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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...

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Detalles Bibliográficos
Autores principales: Huang, Jing, Ruan, Xiaogang, Yu, Naigong, Fan, Qingwu, Li, Jiaming, Cai, Jianxian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2016
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.
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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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