Intergenerational effects of parental substance-related convictions and adult drug treatment court participation on children's school performance.

This study examined the intergenerational effects of parental conviction of a substance-related charge on children's academic performance and, conditional on a conviction, whether completion of an adult drug treatment court (DTC) program was associated with improved school performance. State administrative data from North Carolina courts, birth records, and school records were linked for 2005-2012. Math and reading end-of-grade test scores and absenteeism were examined for 5 groups of children, those with parents who: were not convicted on any criminal charge, were convicted on a substance-related charge and not referred by a court to a DTC, were referred to a DTC but did not enroll, enrolled in a DTC but did not complete, and completed a DTC program. Accounting for demographic and socioeconomic factors, the school performance of children whose parents were convicted of a substance-related offense was worse than that of children whose parents were not convicted on any charge. These differences were statistically significant but substantially reduced after controlling for socioeconomic characteristics; for example, mother's educational attainment. We found no evidence that parent participation in an adult DTC program led to improved school performance of their children. While the children of convicted parents fared worse on average, much--but not all--of this difference was attributed to socioeconomic factors, with the result that parental conviction remained a risk factor for poorer school performance. Even though adult DTCs have been shown to have other benefits, we could detect no intergenerational benefit in improved school performance of their children.

The impact of anxiety-inducing distraction on cognitive performance: a combined brain imaging and personality investigation.

BACKGROUND: Previous investigations revealed that the impact of task-irrelevant emotional distraction on ongoing goal-oriented cognitive processing is linked to opposite patterns of activation in emotional and perceptual vs. cognitive control/executive brain regions. However, little is known about the role of individual variations in these responses. The present study investigated the effect of trait anxiety on the neural responses mediating the impact of transient anxiety-inducing task-irrelevant distraction on cognitive performance, and on the neural correlates of coping with such distraction. We investigated whether activity in the brain regions sensitive to emotional distraction would show dissociable patterns of co-variation with measures indexing individual variations in trait anxiety and cognitive performance. METHODOLOGY/PRINCIPAL FINDINGS: Event-related fMRI data, recorded while healthy female participants performed a delayed-response working memory (WM) task with distraction, were investigated in conjunction with behavioural measures that assessed individual variations in both trait anxiety and WM performance. Consistent with increased sensitivity to emotional cues in high anxiety, specific perceptual areas (fusiform gyrus--FG) exhibited increased activity that was positively correlated with trait anxiety and negatively correlated with WM performance, whereas specific executive regions (right lateral prefrontal cortex--PFC) exhibited decreased activity that was negatively correlated with trait anxiety. The study also identified a role of the medial and left lateral PFC in coping with distraction, as opposed to reflecting a detrimental impact of emotional distraction. CONCLUSIONS: These findings provide initial evidence concerning the neural mechanisms sensitive to individual variations in trait anxiety and WM performance, which dissociate the detrimental impact of emotion distraction and the engagement of mechanisms to cope with distracting emotions. Our study sheds light on the neural correlates of emotion-cognition interactions in normal behaviour, which has implications for understanding factors that may influence susceptibility to affective disorders, in general, and to anxiety disorders, in particular.

Knowledge and perceptions among overweight and obese employees about lifestyle-related health benefit changes.

We investigated perceptions among overweight and obese state employees about changes to health insurance that were designed to reduce the scope of health benefits for employees who are obese or who smoke. Before implementation of health benefit plan changes, 658 state employees who were overweight (ie, those with a body mass index [BMI] of 25-29.9) or obese (ie, those with a BMI of > or = 30) enrolled in a weight-loss intervention study were asked about their attitudes and beliefs concerning the new benefit plan changes. Thirty-one percent of employees with a measured BMI of 40 or greater self-reported a BMI of less than 40, suggesting they were unaware that their current BMI would place them in a higher-risk benefit plan. More than half of all respondents reported that the new benefit changes would motivate them to make behavioral changes, but fewer than half felt confident in their ability to make changes. Respondents with a BMI of 40 or greater were more likely than respondents in lower BMI categories to oppose the new changes focused on obesity (P < .001). Current smokers were more likely than former smokers and nonsmokers to oppose the new benefit changes focused on tobacco use (P < .01). Participants represented a sample of employees enrolled in a weight-loss study, limiting generalizability to the larger population of state employees. Benefit plan changes that require employees who are obese and smoke to pay more for health care may motivate some, but not all, individuals to change their behaviors. Since confidence to lose weight was lowest among individuals in the highest BMI categories, more-intense intervention options may be needed to achieve desired health behavior changes.

Delay activity of saccade-related neurons in the caudal dentate nucleus of the macaque cerebellum.

The caudal dentate nucleus (DN) in lateral cerebellum is connected with two visual/oculomotor areas of the cerebrum: the frontal eye field and lateral intraparietal cortex. Many neurons in frontal eye field and lateral intraparietal cortex produce "delay activity" between stimulus and response that correlates with processes such as motor planning. Our hypothesis was that caudal DN neurons would have prominent delay activity as well. From lesion studies, we predicted that this activity would be related to self-timing, i.e., the triggering of saccades based on the internal monitoring of time. We recorded from neurons in the caudal DN of monkeys (Macaca mulatta) that made delayed saccades with or without a self-timing requirement. Most (84%) of the caudal DN neurons had delay activity. These neurons conveyed at least three types of information. First, their activity was often correlated, trial by trial, with saccade initiation. Correlations were found more frequently in a task that required self-timing of saccades (53% of neurons) than in a task that did not (27% of neurons). Second, the delay activity was often tuned for saccade direction (in 65% of neurons). This tuning emerged continuously during a trial. Third, the time course of delay activity associated with self-timed saccades differed significantly from that associated with visually guided saccades (in 71% of neurons). A minority of neurons had sensory-related activity. None had presaccadic bursts, in contrast to DN neurons recorded more rostrally. We conclude that caudal DN neurons convey saccade-related delay activity that may contribute to the motor preparation of when and where to move.

Improvement in visual search with practice: mapping learning-related changes in neurocognitive stages of processing.

Practice can improve performance on visual search tasks; the neural mechanisms underlying such improvements, however, are not clear. Response time typically shortens with practice, but which components of the stimulus-response processing chain facilitate this behavioral change? Improved search performance could result from enhancements in various cognitive processing stages, including (1) sensory processing, (2) attentional allocation, (3) target discrimination, (4) motor-response preparation, and/or (5) response execution. We measured event-related potentials (ERPs) as human participants completed a five-day visual-search protocol in which they reported the orientation of a color popout target within an array of ellipses. We assessed changes in behavioral performance and in ERP components associated with various stages of processing. After practice, response time decreased in all participants (while accuracy remained consistent), and electrophysiological measures revealed modulation of several ERP components. First, amplitudes of the early sensory-evoked N1 component at 150 ms increased bilaterally, indicating enhanced visual sensory processing of the array. Second, the negative-polarity posterior-contralateral component (N2pc, 170-250 ms) was earlier and larger, demonstrating enhanced attentional orienting. Third, the amplitude of the sustained posterior contralateral negativity component (SPCN, 300-400 ms) decreased, indicating facilitated target discrimination. Finally, faster motor-response preparation and execution were observed after practice, as indicated by latency changes in both the stimulus-locked and response-locked lateralized readiness potentials (LRPs). These electrophysiological results delineate the functional plasticity in key mechanisms underlying visual search with high temporal resolution and illustrate how practice influences various cognitive and neural processing stages leading to enhanced behavioral performance.

Growth, Characterization, and Properties of Hybrid Graphene-Carbon Nanotube Films and Related Carbon Nanostructures

Graphene, first isolated in 2004 and the subject of the 2010 Nobel Prize in physics, has generated a tremendous amount of research interest in recent years due to its incredible mechanical and electrical properties. However, difficulties in large-scale production and low as-prepared surface area have hindered commercial applications. In this dissertation, a new material is described incorporating the superior electrical properties of graphene edge planes into the high surface area framework of carbon nanotube forests using a scalable and reproducible technology.

The objectives of this research were to investigate the growth parameters and mechanisms of a graphene-carbon nanotube hybrid nanomaterial termed “graphenated carbon nanotubes” (g-CNTs), examine the applicability of g-CNT materials for applications in electrochemical capacitors (supercapacitors) and cold-cathode field emission sources, and determine materials characteristics responsible for the superior performance of g-CNTs in these applications. The growth kinetics of multi-walled carbon nanotubes (MWNTs), grown by plasma-enhanced chemical vapor deposition (PECVD), was studied in order to understand the fundamental mechanisms governing the PECVD reaction process. Activation energies and diffusivities were determined for key reaction steps and a growth model was developed in response to these findings. Differences in the reaction kinetics between CNTs grown on single-crystal silicon and polysilicon were studied to aid in the incorporation of CNTs into microelectromechanical systems (MEMS) devices. To understand processing-property relationships for g-CNT materials, a Design of Experiments (DOE) analysis was performed for the purpose of determining the importance of various input parameters on the growth of g-CNTs, finding that varying temperature alone allows the resultant material to transition from CNTs to g-CNTs and finally carbon nanosheets (CNSs): vertically oriented sheets of few-layered graphene. In addition, a phenomenological model was developed for g-CNTs. By studying variations of graphene-CNT hybrid nanomaterials by Raman spectroscopy, a linear trend was discovered between their mean crystallite size and electrochemical capacitance. Finally, a new method for the calculation of nanomaterial surface area, more accurate than the standard BET technique, was created based on atomic layer deposition (ALD) of titanium oxide (TiO2).