Vestibular and Visual Control of Eye Movement

项目总结 神经系统的一个特点是它能够转换和组合多个信息源来引导 并通过学习来调整这种信号处理，以便更准确地控制行为。这是怎么回事 自适应信号处理是由神经电路实现的，目前仍在很大程度上尚不清楚，部分原因是 存在混合在一起的反馈环，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 通过前庭和视觉感觉输入支持眼球运动的控制。严谨的实验 将开发协议、计算模型和统计拟合方法来表征信号 在相关神经回路中的多个位置发生的转换，以解开前馈的角色 以及反馈信号对眼动行为的控制。这些方法将用于分析如何 电路处理前庭和视觉信号的方式的具体变化支持适应性变化 对这些感官输入的眼动反应的幅度和时序。通过推进我们的 了解学习如何改变电路的计算方式，这项工作弥合了关键的概念鸿沟 突触水平的神经可塑性和行为水平的学习之间的关系，并提供了一种科学的 开发改进的临床方法以促进恢复或替换的基础 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.