Neural Basis of Object Motion Perception During Self-Motion

描述（由申请人提供）：感知环境中物体的运动对日常生活的许多方面都至关重要。尽管我们对视觉运动感知的神经基础了解很多，但几乎所有这些知识都来自于观察者的眼睛和头部保持静止的实验。当观察者在环境中移动时，物体在视网膜上的运动既取决于物体在世界中的运动，也取决于观察者的自我运动。因此，要估计世界上物体的运动，也必须估计自运动并将其考虑到计算中。这种能力对于日常活动至关重要，例如驾驶车辆，在此期间，准确判断环境中其他物体（例如其他车辆或行人）的运动非常重要。众所周知，在阿尔茨海默病等神经系统疾病和正常衰老过程中，自我运动知觉会退化，因此了解自我运动过程中物体运动知觉的神经基础对于开发治疗这些缺陷的方法具有重要意义。为了开始研究神经回路在哪里以及如何补偿自我运动和计算世界上物体的运动，我们试图建立一个猕猴自我运动过程中物体运动感知的模型。这一努力带来了一些严重的技术和分析挑战，因此我们寻求探索性/发展性研究资助来开发一个有效的动物模型来研究这个问题。目标1寻求发展一种行为范式，在这种范式中，猕猴被训练在自我运动时判断物体的运动，并以世界为中心或以视网膜为中心的坐标报告它们的感知。自我运动的视觉和前庭信号将分别和一起呈现，以确定前庭信号对这项任务的贡献。我们的假设是前庭信号对计算有重要贡献

DESCRIPTION (provided by applicant): Perceiving the motion of objects in our environment is critical to many aspects of daily life. Although much is known about the neural basis of visual motion perception, almost all of that knowledge is derived from experiments in which the observer's eyes and head remain stationary. When an observer is moving through the environment, the motion of an object on the retina depends on both the movement of the object in the world and the self-motion of the observer. Thus, to estimate the motion of objects in the world, self-motion must also be estimated and factored into the computation. This capability is critical to daily activities such as driving a vehicle, during which it is important to accurately judge the movement of other objects in the environment, such as other vehicles or pedestrians. As perception of self-motion is known to be degraded in neurological disorders such as Alzheimer's disease and during normal aging, understanding the neural basis of object motion perception during self-motion is of substantial importance to developing therapies for these deficits. To begin to study where and how neural circuits compensate for self-motion and compute the motion of objects in the world, we seek to develop a macaque model of object motion perception during self-motion. This endeavor poses some serious technical and analytical challenges, thus we seek an Exploratory/Developmental Research grant to develop an effective animal model to study this problem. Aim #1 seeks to develop a behavioral paradigm in which macaques are trained to judge object motion during self-motion, and to report their percepts in world-centered or retinocentric coordinates. Visual and vestibular cues to self-motion will be presented separately and together to determine the contribution of vestibular signals to this task. Our hypothesis is that vestibular signals contribute importantly to computing object motion in world coordinates. Aim #2 seeks to record from single neurons in area MST during performance of the object motion discrimination task. By analyzing single-unit responses and decoding population responses, we will explore the neural mechanisms by which retinal image motion is transformed into a representation of object motion in the world.