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Excitation-Inhibition Balanced Neural Networks for Fast Signal Detection
Excitation-inhibition (E-I) balanced neural networks are a classic model for modeling neural activities and functions in the cortex. The present study investigates the potential application of E-I balanced neural networks for fast signal detection in brain-inspired computation. We first theoreticall...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7497310/ https://www.ncbi.nlm.nih.gov/pubmed/33013343 http://dx.doi.org/10.3389/fncom.2020.00079 |
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author | Tian, Gengshuo Li, Shangyang Huang, Tiejun Wu, Si |
author_facet | Tian, Gengshuo Li, Shangyang Huang, Tiejun Wu, Si |
author_sort | Tian, Gengshuo |
collection | PubMed |
description | Excitation-inhibition (E-I) balanced neural networks are a classic model for modeling neural activities and functions in the cortex. The present study investigates the potential application of E-I balanced neural networks for fast signal detection in brain-inspired computation. We first theoretically analyze the response property of an E-I balanced network, and find that the asynchronous firing state of the network generates an optimal noise structure enabling the network to track input changes rapidly. We then extend the homogeneous connectivity of an E-I balanced neural network to include local neuronal connections, so that the network can still achieve fast response and meanwhile maintain spatial information in the face of spatially heterogeneous signal. Finally, we carry out simulations to demonstrate that our model works well. |
format | Online Article Text |
id | pubmed-7497310 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-74973102020-10-02 Excitation-Inhibition Balanced Neural Networks for Fast Signal Detection Tian, Gengshuo Li, Shangyang Huang, Tiejun Wu, Si Front Comput Neurosci Neuroscience Excitation-inhibition (E-I) balanced neural networks are a classic model for modeling neural activities and functions in the cortex. The present study investigates the potential application of E-I balanced neural networks for fast signal detection in brain-inspired computation. We first theoretically analyze the response property of an E-I balanced network, and find that the asynchronous firing state of the network generates an optimal noise structure enabling the network to track input changes rapidly. We then extend the homogeneous connectivity of an E-I balanced neural network to include local neuronal connections, so that the network can still achieve fast response and meanwhile maintain spatial information in the face of spatially heterogeneous signal. Finally, we carry out simulations to demonstrate that our model works well. Frontiers Media S.A. 2020-09-03 /pmc/articles/PMC7497310/ /pubmed/33013343 http://dx.doi.org/10.3389/fncom.2020.00079 Text en Copyright © 2020 Tian, Li, Huang and Wu. 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 Tian, Gengshuo Li, Shangyang Huang, Tiejun Wu, Si Excitation-Inhibition Balanced Neural Networks for Fast Signal Detection |
title | Excitation-Inhibition Balanced Neural Networks for Fast Signal Detection |
title_full | Excitation-Inhibition Balanced Neural Networks for Fast Signal Detection |
title_fullStr | Excitation-Inhibition Balanced Neural Networks for Fast Signal Detection |
title_full_unstemmed | Excitation-Inhibition Balanced Neural Networks for Fast Signal Detection |
title_short | Excitation-Inhibition Balanced Neural Networks for Fast Signal Detection |
title_sort | excitation-inhibition balanced neural networks for fast signal detection |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7497310/ https://www.ncbi.nlm.nih.gov/pubmed/33013343 http://dx.doi.org/10.3389/fncom.2020.00079 |
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