Abstracts

Rationale: Generalized spike-wave discharges (SWD) occur in generalized epilepsy and have highly variable effects on cognition and/or behavior. Using the Repetitive Tapping Task (RTT) and the more attention-demanding Continuous Performance Task (CPT), our previous investigations show that the amplitude and duration of SWD on EEG may predict performance on these relatively simple tasks. Cognitive and behavioral impairment in more complex tasks like driving has been studied in previous work using computerized driving games. This work suggests that generalized SWD may affect car positioning and prolong reaction time to road obstacles. “Seizure-free” patients who are granted driving privileges may still have subclinical epileptiform SWD associated with transient impairments in cognition and/or behavior, presenting a challenge to patients, clinicians, and driver licensing regulators as they seek to balance patients’ rights and public safety. Consequently, there is a need to characterize the impact of generalized SWD on driving and identifying objective, clinically-available predictors of impaired driving behavior during generalized SWD. We have established a practicable paradigm to test driving behavior during subclinical generalized SWD and to potentially identify EEG features of generalized SWD that impair driving. Methods: Patients 15 years or older, diagnosed with generalized epilepsy and with generalized SWD on ambulatory EEG and no clinical seizures in the preceding month, drive for an hour in a half-cab high-fidelity driving simulator (miniSim^TM) equipped for video and high-density EEG recording. A virtual road obstacle is manually presented every 5 minutes for baseline testing, as well as during each SWD episode. Subjects are instructed to safely pull over when the obstacle is presented. The driving simulator records more than 200 variables throughout the drive. Results: To date, we succeeded in recording reaction time (calculated as time (in msec) between obstacle presentation and application of brakes), brake force (lbs), vehicle speed (mph) and rate of change of steering wheel angle (degrees/sec) at baseline and during 5 SWD episodes in 2 patients with generalized epilepsy. The road obstacle was successfully presented during SWD with a mean delay of 1.46 seconds from onset of SWD. With further EEG and behavioral data collection we anticipate obtaining sufficient SWD with and without impaired driving. Machine learning algorithms will be used to classify SWD as “sparing” vs “impairing” driving ability. Conclusions: This study demonstrates that high-fidelity driving simulators instrumented for HD-EEG and video-monitoring are feasible tools for studying driving behavior in patients with epilepsy. This approach provides a previously unexplored avenue for studying driving safety among patients with epilepsy, particularly in potentially identifying EEG features that may predict driving impairment in subclinical generalized SWD.   Funding: This work was supported by the Betsy and Jonathan Blattmachr Family, the Loughridge Williams Foundation and the NIH CTSA TL1TR000141.