Variation as a neural code

作为神经代码的变异

• 批准号: 8141343
• 负责人: STEPHEN G LISBERGER
• 金额: $ 18.56万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8141343
• 关键词: Variation; neural; code

Visually guided reaching is a centrally important behavior in both human and non-human primates. Reaching is a highly stereotyped behavior, with similar movement paths and velocity profiles observed across a wide range of conditions, across subjects, and even across species. Yet another hallmark of visually guided reaching is trial by trial variability in the details of the movement and in the movement endpoint. The goal of this project is to characterize the nature of this variability and its neural origins and to test two hypotheses about the role that variability plays in such sensorimotor circuits. There are three specific aims. 1) We will characterize the relationship between variability in visually guided reaching and neural activity in Macaque ventral premotor cortex (PMv) and primary motor cortex (M1). We will perform a detailed analysis of the trial by trial movement variability, using a number of novel analysis techniques. In addition to yielding new insight into the nature of movement variability, this analysis will provide a rich set of behavioral variables that can be compared to neural activity. We will record from PMv and M1 in Macaque monkeys while they perform a reaching task. The trial by trial neural activity will be decomposed into variability that can be explained by the behavior and a residual variability that unrelated to behavioral variability. 2) We will test our hypothesis that reach variability is under central control by attempting to alter variability using surreptitious manipulations of movement feedback. With human subjects, we will either reshape the mapping from reach endpoint to reward feedback or introduce time-varying changes in the visual feedback of hand position in order to reshape the variability of reaching. We will then employ these behavioral techniques with Macaque while we record from PMv and M1, and we will correlate the changes in movement variability along each spatial axis with changes in the explained and residual variability of neural activity. 3) We will test our hypothesis about the relationship between neural variability and learning. Specifically, we propose that explained variability in a neural circuit is aids learning in that circuit, since it provides a richer sampling of the input-output space, while residual variability is detrimental for learning, since it degrades the quality of the error signal. We will test this hypothesis by studying a particular form of sensorimotor learning: the rapid adaptation that follows exposure to shifted visual feedback. By comparing the learning rate of shift adaptation to the level of behavioral and neural variability, we will determine whether either type of variability affects sensorimotor learning.

视觉引导的伸手行为对于人类和非人类灵长类动物来说都是非常重要的行为。 到达是一种高度刻板的行为，具有相似的运动路径和速度曲线 在广泛的条件下、跨学科、甚至跨物种中观察到。然而 视觉引导到达的另一个标志是通过尝试运动细节的变化来进行尝试 并在运动终点。该项目的目标是描述这一现象的本质 变异性及其神经起源，并检验关于变异性在神经元中所起的作用的两个假设 这样的感觉运动电路。具体目标有三个。 1）我们将描述关系的特征 猕猴腹侧前运动的视觉引导到达和神经活动的变异性之间 皮层 (PMv) 和初级运动皮层 (M1)。我们将逐个试验进行详细分析 运动变异性，使用许多新颖的分析技术。除了产生新的 深入了解运动变异性的本质，该分析将提供一组丰富的行为 可以与神经活动进行比较的变量。我们将从猕猴的 PMv 和 M1 进行记录 猴子在执行任务时。逐个试验的神经活动将被分解 可以用行为来解释的变异性和与无关的残余变异性 行为变异性。 2）我们将检验我们的假设，即到达变异性受到中央控制 试图通过秘密操纵运动反馈来改变可变性。与人类 主题，我们要么重塑从到达终点到奖励反馈的映射，要么引入 手部位置的视觉反馈随时间变化，以重塑手部位置的可变性 达到。然后，我们将在记录时对猕猴运用这些行为技巧 PMv 和 M1，我们将沿着每个空间轴的运动变异性的变化与 神经活动的可解释变异性和残余变异性的变化。 3）我们将检验我们的假设 关于神经变异和学习之间的关系。具体来说，我们建议 解释神经回路的可变性有助于该回路的学习，因为它提供了更丰富的信息 输入输出空间的采样，而残余变异性对学习是有害的，因为它 降低了误差信号的质量。我们将通过研究一种特定形式来检验这个假设 感觉运动学习：暴露于变化的视觉反馈后的快速适应。经过 将轮班适应的学习率与行为和神经变异水平进行比较，我们 将确定任一类型的变异性是否影响感觉运动学习。