The Relationship between Real-Time EEG Engagement, Distraction and Workload Estimates and Simulator-Based Driving Performance

Identifying potentially impaired drivers is often dependent upon using cognitive testing from a controlled environment (clinic, laboratory) to predict behavior in a dynamic and unpredictable real world driving environment. The goal of this study was to determine the feasibility, and validity, of using a wireless EEG system to ultimately differentiate between impaired and unimpaired drivers. We utilized the B-Alert X10 portable wireless EEG/ECG system and applied previously validated EEG algorithms estimating engagement, workload, and distraction within a sample of normal control (n = 10) and HIV seropositive individuals (n = 14). Participants underwent a 30-minute fully interactive driving simulation. Overall, the HIV+ group evidenced significantly higher distraction during the simulation. When grouped according to poor and good performers on the simulation (regardless of HIV serostatus), those performing worse on the simulation had higher distraction, with a trend for lower workload, levels. We then examined EEG profiles immediately preceding a crash. Prior to a crash, participants evidenced a significant increase in distraction ~ 10-14 seconds leading up to the crash; the greatest increase was seen in the HIV+ group. These preliminary data support the potential utility of using EEG data in patient populations to identify individuals who might be at risk for impaired drivin

Test-Retest Reliability of Standard Deviation of Lane Position as Assessed on a PC-Based Driving Simulator

Driving is an everyday activity that is commonly affected by neurologic disorders and medical treatments. A frequently used metric for assessing driving ability is the standard deviation of lane position (SDLP), or the amount that subjects “swerve” within their driving lane. This measurement has been used with individuals under the influence of alcohol, illicit drugs, and prescribed medications in both on-road and simulator studies. Although good test-retest reliability is critical if one is to measure change in individuals over time, there is surprisingly limited data regarding the test-retest reliability of SDLP. Objective. To examine the test-retest reliability of SDLP in subjects tested at (1) a 3-month retest interval (a time frame common to clinical trials), and (2) a year or longer retest interval (a time period over which one might track changes in neurologic patients. Methods. Group 1 completed retesting an average of 84 (s.d. = 8.1) days after their initial simulator assessment. Both HIV negative (HIV-; n = 16) and positive (HIV+; n = 13) subjects were included to explore short-term reliability in control and mildly ill patient groups. All HIV+ subjects were medically asymptomatic, and unlikely to experience HIV-related changes over this interval. Two HIV+ subjects were neuropsychologically (NP) impaired. Group 2 (n = 31), a different cohort, was retested an average of 19.8 (8.3) months after baseline. All subjects completed NP evaluations at baseline and follow-up, with NP status rated on a scale of 1 (above average) to 9 (severe impairment) by a clinician blinded to simulator performance. Twelve subjects (39%) were NP impaired. In order to examine reliability in a stable neurologic cohort, all subjects were selected because they remained at the same level of NP functioning at follow-up. SDLP was assessed in both groups using an interactive PC-based driving simulator that consisted of a monitor, steering wheel, and brake/accelerator pedals. Participants were required to maintain lane position while holding a constant speed (55 mph) and responding to divided attention tasks in the corner of the monitor. Group 2 completed an existing, standardized scenario (TOPS), while Group 1 completed a newly developed driving scenario. Both simulations lasted approximately 7 minutes. Results. Combined reliability for Group 1 was .74. Test-retest reliability was .68 for the HIVand .83 for the HIV+ subjects. For Group 2, SDLP was significantly correlated with NP functioning at baseline (r = .5, p = .005) and follow-up (r = .48, p = .006), with impaired subjects evidencing a higher SDLP than NP normal subjects at both baseline (mean of 1.9 vs 1.2; p = .006) and follow-up (1.7 vs 1.1, p = .01). Combined test-retest reliability for Group 2 was .86. The NP normal group had a test-retest reliability of .74; test-retest reliability for the NP impaired group was .87. Conclusions. SDLP is a reliable measure for periods ranging from months to years when assessed in cognitively stable subjects. As such, this may serve as a useful tool in tracking the effects of neurologic disorders and pharmacologic treatments on driving abilities

Driving Simulator Performance Across the Lifespan: A Preliminary Study

OBJECTIVES Normal aging is associated with decline in abilities that may put an individual at increased riskfor a crash. Older individuals may have slowed processing speed and motor responses, a reduceduseful field of view (Ball et al., 1988), and greater difficulty with mental rotation (Armstrong etal., 1998). Although collision rates increase with age (Transportation Research Board, 1988), ithas been argued that specific age-related functional impairments, and not age itself, put one atrisk (Ball & Owsley, 2003). The goal of this study was to examine the relationship betweenaging and performance on driving simulations assessing specific components of driving—accident avoidance, divided attention, and navigation—and the degree to which they predict onroaddriving performance.METHODSForty control drivers (age 22 to 84; \u3c 50 yo, n = 14; 50-70 yo, n = 13; and \u3e 70 yo, n = 13)completed 3 simulations and an on-road driving evaluation. Exclusion criteria includedneurologic confounds, substance use and psychiatric disorders, as well as abnormalneuropsychological performance (based upon demographically-corrected norms). Thesimulations were presented on a Pentium III PC computer using a 17” monitor at 1280 x 1024resolution, and running STISIM Drive version 2.0 software (Systems Technology, Inc.;Hawthorne, CA). Hardware included a steering wheel, turn signal, and brake/accelerator pedals.The simulations consisted of 1) Advanced Routine and Emergency Driving (ARED), a 15-minute route simulating city/country driving, in which drivers must obey traffic signs, pass cars,and respond to high-risk crash scenarios; 2) Virtual City (VC), in which drivers must navigate toand from a location in a 5 x 5 block simulated city, and 3) Divided Attention, in which driversare to maintain a constant speed and lane position while responding to divided attention tasks inthe corner of the monitor. Participants also completed a 35-minute on-road assessment. Lastly,participants were assessed on a battery of neuropsychological tests. Earlier versions of thesimulations were predictive of on-road driving performance in an HIV-infected cohort (Marcotteet al., 2004). RESULTSThe three groups performed similarly on ARED (crashes, speeding tickets), as well as on the VCtask when the map was oriented to the same direction as the participant. On the other hand, olderparticipants had significantly more difficulty navigating when their orientation on the map wasreversed (e.g., the \u3c 50 group took 1.2 blocks beyond optimum to return from the destination; the50-70 and \u3e 70 years old groups took approximately 7.5 blocks). The three groups performedsimilarly with respect to lane deviation on the Divided Attention task, but the older groups hadincreased variability in speed maintenance, and the oldest group failed to respond to a greaternumber of divided attention stimuli (\u3c 50 yo = .3 (.83), 50-70 yo = 1.0 (1.3), \u3e 70 yo = 3.6 (2.7)).Although only one participant failed the on-road drive (50-70 yo), the percent of driversconsidered marginal or worse increased with age (7% vs. 25% vs. 55%). In a logistic regression,the simulator variables that best discriminated safe vs. marginal on-road came from the DividedAttention task: the number of missed stimuli and speed deviation, both of which require an intactuseful field of view and the shifting of gaze away from the roadway. Age did not enter into amodel that included these variables.CONCLUSIONSIn this study of normal, healthy controls, older participants drove similarly to young-to-middleaged participants on a simulation that most closely approximated real driving. Consistent withcognitive declines seen in normal aging, older participants had greater difficulty on a taskrequiring navigating when map orientation was reversed (perhaps indicative of impairedegocentric spatial abilities), as well as on a measure of driving-related divided attention, witholder participants appearing to allocate more attention to the roadway at the cost of attending andresponding to peripheral cues. Although older drivers had more difficulty during the on-road test,these difficulties were a function of deficits in the ability to divide attention efficiently, ratherthan aging per se.REFERENCESArmstrong, C.L., & Cloud, B. (1998). The emergence of spatial rotation deficits in dementia andnormal aging. Neuropsychology, 12(2), 208-217.Ball, K.K., Beard, B.L., Roenker, D.L., Miller, R.L., & Griggs, D.S. (1988). Age and visualsearch: Expanding the useful field of view. J Opt Soc Am A, 5(12), 2210-2219.Ball, K., & Owsley, C. (2003). Driving competence: It\u27s not a matter of age. J Am Geriatr Soc,51(10), 1499-1501.Marcotte, T.D., Wolfson, T., Rosenthal, T.J., Heaton, R.K., Gonzalez, R., Ellis, R.J., et al.(2004). A multimodal assessment of driving performance in HIV infection. Neurology, 63(8),1417-1422.Transportation Research Board. (1988). Transportation in an Aging Society, Vol 1. Washington,D.C.: National Research Council

The Impact of Cognitive Deficits and Spasticity on Driving Simulator Performance in Multiple Sclerosis

Multiple sclerosis (MS) is a demyelinating disease that can result in numerous sequelae. Although spasticity and cognitive dysfunction are common in MS, few studies have examined the impact of both factors on driving abilities in persons with physical impairments. The present study assessed driving performance in control participants and MS patients with documented spasticity using two brief simulations designed to measure lane tracking (under high cognitive load) and car following behavior. Seventeen MS patients and 9 controls participated in the study. The MS cohort exhibited a broad range of cognitive functioning (normal to significant impairment) and disability (Expanded Disability Status Scale scores of 3.0 to 7.5). Eight of the MS patients had significant spasticity in their right knee based upon the Modified Ashworth Spasticity Scale. MS patients had greater difficulty than controls on the simulations, particularly on the car following task. MS participants also tended to drive at higher speeds than the control participants. Within the MS cohort, cognitive dysfunction was most strongly associated with lane tracking decrements, whereas the possible relationship between cognitive function and car following behavior was eclipsed by lower limb spasticity. Spastic individuals had greater difficulty mirroring speed changes in the lead car, and were approximately one second slower in responding to its accelerations and decelerations. The current simulations provide important data regarding the impact various MS sequelae may have on driving performance, and may ultimately lead to clinical recommendations regarding specific driving behaviors and their associated risks

Application of regulatory sequence analysis and metabolic network analysis to the interpretation of gene expression data

We present two complementary approaches for the interpretation of clusters of co-regulated genes, such as those obtained from DNA chips and related methods. Starting from a cluster of genes with similar expression profiles, two basic questions can be asked: 1. Which mechanism is responsible for the coordinated transcriptional response of the genes? This question is approached by extracting motifs that are shared between the upstream sequences of these genes. The motifs extracted are putative cis-acting regulatory elements. 2. What is the physiological meaning for the cell to express together these genes? One way to answer the question is to search for potential metabolic pathways that could be catalyzed by the products of the genes. This can be done by selecting the genes from the cluster that code for enzymes, and trying to assemble the catalyzed reactions to form metabolic pathways. We present tools to answer these two questions, and we illustrate their use with selected examples in the yeast Saccharomyces cerevisiae. The tools are available on the web (http://ucmb.ulb.ac.be/bioinformatics/rsa-tools/; http://www.ebi.ac.uk/research/pfbp/; http://www.soi.city.ac.uk/~msch/)

Validation of a liquid chromatography-tandem mass spectrometry method for analyzing cannabinoids in oral fluid.

A liquid chromatography tandem mass spectrometry method was developed for quantifying ten cannabinoids in oral fluid (OF). This method utilizes OF collected by the Quantisal™ device and concurrently quantifies cannabinol (CBN), cannabidiol (CBD), Δ9-tetrahydrocannabinol (THC), 11-hydroxy-Δ9-THC (11-OH-THC), 11-nor-9-carboxy-Δ9-THC (THC-COOH), 11-nor-9-carboxy-Δ9-THC glucuronide (THC-COOH-gluc), Δ9-THC glucuronide (THC-gluc), cannabigerol (CBG), tetrahydrocannabiverin (THCV), and Δ9-tetrahydrocannabinolic acid A (THCA-A). Solid phase extraction was optimized using Oasis Prime HLB 30 mg 96-well plates. Cannabinoids were separated by liquid chromatography over a BEH C18 column and detected by a Waters TQ-S micro tandem mass spectrometer. The lower limits of quantification (LLOQ) were 0.4 ng/mL for CBN, CBD, THC, 11-OH-THC, THC-gluc, and THCV; and 1.0 ng/mL for THC-COOH, THC-COOH-gluc, CBG and THCA-A. Linear ranges extended to 2000 ng/mL for THC and 200 ng/mL for all other analytes. Inter-day analytical bias and imprecision at three levels of quality control (QC) was within ±15%. Mean extraction efficiencies ranged from 26.0-98.8%. Applicability of this method was tested using samples collected from individuals randomly assigned to smoke either a joint containing <0.1%, 5.9%, or 13.4% THC content. This method was able to identify and calculate the concentration of 6 of 10 cannabinoids validated in this method

Validation of a liquid chromatography tandem mass spectrometry (LC-MS/MS) method to detect cannabinoids in whole blood and breath.

Background The widespread availability of cannabis raises concerns regarding its effect on driving performance and operation of complex equipment. Currently, there are no established safe driving limits regarding ∆9-tetrahydrocannabinol (THC) concentrations in blood or breath. Daily cannabis users build up a large body burden of THC with residual excretion for days or weeks after the start of abstinence. Therefore, it is critical to have a sensitive and specific analytical assay that quantifies THC, the main psychoactive component of cannabis, and multiple metabolites to improve interpretation of cannabinoids in blood; some analytes may indicate recent use. Methods A liquid chromatography tandem mass spectrometry (LC-MS/MS) method was developed to quantify THC, cannabinol (CBN), cannabidiol (CBD), 11-hydroxy-THC (11-OH-THC), (±)-11-nor-9-carboxy-Δ9-THC (THCCOOH), (+)-11-nor-Δ9-THC-9-carboxylic acid glucuronide (THCCOOH-gluc), cannabigerol (CBG), and tetrahydrocannabivarin (THCV) in whole blood (WB). WB samples were prepared by solid-phase extraction (SPE) and quantified by LC-MS/MS. A rapid and simple method involving methanol elution of THC in breath collected in SensAbues® devices was optimized. Results Lower limits of quantification ranged from 0.5 to 2 μg/L in WB. An LLOQ of 80 pg/pad was achieved for THC concentrations in breath. Calibration curves were linear (R2>0.995) with calibrator concentrations within ±15% of their target and quality control (QC) bias and imprecision ≤15%. No major matrix effects or drug interferences were observed. Conclusions The methods were robust and adequately quantified cannabinoids in biological blood and breath samples. These methods will be used to identify cannabinoid concentrations in an upcoming study of the effects of cannabis on driving

Genetic attributes of cerebrospinal fluid-derived HIV-1 env

HIV-1 often invades the CNS during primary infection, eventually resulting in neurological disorders in up to 50% of untreated patients. The CNS is a distinct viral reservoir, differing from peripheral tissues in immunological surveillance, target cell characteristics and antiretroviral penetration. Neurotropic HIV-1 likely develops distinct genotypic characteristics in response to this unique selective environment. We sought to catalogue the genetic features of CNS-derived HIV-1 by analysing 456 clonal RNA sequences of the C2-V3 env subregion generated from CSF and plasma of 18 chronically infected individuals. Neuropsychological performance of all subjects was evaluated and summarized as a global deficit score. A battery of phylogenetic, statistical and machine learning tools was applied to these data to identify genetic features associated with HIV-1 neurotropism and neurovirulence. Eleven of 18 individuals exhibited significant viral compartmentalization between blood and CSF (P < 0.01, Slatkin-Maddison test). A CSF-specific genetic signature was identified, comprising positions 9, 13 and 19 of the V3 loop. The residue at position 5 of the V3 loop was highly correlated with neurocognitive deficit (P < 0.0025, Fisher's exact test). Antibody-mediated HIV-1 neutralizing activity was significantly reduced in CSF with respect to autologous blood plasma (P < 0.042, Student's t-test). Accordingly, CSF-derived sequences exhibited constrained diversity and contained fewer glycosylated and positively selected sites. Our results suggest that there are several genetic features that distinguish CSF- and plasma-derived HIV-1 populations, probably reflecting altered cellular entry requirements and decreased immune pressure in the CNS. Furthermore, neurological impairment may be influenced by mutations within the viral V3 loop sequenc

EEG-Based Neurocognitive Metrics May Predict Simulated and On-Road Driving Performance in Older Drivers

The number of older drivers is steadily increasing, and advancing age is associated with a high rate of automobile crashes and fatalities. This can be attributed to a combination of factors including decline in sensory, motor, and cognitive functions due to natural aging or neurodegenerative diseases such as HIV-Associated Neurocognitive Disorder (HAND). Current clinical assessment methods only modestly predict impaired driving. Thus, there is a need for inexpensive and scalable tools to predict on-road driving performance. In this study EEG was acquired from 39 HIV+ patients and 63 healthy participants (HP) during: 3-Choice-Vigilance Task (3CVT), a 30-min driving simulator session, and a 12-mile on-road driving evaluation. Based on driving performance, a designation of Good/Poor (simulator) and Safe/Unsafe (on-road drive) was assigned to each participant. Event-related potentials (ERPs) obtained during 3CVT showed increased amplitude of the P200 component was associated with bad driving performance both during the on-road and simulated drive. This P200 effect was consistent across the HP and HIV+ groups, particularly over the left frontal-central region. Decreased amplitude of the late positive potential (LPP) during 3CVT, particularly over the left frontal regions, was associated with bad driving performance in the simulator. These EEG ERP metrics were shown to be associated with driving performance across participants independent of HIV status. During the on-road evaluation, Unsafe drivers exhibited higher EEG alpha power compared to Safe drivers. The results of this study are 2-fold. First, they demonstrate that high-quality EEG can be inexpensively and easily acquired during simulated and on-road driving assessments. Secondly, EEG metrics acquired during a sustained attention task (3CVT) are associated with driving performance, and these metrics could potentially be used to assess whether an individual has the cognitive skills necessary for safe driving