Visual Computations for Motor Control

描述（由申请人提供）：拟议研究的目标是了解如何使用关于目标物体和移动的手的三维（3D）视觉信息来计划和控制目标导向的手运动。这项研究的重点是视觉运动系统使用什么深度线索来进行规划和在线控制，以及它如何整合这些线索。几个理论考虑为这项工作提供了依据。首先，不同的运动行为对视觉信息映射到运动行为的问题有不同的解决方案。因此，我们解决的问题是，大脑是否使用物体的共同视觉表征，还是依赖于不同的任务特定策略来规划和控制不同类型的手部运动，如手部移动和手部旋转（例如在抓取运动期间）。我们将测量受试者如何在控制手部运动的两个组成部分的场景中权衡双眼视差和物体布局的纹理/图形线索。作为视觉运动计算模块性的探索，我们将使用触觉反馈来适应被试在一个任务中的线索权重，并测量任务间适应效应的转移。其次，不同线索对运动控制的相对贡献取决于线索所提供信息的可靠性和大脑处理这些信息的时间过程。我们将研究线索可靠性的变化如何影响大脑如何利用深度线索提供的信息进行计划和在线控制。我们还将测量处理双眼视差和纹理/图形线索的时间过程，因为它们有助于使用在上一个资助期间开发的扰动技术进行运动控制。为了更深入地了解线索不确定性和时间约束如何相互作用以决定人类视觉运动性能，我们将使用最优滤波（随时间的最优统计估计）和控制方法的计算工作来补充实验研究。

DESCRIPTION (provided by applicant): The goal of the proposed research is to understand how 3-dimensional (3D) visual information, both about target objects and about the moving hand, is used to plan and control goal-directed hand movements. The research focuses on what depth cues the visuomotor system uses for planning and online control and how it integrates those cues. Several theoretical considerations inform the work. First, different motor behaviors admit different solutions to the problem of mapping visual information to motor behavior. We therefore address the question of whether the brain uses a common visual representation of objects or relies on different task-specific strategies for planning and controlling different types of hand movements such as hand transport and hand rotation (e.g. during grasping movements). We will measure how subjects weight binocular disparity and texture/figural cues about object layout in a scene for controlling both components of hand movements. As a probe into the modularity of visuomotor computations, we will use haptic feedback to adapt subjects' cue weights in one task and measure transfer of adaptation effects between tasks. Second, the relative contribution of different cues to motor control depends on both the reliability of the information provided by the cues and the time course with which the brain processes them. We will study how changes in cue reliability affect how the brain uses the information provided by depth cues for both planning and online control. We will also measure the time course of processing binocular disparity and texture/figural cues as they contribute to motor control using a perturbation technique developed in the previous funding period. In order to derive a deeper understanding of how cue uncertainty and timing constraints interact to determine human visuomotor performance, we will supplement the experimental studies with computational work applying methods from optimal filtering (optimal statistical estimation over time) and control.