title: Functional consequences of model complexity in rhythmic systems: II. Systems performance of model and hybrid oscillators.
abstract: 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.
authors.affiliation: Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
authors.forename: M E
authors.initials: ME
authors.lastname: Sorensen
authors.forename: S P
authors.initials: SP
authors.lastname: DeWeerth
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000465:Algorithms; D000818:Animals; D001683:Biological Clocks / Q000502:physiology*; D003198:Computer Simulation; D005246:Feedback / Q000502:physiology; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009474:Neurons / Q000502:physiology*; D010507:Periodicity