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Virtual Reality Platform for Systematic Investigation of Multisensory Integration and Training of Closed-Loop Prosthetic Control

机译:虚拟现实平台,用于多感觉集成的系统研究和闭环假体控制的训练

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Multisensory integration is the process by which information from different sensory modalities is integrated by the nervous system. Understanding this process is important not only from a basic science perspective but also for translational reasons, e.g. for the development of closed-loop neural prosthetic systems. Here we describe a versatile virtual reality platform which can be used to study the neural mechanisms of multisensory integration for the upper limb and could potentially be incorporated into systems for training of robust neural prosthetic control. The platform involves the interaction of multiple computers and programs and allows for selection of different avatar arms and for modification of a selected arm’s visual properties. The system was tested with two non-human primates (NHP) that were trained to reach to multiple targets on a tabletop. Reliability of arm visual feedback was altered by applying different levels of blurring to the arm. In addition, tactile feedback was altered by adding or removing physical targets from the environment. We observed differences in movement endpoint distributions that varied between animals and visual feedback conditions, as well as across targets. The results indicate that the system can be used to study multisensory integration in a well-controlled manner.
机译:多感官整合是神经系统整合来自不同感官形式的信息的过程。不仅从基础科学的角度来看,而且出于翻译等原因(例如,用于开发闭环神经修复系统。在这里,我们描述了一个通用的虚拟现实平台,该平台可用于研究上肢多感觉集成的神经机制,并有可能被整合到训练稳健的神经假体控制系统中。该平台涉及多个计算机和程序的交互,并允许选择不同的化身手臂并修改所选手臂的视觉属性。该系统用两个非人类灵长类动物(NHP)进行了测试,这些非人类灵长类动物经过训练可以达到桌面上的多个目标。通过对手臂应用不同程度的模糊,可以改变手臂视觉反馈的可靠性。另外,通过向环境中添加或移除物理目标来改变触觉反馈。我们观察到动物和视觉反馈条件以及目标之间运动终点分布的差异。结果表明,该系统可用于以良好控制的方式研究多感官整合。

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