Suppr超能文献

节律系统中模型复杂性的功能后果:I. 爆发性神经元模型的系统简化

Functional consequences of model complexity in rhythmic systems: I. Systematic reduction of a bursting neuron model.

作者信息

Sorensen M E, DeWeerth S P

机构信息

Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA.

出版信息

J Neural Eng. 2007 Sep;4(3):179-88. doi: 10.1088/1741-2560/4/3/002. Epub 2007 Apr 20.

Abstract

Neural models are increasingly being used as design components of physical systems. In order to most effectively utilize neuronal models in these novel contexts, we need to develop design rules for neuronal systems that relate how model design affects overall system performance. In this paper and a companion article, we investigate how the complexity of a neural model affects the performance of a two-cell oscillator built from the model. In this paper, we create a series of related neuron models with different mathematical complexity. Starting with a complex mechanistic model of a bursting neuron, we use a variety of techniques to create a series of simplified neuron models. These three reduced models produce bursting activity that is qualitatively very similar to the original model. In the following companion article, we investigate the functional performance of oscillators built from these models.

摘要

神经模型越来越多地被用作物理系统的设计组件。为了在这些新环境中最有效地利用神经元模型,我们需要为神经元系统制定设计规则,这些规则涉及模型设计如何影响整体系统性能。在本文以及一篇配套文章中,我们研究了神经模型的复杂性如何影响由该模型构建的双细胞振荡器的性能。在本文中,我们创建了一系列具有不同数学复杂性的相关神经元模型。从一个复杂的爆发神经元机制模型开始,我们使用各种技术创建了一系列简化的神经元模型。这三个简化模型产生的爆发活动在质量上与原始模型非常相似。在接下来的配套文章中,我们将研究由这些模型构建的振荡器的功能性能。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验