Abstract
It is well known that the motor systems controlling the eyes and the hands are closely linked when executing tasks in peripersonal space. We examine how this coordination is affected by binocular and asymmetric monocular simulated visual impairment. In a stereoscopic display, human observers were required to closely track with their gaze a 1 degree Gabor patch moving in three dimensions on a 1/f noise background. The movement of the Gabor patch was either directly controlled by the observer's unseen hand in real time; or followed their hand movements executed in a previous trial. Hand position was recorded with a Leap Motion hand tracker, and gaze position was recorded with an Eyelink 1000 eye tracker. We simulated visual impairments by Gaussian blurring the visual stimuli independently in each eye. Tracking accuracy was defined as the average correlation coefficient between gaze position and target position along the fronto-parallel plane (pursuit) or the sagittal plane (vergence). We observed a critical blur level up to which pursuit and vergence eye movements maintained fronto-parallel and sagittal tracking accuracy independent of blur level. Monocular blur affected fronto-parallel tracking less than binocular blur, however small amounts of monocular blur impaired tracking in depth much more than binocular blur. Target tracking was more accurate when observers were directly controlling the stimulus than when they tracked a previous hand movement and this benefit was more pronounced with degraded visual input. This suggests that under conditions of visual uncertainty, proprioceptive information is weighed more heavily. Our results confirm that the motor control signals that guide hand movements are utilized by the visual system to plan eye movements. Our findings suggest that hand-eye coordination might be monitored to better understand functional impairments associated with eye disease and may be employed to rehabilitate an array of monocular and binocular visual impairments.
Meeting abstract presented at VSS 2016