Department of Kinesiology, University of Connecticut, Storrs, CT, 06269, USA.
Center for Ecological Study of Perception and Action, University of Connecticut, Storrs, CT, USA.
Exp Brain Res. 2021 Apr;239(4):1305-1316. doi: 10.1007/s00221-021-06066-z. Epub 2021 Feb 25.
The visual, vestibular, and haptic perceptual systems are each able to detect self-motion. Such information can be integrated during locomotion to perceive traversed distances. The process of distance integration is referred to as odometry. Visual odometry relies on information in optic flow patterns. For haptic odometry, such information is associated with leg movement patterns. Recently, it has been shown that haptic odometry is differently calibrated for different types of gaits. Here, we use this fact to examine the relative contributions of the perceptual systems to odometry. We studied a simple homing task in which participants travelled set distances away from an initial starting location (outbound phase), before turning and attempting to walk back to that location (inbound phase). We manipulated whether outbound gait was a walk or a gallop-walk. We also manipulated the outbound availability of optic flow. Inbound reports were performed via walking with eyes closed. Consistent with previous studies of haptic odometry, inbound reports were shorter when the outbound gait was a gallop-walk. We showed that the availability of optic flow decreased this effect. In contrast, the availability of optic flow did not have an observable effect when the outbound gait was walking. We interpreted this to suggest that visual odometry and haptic odometry via walking are similarly calibrated. By measuring the decrease in shortening in the gallop-walk condition, and scaling it relative to the walk condition, we estimated a relative contribution of optic flow to odometry of 41%. Our results present a proof of concept for a new, potentially more generalizable, method for examining the contributions of different perceptual systems to odometry, and by extension, path integration. We discuss implications for understanding human wayfinding.
视觉、前庭和触觉感知系统各自都能够检测到自身运动。这些信息可以在运动过程中进行整合,以感知所经过的距离。这个距离整合的过程被称为里程计。视觉里程计依赖于光流模式中的信息。对于触觉里程计,这些信息与腿部运动模式相关联。最近,已经表明触觉里程计针对不同类型的步态进行了不同的校准。在这里,我们利用这一事实来研究不同感知系统对里程计的相对贡献。我们进行了一项简单的归巢任务研究,参与者在远离初始起始位置的地方行进设定的距离(离站阶段),然后转身并尝试走回该位置(归站阶段)。我们操纵离站步态是步行还是奔步行走。我们还操纵了离站时是否有光流可用。归站报告是在闭着眼睛行走时进行的。与之前的触觉里程计研究一致,当离站步态是奔步行走时,归站报告的距离更短。我们表明,光流的可用性降低了这种效果。相比之下,当离站步态是步行时,光流的可用性对该效果没有明显影响。我们将此解释为表明视觉里程计和通过步行的触觉里程计具有相似的校准。通过测量奔步行走条件下的缩短程度的减少,并将其相对于步行条件进行缩放,我们估计了光流对里程计的相对贡献为 41%。我们的结果为一种新的、潜在更具通用性的方法提供了一个概念验证,用于研究不同感知系统对里程计、进而对路径整合的贡献。我们讨论了对理解人类寻路的意义。