Chronic disability following stroke is a significant problem for Veterans that can affect a variety of daily activities. One area of importance in clinical assessment and treatment planning is the impact of stroke on driving safety. Unfortunately, formal assessments of driving fitness and related cognitive deficits (e.g., visuospatial changes) are often not conducted in left hemisphere stroke patients. The current project will address this gap by evaluating left hemisphere stroke patients on a state-of-the-art driving simulator, comparing their performance to that of both right hemisphere stroke patients and healthy controls. Driving variables assessed by the simulator include the number of collisions, unsafe lane crossings, speed exceedances, and reaction time to stop. Different types of driving errors will then be related to performance on a neuropsychological battery, which includes standardized and experimental measures of visuospatial ability, executive functioning, and language. Last, we will investigate the neural correlates of distinct types of driving errors using voxel-based lesion symptom mapping, which relates structural lesions to behavioral performance on a voxel-by-voxel basis. Participants for the current study include 40 left and 40 right hemisphere Veteran stroke patients with no prior neurologic or severe psychiatric history. A control group of 20 age- and education-matched Veterans with no neurologic or psychiatric history will provide additional context for interpretation of the data. Driving performance will be examined with a state-of-the-art driving simulator that has been demonstrated to have strong ecological validity and predictive validity with respect to on-road driving fitness. It is predicted that 60-70% of left hemisphere patients will exhibit impaired driving performance (?failed? or ?needs training? rating), significantly higher than healthy controls but not significantly different from right hemisphere patients. It is expected, however, that left hemisphere patients will show a distinct pattern of performance from right hemisphere patients. For example, it is expected that LH patients will exhibit disproportionately more errors under complex driving scenarios (e.g., in a construction zone), whereas both stroke groups will exhibit significant visuospatial driving errors (unsafe lane changes and collisions) relative to controls. Partial least squares regression will then be used to identify which neuropsychological measures are most closely related to driving performance variables measured in the simulator. It is predicted that driving errors in left hemisphere patients will correlate with both visuospatial measures (e.g., Useful Field of View/Visual Search) and executive functioning measures (e.g., Trails B). We also propose to relate structural lesion data from high-resolution 3T MRI scans to different types of driving errors. This aspect of the project will utilize voxel-based lesion symptom mapping (VLSM) software that our group helped develop. It is predicted that driving errors related to visuospatial inattention will be associated with lesions to a dorsal fronto-parietal network, whereas driving errors in complex driving scenarios will be additionally associated with lesions to a more ventral network that includes left inferior parietal and prefrontal cortex. In summary, the findings from our study will provide critical information as to the importance of driving safety referrals and evaluations following stroke, particularly in left hemisphere stroke patients. This study will advance the field by identifying neuropsychological test performance and lesion locations that should be flags for additional concern about driving safety following stroke, as well as identifying differences among left and right hemisphere stroke patients. It is our hope that the findings from this study will not only inform clinicians and patients of potential driving risks, but will ultimately provide the type of data needed to support individualized training programs in simulated driving environments for Veterans who wish to return to driving.

Public Health Relevance

Stroke is a leading cause of adult disability affecting almost a million Americans every year and thousands of Veterans. Unfortunately, many individuals do not fully recover from stroke, leaving them with a number of deficits that affect their daily lives. Some of these deficits include changes in visual and cognitive functioning, which are critical for daily activities such as driving. Many stroke patients, however, return to driving without ever receiving a thorough assessment of visuospatial abilities and/or a formal driving evaluation. In the current study, we are proposing to relate cognitive deficits after stroke to driving performance on a driving simulator. Our main goals are to identify the neuropsychological tests (behavioral markers) and brain regions (biological markers) that are most related to driving performance. In addition, we will compare the types of driving errors made among patients with left versus right hemisphere stroke. Findings from this project can lead to improved education and evaluation of Veteran patients who wish to return to driving after stroke.

National Institute of Health (NIH)
Veterans Affairs (VA)
Non-HHS Research Projects (I01)
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Special Emphasis Panel (ZRD1)
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VA Northern California Health Care System
United States
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