Behavioral and Neurophysiological Signatures of Benzodiazepine-Related Driving Impairments.

Impaired driving due to drug use is a growing problem worldwide; estimates show that 18-23.5% of fatal accidents, and up to 34% of injury accidents may be caused by drivers under the influence of drugs (Drummer et al., 2003; Walsh et al., 2004; NHTSA, 2010). Furthermore, at any given time, up to 16% of drivers may be using drugs that can impair one's driving abilities (NHTSA, 2009). Currently, drug recognition experts (DREs; law enforcement officers with specialized training to identify drugged driving), have the most difficult time with identifying drivers potentially impaired on central nervous system (CNS) depressants (Smith et al., 2002). The fact that the use of benzodiazepines, a type of CNS depressant, is also associated with the greatest likelihood of causing accidents (Dassanayake et al., 2011), further emphasizes the need to improve research tools in this area which can facilitate the refinement of, or additions to, current assessments of impaired driving. Our laboratories collaborated to evaluate both the behavioral and neurophysiological effects of a benzodiazepine, alprazolam, in a driving simulation (miniSim(TM)). This drive was combined with a neurocognitive assessment utilizing time synched neurophysiology (electroencephalography, ECG). While the behavioral effects of benzodiazepines are well characterized (Rapoport et al., 2009), we hypothesized that, with the addition of real-time neurophysiology and the utilization of simulation and neurocognitive assessment, we could find objective assessments of drug impairment that could improve the detection capabilities of DREs. Our analyses revealed that (1) specific driving conditions were significantly more difficult for benzodiazepine impaired drivers and (2) the neurocognitive tasks' metrics were able to classify "impaired" vs. "unimpaired" with up to 80% accuracy based on lane position deviation and lane departures. While this work requires replication in larger studies, our results not only identified criteria that could potentially improve the identification of benzodiazepine intoxication by DREs, but also demonstrated the promise for future studies using this approach to improve upon current, real-world assessments of impaired driving.

Characterizing donation behavior from psychophysiological indices of narrative experience.

Research on narrative persuasion has yet to investigate whether this process influences behavior. The current study explored whether: (1) a narrative could persuade participants to donate to a charity, a prosocial, behavioral decision; (2) psychophysiological metrics can delineate the differences between donation/non-donation behaviors; and (3) donation behavior can be correlated with measures of psychophysiology, self-reported reactions to the narrative, and intrinsic characteristics. Participants (n = 49) completed personality/disposition questionnaires, viewed one of two versions of a narrative while EEG and ECG were recorded, completed a questionnaire regarding their reactions to the narrative, and were given an opportunity to donate to a charity related to the themes of the narrative. Results showed that: (1) 34.7% of participants donated; (2) psychophysiological metrics successfully delineated between donation behaviors and the effects of narrative version; and (3) psychophysiology and reactions to the narrative were better able to explain the variance (88 and 65%, respectively) in the amount donated than all 3 metrics combined as well as any metric alone. These findings demonstrate the promise of narrative persuasion for influencing prosocial, behavioral decisions. Our results also illustrate the utility of the previously stated metrics for understanding and possibly even manipulating behaviors resulting from narrative persuasion.

Identifying psychophysiological indices of expert vs. novice performance in deadly force judgment and decision making.

OBJECTIVE: To demonstrate that psychophysiology may have applications for objective assessment of expertise development in deadly force judgment and decision making (DFJDM). BACKGROUND: Modern training techniques focus on improving decision-making skills with participative assessment between trainees and subject matter experts primarily through subjective observation. OBJECTIVE metrics need to be developed. The current proof of concept study explored the potential for psychophysiological metrics in deadly force judgment contexts. METHOD: Twenty-four participants (novice, expert) were recruited. All wore a wireless Electroencephalography (EEG) device to collect psychophysiological data during high-fidelity simulated deadly force judgment and decision-making simulations using a modified Glock firearm. Participants were exposed to 27 video scenarios, one-third of which would have justified use of deadly force. Pass/fail was determined by whether the participant used deadly force appropriately. RESULTS: Experts had a significantly higher pass rate compared to novices (p < 0.05). Multiple metrics were shown to distinguish novices from experts. Hierarchical regression analyses indicate that psychophysiological variables are able to explain 72% of the variability in expert performance, but only 37% in novices. Discriminant function analysis (DFA) using psychophysiological metrics was able to discern between experts and novices with 72.6% accuracy. CONCLUSION: While limited due to small sample size, the results suggest that psychophysiology may be developed for use as an objective measure of expertise in DFDJM. Specifically, discriminant function measures may have the potential to objectively identify expert skill acquisition. APPLICATION: Psychophysiological metrics may create a performance model with the potential to optimize simulator-based DFJDM training. These performance models could be used for trainee feedback, and/or by the instructor to assess performance objectively.

EEG-derived estimators of present and future cognitive performance.

Previous electroencephalography (EEG)-based fatigue-related research primarily focused on the association between concurrent cognitive performance and time-locked physiology. The goal of this study was to investigate the capability of EEG to assess the impact of fatigue on both present and future cognitive performance during a 20-min sustained attention task, the 3-choice active vigilance task (3CVT), that requires subjects to discriminate one primary target from two secondary non-target geometric shapes. The current study demonstrated the ability of EEG to estimate not only present, but also future cognitive performance, utilizing a single, combined reaction time (RT), and accuracy performance metric. The correlations between observed and estimated performance, for both present and future performance, were strong (up to 0.89 and 0.79, respectively). The models were able to consistently estimate "unacceptable" performance throughout the entire 3CVT, i.e., excessively missed responses and/or slow RTs, while acceptable performance was recognized less accurately later in the task. The developed models were trained on a relatively large dataset (n = 50 subjects) to increase stability. Cross-validation results suggested the models were not over-fitted. This study indicates that EEG can be used to predict gross-performance degradations 5-15 min in advance.

Drowsiness/alertness algorithm development and validation using synchronized EEG and cognitive performance to individualize a generalized model.

A great deal of research over the last century has focused on drowsiness/alertness detection, as fatigue-related physical and cognitive impairments pose a serious risk to public health and safety. Available drowsiness/alertness detection solutions are unsatisfactory for a number of reasons: (1) lack of generalizability, (2) failure to address individual variability in generalized models, and/or (3) lack of a portable, un-tethered application. The current study aimed to address these issues, and determine if an individualized electroencephalography (EEG) based algorithm could be defined to track performance decrements associated with sleep loss, as this is the first step in developing a field deployable drowsiness/alertness detection system. The results indicated that an EEG-based algorithm, individualized using a series of brief "identification" tasks, was able to effectively track performance decrements associated with sleep deprivation. Future development will address the need for the algorithm to predict performance decrements due to sleep loss, and provide field applicability.

Glucocorticoid exposure alters the pathogenesis of Theiler's murine encephalomyelitis virus during acute infection.

Previous research has shown that chronic restraint stress exacerbates Theiler's virus infection, a murine model for CNS inflammation and multiple sclerosis. The current set of experiments was designed to evaluate the potential role of glucocorticoids in the deleterious effects of restraint stress on acute CNS inflammatory disease. Exposure to chronic restraint stress resulted in elevated levels of corticosterone as well as increased clinical scores and weight loss (Experiment 1). In addition, corticosterone administration alone exacerbated behavioral signs of TMEV-induced sickness (i.e. decreased body weight, increased symptoms of encephalitis, and increased mortality) and reduced inflammation in the CNS (Experiment 2). Infected subjects receiving exogenous corticosterone showed exacerbation of acute phase measures of sickness and severe mortality as well as decreased viral clearance from CNS (Experiment 3). These findings indicate that corticosterone exposure alone is sufficient to exacerbate acute CNS inflammatory disease.

Social conflict exacerbates an animal model of multiple sclerosis.

A growing body of evidence suggests that social conflict is associated with inflammatory disease onset and exacerbations in multiple sclerosis (MS) patients and in animal models of MS. This review illustrates how animal research can be used to elucidate the biobehavioral mechanisms underlying the adverse health effects of social conflict. The authors review studies indicating that social conflict exacerbates a virally initiated animal model of MS. This research suggests that the deleterious effects of social conflict may be partially mediated by stress-induced increases in pro-inflammatory cytokine levels in the central nervous system. In addition, they provide evidence that the adverse health effects of social conflict can be prevented by blocking the stress-induced increases in cytokine activity. This suggests that interventions designed to prevent or reverse the stress-induced increases in cytokine activity may be able to prevent or reverse some of the negative health effects of social conflict in humans.

Interleukin-6 as a mechanism for the adverse effects of social stress on acute Theiler's virus infection.

Prior exposure to social disruption stress (SDR) exacerbates both the acute and chronic phase of Theiler's murine encephalomyelitis virus infection (TMEV; [Johnson, R.R., Storts, R., Welsh, T.H., Jr., Welsh, C.J., Meagher, M.W., 2004. Social stress alters the severity of acute Theiler's virus infection. J. Neuroimmunol. 148, 74--85; Johnson, R.R., Prentice, T.W., Bridegam, P., Young, C.R., Steelman, A.J., Welsh, T.H., Welsh, C.J.R., Meagher, M.W., 2006. Social stress alters the severity and onset of the chronic phase of Theiler's virus infection. J. Neuroimmunol. 175, 39--51]). However, the neuroimmune mechanism(s) mediating this effect have not been determined. The present study examined whether stress-induced increases in the proinflammatory cytokine interleukin-6 (IL-6) contributes to the adverse effects of SDR on acute TMEV infection. Experiment 1 demonstrated that SDR increases central and peripheral levels of IL-6 and that this effect is reversed by intracerebral ventricular infusion of neutralizing antibody to IL-6 prior to each of six SDR sessions. Although SDR reduced the sensitivity of spleen cells to the anti-inflammatory effects of corticosterone, the neutralizing antibody to IL-6 did not alter this effect. To investigate whether stress-induced increases in IL-6 contribute to the exacerbation of acute TMEV infection, Experiment 2 examined whether intracerebral administration of neutralizing antibody to IL-6 during SDR would prevent the subsequent exacerbation of acute TMEV infection. Experiment 3 then replaced the social stress with intracerebral infusion of IL-6 to assess sufficiency. As expected, prior exposure to SDR subsequently increased infection-related sickness behaviors, motor impairment, CNS viral titers, and CNS inflammation. These deleterious effects of SDR were either prevented or significantly attenuated by intracerebral infusion of neutralizing antibody to IL-6 during the stress exposure period. However, infusion of IL-6 alone did not mimic the adverse effects of SDR. We conclude that IL-6 is necessary but not sufficient to exacerbate acute TMEV infection.

Social stress alters the severity and onset of the chronic phase of Theiler's virus infection.

Social stress alters the acute phase of Theiler's virus infection (TMEV), a model of multiple sclerosis. Stress applied prior to infection had deleterious disease outcomes, while stress applied concurrent with infection was protective. The current study examined multiple behavioral (motor impairment, open field activity) and immunological measures (IL-6, antibodies to virus and myelin proteins) in both the acute and chronic phases of TMEV. It was found that stress applied prior to infection exacerbated disease outcomes, while concurrent application was protective in both disease phases.