Abstract
Stereopsis is the rich impression of three-dimensionality, based on binocular disparity—the differences between the two retinal images of the same world. However, a substantial proportion of the population is stereo deficient, and relies mostly on monocular cues to judge the relative depth or distance of objects in the environment. In this study we trained eleven adults who were stereo blind or stereo deficient due to strabismus and/or amblyopia in a natural visuo-motor task – a "bug squashing" game - in a virtual reality (VR) environment. The subjects' task was to squash a virtual dichoptic bug on a slanted surface, by hitting it with a cylinder. The slant of the surface was determined by purely stereoscopic cues (stereo-cue trials), monocular texture as well as stereoscopic cues (cue-consistent trials), and conflicting monocular and stereo cues (cue-conflict trials). A motion-capture system tracked the 3D position and orientation of the cylinder. We determined the relative weight that participants gave to stereo cues by regressing the slant of the cylinder just prior to contact with the surface against the slant depicted by the texture and the slant depicted by stereoscopic disparities [Knill, 2005]. Following 35 training sessions of about 1hour, eight of the eleven participants (two anisometropic and six strabismic) showed greater reliance on stereoscopic cues, and improved stereo-acuity. Importantly, the training-induced changes in relative stereo weights were significant predictors of the improvements in stereoacuity. Additionally, all but one subject showed reduced suppression, and three also showed improved visual acuity. We conclude that some adults deprived of normal binocular vision and insensitive to the disparity information can, with experience in bug squashing, recover access to more reliable disparity information. Importantly, our bug squashing training involves integrating not just multiple visual cues, but also the rich information from tactile and kinesthetic feedback.
Meeting abstract presented at VSS 2016