Mild Jugular Compression Collar Ameliorated Changes in Brain Activation of Working Memory after One Soccer Season in Female High School Athletes.

Recent neuroimaging studies have suggested that repetitive subconcussive head impacts, even after only one sport season, may lead to pre- to post-season structural and functional alterations in male high school football athletes. However, data on female athletes are limited. In the current investigation, we aimed to (1) assess the longitudinal pre- to post-season changes in functional MRI (fMRI) of working memory and working memory performance, (2) quantify the association between the pre- to post-season change in fMRI of working memory and the exposure to head impact and working memory performance, and (3) assess whether wearing a neck collar designed to reduce intracranial slosh via mild compression of the jugular veins can ameliorate the changes in fMRI brain activation observed in the female high school athletes who did not wear collars after a full soccer season. A total of 48 female high school soccer athletes (age range: 14.00-17.97 years) were included in the study. These athletes were assigned to the non-collar group (n = 21) or to the collar group (n = 27). All athletes undewent MRI at both pre-season and post-season. In each session, a fMRI verbal N-Back task was used to engage working memory. A significant pre- to post-season increase in fMRI blood oxygen level dependent (BOLD) signal was demonstrated when performing the N-back working memory task in the non-collar group but not in the collar group, despite the comparable exposure to head impacts during the season between the two groups. The collar group demonstrated significantly smaller pre- to post-season change in fMRI BOLD signal than the non-collar group, suggesting a potential protective effect from the collar device. Significant correlations were also found between the pre- to post-season increase in fMRI brain activation and the decrease in task accuracy in the non-collar group, indicating an association between the compensatory mechanism in underlying neurophysiology and the alteration in the behavioral outcomes.

A Computational Model for the Automatic Diagnosis of Attention Deficit Hyperactivity Disorder Based on Functional Brain Volume.

In this paper, we investigated the problem of computer-aided diagnosis of Attention Deficit Hyperactivity Disorder (ADHD) using machine learning techniques. With the ADHD-200 dataset, we developed a Support Vector Machine (SVM) model to classify ADHD patients from typically developing controls (TDCs), using the regional brain volumes as predictors. Conventionally, the volume of a brain region was considered to be an anatomical feature and quantified using structural magnetic resonance images. One major contribution of the present study was that we had initially proposed to measure the regional brain volumes using fMRI images. Brain volumes measured from fMRI images were denoted as functional volumes, which quantified the volumes of brain regions that were actually functioning during fMRI imaging. We compared the predictive power of functional volumes with that of regional brain volumes measured from anatomical images, which were denoted as anatomical volumes. The former demonstrated higher discriminative power than the latter for the classification of ADHD patients vs. TDCs. Combined with our two-step feature selection approach which integrated prior knowledge with the recursive feature elimination (RFE) algorithm, our SVM classification model combining functional volumes and demographic characteristics achieved a balanced accuracy of 67.7%, which was 16.1% higher than that of a relevant model published previously in the work of Sato et al. Furthermore, our classifier highlighted 10 brain regions that were most discriminative in distinguishing between ADHD patients and TDCs. These 10 regions were mainly located in occipital lobe, cerebellum posterior lobe, parietal lobe, frontal lobe, and temporal lobe. Our present study using functional images will likely provide new perspectives about the brain regions affected by ADHD.

National trends in psychotropic medication use in young children: 1994-2009.

OBJECTIVE: To examine recent national trends in psychotropic use for very young children at US outpatient medical visits. METHODS: Data for 2- to 5-year-old children (N = 43 598) from the 1994-2009 National Ambulatory and National Hospital Ambulatory Medical Care Surveys were used to estimate the weighted percentage of visits with psychotropic prescriptions. Multivariable logistic regression was used to identify factors associated with psychotropic use. Time effects were examined in 4-year blocks (1994-1997, 1998-2001, 2002-2005, and 2006-2009). RESULTS: Psychotropic prescription rates were 0.98% from 1994-1997, 0.83% from 1998-2001, 1.45% from 2002-2005, and 1.00% from 2006-2009. The likelihood of preschool psychotropic use was highest in 2002-2005 (1994-1997 adjusted odds ratio [AOR] versus 2002-2005: 0.67; 1998-2001 AOR versus 2002-2005: 0.63; 2006-2009 AOR versus 2002-2005: 0.64), then diminished such that the 2006-2009 probability of use did not differ from 1994-1997 or from 1998-2001. Boys (AOR versus girls: 1.64), white children (AOR versus other race: 1.42), older children (AOR for 4 to 5 vs 2 to 3 year olds: 3.87), and those lacking private insurance (AOR versus privately insured: 2.38) were more likely than children from other groups to receive psychotropic prescriptions. CONCLUSIONS: Psychotropic prescription was notable for peak usage in 2002-2005 and sociodemographic disparities in use. Further study is needed to discern why psychotropic use in very young children stabilized in 2006-2009, as well as reasons for increased use in boys, white children, and those lacking private health insurance.

Pre- and postnatal risk factors for ADHD in a nonclinical pediatric population.

OBJECTIVE: The authors characterized pre- and postnatal risk factors for ADHD among a population-based sample of 8-year-old children followed since birth (N = 604). METHOD: Parents and teachers rated ADHD symptoms, including inattention and impulsivity/hyperactivity. The authors reviewed pediatric medical records for history of an ADHD diagnosis, and parents reported ADHD medication use. The authors analyzed risk factors in relationship to outcomes using multivariable regression models. RESULTS: Low paternal education, prenatal smoking, prenatal illicit drug use, maternal depression, and low Home Observation for Measurement of the Environment score were associated with greater risk for ADHD behaviors assessed via rating scale. Low income and being male were associated with ADHD diagnosis in medical records and ADHD medication use. CONCLUSION: The authors found associations between socioeconomic, psychosocial, and prenatal exposures and ADHD-related behavior. Selection bias due to access to care and recall bias from inaccurate report of past exposures is minimized in this large, nonclinical, prospective cohort study.

Assessing Homework Problems in Children with ADHD: Validation of a Parent-Report Measure and Evaluation of Homework Performance Patterns.

The factor structure of a parent-report measure of child homework problems, the Homework Problems Checklist, was examined in a geographically and ethnically diverse sample of children with Attention-Deficit/Hyperactivity Disorder (ADHD). This measure was completed by the parents of 579 children ages 7.0-9.9 diagnosed with ADHD Combined Type as part of the Multimodal Treatment Study of Children with ADHD (MTA). Results replicated previous work showing two salient factors that measure homework completion behaviors (Factor I) and homework management behaviors (Factor II). This two-factor solution remained consistent when examined across child sex and ethnicity subgroups. Analysis of patterns revealed that homework problems are greater for children in higher grades and that children with ADHD and comorbid Learning Disabilities experience significantly more homework problems than children with ADHD alone. This study also replicated previous work showing that homework problems and ADHD inattentive symptoms are highly correlated whereas correlations between homework problems and hyperactivity and impulsivity are low to moderate. Implications of the findings for the assessment of homework problems in children with ADHD and for intervention are discussed.

Effects of smoking abstinence on reaction time variability in smokers with and without ADHD: an ex-Gaussian analysis.

Smoking abstinence differentially affects cognitive functioning in smokers with ADHD, compared to non-ADHD smokers. Alternative approaches for analyzing reaction time data from these tasks may further elucidate important group differences. Adults smoking > or = 15 cigarettes with (n=12) or without (n=14) a diagnosis of ADHD completed a continuous performance task (CPT) during two sessions under two separate laboratory conditions--a 'Satiated' condition wherein participants smoked up to and during the session; and an 'Abstinent' condition, in which participants were abstinent overnight and during the session. Reaction time (RT) distributions from the CPT were modeled to fit an ex-Gaussian distribution. The indicator of central tendency for RT from the normal component of the RT distribution (mu) showed a main effect of Group (ADHD < Control) and a Group x Session interaction (ADHD group RTs decreased when abstinent). RT standard deviation for the normal component of the distribution (sigma) showed no effects. The ex-Gaussian parameter tau, which describes the mean and standard deviation of the non-normal component of the distribution, showed significant effects of session (Abstinent > Satiated), Group x Session interaction (ADHD increased significantly under Abstinent condition compared to Control), and a trend toward a main effect of Group (ADHD > Control). Alternative approaches to analyzing RT data provide a more detailed description of the effects of smoking abstinence in ADHD and non-ADHD smokers and results differ from analyses using more traditional approaches. These findings have implications for understanding the neuropsychopharmacology of nicotine and nicotine withdrawal.