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Retinal ganglion cells undergo cell type—specific functional changes in a computational model of cone-mediated retinal degeneration

INTRODUCTION: Understanding the retina in health and disease is a key issue for neuroscience and neuroengineering applications such as retinal prostheses. During degeneration, the retinal network undergoes complex and multi-stage neuroanatomical alterations, which drastically impact the retinal gang...

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Autores principales: Xu, Aiwen, Beyeler, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10233015/
https://www.ncbi.nlm.nih.gov/pubmed/37274203
http://dx.doi.org/10.3389/fnins.2023.1147729
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author Xu, Aiwen
Beyeler, Michael
author_facet Xu, Aiwen
Beyeler, Michael
author_sort Xu, Aiwen
collection PubMed
description INTRODUCTION: Understanding the retina in health and disease is a key issue for neuroscience and neuroengineering applications such as retinal prostheses. During degeneration, the retinal network undergoes complex and multi-stage neuroanatomical alterations, which drastically impact the retinal ganglion cell (RGC) response and are of clinical importance. Here we present a biophysically detailed in silico model of the cone pathway in the retina that simulates the network-level response to both light and electrical stimulation. METHODS: The model included 11, 138 cells belonging to nine different cell types (cone photoreceptors, horizontal cells, ON/OFF bipolar cells, ON/OFF amacrine cells, and ON/OFF ganglion cells) confined to a 300 × 300 × 210μm patch of the parafoveal retina. After verifying that the model reproduced seminal findings about the light response of retinal ganglion cells (RGCs), we systematically introduced anatomical and neurophysiological changes (e.g., reduced light sensitivity of photoreceptor, cell death, cell migration) to the network and studied their effect on network activity. RESULTS: The model was not only able to reproduce common findings about RGC activity in the degenerated retina, such as hyperactivity and increased electrical thresholds, but also offers testable predictions about the underlying neuroanatomical mechanisms. DISCUSSION: Overall, our findings demonstrate how biophysical changes typified by cone-mediated retinal degeneration may impact retinal responses to light and electrical stimulation. These insights may further our understanding of retinal processing and inform the design of retinal prostheses.
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spelling pubmed-102330152023-06-02 Retinal ganglion cells undergo cell type—specific functional changes in a computational model of cone-mediated retinal degeneration Xu, Aiwen Beyeler, Michael Front Neurosci Neuroscience INTRODUCTION: Understanding the retina in health and disease is a key issue for neuroscience and neuroengineering applications such as retinal prostheses. During degeneration, the retinal network undergoes complex and multi-stage neuroanatomical alterations, which drastically impact the retinal ganglion cell (RGC) response and are of clinical importance. Here we present a biophysically detailed in silico model of the cone pathway in the retina that simulates the network-level response to both light and electrical stimulation. METHODS: The model included 11, 138 cells belonging to nine different cell types (cone photoreceptors, horizontal cells, ON/OFF bipolar cells, ON/OFF amacrine cells, and ON/OFF ganglion cells) confined to a 300 × 300 × 210μm patch of the parafoveal retina. After verifying that the model reproduced seminal findings about the light response of retinal ganglion cells (RGCs), we systematically introduced anatomical and neurophysiological changes (e.g., reduced light sensitivity of photoreceptor, cell death, cell migration) to the network and studied their effect on network activity. RESULTS: The model was not only able to reproduce common findings about RGC activity in the degenerated retina, such as hyperactivity and increased electrical thresholds, but also offers testable predictions about the underlying neuroanatomical mechanisms. DISCUSSION: Overall, our findings demonstrate how biophysical changes typified by cone-mediated retinal degeneration may impact retinal responses to light and electrical stimulation. These insights may further our understanding of retinal processing and inform the design of retinal prostheses. Frontiers Media S.A. 2023-05-18 /pmc/articles/PMC10233015/ /pubmed/37274203 http://dx.doi.org/10.3389/fnins.2023.1147729 Text en Copyright © 2023 Xu and Beyeler. https://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
Xu, Aiwen
Beyeler, Michael
Retinal ganglion cells undergo cell type—specific functional changes in a computational model of cone-mediated retinal degeneration
title Retinal ganglion cells undergo cell type—specific functional changes in a computational model of cone-mediated retinal degeneration
title_full Retinal ganglion cells undergo cell type—specific functional changes in a computational model of cone-mediated retinal degeneration
title_fullStr Retinal ganglion cells undergo cell type—specific functional changes in a computational model of cone-mediated retinal degeneration
title_full_unstemmed Retinal ganglion cells undergo cell type—specific functional changes in a computational model of cone-mediated retinal degeneration
title_short Retinal ganglion cells undergo cell type—specific functional changes in a computational model of cone-mediated retinal degeneration
title_sort retinal ganglion cells undergo cell type—specific functional changes in a computational model of cone-mediated retinal degeneration
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10233015/
https://www.ncbi.nlm.nih.gov/pubmed/37274203
http://dx.doi.org/10.3389/fnins.2023.1147729
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