The computational importance of cerebellar processing

描述(由申请人提供)：小脑处理与一系列行为的准确表现有关，从感觉运动转换到执行控制。鉴于这种广泛的范围，在小脑微电路的组织和小脑区域与其他大脑区域的闭合环路连接方式上，不同形态和物种之间存在显著的一致性。这种一致性表明了一种常见的计算角色，我们假设它最通常被描述为自适应时间过滤器。为了验证这一假说，我们将考察小脑功能在简单运动可塑性、学习注视稳定性方面的作用。在这种情况下，作为自适应滤波器的处理应该被实现为小脑中的能力，以交替地充当成比例、积分或微分的增益元件。在目标1中，将通过在斑马鱼幼体中使用双光子钙成像来评估小脑滤过，以测量输入颗粒和输出浦肯野细胞种群的活动。过滤器的适应性将通过测量输入和输出神经元之间关系的变化来确定，因为注视被训练成更稳定或更不稳定。在目标2中，将构建小脑的计算模型，以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部刺激和由此产生的浦肯野神经元反应的测量来验证。综合起来，这些数据有望产生迄今为止对小脑在行为计算中的重要性的最完整的理解。 与公共健康相关：小脑包含了大脑中几乎一半的神经元，但我们对小脑的功能尚不清楚。在这个项目中，我们将通过记录行为过程中的大多数小脑神经元来确定信息在小脑中是如何处理的。这些结果将为开发小脑功能疾病的治疗方法奠定必要的基础，包括脊髓-小脑性共济失调、阅读障碍和自闭症。

DESCRIPTION (provided by applicant): 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. PUBLIC HEALTH RELEVANCE: The cerebellum contains almost half of all neurons in the brain, yet we don't have clear understanding what the cerebellum does. In this project we will determine how information is processed in the cerebellum by recording from the majority of cerebellar neurons during behavior. These results will lay the groundwork necessary to develop treatments for diseases of cerebellar function, including spino-cerebellar ataxia, dyslexia, and autism.