Computational models of neuron-astrocyte interactions lead to improved efficacy in the performance of neural networks.

Computational models of neuron-astrocyte interactions lead to improved efficacy in the performance of neural networks.
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DOI:
10.1155/2012/476324
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发表时间:
2012
影响因子:
--
通讯作者:
Porto-Pazos AB
Porto-Pazos AB
中科院分区:
工程技术4区
文献类型:
--
作者:
Alvarellos-González A;Pazos A;Porto-Pazos AB

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星形胶质细胞是神经胶质系统的一部分,它对大脑信息处理的重要性最近已经被证明。关于多层连接主义系统中的信息处理,已经表明,包括人工神经元和星形胶质细胞(人工神经元-Glia网络)的系统比仅包括人工神经元的相同系统具有众所周知的优势。由于星形胶质细胞在神经网络功能中的实际影响尚不清楚,我们利用计算模型研究了不同的星形胶质细胞-神经元相互作用用于信息处理;不同的神经元-神经胶质算法被用于面向分类问题解决的多层人工神经元-Glia网络的训练和验证。测试的结果表明,所有模拟星形胶质细胞诱导的突触增强的算法都改善了人工神经网络的性能,但它们的有效性取决于问题的复杂程度。
The importance of astrocytes, one part of the glial system, for information processing in the brain has recently been demonstrated. Regarding information processing in multilayer connectionist systems, it has been shown that systems which include artificial neurons and astrocytes (Artificial Neuron-Glia Networks) have well-known advantages over identical systems including only artificial neurons. Since the actual impact of astrocytes in neural network function is unknown, we have investigated, using computational models, different astrocyte-neuron interactions for information processing; different neuron-glia algorithms have been implemented for training and validation of multilayer Artificial Neuron-Glia Networks oriented toward classification problem resolution. The results of the tests performed suggest that all the algorithms modelling astrocyte-induced synaptic potentiation improved artificial neural network performance, but their efficacy depended on the complexity of the problem.
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