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A Cognitive Model Based on Neuromodulated Plasticity
Associative learning, including classical conditioning and operant conditioning, is regarded as the most fundamental type of learning for animals and human beings. Many models have been proposed surrounding classical conditioning or operant conditioning. However, a unified and integrated model to ex...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5107251/ https://www.ncbi.nlm.nih.gov/pubmed/27872638 http://dx.doi.org/10.1155/2016/4296356 |
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author | Huang, Jing Ruan, Xiaogang Yu, Naigong Fan, Qingwu Li, Jiaming Cai, Jianxian |
author_facet | Huang, Jing Ruan, Xiaogang Yu, Naigong Fan, Qingwu Li, Jiaming Cai, Jianxian |
author_sort | Huang, Jing |
collection | PubMed |
description | Associative learning, including classical conditioning and operant conditioning, is regarded as the most fundamental type of learning for animals and human beings. Many models have been proposed surrounding classical conditioning or operant conditioning. However, a unified and integrated model to explain the two types of conditioning is much less studied. Here, a model based on neuromodulated synaptic plasticity is presented. The model is bioinspired including multistored memory module and simulated VTA dopaminergic neurons to produce reward signal. The synaptic weights are modified according to the reward signal, which simulates the change of associative strengths in associative learning. The experiment results in real robots prove the suitability and validity of the proposed model. |
format | Online Article Text |
id | pubmed-5107251 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-51072512016-11-21 A Cognitive Model Based on Neuromodulated Plasticity Huang, Jing Ruan, Xiaogang Yu, Naigong Fan, Qingwu Li, Jiaming Cai, Jianxian Comput Intell Neurosci Research Article Associative learning, including classical conditioning and operant conditioning, is regarded as the most fundamental type of learning for animals and human beings. Many models have been proposed surrounding classical conditioning or operant conditioning. However, a unified and integrated model to explain the two types of conditioning is much less studied. Here, a model based on neuromodulated synaptic plasticity is presented. The model is bioinspired including multistored memory module and simulated VTA dopaminergic neurons to produce reward signal. The synaptic weights are modified according to the reward signal, which simulates the change of associative strengths in associative learning. The experiment results in real robots prove the suitability and validity of the proposed model. Hindawi Publishing Corporation 2016 2016-10-30 /pmc/articles/PMC5107251/ /pubmed/27872638 http://dx.doi.org/10.1155/2016/4296356 Text en Copyright © 2016 Jing Huang et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Huang, Jing Ruan, Xiaogang Yu, Naigong Fan, Qingwu Li, Jiaming Cai, Jianxian A Cognitive Model Based on Neuromodulated Plasticity |
title | A Cognitive Model Based on Neuromodulated Plasticity |
title_full | A Cognitive Model Based on Neuromodulated Plasticity |
title_fullStr | A Cognitive Model Based on Neuromodulated Plasticity |
title_full_unstemmed | A Cognitive Model Based on Neuromodulated Plasticity |
title_short | A Cognitive Model Based on Neuromodulated Plasticity |
title_sort | cognitive model based on neuromodulated plasticity |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5107251/ https://www.ncbi.nlm.nih.gov/pubmed/27872638 http://dx.doi.org/10.1155/2016/4296356 |
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