author Ouyang, Qiangqiang
Wu, Juan
Shao, Zhiyu
Wu, Miao
Cao, Zhiyong
author_facet Ouyang, Qiangqiang
Wu, Juan
Shao, Zhiyu
Wu, Miao
Cao, Zhiyong
author_sort Ouyang, Qiangqiang
collection PubMed
description This work presents a pieces of Python code to rapidly simulate the spiking responses of large numbers of single cutaneous tactile afferents with millisecond precision. To simulate the spike responses of all the major types of cutaneous tactile afferents, we proposed an electromechanical circuit model, in which a two-channel filter was developed to characterize the mechanical selectivity of tactile receptors, and a spike synthesizer was designed to recreate the action potentials evoked in afferents. The parameters of this model were fitted using previous neurophysiological datasets. Several simulation examples were presented in this paper to reproduce action potentials, sensory adaptation, frequency characteristics and spiking timing for each afferent type. The results indicated that the simulated responses matched previous neurophysiological recordings well. The model allows for a real-time reproduction of the spiking responses of about 4,000 tactile units with a timing precision of <6 ms. The current work provides a valuable guidance to designing highly realistic tactile interfaces such as neuroprosthesis and haptic devices
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spelling pubmed-64788142019-05-03 A Python Code for Simulating Single Tactile Receptors and the Spiking Responses of Their Afferents Ouyang, Qiangqiang Wu, Juan Shao, Zhiyu Wu, Miao Cao, Zhiyong Front Neuroinform Neuroscience This work presents a pieces of Python code to rapidly simulate the spiking responses of large numbers of single cutaneous tactile afferents with millisecond precision. To simulate the spike responses of all the major types of cutaneous tactile afferents, we proposed an electromechanical circuit model, in which a two-channel filter was developed to characterize the mechanical selectivity of tactile receptors, and a spike synthesizer was designed to recreate the action potentials evoked in afferents. The parameters of this model were fitted using previous neurophysiological datasets. Several simulation examples were presented in this paper to reproduce action potentials, sensory adaptation, frequency characteristics and spiking timing for each afferent type. The results indicated that the simulated responses matched previous neurophysiological recordings well. The model allows for a real-time reproduction of the spiking responses of about 4,000 tactile units with a timing precision of <6 ms. The current work provides a valuable guidance to designing highly realistic tactile interfaces such as neuroprosthesis and haptic devices Frontiers Media S.A. 2019-04-17 /pmc/articles/PMC6478814/ /pubmed/31057386 http://dx.doi.org/10.3389/fninf.2019.00027 Text en Copyright © 2019 Ouyang, Wu, Shao, Wu and Cao. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Ouyang, Qiangqiang
Wu, Juan
Shao, Zhiyu
Wu, Miao
Cao, Zhiyong
A Python Code for Simulating Single Tactile Receptors and the Spiking Responses of Their Afferents
title A Python Code for Simulating Single Tactile Receptors and the Spiking Responses of Their Afferents
title_full A Python Code for Simulating Single Tactile Receptors and the Spiking Responses of Their Afferents
title_fullStr A Python Code for Simulating Single Tactile Receptors and the Spiking Responses of Their Afferents
title_full_unstemmed A Python Code for Simulating Single Tactile Receptors and the Spiking Responses of Their Afferents
title_short A Python Code for Simulating Single Tactile Receptors and the Spiking Responses of Their Afferents
title_sort python code for simulating single tactile receptors and the spiking responses of their afferents
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6478814/
https://www.ncbi.nlm.nih.gov/pubmed/31057386
http://dx.doi.org/10.3389/fninf.2019.00027
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