Sorensen M E, DeWeerth S P
Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
J Neural Eng. 2007 Sep;4(3):189-96. doi: 10.1088/1741-2560/4/3/003. Epub 2007 Apr 20.
Neural models are increasingly being used as design components of physical systems. In order to best use models in these novel contexts, we must develop design rules that describe how decisions in model construction relate to the functional performance of the resulting system. In the accompanying paper, we described a series of related neuron models of varying complexity. Here, we use these models to build several half-center oscillators, and investigate how model complexity influences the robustness and flexibility of these oscillators. Our results indicate that model complexity has a significant effect on the robustness and flexibility of systems that incorporate neural models.
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佳地使用模型,我们必须制定设计规则,描述模型构建中的决策如何与最终系统的功能性能相关。在随附的论文中,我们描述了一系列复杂度各异的相关神经元模型。在此,我们使用这些模型构建了几个半中枢振荡器,并研究模型复杂度如何影响这些振荡器的稳健性和灵活性。我们的结果表明,模型复杂度对包含神经模型的系统的稳健性和灵活性有显著影响。