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Signal denoising through topographic modularity of neural circuits
Information from the sensory periphery is conveyed to the cortex via structured projection pathways that spatially segregate stimulus features, providing a robust and efficient encoding strategy. Beyond sensory encoding, this prominent anatomical feature extends throughout the neocortex. However, th...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9981157/ https://www.ncbi.nlm.nih.gov/pubmed/36700545 http://dx.doi.org/10.7554/eLife.77009 |
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author | Zajzon, Barna Dahmen, David Morrison, Abigail Duarte, Renato |
author_facet | Zajzon, Barna Dahmen, David Morrison, Abigail Duarte, Renato |
author_sort | Zajzon, Barna |
collection | PubMed |
description | Information from the sensory periphery is conveyed to the cortex via structured projection pathways that spatially segregate stimulus features, providing a robust and efficient encoding strategy. Beyond sensory encoding, this prominent anatomical feature extends throughout the neocortex. However, the extent to which it influences cortical processing is unclear. In this study, we combine cortical circuit modeling with network theory to demonstrate that the sharpness of topographic projections acts as a bifurcation parameter, controlling the macroscopic dynamics and representational precision across a modular network. By shifting the balance of excitation and inhibition, topographic modularity gradually increases task performance and improves the signal-to-noise ratio across the system. We demonstrate that in biologically constrained networks, such a denoising behavior is contingent on recurrent inhibition. We show that this is a robust and generic structural feature that enables a broad range of behaviorally relevant operating regimes, and provide an in-depth theoretical analysis unraveling the dynamical principles underlying the mechanism. |
format | Online Article Text |
id | pubmed-9981157 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-99811572023-03-03 Signal denoising through topographic modularity of neural circuits Zajzon, Barna Dahmen, David Morrison, Abigail Duarte, Renato eLife Neuroscience Information from the sensory periphery is conveyed to the cortex via structured projection pathways that spatially segregate stimulus features, providing a robust and efficient encoding strategy. Beyond sensory encoding, this prominent anatomical feature extends throughout the neocortex. However, the extent to which it influences cortical processing is unclear. In this study, we combine cortical circuit modeling with network theory to demonstrate that the sharpness of topographic projections acts as a bifurcation parameter, controlling the macroscopic dynamics and representational precision across a modular network. By shifting the balance of excitation and inhibition, topographic modularity gradually increases task performance and improves the signal-to-noise ratio across the system. We demonstrate that in biologically constrained networks, such a denoising behavior is contingent on recurrent inhibition. We show that this is a robust and generic structural feature that enables a broad range of behaviorally relevant operating regimes, and provide an in-depth theoretical analysis unraveling the dynamical principles underlying the mechanism. eLife Sciences Publications, Ltd 2023-01-26 /pmc/articles/PMC9981157/ /pubmed/36700545 http://dx.doi.org/10.7554/eLife.77009 Text en © 2023, Zajzon et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Neuroscience Zajzon, Barna Dahmen, David Morrison, Abigail Duarte, Renato Signal denoising through topographic modularity of neural circuits |
title | Signal denoising through topographic modularity of neural circuits |
title_full | Signal denoising through topographic modularity of neural circuits |
title_fullStr | Signal denoising through topographic modularity of neural circuits |
title_full_unstemmed | Signal denoising through topographic modularity of neural circuits |
title_short | Signal denoising through topographic modularity of neural circuits |
title_sort | signal denoising through topographic modularity of neural circuits |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9981157/ https://www.ncbi.nlm.nih.gov/pubmed/36700545 http://dx.doi.org/10.7554/eLife.77009 |
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