Stroke continues to be the leading cause of long-term disability among adults and its prevalence will continue to rise as the population ages. Developing analytical strategies for improving quality of life and independence following stroke are of tall importance. For this endeavor to be successful, a critical and necessary step is to understand the neuro-scientific basis of the underlying mechanisms. and to integrate this knowledge with the translational science of rehabilitation. This is what we propose to do. Over the next 2 years, we propose a quantitative and multifaceted research program that integrates neurology, neuroscience, psychophysics and brain imaging to study the visual mechanisms directly relevant to visually guided behavior and the effects of brain lesions (from stroke) on patients'ability to carry out everyday activities. We employ a hypothesis-driven approach to provide a solid scientific basis for integrating basic neuroscience with the translational science of recovery and rehabilitation. We have three Specific Aims: Aim 1. To characterize the mechanisms for recovering an object's 3D motion during selfmotion through the environment. We test the hypothesis that recovery of object trajectory during selfmotion requires the visual system to account for the induced motion of stationary objects in the scene. Aim 2. To examine the functional organization of visual motion processing for collision detection in the human brain and test the sufficiency of alternate visual cues and behavioral strategies when primary mechanisms are impaired. We test the hypothesis that collision detection is mediated by a distributed network of relative motion mechanisms that support obstacle avoidance and investigate the use of alternative strategies for recovering obstacle avoidance following stroke. Aim 3. To determine the relationship between performance on early visual motion tasks and activities of visually guided navigation. The experimental results obtained from patients on the screening tests batteries will be analyzed across the patient population using quantitative statistical analysis (k-means clustering) to identify clusters of early visual motion and attention tests that diagnostic of selective deficits in stroke patients. The work we propose to carry out over the next two years will elucidate the neuronal substrate of essential visual mechanisms involved in visually guided navigation and explore alternate cues that patients impaired on these tasks may use for coping with specific aspects of their environment. Furthermore, we expect that the outcome of the research proposed here will have a significant clinical impact on future design of targeted neurorehabilitative therapies for functional recovery from deficits of visually guided navigation and mobility.