Bethany K. Bracken

Response inhibition and psychomotor speed during methadone maintenance: impact of treatment duration, dose, and sleep deprivation

BACKGROUND In opiate-dependent individuals, abstinence results in deficits in cognitive functioning, which may be exacerbated by medication-associated sleep disruption. METHOD To assess cognitive function and the influence of sleep deprivation (SD), 14 healthy control (HC) and 22 methadone maintained (MM) participants completed the continuous performance task (CPT) after a baseline night, a night of total SD, and two recovery sleep nights. The digit symbol substitution task (DSST) was administered at bedtime and in the morning. Secondary analyses separated MM participants into short- (< 12 months; n=8) and long-term (≥ 12 months; n=14) treatment duration groups, and into low- (< 80 mg; n=9) and high-dose (≥ 80 mg; n=13) groups. RESULTS Linear mixed model ANOVAs revealed that there was no effect of SD. Across all days MM participants had more errors of omission, fewer correct responses, and slower reaction times (RTs) on the CPT, and fewer accurate substitutions on the evening and morning DSST. Short-term MM participants exhibited slower RTs on the CPT, and fewer correct substitutions on the evening DSST compared to long-term MM participants. Low-dose MM participants had slower RTs on the CPT than HCs and high-dose MM participants. CONCLUSION These data demonstrate that methadone-maintained individuals exhibit poorer performance on tasks of psychomotor speed and selective attention/impulsivity, but with longer-term treatment, performance appears to return toward control levels. Furthermore, while one day of SD was enough to alter subjective reports of sleep quality, cognitive function may be more resilient.

Sex, Age, and Progression of Drug Use in Adolescents Admitted for Substance Use Disorder Treatment in the Northeastern United States: Comparison With a National Survey

ABSTRACT. Background: National adolescent drug use surveys are distributed in United States schools. Survey results determine trends in drug use and inform research and prevention efforts; however, students who have dropped out of school or were truant the day of the survey are excluded. Examining drug trends in a high-risk population (adolescents admitted for drug treatment) may better characterize drug users and their use patterns. Methods: The current study examined questionnaires completed by 939 adolescents admitted for substance abuse treatment between 1995 and 2010. Results: Age of first use (ranging from 13.2 years for alcohol to 15.1 years for cocaine) was significantly younger for cigarettes, alcohol, and cannabis than for “harder” drugs such as cocaine and heroin, and adolescents increased their use of almost every substance (except inhalants) with increasing age. This was not true of national data. Additionally, in the national data, less than 1.5% of participants reported using any of the harder drugs more than 5 times, but in the McLean data, even for harder drugs, >10% of adolescents used >50 times. Conclusions: In the high-risk sample examined here, progression to harder drugs is accelerated and increases with age regardless of sex. These data underscore the importance of prevention and immediate treatment when adolescent substance use is identified.

Brain metabolite concentrations across cortical regions in healthy adults

Magnetic resonance spectroscopy (MRS) can provide in vivo information about metabolite levels across multiple brain regions. This study used MRS to examine concentrations of N-acetylaspartate (NAA), a marker of neuronal integrity and function, and choline (Cho), which is related to the amount of cell membrane per unit volume, in anterior cingulate cortex (ACC) and parieto-occipital cortex (POC) in healthy individuals. Data were drawn from two experiments which examined glutamatergic and GABAergic signaling in schizophrenia and bipolar disorder. After controlling for gray matter percentages, NAA/creatine (Cr) was 18% higher in POC than in ACC (p<0.001); Cho/Cr was 46% lower in POC than in ACC (p<0.001). There was an effect of study (p<0.001 for both metabolites), but no region by study interaction (NAA p=0.101, Cho p=0.850). Since NAA is localized to the intracellular space, these data suggest that ACC neuronal compartment is reduced as compared with POC, or that there is a lower concentration of NAA per cell in the ACC than POC, or both. Since elevated Cho suggests more cell membrane per unit volume, reduced NAA in ACC appears to be coupled with increases in overall cell membrane compartment. These findings are consistent with a number of previous studies using proton MRS which found increasing NAA and decreasing Cho moving caudally, and with postmortem anatomical studies which found neurons in more widely spaced bundles in ACC when compared to parietal and occipital cortices. MRS may be a useful tool for studying physical properties of the living human brain.

T2 relaxation effects on apparent N-acetylaspartate concentration in proton magnetic resonance studies of schizophrenia.

Over the past two decades, many magnetic resonance spectroscopy (MRS) studies reported lower N-acetylaspartate (NAA) in key brain regions of patients with schizophrenia (SZ) compared to healthy subjects. A smaller number of studies report no difference in NAA. Many sources of variance may contribute to these discordant results including heterogeneity of the SZ subject populations and methodological differences such as MRS acquisition parameters, and post-acquisition analytic methods. The current study reviewed proton MRS literature reporting measurements of NAA in SZ with a focus on methodology. Studies which reported lower NAA were significantly more likely to have used longer echo times (TEs), while studies with shorter TEs reported no concentration difference. This suggests that NAA quantitation using MRS was affected by the choice of TE, and that published MRS literature reporting NAA in SZ using a long TE is confounded by apparent differential T2 relaxation effects between SZ and healthy control groups. Future MRS studies should measure T2 relaxation times. This would allow for spectral concentration measurements to be appropriately corrected for these relaxation effects. In addition, as metabolite concentration and T2 relaxation times are completely independent variables, this could offer distinct information about the metabolite of interest.

Kudzu Root Extract Does Not Perturb the Sleep/Wake Cycle of Moderate Drinkers

OBJECTIVES According to ancient Chinese medicine, kudzu root has been used as an ingredient to treat alcohol intoxication for centuries. Kudzu root extract is effective at reducing alcohol intake in animals and in humans, both in a natural-settings laboratory environment and on an outpatient basis. In dependent populations, withdrawal from alcohol is associated with disturbed sleep. These disturbances to the quantity and quality of sleep likely impact relapse to drinking. Many medications used to treat alcohol dependence also affect sleep. Therefore, as a possible treatment for alcohol dependence, the impact of kudzu root extract on the sleep/wake cycle is an important aspect of its effectiveness. DESIGN This double-blind, placebo-controlled, crossover trial tested the effects of kudzu root extract on the sleep/wake cycles of moderate drinkers. RESULTS Kudzu extract had no effect on any of the sleep parameters measured, including sleep efficiency, sleep latency, total time asleep per night, number of waking episodes, time awake per episode, number of moving minutes, number of sleep episodes, time asleep per episode, and number of immobile minutes. CONCLUSIONS These data suggest that the administration of kudzu root extract does not disturb sleep/wake cycles of moderate drinkers, and as such its utility as an adjunct treatment for alcohol dependence remains free of any potential side-effects on sleep.

Effects of Sleep Deprivation on Brain Bioenergetics, Sleep, and Cognitive Performance in Cocaine-Dependent Individuals

In cocaine-dependent individuals, sleep is disturbed during cocaine use and abstinence, highlighting the importance of examining the behavioral and homeostatic response to acute sleep loss in these individuals. The current study was designed to identify a differential effect of sleep deprivation on brain bioenergetics, cognitive performance, and sleep between cocaine-dependent and healthy control participants. 14 healthy control and 8 cocaine-dependent participants experienced consecutive nights of baseline, total sleep deprivation, and recovery sleep in the research laboratory. Participants underwent [31]P magnetic resonance spectroscopy (MRS) brain imaging, polysomnography, Continuous Performance Task, and Digit Symbol Substitution Task. Following recovery sleep, [31]P MRS scans revealed that cocaine-dependent participants exhibited elevated global brain β-NTP (direct measure of adenosine triphosphate), α-NTP, and total NTP levels compared to those of healthy controls. Cocaine-dependent participants performed worse on the Continuous Performance Task and Digit Symbol Substitution Task at baseline compared to healthy control participants, but sleep deprivation did not worsen cognitive performance in either group. Enhancements of brain ATP levels in cocaine dependent participants following recovery sleep may reflect a greater impact of sleep deprivation on sleep homeostasis, which may highlight the importance of monitoring sleep during abstinence and the potential influence of sleep loss in drug relapse.

Are Behavioral Measures Useful for Detecting Cognitive Workload During Human-Computer Interaction?

Commonly used techniques for measuring cognitive workload during human-computer interactions can be cumbersome or intrusive to task performance. In the current work, we examine the utility of heuristic behavior analysis, including keystroke dynamics, mouse tracking, and body positioning for measuring cognitive workload during direct interactions between humans and computers. We present a method for modeling behavioral measures as well as physiological and neurophysiological data using probabilistic, statistical, and machine learning algorithms for real-time estimation of human states. We believe this discussion will inform the capability to provide estimates of cognitive workload in real-world scenarios.

Physiological Synchronization Is Associated with Narrative Emotionality and Subsequent Behavioral Response

Neurophysiological compliance is a correlation of neurophysiological measures (synchronicity) between individuals. Higher compliance among team members is related to better performance, and higher synchronicity occurs during emotional moments of a stimulus. The aim of the current study is to examine whether synchrony may be observable via peripheral nervous system (PNS) activity. We used inter-subject correlation (ISC) analysis to assess whether synchronicity of PNS measures are related to stimulus emotionality or similarity in behavioral responses. Participants viewed a 100-second emotional video, followed by an appeal to donate experimental earnings to a related charity. We found high ISC for cardiac and electrodermal activity (EDA) between donors versus non-donors. For both groups, we found an association between ISC of cardiac activity and emotional moments in the stimulus. For non-donors we found an association between ISC of EDA and emotional moments. Our findings indicate that PNS measures yield similar results to neurophysiological measures.

A prototype toolkit for sensing and modeling individual and team state

Teams of individuals working together toward a common goal must be skilled at multi-tasking to perform their own work while maintaining shared attention across the team. Experimenters who study team performance can use cutting edge methods to assess physiological, neurophysiological, and behavioral underpinnings of optimal performance; however, this requires an adequate understanding of how these signals correlate with individual and team performance. We designed a toolkit to support experimenters in evaluating individual and team performance in a laboratory setting, in testing and validating models of performance, and in developing and validating augmentation strategies to improve performance. Our toolkit provides a framework that flexibly integrates current and emerging sensors. The data fusion tool fuses time-synchronized sensor data to assess performance. The model-building and execution toolset enables experimenters to choose previously entered models, adapt these models according to the current experiment, or develop new models to test. The real-time assessment tool enables experimenters to monitor the state of individual subjects and the team as a whole (e.g., stress, workload, focused attention) throughout the experiment, and how these states relate to performance. This information is then used by the real-time augmentation tool, which suggests augmentations to optimize that performance. Together, these tools provide a proof-of-concept prototype of a flexible modeling tool that would allow sensor inputs to be used to model and predict both individual and team performance.

A Toolkit to Assist Researchers to More Efficiently Conduct Experiments Assessing Human State

For teams to perform effectively, individuals must focus on their own tasks, while simultaneously maintaining awareness of other team members. Researchers studying and attempting to optimize performance of teams as well as individual team members use assessments of behavioral, neurophysiological, and physiological signals that correlate with individual and team performance. However, synchronizing data from multiple sensor devices can be difficult, and building and using models to assess human states of interest can be time-consuming and non-intuitive. To assist researchers, we built an Adaptable Toolkit for the Assessment and Augmentation of Performance by Teams in Real Time (ADAPTER), which provides a framework that flexibly integrates sensors and fuses sensor data to assess performance. ADAPTER flexibly integrates current and emerging sensors; assists researchers in creating and implementing models that support research on performance and the development of augmentation strategies; and enables comprehensive and holistic characterization of team member performance during real-time experimental protocols.