一种新的小脑计算模型
A new model for Cerebellar computation
摘要：
标准的状态空间模型被广泛认为可以解释运动适应任务中的小脑计算[1]。在这里，我们展示了最近的几个实验[2-4]，其中视觉反馈与运动反应无关，挑战了标准模型。此外，我们提出了一个新的模型，占的结果在[2-4]。根据这个新的模型，学习和遗忘是耦合的，并且是错误大小相关的。我们还表明，在合理的假设下，我们提出的模型是唯一的模型，既占经典的适应范式，以及最近的实验[2-4]。
英文摘要：
The standard state space model is widely believed to account for the cerebellar computation in motor adaptation tasks [1]. Here we show that several recent experiments [2-4] where the visual feedback is irrelevant to the motor response challenge the standard model. Furthermore, we propose a new model that accounts for the the results presented in [2-4]. According to this new model, learning and forgetting are coupled and are error size dependent. We also show that under reasonable assumptions, our proposed model is the only model that accounts for both the classical adaptation paradigm as well as the recent experiments [2-4].
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