Vestibular and Visual Control of Eye Movement

项目摘要 神经系统的一个标志是它能够转换和联合收割机多种信息源， 行为，并通过学习来调整这种信号处理，以更准确地控制行为。这如何 自适应信号处理是由神经电路实现的，这在很大程度上是未知的，部分原因是 反馈回路的存在混合在一起，并以复杂的方式在时间上塑造神经信号。这个项目 使用跨学科的实验计算方法来剖析信号处理操作 支持通过前庭和视觉感官输入控制眼球运动。严格的实验 将开发协议、计算模型和统计拟合方法来表征信号 转换发生在多个网站在相关的神经电路，以解开前馈的作用， 和反馈信号控制眼球运动行为。这些方法将用于分析如何 前庭和视觉信号被回路处理的方式的特定变化支持适应性变化 在对这些感觉输入的眼动反应的幅度和时间上。通过推进我们的 了解学习如何改变电路计算的方式，这项工作弥合了关键的概念差距 在突触水平的神经可塑性和行为水平的学习之间，并提供了一个科学的 基金会的发展，改善临床方法，以促进恢复或取代 前庭功能

PROJECT SUMMARY A hallmark of the nervous system is its ability to transform and combine multiple sources of information to guide behavior, and to tune this signal processing through learning, for more accurate control of behavior. How this adaptive signal processing is implemented by neural circuits remains largely unknown, due in part to the presence of feedback loops that mix together and temporally shape neural signals in complex ways. This project uses an interdisciplinary experimental-computational approach to dissect the signal processing operations supporting the control of eye movements by vestibular and visual sensory inputs. Rigorous experimental protocols, computational models, and statistical fitting approaches will be developed to characterize the signal transformations occurring at multiple sites in the relevant neural circuitry, to disentangle the roles of feedforward and feedback signals in the control of eye movement behavior. These approaches will be used to analyze how specific changes in the way vestibular and visual signals are processed by the circuit support adaptive changes in the amplitude and timing of the eye movement responses to these sensory inputs. By advancing our understanding of how learning alters the way a circuit computes, this work bridges the key conceptual gap between neural plasticity at the synaptic level and learning at the behavioral level, and provides a scientific foundation for the development of improved clinical approaches for promoting recovery or replacement of vestibular function.