Integrating perception and action: the multi-channel model of visuo-motor control

整合感知与行动：视觉运动控制的多通道模型

• 批准号: BB/J009458/1
• 负责人: Jörn Diedrichsen
• 金额: $ 33.93万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2012
• 资助国家: 英国
• 起止时间: 2012 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FJ009458%2F1
• 关键词: Integrating; perception; action; multi; channel

When a skilled cricket player reaches out to catch a ball, multiple brain systems simultaneously predict the position of the ball and the arm. Based on this visual information, the motor system must rapidly correct the ongoing movement, driving the hand in a manner that ensures successful grasp of the ball. Similar visual and motor pathways are used in all sports, where an athlete is required to respond as quickly and accurately as possible to the small changes in the world signalled by visual feedback. Indeed, these processes are fundamental to most skilled movements in everyday life. The visually sensed changes may refer either to one's own body, or to objects in the external world (such as a ball). By assigning these visual changes to either itself or to an external item, the visuo-motor control system can respond quickly in the correct manner to ensure skilled action. In this project, we will investigate the neural pathways that constitute this vision to motor action loop. Specifically, we will study three major questions: The first question is how these different pathways, signalling either our hand location or the target location (e.g. ball), interact with one another. The current scientific view is that the brain simply calculates the difference between the target and hand locations and uses this difference to correct the movement. However, our preliminary experiments demonstrate that this is not true, but rather suggest that the two pathways lead to partially independent responses. Using a robotic device, we will carefully measure the interactions and independence of these two feedback pathways.The second question investigates which parts of the brain are dedicated to the processing of the two feedback pathways. We will investigate active reaching movements using a robotic device while measuring brain activity using functional magnetic resonance imaging. The individual activity pattern in each region will reveal how target and hand information are represented in different brain regions, and how these regions interact. The third question is how the brain assigns visual signals to one's own movements, or other action-relevant objects. For example, a huge number of sports utilize bats, or rackets that act as an extension of the subjects own hand. The brain must therefore assign agency to these objects, marking them as self, in order to respond correctly to visual changes in these objects, which may be a different action than responding to changes in external objects such as the ball. We will investigate the process by which this occurs and attempt to distinguish it from attention mechanisms. This project investigates the basic vision to motor action pathways that underlie skilled movements. Understanding these pathways and the manner in which the brain utilizes them for fast action will lead to improvements of training regimes for high-performance sports. In many sports, the highest level of performance requires the ability to respond accurately and with exceptional speed to small, barely detectible visual information. The research also produces an essential understanding of the pathways directly involved in learning of action. As such, it provides important information on the mechanisms used in learning and retraining skills and movements. This has particular relevance for rehabilitation after brain injury, such as stroke. Extensive techniques are being developed which use robotic devices for retraining after brain injury, where feedback is also provided visually. By understanding in detail how and where this visual information is processed, optimal training designs for stroke rehabilitation can be developed, which take into account individual deficits in the various feedback loops.

当一个熟练的板球运动员伸手接球时，多个大脑系统同时预测球和手臂的位置。基于这种视觉信息，运动系统必须迅速纠正正在进行的运动，以确保成功抓住球的方式驱动手。类似的视觉和运动路径在所有运动中都有使用，运动员需要尽可能快速准确地对视觉反馈所发出的世界变化做出反应。事实上，这些过程是日常生活中大多数熟练动作的基础。视觉上感知到的变化可能是指自己的身体，也可能是指外部世界中的物体（如球）。通过将这些视觉变化分配给自身或外部项目，视觉运动控制系统可以以正确的方式快速响应，以确保熟练的动作。在这个项目中，我们将研究构成这个视觉到运动动作回路的神经通路。具体来说，我们将研究三个主要问题：第一个问题是这些不同的通路，信号要么我们的手的位置或目标位置（如球），如何相互作用。目前的科学观点认为，大脑只是简单地计算目标和手的位置之间的差异，并利用这种差异来纠正运动。然而，我们的初步实验表明，这是不正确的，而是表明，这两个途径导致部分独立的反应。使用机器人设备，我们将仔细测量这两个反馈通路的相互作用和独立性。第二个问题研究大脑的哪些部分专门用于处理这两个反馈通路。我们将使用机器人设备来研究主动接触运动，同时使用功能性磁共振成像来测量大脑活动。每个区域中的个体活动模式将揭示目标和手的信息如何在不同的大脑区域中表示，以及这些区域如何相互作用。第三个问题是大脑如何将视觉信号分配给自己的动作或其他与动作相关的物体。例如，大量的体育运动利用球棒或球拍作为主体自己的手的延伸。因此，大脑必须为这些物体分配代理，将它们标记为自我，以便对这些物体的视觉变化做出正确的反应，这可能是一种不同于对外部物体（如球）变化做出反应的行为。我们将研究这种现象发生的过程，并试图将其与注意力机制区分开来。这个项目调查的基本视觉运动动作的途径，基础熟练的动作。了解这些途径以及大脑利用它们快速行动的方式将有助于改善高性能运动的训练制度。在许多体育运动中，最高水平的表现需要能够准确地反应，并以非凡的速度对微小的，几乎无法察觉的视觉信息做出反应。这项研究还对直接参与行动学习的途径产生了重要的理解。因此，它提供了关于学习和再培训技能和动作的机制的重要信息。这与脑损伤（如中风）后的康复特别相关。正在开发的广泛技术使用机器人设备进行脑损伤后的再训练，其中还提供视觉反馈。通过详细了解这些视觉信息是如何以及在哪里被处理的，可以开发出中风康复的最佳训练设计，其中考虑到各种反馈回路中的个体缺陷。

项目成果

Flexible switching of feedback control mechanisms allows for learning of different task dynamics.

• DOI: 10.1371/journal.pone.0054771
• 发表时间: 2013
• 期刊: PloS one
• 影响因子: 3.7
• 作者: White O;Diedrichsen J
• 通讯作者: Diedrichsen J

Fractionation of the visuomotor feedback response to directions of movement and perturbation.

• DOI: 10.1152/jn.00377.2013
• 发表时间: 2014-11-01
• 期刊: Journal of neurophysiology
• 影响因子: 2.5
• 作者: Franklin DW;Franklin S;Wolpert DM
• 通讯作者: Wolpert DM

A dedicated binding mechanism for the visual control of movement.

• DOI: 10.1016/j.cub.2014.02.030
• 发表时间: 2014-03-31
• 期刊: CURRENT BIOLOGY
• 影响因子: 9.2
• 作者: Reichenbach, Alexandra;Franklin, David W.;Zatka-Haas, Peter;Diedrichsen, Joern
• 通讯作者: Diedrichsen, Joern

Mirror reversal and visual rotation are learned and consolidated via separate mechanisms: recalibrating or learning de novo?

镜子反转和视觉旋转是通过不同的机制学习和巩固的：重新校准还是从头学习？

• DOI: 10.1523/jneurosci.5306-13.2014
• 发表时间: 2014
• 期刊: the official journal of the Society for Neuroscience
• 作者: Telgen S