The computational importance of cerebellar processing

摘要 小脑处理与一系列的精确表现有关， 从感觉运动转换到执行控制。鉴于这一广泛 范围内，在组织中的模态和物种之间存在显著的一致性 小脑微电路和小脑区域的闭环方式， 连接到其他大脑区域。这种一致性表明， 角色，我们假设最通常被描述为自适应时间滤波器。到 为了验证这一假设，我们将研究小脑在简单运动可塑性中的功能， 学习固视稳定性。在此设置中，作为自适应滤波器的处理应该是 在小脑中，这种能力可以作为一种比例，积分， 或微分增益元件。在目标1中，小脑过滤将通过使用 在斑马鱼幼体中进行双光子钙成像，以测量两个输入端的活动 颗粒和输出浦肯野细胞群。将确定滤波器的适应性 通过测量输入和输出神经元之间关系的变化， 都被训练成更高或更低的稳定性。在目标2中， 小脑将被构造成产生实验测量的信号 转换并预测小脑过滤的机制。这些 预测将通过颗粒细胞的局灶刺激和 导致浦肯野神经元反应。这些数据加在一起， 完全理解小脑的计算重要性， 行为

ABSTRACT Cerebellar processing is associated with the accurate performance of a range of behaviors, from sensorimotor transformations to executive control. Given this wide range, there is remarkable consistency across modality and species in the organization of cerebellar microcircuitry and the closed-loop manner with which cerebellar regions are connected to other brain areas. This consistency suggests a common computational role, which we hypothesize is most generally described as an adaptive temporal filter. To test this hypothesis, we will investigate cerebellar function in a simple motor plasticity, the learning of fixation stability. In this setting, processing as an adaptive filter should be realized as a capacity in the cerebellum to alternatively act as a proportional, integrating, or differentiating gain element. In Aim 1, cerebellar filtering will be assessed by using two-photon calcium imaging in the larval zebrafish to measure activity at both input granule and output Purkinje cells populations. Adaptation of the filter will be determined by measuring changes in the relationship between input and output neurons as fixations are trained toward greater or lesser stability. In Aim 2, computational models of the cerebellum will be constructed that generate the experimentally measured signal transformation and make predictions about the mechanisms of cerebellar filtering. These predictions will be tested by focal stimulation of granule cells and measurement of resultant Purkinje neuron responses. Together these data promise to generate the most complete understanding to date of the cerebellum's computational importance in behavior.