The Role of the Frontal Eye Fields in Pursuit Learning

描述（由申请人提供）：运动学习的一个重要方面是动作的准确时机。平滑追求是研究大脑如何产生暂时精确的习得运动的绝佳行为。追逐目标在开始移动（学习时间）后，会在一段固定的时间内不断改变方向。在反复接触这种刺激后，受试者学会在学习期间调整他们的平滑眼动。我们建议在额叶视场平滑追逐区（FEFSEM）寻找控制习得性眼球运动时间的神经信号。不同的FEFSEM神经元在平滑追求的不同时间段优先活跃。在这个提议中，我们测试了我们的预测，支持我们的初步数据，即学习期间平均放电率的变化集中在FEFSEM神经元中，这些神经元更喜欢在学习时间前后进行短暂的追求。首先，我们将比较在相同的学习时间内，偏好不同时间段的神经元的平均放电率的变化。然后，我们将研究单个神经元如何在两个单独的学习模块中调节它们的放电速率，这两个学习模块的唯一区别是当目标改变方向时。我们的第二个目标是确定学习是否调节不同FEFSEM神经元对眼球运动的贡献。神经反应和行为反应之间的试对试相关性测量了神经元输出反映运动信号的程度，该运动信号在神经群中共享，因此是评估神经群功能特性的有价值的工具。神经元-行为相关性的变化可以归因于有限数量的因素，包括神经元权重的变化，驱动眼球运动的神经池的大小，或池内神经同步性的数量。结合目标1和目标2的结果将阐明学习如何改变FEFSEM神经元的活动及其与行为的关系。许多患有包括额叶功能障碍在内的神经系统疾病的患者，如阿尔茨海默病和额颞叶痴呆，都表现出明显的动眼肌缺陷。更好地了解额叶皮层在动眼病控制中的作用，可能有助于了解这些疾病中特定额叶回路是如何被破坏的。健康大脑的一个关键功能是产生和控制运动。了解大脑的不同部分是如何参与运动控制的，可以帮助我们通过检查病人在简单运动任务中的表现，安全地诊断出这些大脑区域的问题。

DESCRIPTION (provided by applicant): An important aspect of motor learning is the accurate timing of movements. Smooth pursuit is an excellent behavior to study how the brain produces temporally precise learned movements. A pursuit target consistently changes its direction a fixed amount of time after it starts moving (the learning time). Upon repeated exposure to this stimulus, subjects leam to modify their smooth eye movement around the learning time. We propose to look for neural signals that control the timing of the learned eye movement in the smooth pursuit region of the frontal eye fields (FEFSEM). Different FEFSEM neurons are preferentially active during distinct temporal segments of smooth pursuit. In this proposal, we test the prediction, supported by our preliminary data, that changes in mean firing rate during learning are concentrated in FEFSEM neurons that prefer a temporal segment of pursuit around the learning time. First, we will compare changes in mean firing rate for the same learning time across neurons that prefer different temporal segments of pursuit. We will then examine how individual neurons modulate their firing rate during two separate learning blocks whose only difference is when the target changes direction. Our second goal is to determine whether learning modulates how different FEFSEM neurons contribute to the eye movement. The trial-by-trial correlation between the neural response and the behavioral response measures the extent to which a neuron's output reflects a motor signal that is shared across the neural population, and is therefore a valuable tool for assessing the functional properties of the population. Shifts in the neuron-behavior correlation can be attributed to a limited number of factors, including changes in the weighting of the neuron, the size of the neural pool that drives the eye movement, or the amount of neural synchrony within the pool. Combining the results from aim 1 and aim 2 will shed light on how learning alters the activity of FEFSEM neurons and their relationship to behavior. Many patients suffering from neurological disorders that involve frontal lobe dysfunction, such as Alzheimer's disease and frontotemporal dementia, exhibit striking oculomotor deficits. A better understanding of the role of the frontal cortex in oculomotor control may provide insight into how specific frontal circuits are disrupted in these diseases. A critical function of the healthy brain is to produce and control movements. Understanding how different parts of the brain are involved in motor control can help us safely diagnose problems with these brain regions by examining a patient's performance on simple motor tasks.