Using Virtual Reality Driving Simulation And A New Responsiveness In Epilepsy Scale To Investigate Impaired Consciousness In Epileptic Seizures

Part one:Using virtual reality driving stimulation to investigate impaired consciousness in epilepsyBackground and objectiveLoss of consciousness during seizures is a major mechanism of morbidity and mortality in epilepsy. Frequent seizure attacks interfere with patients'daily activities, reduce the cognitive functions and responsiveness, diminish school and work performance, and lead to social stigma. Furthermore, patients with epilepsy are at increased risk of injuries, drowning, accidental suffocation, and serious automobile accidents, compared to the general population, presumably due to temporary impairment in their ability to interact consciously with their environment during seizures. Numerous retrospective studies have shown patients with epilepsy have approximately twice of accidental incidence during driving. Thus, most developed countries impose restrictions on driving ability for epilepsy patients. However, driving is an essential part of normal daily life in the modern age, and depriving patients of driving privileges can have enormous consequences on their economic and social well-being, as well as employeement. The question of how to restrict driving is emblematic of the dilemmas faced by regulators, and clinicians related to impaired consciousness in epilepsy. Though laws vary, many jurisdictions have addressed these competing priorities by requiring patients to have a seizure-free interval, usually one year, before resuming driving. Several problems exist with this approach. First, the regulatations were not based on detailed research data actually acquired during seizures; second, many patients do not abide by their driving restrictions; furthermore, one-size-fits-all waiting periods fail to account for the vast differences between different seizure types, especially in terms of their impairment of consciousness.To our knowledge, no one has directly observed patients driving or performing driving-like tasks during seizures to determine if there are differential effects of different seizure types on driving ability. Probably due to the unpredictability of seizures, difficulties in time synchronizing of patients'behavior and EEG, shortage of established driving model, and the conflict between the intense magnetic field in fMRI and research equipment etc. However, driving simulators and instrumented vehicles have been used successfully to study the mechanisms and effects of other conditions associated with driving safety problems, such as alcohol intoxication, Alzheimer's disease and excessive daytime sleepiness.The purpose of the study is to use a newly developed virtual reality driving stimulation technique to directly observe driving behaviors and performances during epileptic seizures, and to use variables related to driving safety such us collisions, steering wheel velocity, throttle position, car velocity to gain insight into whether different types of seizures have different effects on driving ability. Moreover, this study innovatively combined continuous video-EEG monitoring, functional magnetic resonance, SPECT and other imaging and electrophysiological techniques to evaluate impaired consciousness in epilepsy. The feasibility and validity of this method has been evaluated. This methodology may ultimately lead to further investigation on the brain regions related to impaired consciousness in epilepsy, its anatomical network mechanisms, and targets for future drug and surgical treatment. Methods1.This study developed a rFactor driving game based virtual reality driving simulation model. Driving data were output by program code as different variables. All driving data output an electrical timing-TTL pulse generated every 1/30s to facilitate synchronization of system data with that of the clinical data collection system by millisecond.2.Patients are incentivized to drive as much as possible. Spontaneous seizures were induced by AED tapering, photic stimulation, sleep deprivation etc.We use this system to capture the seizure events occurred with patients with epilepsy undergoing continuous video/EEG monitoring. By VEEG analysis, events were classified as:?interictal activity,?subclinical seizures,?auras,?partial seizures,?absence seizures or?secondarily generalized tonic-clonic seizures by neurologists specializing in epilepsy at Yale epilepsy center. Patients'driving performance were analyzed.3.We use MATLAB to calculate the following variables over time: steering wheel velocity, throttle position, car position and car velocity. Seizure onset time, offset time, and any collisions were marked. A random four minute period with no epileptiform activity for each patient who had seizure during driving were selected for impairement comparison. The impairmend criteria were set up for each variable. Each seizure was then analyzed for evidence of impairment in one of the four variables. The variables were analyzed according to seizure types as well as behaviors. Results1. Participation and feasibility:from Oct,2008 to Feb,2009, a total of 91 patients with epilepsy participated in this study from Yale epilepsy program. (18 pediatrics and 73 adults,45 males and 46 females, mean age 30.9y, range 7-64y). The mean time of driving per patient was 268 min. There were no significant differences of driving time based on adult vs. pediatric patients or based on gender. A total of 13 patients (14.3% of participants) had seizures while driving. The overall number of seizures captured while patients driving was 22, an average of one seizure every 18.5 h of driving. In addition, there were a total of 105 interictal discharges in 14 patients while driving.2. Behavioral results based on video review:Patients demonstrate differences on driving performance during different types of seizure events. During subclinical seizures, patients continued to interact with driving stimulator. During two of five auras, patients continued to drive, but either to explain the symptoms or to push the event button during driving. Ictal behavior varied greatly during seven partial seizures while driving. Some patients continued to drive, others stopped driving. During total of five absence seizures, the patient appeared to have no obvious cognitive impairment during driving activity. During two secondarily generalized tonic-clonic seizures, the patient exhibited a dystonic posture suddenly and stopped pressing throttle while his right hand continued moving the steering wheel back and forth by automatism.3. Driving performance based on rFactor output data:Each seizure was analyzed for impairment based on the presence of collisions and/or decreased steering wheel velocity, throttle position, or car velocity. None (0%) of the subclinical seizures met our criteria for impairment in any of the rFactor output variables.75% partial seizures met our criteria for impairment in at least one category. Steering wheel velocity was impaired in one of three events (33% ), whereas throttle and vehicle speed were impaired in two of three events (67%). Total 4 collisions occurred during 4 seizures.50% of absence seizures demonstrated impairment according to our criteria. Neither of the absence seizures (0%) showed impairment in steering wheel velocity, throttle, or car velocity. There were three collisions during one of the seizures.100% of secondarily generalized tonic clonic seizures involved impairment of at least one variable. Steering wheel velocity was impaired in one of two seizures (50%), throttle and vehicle speed were impaired in both secondarily generalized tonic-clonic seizures (100%).There were no collisions during secondarily generalized tonic-clonic seizures.Conclusions1. This study has for the first time demonstrated that using a rFactor based virtual reality driving smilation system to investigate driving performance by recruiting patients with epilepsy during 24h video/EEG monitoring is feasible.2. We have identified preliminary trends regarding the differential effects of different types of seizures on driving performance and driving ability.3. These results could be extended to identify brain regions implicated in impaired driving performance during seizures. This new prospective approach will be useful both to patients and to their health care providers in guiding decisions on driving safety, and ultimately may also facilitate the development of drug or surgical target treatments that reduce driving risk in epilepsy.Part Two:Using a new Responsiveness in Epilepsy Scale to investigate impaired consciousness in epileptic seizuresBackground and objectiveImpaired consciousness in epileptic seizures has a major negative impact on patient quality of life. Prior work on epileptic unconsciousness has mainly used retrospective and nonstandardized methods. Our goal was to validate and to obtain initial data using a standardized prospective testing battery.MethodsThe responsiveness in epilepsy scale (RES) was used on 52 patients during continuous video/EEG monitoring. RES begins with higher-level questions and commands, and switches adaptively to more basic sensorimotor responses depending on patient performance. RES continues after seizures and includes postictal memory testing. Scoring was conducted based on video review.ResultsTesting on standardized seizure simulations yielded good intra-rater and inter-rater reliability. We captured 59 seizures from 18 patients (35% of participants) during 1420 hours of RES monitoring. RES impairment was greatest during and after generalized tonic-clonic seizures, less in partial seizures, and minimal in auras and subclinical seizures. In partial seizures, ictal RES impairment was significantly greater if EEG changes were present. Maximum RES impairment (lowest ictal score) was also significantly correlated with long postictal recovery time, and poor postictal memory.Conclusions1. Prospective testing of responsiveness during seizures is feasible and reliable.2.RES impairment was related to EEG changes during seizures, as well as to postictal memory deficits and recovery time.3.With a larger patient sample it is hoped that this approach can identify brain networks underlying specific components of impaired consciousness in seizures. This may allow the development of improved treatments targeted at preventing dysfunction in these networks.