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.

在人类和非人类灵长类动物中，视觉引导到达是中心重要的行为。 到达是一种高度定型的行为，具有相似的运动路径和速度曲线 在各种条件，跨受试者甚至物种之间观察到。然而 视觉指导到达的另一个标志是通过试用的变异性在运动的细节中试用 并在运动端点。该项目的目的是表征这一点的性质 可变性及其神经起源，并检验两个关于可变性在 这样的感觉运动电路。有三个特定的目标。 1）我们将描述这种关系 在视觉引导到达的变异性与猕猴腹前运动中的神经活动之间 皮层（PMV）和一级运动皮层（M1）。我们将通过审判对试验进行详细分析 运动变异性，使用多种新颖的分析技术。除了产生新的 深入了解运动变异性的性质，该分析将提供丰富的行为 可以比较神经活动的变量。我们将从猕猴中的PMV和M1录制 猴子在执行一项完成任务时。试验神经活动的试验将被分解 变异性可​​以通过行为和残差可变性来解释的变异性无关 行为差异。 2）我们将测试我们的假设，即通过 试图使用运动反馈的秘密操纵来改变变异性。与人类 受试者，我们要么将映射从接触端点重塑以奖励反馈或介绍 为了重塑手部位置的视觉反馈的时变变化，以重塑可变性 到达。然后，我们将在记录中使用这些行为技巧 PMV和M1，我们将将每个空间轴的运动变异性变化与 神经活动的解释和残差变化的变化。 3）我们将检验我们的假设 关于神经变异性与学习之间的关系。具体来说，我们建议 在神经电路中解释的可变性是该电路中的艾滋病学习，因为它提供了更丰富的 输入输出空间的采样，而残留的可变性对学习有害，因为它是有害的 降低错误信号的质量。我们将通过研究特定形式的 感觉运动学习：暴露于移动的视觉反馈之后的快速适应。经过 将适应性的学习率与行为和神经变异性水平进行比较，我们 将确定两种类型的可变性是否会影响感觉运动学习。