Cerebellar synaptic plasticity is vital for adaptability and fine tuning of goal-directed movements. The perceived sensory errors between desired and actual movement outcomes are commonly considered to induce plasticity in the cerebellar synapses, with an objective to improve desirability of the executed movements. In rapid goal-directed eye movements called saccades, the only available sensory feedback is the direction of reaching error information received only at end of the movement. Moreover, this sensory error dependent plasticity can only improve the accuracy of the movements, while ignoring other essential characteristics such as reaching in minimum-time. In this work we propose a rate based, cerebellum inspired adaptive filter model to address refinement of both accuracy and movement-time of saccades. We use optimal control approach in conjunction with information constraints posed by the cerebellum to derive bio-plausible supervised plasticity rules. We implement and validate this bio-inspired scheme on a humanoid robot. We found out that, separate plasticity mechanisms in the model cerebellum separately control accuracy and movement-time. These plasticity mechanisms ensure that optimal saccades are produced by just receiving the direction of end reaching error as an evaluative signal. Furthermore, the model emulates encoding in the cerebellum of movement kinematics as observed in biological experiments.

小脑突触可塑性对于目标导向运动的适应性和微调至关重要。期望运动结果和实际运动结果之间的感知感觉误差通常被认为会引起小脑突触的可塑性，目的是提高执行运动的可取性。在称为扫视的快速目标导向眼球运动中，唯一可用的感觉反馈是到达仅在运动结束时收到的错误信息的方向。此外，这种依赖于感觉误差的可塑性只能提高动作的准确性，而忽略了其他基本特征，例如在最短时间达到。在这项工作中，我们提出了一种基于速率的、受小脑启发的自适应滤波器模型，以解决扫视的准确性和运动时间的改进。我们使用最优控制方法与小脑提出的信息约束相结合，以推导出生物似是而非的监督可塑性规则。我们在人形机器人上实施并验证了这种仿生方案。我们发现，模型小脑中单独的可塑性机制分别控制精度和运动时间。这些可塑性机制确保通过仅接收末端到达误差的方向作为评估信号来产生最佳的眼跳。此外，该模型模拟了在生物实验中观察到的运动学小脑中的编码。模型小脑中的独立可塑性机制分别控制精度和运动时间。这些可塑性机制确保通过仅接收末端到达误差的方向作为评估信号来产生最佳的眼跳。此外，该模型模拟了在生物实验中观察到的运动学小脑中的编码。模型小脑中的独立可塑性机制分别控制精度和运动时间。这些可塑性机制确保通过仅接收末端到达误差的方向作为评估信号来产生最佳的眼跳。此外，该模型模拟了在生物实验中观察到的运动学小脑中的编码。