Explore the vast range of titles available.

The objective of the study was to gather perspectives and experiences of parents, coaches, and organizational leaders surrounding safety in youth football as it relates to roles and responsibilities of the coach. Parents (n = 13) and coaches (n = 10) of two youth football teams participated in separate, team-specific monthly focus groups to gather their perspectives and experiences surrounding youth football safety. Six organizational leaders participated in one-on-one interviews. Focus groups were coded in Atlas.ti. Interviews were summarized using methods of rapid analysis. Data from focus groups and interviews were integrated and analyzed for thematic content. Parents, coaches, and organizational leaders regarded the youth football coach’s role as “so much more than football,” often serving as role models, mentors, and father figures to athletes. Parents place trust in their son’s coaches and expect them to have knowledge and skills necessary to coach football and teach proper skills to prevent injuries. Organizational leaders set expectations of coaches but recognized the coaches’ autonomy in determining team activities and responsibility for safety. Coaches who teach techniques that are not aligned with current practices and coaches who prioritize winning over safety were identified as concerns for safety. Results demonstrate the important role coaches play in the personal and technical skill development and safety of youth football players and should be considered in the development and implementation of evidence-based strategies to improve safety in community-based sports.

Mild traumatic brain injury (mTBI) is an important public health problem. Although conventional medical imaging techniques can detect moderate-to-severe injuries, they are relatively insensitive to mTBI. In this study, we used hybrid diffusion imaging (HYDI) to detect white matter alterations in 19 patients with mTBI and 23 other trauma control patients. Within 15 days (standard deviation = 10) of brain injury, all subjects underwent magnetic resonance HYDI and were assessed with a battery of neuropsychological tests of sustained attention, memory, and executive function. Tract-based spatial statistics (TBSS) was used for voxel-wise statistical analyses within the white matter skeleton to study between-group differences in diffusion metrics, within-group correlations between diffusion metrics and clinical outcomes, and between-group interaction effects. The advanced diffusion imaging techniques, including neurite orientation dispersion and density imaging (NODDI) and q-space analyses, appeared to be more sensitive then classic diffusion tensor imaging. Only NODDI-derived intra-axonal volume fraction (Vic) demonstrated significant group differences (i.e., 5–9% lower in the injured brain). Within the mTBI group, Vic and a q-space measure, P0, correlated with 6 of 10 neuropsychological tests, including measures of attention, memory, and executive function. In addition, the direction of correlations differed significantly between groups (R 2 > 0.71 and pinteration < 0.03). Specifically, in the control group, higher Vic and P0 were associated with better performances on clinical assessments, whereas in the mTBI group, higher Vic and P0 were associated with worse performances with correlation coefficients >0.83. In summary, the NODDI-derived axonal density index and q-space measure for tissue restriction demonstrated superior sensitivity to white matter changes shortly after mTBI. These techniques hold promise as a neuroimaging biomarker for mTBI.

To understand the relationship between type 2 diabetes (T2D) and risk for developing cognitive impairment, this study is the first to examine association between metabolites measured at mid-life and cognitive performance assessed later in life (8–10 years) in a T2D-enriched cohort. The discovery set included metabolomics from European Americans (EAs; n  = 137) and African Americans (AAs; n  = 134) from the Diabetes Heart Study (DHS) and the African American-DHS (AA-DHS). The cognitive testing battery included measures of executive function, memory, attention, language, and global cognition. Ancestry-specific linear regression analyses were performed and a false discovery rate (FDR)-corrected p-value was used to assess significance. Overall, fewer significant metabolites were associated with cognitive performance in AAs ( n  = 19) as compared to EAs ( n  = 118) suggesting racial differences. There was a positive association between sphingomyelins and cognitive performance, consistent with prior reports. Novel findings implicated partially characterized metabolites linked to oxidative breakdown of bilirubin to multiple cognitive domains suggesting further exploration of this class of metabolites towards improving pathophysiologic understanding and early intervention. Cross-ancestry replication identified four metabolites that generalized to both populations. Replication was performed among additional study participants, i.e. 421 EAs and 167 AAs, followed by a formal meta-analysis. Replication bolstered the association of multiple metabolites with cognitive function. Among these, cortisol was associated in AAs suggesting a link between stress and risk for reduced cognitive function. Further work is needed to provide insight into the pathophysiologic mechanisms and highlight metabolites for inclusion in risk stratification models of cognitive performance.

Diffusion MRI (dMRI) data acquired on different scanners varies significantly in its content throughout the brain even if the acquisition parameters are nearly identical. Thus, proper harmonization of such data sets is necessary to increase the sample size and thereby the statistical power of neuroimaging studies. In this paper, we present a novel approach to harmonize dMRI data (the raw signal, instead of dMRI derived measures such as fractional anisotropy) using rotation invariant spherical harmonic (RISH) features embedded within a multi-modal image registration framework. All dMRI data sets from all sites are registered to a common template and voxel-wise differences in RISH features between sites at a group level are used to harmonize the signal in a subject-specific manner. We validate our method on diffusion data acquired from seven different sites (two GE, three Philips, and two Siemens scanners) on a group of age-matched healthy subjects. We demonstrate the efficacy of our method by statistically comparing diffusion measures such as fractional anisotropy, mean diffusivity and generalized fractional anisotropy across these sites before and after data harmonization. Validation was also done on a group oftest subjects, which were not used to “learn” the harmonization parameters. We also show results using TBSS before and after harmonization for independent validation of the proposed methodology. Using synthetic data, we show that any abnormality in diffusion measures due to disease is preserved during the harmonization process. Our experimental results demonstrate that, for nearly identical acquisition protocol across sites, scanner-specific differences in the signal can be removed using the proposed method in a model independent manner.

The objective of this study was to explore the effects of increasing working memory (WM) processing load on previously observed abnormalities in activation of WM circuitry shortly after mild traumatic brain injury (MTBI). Brain activation patterns in response to increasing WM processing load (auditory n-back: 0-, 1-, 2-, and 3-back conditions) were assessed with fMRI in 18 MTBI patients within 1 month of their injury and in 12 healthy controls. Performance accuracy on these tasks was also measured. Brain activation patterns differed between MTBI patients and controls in response to increasing WM processing loads. Controls maintained their ability to increase activation in regions of WM circuitry with each increase in WM processing load. MTBI patients showed disproportionately increased activation during the moderate processing load condition, but very little increase in activation associated with the highest processing load condition. Task performance did not differ significantly between groups on any task condition. MTBI patients showed a different pattern of allocation of processing resources associated with a high processing load condition compared to healthy controls, despite similar task performance. This suggests that injury-related changes in ability to activate or modulate WM processing resources might underlie some of the memory complaints after MTBI.

Coping with stressful life events requires a degree of skill in the ability to attend to, comprehend, label, communicate and regulate emotions. Individuals vary in the extent to which these skills are developed, with the term ‘alexithymia’ often applied in the clinical and personality literature to those individuals most compromised in these skills. Although a frontal lobe model of alexithymia is emerging, it is unclear whether such a model satisfactorily reflects brain-related patterns associated with perceived emotional intelligence at the facet level. To determine whether these trait meta-mood facets (ability to attend to, have clarity of and repair emotions) have unique gray matter volume correlates, a voxel-based morphometry study was conducted in 30 healthy adults using the Trait Meta Mood Scale while co-varying for potentially confounding sociodemographic variables. Poorer Attention to Emotion was associated with lower gray matter volume in clusters distributed primarily throughout the frontal lobe, with peak correlation in the left medial frontal gyrus. Poorer Mood Repair was related to lower gray matter volume in three clusters in frontal and inferior parietal areas, with peak correlation in the left anterior cingulate. No significant volumetric correlations emerged for the Clarity of Emotion facet. We discuss the localization of these areas in the context of cortical circuits known to be involved in processes of self-reflection and cognitive control.

Objectives: The Forced Choice Recognition (FCR) trial of the California Verbal Learning Test, 2nd edition, was designed as an embedded performance validity test (PVT). To our knowledge, this is the first systematic review of classification accuracy against reference PVTs. Methods: Results from peer-reviewed studies with FCR data published since 2002 encompassing a variety of clinical, research, and forensic samples were summarized, including 37 studies with FCR failure rates (N=7575) and 17 with concordance rates with established PVTs (N=4432). Results: All healthy controls scored >14 on FCR. On average, 16.9% of the entire sample scored ≤14, while 25.9% failed reference PVTs. Presence or absence of external incentives to appear impaired (as identified by researchers) resulted in different failure rates (13.6% vs. 3.5%), as did failing or passing reference PVTs (49.0% vs. 6.4%). FCR ≤14 produced an overall classification accuracy of 72%, demonstrating higher specificity (.93) than sensitivity (.50) to invalid performance. Failure rates increased with the severity of cognitive impairment. Conclusions: In the absence of serious neurocognitive disorder, FCR ≤14 is highly specific, but only moderately sensitive to invalid responding. Passing FCR does not rule out a non-credible presentation, but failing FCR rules it in with high accuracy. The heterogeneity in sample characteristics and reference PVTs, as well as the quality of the criterion measure across studies, is a major limitation of this review and the basic methodology of PVT research in general. (JINS, 2016, 22, 851–858)

Microscale brain injury studies suggest axonal elongation as a potential mechanism for diffuse axonal injury (DAI). Recent studies have begun to incorporate white matter (WM) structural anisotropy in injury analysis, with initial evidence suggesting improved injury prediction performance. In this study, we further develop a tractography-based approach to analyze fiber strains along the entire lengths of fibers from voxel- or anatomically constrained whole-brain tractography. This technique potentially extends previous element- or voxel-based methods that instead utilize WM fiber orientations averaged from typically coarse elements or voxels. Perhaps more importantly, incorporating tractography-based axonal structural information enables assessment of the overall injury risks to functionally important neural pathways and the anatomical regions they connect, which is not possible with previous methods. A DAI susceptibility index was also established to quantify voxel-wise WM local structural integrity and tract-wise damage of individual neural pathways. This “graded” injury susceptibility potentially extends the commonly employed treatment of injury as a simple binary condition. As an illustration, we evaluate the DAI susceptibilities of WM voxels and transcallosal fiber tracts in three idealized head impacts. Findings suggest the potential importance of the tractography-based approach for injury prediction. These efforts may enable future studies to correlate WM mechanical responses with neuroimaging, cognitive alteration, and concussion, and to reveal the relative vulnerabilities of neural pathways and identify the most vulnerable ones in real-world head impacts.

Sports-related concussion is a major public health problem in the United States and yet its biomechanical mechanisms remain unclear. In vitro studies demonstrate axonal elongation as a potential injury mechanism; however, current response-based injury predictors (e.g., maximum principal strain, \\documentclass{aastex}\\usepackage{amsbsy}\\usepackage{amsfonts}\\usepackage{amssymb}\\usepackage{bm}\\usepackage{mathrsfs}\\usepackage{pifont}\\usepackage{stmaryrd}\\usepackage{textcomp}\\usepackage{portland, xspace}\\usepackage{amsmath, amsxtra}\\pagestyle{empty}\\DeclareMathSizes {10} {9} {7} {6} \\begin{document}$$\\varepsilon_{ep}$$ \\end{document} ) typically do not incorporate axonal orientations. We investigated the significance of white matter (WM) fiber orientation in strain estimation and compared fiber strain ( \\documentclass{aastex}\\usepackage{amsbsy}\\usepackage{amsfonts}\\usepackage{amssymb}\\usepackage{bm}\\usepackage{mathrsfs}\\usepackage{pifont}\\usepackage{stmaryrd}\\usepackage{textcomp}\\usepackage{portland, xspace}\\usepackage{amsmath, amsxtra}\\pagestyle{empty}\\DeclareMathSizes {10} {9} {7} {6} \\begin{document}$$\\varepsilon_n$$ \\end{document} ) with \\documentclass{aastex}\\usepackage{amsbsy}\\usepackage{amsfonts}\\usepackage{amssymb}\\usepackage{bm}\\usepackage{mathrsfs}\\usepackage{pifont}\\usepackage{stmaryrd}\\usepackage{textcomp}\\usepackage{portland, xspace}\\usepackage{amsmath, amsxtra}\\pagestyle{empty}\\DeclareMathSizes {10} {9} {7} {6} \\begin{document}$$\\varepsilon_{ep}$$ \\end{document} for 11 athletes with a clinical diagnosis of concussion. Geometrically accurate subject-specific head models with high mesh quality were created based on the Dartmouth Head Injury Model (DHIM), which was successfully validated (performance categorized as “good” to “excellent”). For WM regions estimated to be exposed to high strains using a range of injury thresholds (0.09–0.28), substantial differences existed between \\documentclass{aastex}\\usepackage{amsbsy}\\usepackage{amsfonts}\\usepackage{amssymb}\\usepackage{bm}\\usepackage{mathrsfs}\\usepackage{pifont}\\usepackage{stmaryrd}\\usepackage{textcomp}\\usepackage{portland, xspace}\\usepackage{amsmath, amsxtra}\\pagestyle{empty}\\DeclareMathSizes {10} {9} {7} {6} \\begin{document}$$\\varepsilon_n$$ \\end{document} and \\documentclass{aastex}\\usepackage{amsbsy}\\usepackage{amsfonts}\\usepackage{amssymb}\\usepackage{bm}\\usepackage{mathrsfs}\\usepackage{pifont}\\usepackage{stmaryrd}\\usepackage{textcomp}\\usepackage{portland, xspace}\\usepackage{amsmath, amsxtra}\\pagestyle{empty}\\DeclareMathSizes {10} {9} {7} {6} \\begin{document}$$\\varepsilon_{ep}$$ \\end{document} in both distribution (Dice coefficient of 0.13–0.33) and extent (∼5–10-fold differences), especially at higher threshold levels and higher rotational acceleration magnitudes. For example, an average of 3.2% vs. 29.8% of WM was predicted above an optimal threshold of 0.18 established from an in vivo animal study using \\documentclass{aastex}\\usepackage{amsbsy}\\usepackage{amsfonts}\\usepackage{amssymb}\\usepackage{bm}\\usepackage{mathrsfs}\\usepackage{pifont}\\usepackage{stmaryrd}\\usepackage{textcomp}\\usepackage{portland, xspace}\\usepackage{amsmath, amsxtra}\\pagestyle{empty}\\DeclareMathSizes {10} {9} {7} {6} \\begin{document}$$\\varepsilon_n$$ \\end{document} and \\documentclass{aastex}\\usepackage{amsbsy}\\usepackage{amsfonts}\\usepackage{amssymb}\\usepackage{bm}\\usepackage{mathrsfs}\\usepackage{pifont}\\usepackage{stmaryrd}\\usepackage{textcomp}\\usepackage{portland, xspace}\\usepackage{amsmath, amsxtra}\\pagestyle{empty}\\DeclareMathSizes {10} {9} {7} {6} \\begin{document}$$\\varepsilon_{ep}$$ \\end{document} , respectively, with an average Dice coefficient of 0.14. The distribution of WM regions with high \\documentclass{aastex}\\usepackage{amsbsy}\\usepackage{amsfonts}\\usepackage{amssymb}\\usepackage{bm}\\usepackage{mathrsfs}\\usepackage{pifont}\\usepackage{stmaryrd}\\usepackage{textcomp}\\usepackage{portland, xspace}\\usepackage{amsmath, amsxtra}\\pagestyle{empty}\\DeclareMathSizes {10} {9} {7} {6} \\begin{document}$$\\varepsilon_n$$ \\end{document} was consistent with typical heterogeneous patterns of WM disruptions in diffuse axonal injury, and the group-wise extent at the optimal threshold matched well with the percentage of WM voxels experiencing significant longitudinal changes of fractional anisotropy and mean diffusivity (3.2% and 3.44%, respectively) found from a separate independent study. These results suggest the significance of incorporating WM microstructural anisotropy in future brain injury studies.

On-field monitoring of head impacts, combined with finite element (FE) biomechanical simulation, allow for predictions of regional strain associated with a diagnosed concussion. However, attempts to correlate these predictions with in vivo measures of brain injury have not been published. This article reports an approach to and preliminary results from the correlation of subject-specific FE model-predicted regions of high strain associated with diagnosed concussion and diffusion tensor imaging to assess changes in white matter integrity in the corpus callosum (CC). Ten football and ice hockey players who wore instrumented helmets to record head impacts sustained during play completed high field magnetic resonance imaging preseason and within 10 days of a diagnosed concussion. The Dartmouth Subject-Specific FE Head model was used to generate regional predictions of strain and strain rate following each impact associated with concussion. Maps of change in fractional anisotropy (FA) and median diffusivity (MD) were generated for the CC of each athlete to correlate strain with change in FA and MD. Mean and maximum strain rate correlated with change in FA (Spearman ρ  = 0.77, p  = 0.01; 0.70, p  = 0.031), and there was a similar trend for mean and maximum strain (0.56, p  = 0.10; 0.6, p  = 0.07), as well as for maximum strain with change in MD (−0.63, p  = 0.07). Change in MD correlated with injury-to-imaging interval ( ρ  = −0.80, p  = 0.006) but change in FA did not ( ρ  = 0.18, p  = 0.62). These results provide preliminary confirmation that model-predicted strain and strain rate in the CC correlate with changes in indices of white matter integrity.