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Investigators in neuroscience have turned to Big Data to address replication and reliability issues by increasing sample size. These efforts unveil new questions about how to integrate data across distinct sources and instruments. The goal of this study was to link scores across common auditory verbal learning tasks (AVLTs). This international secondary analysis aggregated multisite raw data for AVLTs across 53 studies totaling 10,505 individuals. Using the ComBat-GAM algorithm, we isolated and removed the component of memory scores associated with site effects while preserving instrumental effects. After adjustment, a continuous item response theory model used multiple memory items of varying difficulty to estimate each individual's latent verbal learning ability on a single scale. Equivalent raw scores across AVLTs were then found by linking individuals through the ability scale. Harmonization reduced total cross-site score variance by 37% while preserving meaningful memory effects. Age had the largest impact on scores overall (- 11.4%), while race/ethnicity variable was not significant (p > 0.05). The resulting tools were validated on dually administered tests. The conversion tool is available online so researchers and clinicians can convert memory scores across instruments. This work demonstrates that global harmonization initiatives can address reproducibility challenges across the behavioral sciences.

Traumatic brain injury (TBI) in military populations can cause disruptions in brain structure and function, along with cognitive and psychological dysfunction. Diffusion magnetic resonance imaging (dMRI) can detect alterations in white matter (WM) microstructure, but few studies have examined brain asymmetry. Examining asymmetry in large samples may increase sensitivity to detect heterogeneous areas of WM alteration in mild TBI. Through the Enhancing Neuroimaging Genetics Through Meta-Analysis Military-Relevant Brain Injury working group, we conducted a mega-analysis of neuroimaging and clinical data from 16 cohorts of Active Duty Service Members and Veterans (n = 2598). dMRI data were processed together along with harmonized demographic, injury, psychiatric, and cognitive measures. Fractional anisotropy in the cingulum showed greater asymmetry in individuals with deployment-related TBI, driven by greater left lateralization in TBI. Results remained significant after accounting for potentially confounding variables including posttraumatic stress disorder, depression, and handedness, and were driven primarily by individuals whose worst TBI occurred before age 40. Alterations in the cingulum were also associated with slower processing speed and poorer set shifting. The results indicate an enhancement of the natural left laterality of the cingulum, possibly due to vulnerability of the nondominant hemisphere or compensatory mechanisms in the dominant hemisphere. The cingulum is one of the last WM tracts to mature, reaching peak FA around 42 years old. This effect was primarily detected in individuals whose worst injury occurred before age 40, suggesting that the protracted development of the cingulum may lead to increased vulnerability to insults, such as TBI.

Results of neuroimaging datasets aggregated from multiple sites may be biased by site-specific profiles in participants' demographic and clinical characteristics, as well as MRI acquisition protocols and scanning platforms. We compared the impact of four different harmonization methods on results obtained from analyses of cortical thickness data: (1) linear mixed-effects model (LME) that models site-specific random intercepts (LMEINT), (2) LME that models both site-specific random intercepts and age-related random slopes (LMEINT+SLP), (3) ComBat, and (4) ComBat with a generalized additive model (ComBat-GAM). Our test case for comparing harmonization methods was cortical thickness data aggregated from 29 sites, which included 1,340 cases with posttraumatic stress disorder (PTSD) (6.2-81.8 years old) and 2,057 trauma-exposed controls without PTSD (6.3-85.2 years old). We found that, compared to the other data harmonization methods, data processed with ComBat-GAM was more sensitive to the detection of significant case-control differences (Χ2(3) = 63.704, p < 0.001) as well as case-control differences in age-related cortical thinning (Χ2(3) = 12.082, p = 0.007). Both ComBat and ComBat-GAM outperformed LME methods in detecting sex differences (Χ2(3) = 9.114, p = 0.028) in regional cortical thickness. ComBat-GAM also led to stronger estimates of age-related declines in cortical thickness (corrected p-values < 0.001), stronger estimates of case-related cortical thickness reduction (corrected p-values < 0.001), weaker estimates of age-related declines in cortical thickness in cases than controls (corrected p-values < 0.001), stronger estimates of cortical thickness reduction in females than males (corrected p-values < 0.001), and stronger estimates of cortical thickness reduction in females relative to males in cases than controls (corrected p-values < 0.001). Our results support the use of ComBat-GAM to minimize confounds and increase statistical power when harmonizing data with non-linear effects, and the use of either ComBat or ComBat-GAM for harmonizing data with linear effects.

Mild Traumatic brain injury (mTBI) is a signature wound in military personnel, and repetitive mTBI has been linked to age-related neurogenerative disorders that affect white matter (WM) in the brain. However, findings of injury to specific WM tracts have been variable and inconsistent. This may be due to the heterogeneity of mechanisms, etiology, and comorbid disorders related to mTBI. Non-negative matrix factorization (NMF) is a data-driven approach that detects covarying patterns (components) within high-dimensional data. We applied NMF to diffusion imaging data from military Veterans with and without a self-reported TBI history. NMF identified 12 independent components derived from fractional anisotropy (FA) in a large dataset (n = 1,475) gathered through the ENIGMA (Enhancing Neuroimaging Genetics through Meta-Analysis) Military Brain Injury working group. Regressions were used to examine TBI- and mTBI-related associations in NMF-derived components while adjusting for age, sex, post-traumatic stress disorder, depression, and data acquisition site/scanner. We found significantly stronger age-dependent effects of lower FA in Veterans with TBI than Veterans without in four components (q

The ENIGMA-DTI (diffusion tensor imaging) workgroup supports analyses that examine the effects of psychiatric, neurological, and developmental disorders on the white matter pathways of the human brain, as well as the effects of normal variation and its genetic associations. The seven ENIGMA disorder-oriented working groups used the ENIGMA-DTI workflow to derive patterns of deficits using coherent and coordinated analyses that model the disease effects across cohorts worldwide. This yielded the largest studies detailing patterns of white matter deficits in schizophrenia spectrum disorder (SSD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), posttraumatic stress disorder (PTSD), traumatic brain injury (TBI), and 22q11 deletion syndrome. These deficit patterns are informative of the underlying neurobiology and reproducible in independent cohorts. We reviewed these findings, demonstrated their reproducibility in independent cohorts, and compared the deficit patterns across illnesses. We discussed translating ENIGMA-defined deficit patterns on the level of individual subjects using a metric called the regional vulnerability index (RVI), a correlation of an individual's brain metrics with the expected pattern for a disorder. We discussed the similarity in white matter deficit patterns among SSD, BD, MDD, and OCD and provided a rationale for using this index in cross-diagnostic neuropsychiatric research. We also discussed the difference in deficit patterns between idiopathic schizophrenia and 22q11 deletion syndrome, which is used as a developmental and genetic model of schizophrenia. Together, these findings highlight the importance of collaborative large-scale research to provide robust and reproducible effects that offer insights into individual vulnerability and cross-diagnosis features.

Studies of posttraumatic stress disorder (PTSD) report volume abnormalities in multiple regions of the cerebral cortex. However, findings for many regions, particularly regions outside commonly studied emotion-related prefrontal, insular, and limbic regions, are inconsistent and tentative. Also, few studies address the possibility that PTSD abnormalities may be confounded by comorbid depression. A mega-analysis investigating all cortical regions in a large sample of PTSD and control subjects can potentially provide new insight into these issues. Given this perspective, our group aggregated regional volumes data of 68 cortical regions across both hemispheres from 1379 PTSD patients to 2192 controls without PTSD after data were processed by 32 international laboratories using ENIGMA standardized procedures. We examined whether regional cortical volumes were different in PTSD vs. controls, were associated with posttraumatic stress symptom (PTSS) severity, or were affected by comorbid depression. Volumes of left and right lateral orbitofrontal gyri (LOFG), left superior temporal gyrus, and right insular, lingual and superior parietal gyri were significantly smaller, on average, in PTSD patients than controls (standardized coefficients = -0.111 to -0.068, FDR corrected P values

A growing number of studies have examined alterations in white matter organization in people with posttraumatic stress disorder (PTSD) using diffusion MRI (dMRI), but the results have been mixed which may be partially due to relatively small sample sizes among studies. Altered structural connectivity may be both a neurobiological vulnerability for, and a result of, PTSD. In an effort to find reliable effects, we present a multi-cohort analysis of dMRI metrics across 3047 individuals from 28 cohorts currently participating in the PGC-ENIGMA PTSD working group (a joint partnership between the Psychiatric Genomics Consortium and the Enhancing NeuroImaging Genetics through Meta-Analysis consortium). Comparing regional white matter metrics across the full brain in 1426 individuals with PTSD and 1621 controls (2174 males/873 females) between ages 18-83, 92% of whom were trauma-exposed, we report associations between PTSD and disrupted white matter organization measured by lower fractional anisotropy (FA) in the tapetum region of the corpus callosum (Cohen's d = -0.11, p = 0.0055). The tapetum connects the left and right hippocampus, for which structure and function have been consistently implicated in PTSD. Results were consistent even after accounting for the effects of multiple potentially confounding variables: childhood trauma exposure, comorbid depression, history of traumatic brain injury, current alcohol abuse or dependence, and current use of psychotropic medications. Our results show that PTSD may be associated with alterations in the broader hippocampal network.

ObjectiveOur study addressed aims: (1) test the hypothesis that moderate-severe TBI in pediatric patients is associated with widespread white matter (WM) disruption; (2) test the hypothesis that age and sex impact WM organization after injury; and (3) examine associations between WM organization and neurobehavioral outcomes.MethodsData from ten previously enrolled, existing cohorts recruited from local hospitals and clinics were shared with the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Pediatric msTBI working group. We conducted a coordinated analysis of diffusion MRI (dMRI) data using the ENIGMA dMRI processing pipeline.ResultsFive hundred and seven children and adolescents (244 with complicated mild to severe TBI [msTBI] and 263 controls) were included. Patients were clustered into three post-injury intervals: acute/subacute -

Traumatic brain injury (TBI) is common among military personnel and the civilian population and is often followed by a heterogeneous array of clinical, cognitive, behavioral, mood, and neuroimaging changes. Unlike many neurological disorders that have a characteristic abnormal central neurologic area(s) of abnormality pathognomonic to the disorder, a sufficient head impact may cause focal, multifocal, diffuse or combination of injury to the brain. This inconsistent presentation makes it difficult to establish or validate biological and imaging markers that could help improve diagnostic and prognostic accuracy in this patient population. The purpose of this manuscript is to describe both the challenges and opportunities when conducting military-relevant TBI research and introduce the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Military Brain Injury working group. ENIGMA is a worldwide consortium focused on improving replicability and analytical power through data sharing and collaboration. In this paper, we discuss challenges affecting efforts to aggregate data in this patient group. In addition, we highlight how "big data" approaches might be used to understand better the role that each of these variables might play in the imaging and functional phenotypes of TBI in Service member and Veteran populations, and how data may be used to examine important military specific issues such as return to duty, the late effects of combat-related injury, and alteration of the natural aging processes.

Proton (1H) magnetic resonance spectroscopy provides a non-invasive and quantitative measure of brain metabolites. Traumatic brain injury impacts cerebral metabolism and a number of research groups have successfully used this technique as a biomarker of injury and/or outcome in both pediatric and adult TBI populations. However, this technique is underutilized, with studies being performed primarily at centers with access to MR research support. In this paper we present a technical introduction to the acquisition and analysis of in vivo 1H magnetic resonance spectroscopy and review 1H magnetic resonance spectroscopy findings in different injury populations. In addition, we propose a basic 1H magnetic resonance spectroscopy data acquisition scheme (Supplemental Information) that can be added to any imaging protocol, regardless of clinical magnetic resonance platform. We outline a number of considerations for study design as a way of encouraging the use of 1H magnetic resonance spectroscopy in the study of traumatic brain injury, as well as recommendations to improve data harmonization across groups already using this technique.

The global burden of mortality and morbidity caused by traumatic brain injury (TBI) is significant, and the heterogeneity of TBI patients and the relatively small sample sizes of most current neuroimaging studies is a major challenge for scientific advances and clinical translation. The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Adult moderate/severe TBI (AMS-TBI) working group aims to be a driving force for new discoveries in AMS-TBI by providing researchers world-wide with an effective framework and platform for large-scale cross-border collaboration and data sharing. Based on the principles of transparency, rigor, reproducibility and collaboration, we will facilitate the development and dissemination of multiscale and big data analysis pipelines for harmonized analyses in AMS-TBI using structural and functional neuroimaging in combination with non-imaging biomarkers, genetics, as well as clinical and behavioral measures. Ultimately, we will offer investigators an unprecedented opportunity to test important hypotheses about recovery and morbidity in AMS-TBI by taking advantage of our robust methods for large-scale neuroimaging data analysis. In this consensus statement we outline the working group's short-term, intermediate, and long-term goals.

Traumatic brain injury (TBI) is a major cause of death and disability in children in both developed and developing nations. Children and adolescents suffer from TBI at a higher rate than the general population, and specific developmental issues require a unique context since findings from adult research do not necessarily directly translate to children. Findings in pediatric cohorts tend to lag behind those in adult samples. This may be due, in part, both to the smaller number of investigators engaged in research with this population and may also be related to changes in safety laws and clinical practice that have altered length of hospital stays, treatment, and access to this population. The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Pediatric Moderate/Severe TBI (msTBI) group aims to advance research in this area through global collaborative meta-analysis of neuroimaging data. In this paper, we discuss important challenges in pediatric TBI research and opportunities that we believe the ENIGMA Pediatric msTBI group can provide to address them. With the paucity of research studies examining neuroimaging biomarkers in pediatric patients with TBI and the challenges of recruiting large numbers of participants, collaborating to improve statistical power and to address technical challenges like lesions will significantly advance the field. We conclude with recommendations for future research in this field of study.

The volume of subcortical structures represents a reliable, quantitative, and objective phenotype that captures genetic effects, environmental effects such as trauma, and disease effects such as posttraumatic stress disorder (PTSD). Trauma and PTSD represent potent exposures that may interact with genetic markers to influence brain structure and function. Genetic variants, associated with subcortical volumes in two large normative discovery samples, were used to compute polygenic scores (PGS) for the volume of seven subcortical structures. These were applied to a target sample enriched for childhood trauma and PTSD. Subcortical volume PGS from the discovery sample were strongly associated in our trauma/PTSD enriched sample (n = 7580) with respective subcortical volumes of the hippocampus (p = 1.10 × 10-20), thalamus (p = 7.46 × 10-10), caudate (p = 1.97 × 10-18), putamen (p = 1.7 × 10-12), and nucleus accumbens (p = 1.99 × 10-7). We found a significant association between the hippocampal volume PGS and hippocampal volume in control subjects from our sample, but was absent in individuals with PTSD (GxE; (beta = -0.10, p = 0.027)). This significant GxE (PGS × PTSD) relationship persisted (p

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.

Increased task-related blood oxygen level dependent (BOLD) activation is commonly observed in functional magnetic resonance imaging (fMRI) studies of moderate/severe traumatic brain injury (msTBI), but the functional relevance of these hyperactivations and how they are linked to more direct measures of neuronal function remain largely unknown. Here, we investigated how working memory load (WML)-dependent BOLD activation was related to an electrophysiological measure of interhemispheric transfer time (IHTT) in a sample of 18 msTBI patients and 26 demographically matched controls from the UCLA RAPBI (Recovery after Pediatric Brain Injury) study. In the context of highly similar fMRI task performance, a subgroup of TBI patients with slow IHTT had greater BOLD activation with higher WML than both healthy control children and a subgroup of msTBI patients with normal IHTT. Slower IHTT treated as a continuous variable was also associated with BOLD hyperactivation in the full TBI sample and in controls. Higher WML-dependent BOLD activation was related to better performance on a clinical cognitive performance index, an association that was more pronounced within the patient group with slow IHTT. Our previous work has shown that a subgroup of children with slow IHTT after pediatric msTBI has increased risk for poor white matter organization, long-term neurodegeneration, and poor cognitive outcome. BOLD hyperactivations after msTBI may reflect neuronal compensatory processes supporting higher-order capacity demanding cognitive functions in the context of inefficient neuronal transfer of information. The link between BOLD hyperactivations and slow IHTT adds to the multi-modal validation of this electrophysiological measure as a promising biomarker.

Traumatic brain injury is the leading cause of death and disability in the United States, and may be associated with long lasting impairments into adulthood. The multitude of ongoing neurobiological processes that occur during brain maturation confer both considerable vulnerability to TBI but may also provide adaptability and potential for recovery. This review will examine and synthesize our current understanding of developmental neurobiology in the context of pediatric TBI. Delineating this biology will facilitate more targeted initial care, mechanism-based therapeutic interventions and better long-term prognostication and follow-up.

Introduction: Neuroimaging has expanded our understanding of pediatric brain disorders in which white matter organization and connectivity are crucial to functioning. Paralleling the known pathobiology of many neurodevelopmental disorders, traumatic brain injury (TBI) in childhood can alter trajectories of brain development. Specifically, diffusion tensor imaging (DTI) studies in TBI have demonstrated white matter (WM) abnormalities that suggest microstructural disruptions that may underlie atypical neurodevelopment. The neurocognitive correlates of these previous findings will be explored in this study. Methods: Indicators of WM organization were collected in 44 pediatric patients with moderate/severe TBI and 76 controls over two post-injury time points: T1 (8–20 weeks) and T2 (54–96 weeks). Our previous work identified two TBI subgroups based on information processing differences: one with slower interhemispheric transfer times (IHTT) of visual information than controls and another with comparable IHTT. We extend this prior work by evaluating neurocognitive trajectories associated with divergent WM structure post-injury in slow and normal IHTT TBI subgroups. Results: At T1, both TBI subgroups performed significantly worse than controls on a norm-referenced working memory index (WMI), but only the Normal IHTT TBI subgroup significantly improved over the 12-month follow-up period (p = 0.014) to match controls (p = 0.119). In contrast, the Slow IHTT TBI subgroup did not show any recovery in working memory performance over time and performed more poorly than the control group (p < 0.001) at T2. Improvement in one of the two WMI subtests was associated with DTI indicators of WM disorganization in CC tracts to the precentral, postcentral, frontal, and parietal cortices. IHTT and WM mean diffusivity predicted 79% of the variance in cognitive recovery from T1 to T2 when also accounting for other known predictors of TBI recovery. Discussion: In the year following TBI, some pediatric patients experienced persisting working memory disturbance while others exhibited recovery; stratification was based on an event-related potential marker. More or less improvement in neurocognition was also associated with the degree of WM disorganization. IHTT, measured post-acutely after TBI, and progression of WM disorganization over time predicted neurocognitive trajectories at the chronic timeframe - potentially representing a prognostic biomarker. [ABSTRACT FROM AUTHOR]

Traumatic brain injury (TBI) is a significant public health problem in the United States, especially for children and adolescents. Current epidemiological data estimate over 600,000 patients younger than 20 years are treated for TBI in emergency rooms annually. While many patients experience a full recovery, for others there can be long-lasting cognitive, neurological, psychological, and behavioral disruptions. TBI in youth can disrupt ongoing brain development and create added family stress during a formative period. The neuroimaging methods used to assess brain injury improve each year, providing researchers a more detailed characterization of the injury and recovery process. In this review, we cover current imaging methods used to quantify brain disruption post-injury, including structural magnetic resonance imaging (MRI), diffusion MRI, functional MRI, resting state fMRI, and magnetic resonance spectroscopy (MRS), with brief coverage of other methods, including electroencephalography (EEG), single-photon emission computed tomography (SPECT), and positron emission tomography (PET). We include studies focusing on pediatric moderate-severe TBI from 2 months post-injury and beyond. While the morbidity of pediatric TBI is considerable, continuing advances in imaging methods have the potential to identify new treatment targets that can lead to significant improvements in outcome.

Traumatic brain injury can cause extensive damage to the white matter (WM) of the brain. These disruptions can be especially damaging in children, whose brains are still maturing. Diffusion magnetic resonance imaging (dMRI) is the most commonly used method to assess WM organization, but it has limited resolution to differentiate causes of WM disruption. Magnetic resonance spectroscopy (MRS) yields spectra showing the levels of neurometabolites that can indicate neuronal/axonal health, inflammation, membrane proliferation/turnover, and other cellular processes that are on-going post-injury. Previous analyses on this dataset revealed a significant division within the msTBI patient group, based on interhemispheric transfer time (IHTT); one subgroup of patients (TBI-normal) showed evidence of recovery over time, while the other showed continuing degeneration (TBI-slow). We combined dMRI with MRS to better understand WM disruptions in children with moderate-severe traumatic brain injury (msTBI). Tracts with poorer WM organization, as shown by lower FA and higher MD and RD, also showed lower N-acetylaspartate (NAA), a marker of neuronal and axonal health and myelination. We did not find lower NAA in tracts with normal WM organization. Choline, a marker of inflammation, membrane turnover, or gliosis, did not show such associations. We further show that multi-modal imaging can improve outcome prediction over a single modality, as well as over earlier cognitive function measures. Our results suggest that demyelination plays an important role in WM disruption post-injury in a subgroup of msTBI children and indicate the utility of multi-modal imaging.

Traumatic brain injury (TBI) is a major public health issue around the world and can be especially devastating in children as TBI can derail cognitive and social development. White matter (WM) is particularly vulnerable to disruption post-TBI, as myelination is ongoing during this period. Diffusion magnetic resonance imaging (dMRI) is a versatile modality for identifying and quantifying WM disruption and can detect diffuse axonal injury (DAI or TAI (traumatic axonal injury)). This review covers dMRI studies of pediatric TBI, including mild to severe injuries, and covering all periods post-injury. While there have been considerable advances in our understanding of pediatric TBI through the use of dMRI, there are still large gaps in our knowledge, which will be filled in by larger studies and more longitudinal studies. Heterogeneity post-injury is an obstacle in all TBI studies, but we expect that larger better-characterized samples will aid in identifying clinically meaningful subgroups within the pediatric TBI patient population.

ObjectiveTo examine longitudinal trajectories of white matter organization in pediatric moderate/severe traumatic brain injury (msTBI) over a 12-month period.MethodsWe studied 21 children (16 M/5 F) with msTBI, assessed 2-5 months postinjury and again 13-19 months postinjury, as well as 20 well-matched healthy control children. We assessed corpus callosum function through interhemispheric transfer time (IHTT), measured using event-related potentials, and related this to diffusion-weighted MRI measures of white matter (WM) microstructure. At the first time point, half of the patients with TBI had significantly slower IHTT (TBI-slow-IHTT, n = 11) and half were in the normal range (TBI-normal-IHTT, n = 10).ResultsThe TBI-normal-IHTT group did not differ significantly from healthy controls, either in WM organization in the chronic phase or in the longitudinal trajectory of WM organization between the 2 evaluations. In contrast, the WM organization of the TBI-slow-IHTT group was significantly lower than in healthy controls across a large portion of the WM. Longitudinal analyses showed that the TBI-slow-IHTT group experienced a progressive decline between the 2 evaluations in WM organization throughout the brain.ConclusionsWe present preliminary evidence suggesting a potential biomarker that identifies a subset of patients with impaired callosal organization in the first months postinjury who subsequently experience widespread continuing and progressive degeneration in the first year postinjury.

Traumatic brain injury (TBI) is a significant public health concern, and can be especially disruptive in children, derailing on-going neuronal maturation in periods critical for cognitive development. There is considerable heterogeneity in post-injury outcomes, only partially explained by injury severity. Understanding the time course of recovery, and what factors may delay or promote recovery, will aid clinicians in decision-making and provide avenues for future mechanism-based therapeutics. We examined regional changes in brain volume in a pediatric/adolescent moderate-severe TBI (msTBI) cohort, assessed at two time points. Children were first assessed 2-5 months post-injury, and again 12 months later. We used tensor-based morphometry (TBM) to localize longitudinal volume expansion and reduction. We studied 21 msTBI patients (5 F, 8-18 years old) and 26 well-matched healthy control children, also assessed twice over the same interval. In a prior paper, we identified a subgroup of msTBI patients, based on interhemispheric transfer time (IHTT), with significant structural disruption of the white matter (WM) at 2-5 months post injury. We investigated how this subgroup (TBI-slow, N = 11) differed in longitudinal regional volume changes from msTBI patients (TBI-normal, N = 10) with normal WM structure and function. The TBI-slow group had longitudinal decreases in brain volume in several WM clusters, including the corpus callosum and hypothalamus, while the TBI-normal group showed increased volume in WM areas. Our results show prolonged atrophy of the WM over the first 18 months post-injury in the TBI-slow group. The TBI-normal group shows a different pattern that could indicate a return to a healthy trajectory.

Traumatic brain injury (TBI) is the leading cause of death and disability in children, and can lead to long lasting functional impairment. Many factors influence outcome, but imaging studies examining effects of individual variables are limited by sample size. Roughly 20-40% of hospitalized TBI patients experience seizures, but not all of these patients go on to develop a recurrent seizure disorder. Here we examined differences in structural network connectivity in pediatric patients who had sustained a moderate-severe TBI (msTBI). We compared those who experienced early post-traumatic seizures to those who did not; we found network differences months after seizure activity stopped. We also examined correlations between network measures and a common measure of injury severity, the Glasgow Coma Scale (GCS). The global GCS score did not have a detectable relationship to brain integrity, but sub-scores of the GCS (eyes, motor, verbal) were more closely related to imaging measures.

In this review, we discuss recent work by the ENIGMA Consortium (http://enigma.ini.usc.edu) - a global alliance of over 500 scientists spread across 200 institutions in 35 countries collectively analyzing brain imaging, clinical, and genetic data. Initially formed to detect genetic influences on brain measures, ENIGMA has grown to over 30 working groups studying 12 major brain diseases by pooling and comparing brain data. In some of the largest neuroimaging studies to date - of schizophrenia and major depression - ENIGMA has found replicable disease effects on the brain that are consistent worldwide, as well as factors that modulate disease effects. In partnership with other consortia including ADNI, CHARGE, IMAGEN and others1, ENIGMA's genomic screens - now numbering over 30,000 MRI scans - have revealed at least 8 genetic loci that affect brain volumes. Downstream of gene findings, ENIGMA has revealed how these individual variants - and genetic variants in general - may affect both the brain and risk for a range of diseases. The ENIGMA consortium is discovering factors that consistently affect brain structure and function that will serve as future predictors linking individual brain scans and genomic data. It is generating vast pools of normative data on brain measures - from tens of thousands of people - that may help detect deviations from normal development or aging in specific groups of subjects. We discuss challenges and opportunities in applying these predictors to individual subjects and new cohorts, as well as lessons we have learned in ENIGMA's efforts so far.

Background and Purpose: Sport-specific training may improve postural control, while repetitive head acceleration events (RHAEs) may compromise it. Understanding the neural mechanisms underlying postural control may contextualize changes due to training and RHAE. The goal of this study was to determine whether postural sway during the Balance Error Scoring System (BESS) is related to white matter organization (WMO) in collegiate athletes. Methods: Collegiate soccer (N = 33) and non-soccer athletes (N = 44) completed BESS and diffusion tensor imaging. Postural sway during each BESS stance, fractional anisotropy (FA), and mean diffusivity (MD) were extracted for each participant. Partial least squares analyses determined group differences in postural sway and WMO and the relationship between postural sway andWMOin soccer and non-soccer athletes separately. Results: Soccer athletes displayed better performance during BESS 6, with lower FA and higher MD in the medial lemniscus (ML) and inferior cerebellar peduncle (ICP), compared to non-soccer athletes. In soccer athletes, lower sway during BESS 2, 5, and 6 was associated with higher FA and lower MD in the corticospinal tract, ML, and ICP. In non-soccer athletes, lower sway during BESS 2 and 4 was associated with higher FA and lower MD in the ML and ICP. BESS 1 was associated with higher FA, and BESS 3 was associated with lower MD in the same tracts in non-soccer athletes. Discussion and Conclusions: Soccer and non-soccer athletes showed unique relationships between sway and WMO, suggesting that sportspecific exposures are partly responsible for changes in neurological structure and accompanying postural control performance and should be considered when evaluating postural control after injury. [ABSTRACT FROM AUTHOR]

Traumatic brain injury (TBI) can disrupt the white matter (WM) integrity in the brain, leading to functional and cognitive disruptions that may persist for years. There is considerable heterogeneity within the patient group, which complicates group analyses. Here we present improvements to a tract identification workflow, automated multi-atlas tract extraction (autoMATE), evaluating the effects of improved registration. Use of study-specific template improved group classification accuracy over the standard workflow. The addition of a multi-modal registration that includes information from diffusion weighted imaging (DWI), T1-weighted, and Fluid-Attenuated Inversion Recovery (FLAIR) further improved classification accuracy. We also examined whether particular tracts contribute more to group classification than others. Parts of the corpus callosum contributed most, and there were unexpected asymmetries between bilateral tracts.

Traumatic brain injury (TBI) often results in traumatic axonal injury and white matter (WM) damage, particularly to the corpus callosum (CC). Damage to the CC can lead to impaired performance on neurocognitive tasks, but there is a high degree of heterogeneity in impairment following TBI. Here we examined the relation between CC microstructure and function in pediatric TBI. We used high angular resolution diffusion-weighted imaging (DWI) to evaluate the structural integrity of the CC in humans following brain injury in a sample of 32 children (23 males and 9 females) with moderate-to-severe TBI (msTBI) at 1-5 months postinjury, compared with well matched healthy control children. We assessed CC function through interhemispheric transfer time (IHTT) as measured using event-related potentials (ERPs), and related this to DWI measures of WM integrity. Finally, the relation between DWI and IHTT results was supported by additional results of neurocognitive performance assessed using a single composite performance scale. Half of the msTBI participants (16 participants) had significantly slower IHTTs than the control group. This slow IHTT group demonstrated lower CC integrity (lower fractional anisotropy and higher mean diffusivity) and poorer neurocognitive functioning than both the control group and the msTBI group with normal IHTTs. Lower fractional anisotropy-a common sign of impaired WM-and slower IHTTs also predicted poor neurocognitive function. This study reveals that there is a subset of pediatric msTBI patients during the post-acute phase of injury who have markedly impaired CC functioning and structural integrity that is associated with poor neurocognitive functioning.Significance statementTraumatic brain injury (TBI) is the primary cause of death and disability in children and adolescents. There is considerable heterogeneity in postinjury outcome, which is only partially explained by injury severity. Imaging biomarkers may help explain some of this variance, as diffusion weighted imaging is sensitive to the white matter disruption that is common after injury. The corpus callosum (CC) is one of the most commonly reported areas of disruption. In this multimodal study, we discovered a divergence within our pediatric moderate-to-severe TBI sample 1-5 months postinjury. A subset of the TBI sample showed significant impairment in CC function, which is supported by additional results showing deficits in CC structural integrity. This subset also had poorer neurocognitive functioning. Our research sheds light on postinjury heterogeneity.

Traumatic brain injury (TBI) is the leading cause of death and disability in children. Diffusion weighted imaging (DWI) methods have been shown to be especially sensitive to white matter abnormalities in TBI. We used our newly developed autoMATE algorithm (automated multi-atlas tract extraction) to map altered WM integrity in TBI. Even so, tractography methods include a free parameter that limits the maximum permissible turning angles for extracted fibers, with little investigation of how this may affect statistical group comparisons. Here, we examined WM integrity calculated over a range of fiber turning angles to determine to what extent this parameter affects our ability to detect group differences. Fiber turning angle threshold has a subtle, but sometimes significant, effect on the differences we were able to detect between TBI and healthy children.

Traumatic brain injury (TBI) is the leading cause of death and disability in children and can lead to a wide range of impairments. Brain imaging methods such as DTI (diffusion tensor imaging) are uniquely sensitive to the white matter (WM) damage that is common in TBI. However, higher-level analyses using tractography are complicated by the damage and decreased FA (fractional anisotropy) characteristic of TBI, which can result in premature tract endings. We used the newly developed autoMATE (automated multi-atlas tract extraction) method to identify differences in WM integrity. 63 pediatric patients aged 8-19 years with moderate/severe TBI were examined with cross sectional scanning at one or two time points after injury: a post-acute assessment 1-5 months post-injury and a chronic assessment 13-19 months post-injury. A battery of cognitive function tests was performed in the same time periods. 56 children were examined in the first phase, 28 TBI patients and 28 healthy controls. In the second phase 34 children were studied, 17 TBI patients and 17 controls (27 participants completed both post-acute and chronic phases). We did not find any significant group differences in the post-acute phase. Chronically, we found extensive group differences, mainly for mean and radial diffusivity (MD and RD). In the chronic phase, we found higher MD and RD across a wide range of WM. Additionally, we found correlations between these WM integrity measures and cognitive deficits. This suggests a distributed pattern of WM disruption that continues over the first year following a TBI in children.