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Synapse fits neuron: joint reduction by model inversion
In this paper, we introduce a novel simplification method for dealing with physical systems that can be thought to consist of two subsystems connected in series, such as a neuron and a synapse. The aim of our method is to help find a simple, yet convincing model of the full cascade-connected system,...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5506247/ https://www.ncbi.nlm.nih.gov/pubmed/28689352 http://dx.doi.org/10.1007/s00422-017-0722-1 |
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author | van der Scheer, H. T. Doelman, A. |
author_facet | van der Scheer, H. T. Doelman, A. |
author_sort | van der Scheer, H. T. |
collection | PubMed |
description | In this paper, we introduce a novel simplification method for dealing with physical systems that can be thought to consist of two subsystems connected in series, such as a neuron and a synapse. The aim of our method is to help find a simple, yet convincing model of the full cascade-connected system, assuming that a satisfactory model of one of the subsystems, e.g., the neuron, is already given. Our method allows us to validate a candidate model of the full cascade against data at a finer scale. In our main example, we apply our method to part of the squid’s giant fiber system. We first postulate a simple, hypothetical model of cell-to-cell signaling based on the squid’s escape response. Then, given a FitzHugh-type neuron model, we derive the verifiable model of the squid giant synapse that this hypothesis implies. We show that the derived synapse model accurately reproduces synaptic recordings, hence lending support to the postulated, simple model of cell-to-cell signaling, which thus, in turn, can be used as a basic building block for network models. |
format | Online Article Text |
id | pubmed-5506247 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-55062472017-07-27 Synapse fits neuron: joint reduction by model inversion van der Scheer, H. T. Doelman, A. Biol Cybern Original Article In this paper, we introduce a novel simplification method for dealing with physical systems that can be thought to consist of two subsystems connected in series, such as a neuron and a synapse. The aim of our method is to help find a simple, yet convincing model of the full cascade-connected system, assuming that a satisfactory model of one of the subsystems, e.g., the neuron, is already given. Our method allows us to validate a candidate model of the full cascade against data at a finer scale. In our main example, we apply our method to part of the squid’s giant fiber system. We first postulate a simple, hypothetical model of cell-to-cell signaling based on the squid’s escape response. Then, given a FitzHugh-type neuron model, we derive the verifiable model of the squid giant synapse that this hypothesis implies. We show that the derived synapse model accurately reproduces synaptic recordings, hence lending support to the postulated, simple model of cell-to-cell signaling, which thus, in turn, can be used as a basic building block for network models. Springer Berlin Heidelberg 2017-07-08 2017 /pmc/articles/PMC5506247/ /pubmed/28689352 http://dx.doi.org/10.1007/s00422-017-0722-1 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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. |
spellingShingle | Original Article van der Scheer, H. T. Doelman, A. Synapse fits neuron: joint reduction by model inversion |
title | Synapse fits neuron: joint reduction by model inversion |
title_full | Synapse fits neuron: joint reduction by model inversion |
title_fullStr | Synapse fits neuron: joint reduction by model inversion |
title_full_unstemmed | Synapse fits neuron: joint reduction by model inversion |
title_short | Synapse fits neuron: joint reduction by model inversion |
title_sort | synapse fits neuron: joint reduction by model inversion |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5506247/ https://www.ncbi.nlm.nih.gov/pubmed/28689352 http://dx.doi.org/10.1007/s00422-017-0722-1 |
work_keys_str_mv | AT vanderscheerht synapsefitsneuronjointreductionbymodelinversion AT doelmana synapsefitsneuronjointreductionbymodelinversion |