Department of Psychology, University of Sheffield Western Bank, Sheffield, UK.
Front Comput Neurosci. 2010 Oct 4;4:140. doi: 10.3389/fncom.2010.00140. eCollection 2010.
Marr-Albus adaptive filter models of the cerebellum have been applied successfully to a range of sensory and motor control problems. Here we analyze their properties when applied to classical conditioning of the nictitating membrane response in rabbits. We consider a system-level model of eyeblink conditioning based on the anatomy of the eyeblink circuitry, comprising an adaptive filter model of the cerebellum, a comparator model of the inferior olive and a linear dynamic model of the nictitating membrane plant. To our knowledge, this is the first model that explicitly includes all these principal components, in particular the motor plant that is vital for shaping and timing the behavioral response. Model assumptions and parameters were systematically investigated to disambiguate basic computational capacities of the model from features requiring tuning of properties and parameter values. Without such tuning, the model robustly reproduced a range of behaviors related to sensory prediction, by displaying appropriate trial-level associative learning effects for both single and multiple stimuli, including blocking and conditioned inhibition. In contrast, successful reproduction of the real-time motor behavior depended on appropriate specification of the plant, cerebellum and comparator models. Although some of these properties appear consistent with the system biology, fundamental questions remain about how the biological parameters are chosen if the cerebellar microcircuit applies a common computation to many distinct behavioral tasks. It is possible that the response profiles in classical conditioning of the eyeblink depend upon operant contingencies that have previously prevailed, for example in naturally occurring avoidance movements.
马鲁-阿尔布斯小脑自适应滤波器模型已成功应用于一系列感觉和运动控制问题。在这里，我们分析了它们在兔子的瞬目膜条件反射中的应用特性。我们考虑了一种基于瞬目电路解剖结构的眨眼条件反射系统级模型，该模型包括小脑的自适应滤波器模型、橄榄下核的比较器模型和瞬目膜植物的线性动态模型。据我们所知，这是第一个明确包含所有这些主要组成部分的模型，特别是对塑造和定时行为反应至关重要的运动植物。系统地研究了模型假设和参数，以区分模型的基本计算能力与需要调整特性和参数值的特征。在没有这种调整的情况下，该模型通过对单个和多个刺激显示出适当的试验级联学习效应，包括阻断和条件抑制，稳健地再现了与感觉预测相关的一系列行为。相比之下，实时运动行为的成功再现取决于对植物、小脑和比较器模型的适当规范。尽管这些特性中的一些与系统生物学一致，但如果小脑微电路将相同的计算应用于许多不同的行为任务，仍然存在一些关于如何选择生物参数的基本问题。瞬目条件反射的反应特征可能取决于先前存在的操作性条件，例如在自然发生的回避运动中。
