The purpose of this research is to better understand the impact of cortically-induced blindness (CB) and the compensatory strategies subjects with this condition may develop on naturalistic behaviors, specifically, driving. Using a novel Virtual Reality (VR) program, the researchers will gather data on steering behavior in a variety of simulated naturalistic environments. Through the combined use of computer vision, deep learning, and gaze-contingent manipulations of the visual field, this work will test the central hypothesis that changes to visually guided steering behaviors in CB are a consequence of changes to the visual sampling and processing of task-related motion information (i.e., optic flow).
Residents of the United States or Canada
Presence of one-sided stroke or stroke-like damage to primary visual cortex or its immediate afferent white matter sustained within the specified age range of 21 - 75 years (verified by MRI and/or CT scans)
Reliable visual field defects in both eyes (homonymous defects) as measured by Humphrey or equivalent perimetry.
Willing, able, and competent to provide their own informed consent
Those who have never driven or earned a drivers' license
Past or present ocular disease interfering with visual acuity
Best corrected visual acuity (BCVA) worse than 20/40 in either eye
Sustained damage to the dorsal lateral geniculate nucleus
University of Rochester
Lead sponsor
Rochester Institute of Technology
Collaborator