1,445 research outputs found

    Enhanced pre-frontal functional-structural networks to support postural control deficits after traumatic brain injury in a pediatric population

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    Traumatic brain injury (TBI) affects the structural connectivity, triggering the re-organization of structural-functional circuits in a manner that remains poorly understood. We focus here on brain networks re-organization in relation to postural control deficits after TBI. We enrolled young participants who had suffered moderate to severeTBI, comparing them to young typically developing control participants. In comparison to control participants, TBI patients (but not controls) recruited prefrontal regions to interact with two separated networks: 1) a subcortical network including part of the motor network, basal ganglia, cerebellum, hippocampus, amygdala, posterior cingulum and precuneus; and 2) a task-positive network, involving regions of the dorsal attention system together with the dorsolateral and ventrolateral prefrontal regions

    ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

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    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

    Neural correlates of post-traumatic brain injury (TBI) attention deficits in children

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    Traumatic brain injury (TBI) in children is a major public health concern worldwide. Attention deficits are among the most common neurocognitive and behavioral consequences in children post-TBI which have significant negative impacts on their educational and social outcomes and compromise the quality of their lives. However, there is a paucity of evidence to guide the optimal treatment strategies of attention deficit related symptoms in children post-TBI due to the lack of understanding regarding its neurobiological substrate. Thus, it is critical to understand the neural mechanisms associated with TBI-induced attention deficits in children so that more refined and tailored strategies can be developed for diagnoses and long-term treatments and interventions. This dissertation is the first study to investigate neurobiological substrates associated with post-TBI attention deficits in children using both anatomical and functional neuroimaging data. The goals of this project are to discover the quantitatively measurable markers utilizing diffusion tensor imaging (DTI), structural magnetic resonance imaging (MRI), and functional MRI (fMRI) techniques, and to further identify the most robust neuroimaging features in predicting severe post-TBI attention deficits in children, by utilizing machine learning and deep learning techniques. A total of 53 children with TBI and 55 controls from age 9 to 17 are recruited. The results show that the systems-level topological properties in left frontal regions, parietal regions, and medial occipitotemporal regions in structural and functional brain network are significantly associated with inattentive and/or hyperactive/impulsive symptoms in children post-TBI. Semi-supervised deep learning modeling further confirms the significant contributions of these brain features in the prediction of elevated attention deficits in children post-TBI. The findings of this project provide valuable foundations for future research on developing neural markers for TBI-induced attention deficits in children, which may significantly assist the development of more effective and individualized diagnostic and treatment strategies

    Direction-Dependent Responses To Traumatic Brain Injury In Pediatric Pigs

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    Traumatic brain injury (TBI) in children is a costly and alarmingly prevalent public health concern. Children (4-11 years of age) in the US have the highest rate of TBI-related emergency department visits. The plane of head rotation significantly affects neurocognitive deficits and pathophysiological responses such as axonal injury, but is largely ignored in TBI literature. In Chapter 1, an outline of existing research is provided, including the lack of attention to diagnosis, treatment, and prevention in children, who exhibit distinct biomechanical and neuropathological responses to TBI. Additionally, we hypothesize that the plane of head rotation in TBI induces a) region-specific changes in axonal injury, which lead to acute and chronic changes in electrophysiological responses; b) changes to event-related potentials and resting state electroencephalography (EEG) and c) tract-oriented strain and strain rate alterations in the white matter. All work in this dissertation is based on a well-established piglet model of TBI. In Chapter 2, we assess a novel rotational head kinematic metric, rotational work (RotWork), which incorporates head rotation rate, direction, and brain shape, as a predictor of acute axonal injury. This metric provides an improvement over existing metrics and could be useful in the development of effective child safety equipment used in recreation or transportation. In Chapter 3, we generate functional networks from auditory event-related potentials and use the patterns of change to distinguish injured brains from non-injured; the resulting algorithm showed an 82% predictive accuracy. In Chapter 4, we find elevations in network nodal strength, modularity and clustering coefficient after TBI across all frequency bands relative to baseline, whereas both metrics were reduced in shams. We report the first study using resting state EEG to create functional networks in relation to pediatric TBI, noting that this work may assist in the development of TBI biomarkers. In Chapter 5, we use a high-resolution finite element model to examine the effects of head rotation plane on the distribution of regional strains and strain rates. Sagittal rapid head rotations induced significantly larger volume fraction of damaged brainstem than axial and coronal rotations. We also found that local tissue deformation and histopathology were head direction- and region- dependent but poorly correlated at a local scale. Finally, in Chapter 6, we conclude that the work presented in this dissertation is novel and contributes valuable knowledge to the study of pediatric TBI, and that consideration of the plane of head rotation is critical to the understanding and accurate prediction of pediatric functional and region-dependent responses to TBI

    Anatomic Insights into Disrupted Small-World Networks in Pediatric Posttraumatic Stress Disorder.

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    Purpose To use diffusion-tensor (DT) imaging and graph theory approaches to explore the brain structural connectome in pediatric posttraumatic stress disorder (PTSD). Materials and Methods This study was approved by the relevant research ethics committee, and all participants’ parents or guardians provided informed consent. Twenty-four pediatric patients with PTSD and 23 control subjects exposed to trauma but without PTSD were recruited after the 2008 Sichuan earthquake. The structural connectome was constructed by using DT imaging tractography and thresholding the mean fractional anisotropy of 90 brain regions to yield 90 × 90 partial correlation matrixes. Graph theory analysis was used to examine the group-specific topologic properties, and nonparametric permutation tests were used for group comparisons of topologic metrics. Results Both groups exhibited small-world topology. However, patients with PTSD showed an increase in the characteristic path length (P = .0248) and decreases in local efficiency (P = .0498) and global efficiency (P = .0274). Furthermore, patients with PTSD showed reduced nodal centralities, mainly in the default mode, salience, central executive, and visual regions (P < .05, corrected for false-discovery rate). The Clinician-Administered PTSD Scale score was negatively correlated with the nodal efficiency of the left superior parietal gyrus (r = −0.446, P = .043). Conclusion The structural connectome showed a shift toward “regularization,” providing a structural basis for functional alterations of pediatric PTSD. These abnormalities suggest that PTSD can be understood by examining the dysfunction of large-scale spatially distributed neural networks
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