Moving heads, stable worlds: estimation, compensation, and calibration during active self-motion

自我相对于环境运动的知识是所有可移动生物体正常认知功能的基础。这种知识在很大程度上依赖于对头部运动的预测，这些预测来自于主动运动命令，以在身体上和空间中移动头部。这些基于运动的预测不仅奠定了我们感知自我运动的能力，也奠定了我们感知空间恒定的能力，即我们为了感知稳定的外部世界而补偿变化的感觉刺激的能力。尽管主动头部控制对于估计和补偿自我运动具有基本的重要性，但我们仍然对主动控制信号如何与传入的视觉和前庭信号相互作用有一个初步的了解。因此，主动头部控制代表了一个非常重要但研究较少的电机控制模型系统。目前的提案使用尖端技术来研究这一系统，以解决重要的开放问题：感觉和运动信号是如何比较和整合的？感觉-运动冲突的后果是什么？运动信号如何影响知觉？心理物理实验将使用由六足运动平台和立体视觉显示器组成的虚拟现实装置进行。活动的头部运动将由运动跟踪设备跟踪，视觉和前庭刺激将根据头部的运动进行渲染。实验将评估前庭、视觉和传出复制信号如何与估计的头部运动、身体运动或环境运动进行比较和整合。感觉运动校准的概率模型将被用来预测神经系统如何适应持续的冲突。结果将为高度相关的医疗和技术应用提供信息，例如眩晕治疗和头盔虚拟现实显示系统。

Knowledge of self-movement relative to the environment is fundamental to normal cognitive function for all mobile organisms. This knowledge depends largely on predictions of head motion derived from active motor commands to move the head on the body and through space. These motor-based predictions underlie our ability not only to perceive our own self-motion but also our capacity for spatial constancy, i.e. our ability to compensate for changing sensory stimulation in order to perceive a stable external world.Despite the fundamental importance of active head control for estimating and compensating self-motion, we still have only a preliminary understanding of how active control signals interact with incoming visual and vestibular signals. Thus, active head control represents a highly important but understudied model system for motor control. The current proposal investigates this system using cutting-edge technology to address important open questions: How are sensory and motor signals compared and integrated? What are the consequences of sensory-motor conflict? How do motor signals impact perception? Psychophysical experiments will be conducted using a virtual reality setup consisting of a hexapod motion platform and stereo visual display. Active head movements will be tracked with motion tracking equipment and visual and vestibular stimuli will be rendered contingent on the head motion. Experiments will evaluate how vestibular, visual and efference copy signals are compared and integrated to estimated head motion, body motion, or environmental motion. Probabilistic modeling of sensorimotor calibration will be used to predict how the nervous system adapts to persistent conflicts. Results will inform highly relevant medical and technical applications, such as vertigo treatment and head-mounted virtual reality display systems.