Changes in Structural Connectivity Following a Cognitive Intervention in Children With Traumatic Brain Injury

Altered functional connectivity of brainstem ARAS nuclei unveils the mechanisms of disorders of consciousness in sTBI: an exploratory study

OBJECTIVE

To investigate the functional connectivity (FC) characteristics of Ascending Reticular Activating System (ARAS) in patients with disorders of consciousness (DOC) following severe traumatic brain injury (sTBI), while introducing the Linear support vector machine (LSVM) to predict the recovery of consciousness.

METHODS

Resting-state MRI was used to measure FC changes between the brainstem ARAS nuclei and whole-brain voxels. We compared the differences in FC between sTBI patients and healthy controls, as well as between the wake and DOC groups. Furthermore, the LSVM model for consciousness recovery was developed based on the Z-values of regions of interest (ROIs) and/or scale to distinguish the prognosis of sTBI patients.

RESULTS

A total of 28 sTBI patients with DOC and 30 healthy controls were included, with no significant baseline differences (p > 0.05). Using the brainstem ARAS nuclei as the ROI, we observed increased FC in the subcortical regions compared to healthy controls. The strength of FC was significantly different between patients who recovered consciousness and those who did not at 6 months post-sTBI (AlphaSim corrected, p < 0.05, Cluster > 154). Furthermore, the LSVM model demonstrated strong predictive performance, with an area under the receiver operating characteristic curve of 0.81-0.98.

CONCLUSIONS

Our study suggest that the disruption FC of ARAS from the subcortex to the cortex may be associated with DOC and prognosis in sTBI patients. Furthermore, the LSVM model shows potential value in distinguishing the recovery of consciousness.

Correlations Between Morpho-structural Properties of the Brain and Cognitive and Motor Deficits in Individuals with Traumatic Brain Injury

Traumatic brain injury (TBI) results in changes in brain networks followed by long-lasting behavioral and social impairments. This study explores the relationship between neurobehavioral as well as physical function deficits and structural changes in brain white matter (WM) and gray matter (GM) in individuals with TBI by evaluating morphometric magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) data. The structural MRI-based fractal analysis has emerged as a promising new approach to measure the morphology of the WM and GM. While DTI metrics reflect the microstructural properties of WM, the fractal dimension (FD) is regarded as a measure of morphometric complexity of the system, thus providing complementary information on the brain structure. This study included 10 individuals having moderate-to-severe TBI with balance/postural control deficits and 8 healthy controls. The network-based GM and WM morphologies were measured using FD and structural connectivity metrics, and fractional anisotropy (FA) was assessed using DTI in major WM tracts. The associations between brain structural (FA and FD) measures and a number of neuropsychological assessment and sensorimotor function outcomes were evaluated using partial least square correlation analysis. Our findings showed that the complexity in GM of default mode network, salience network, sensorimotor network, and frontoparietal network is positively correlated with the performance in cognitive and balance outcomes in patients with TBI. On the contrary, in DTI connectivity measures, only few regions including corona radiata, inferior longitudinal fasciculus, and middle cerebellar peduncle were strongly correlated with the behavioral outcomes in the TBI group. Our study suggests that the brain structure complexity measured by FD is a promising and complementary approach to DTI for potentially serving as a biomarker of cognitive and sensorimotor functions in TBI population.

Relationship Between Structural and Functional Network Connectivity Changes for Patients With Traumatic Brain Injury and Chronic Health Symptoms

Combination of structural and functional brain connectivity methods provides a more complete and effective avenue into the investigation of cortical network responses to traumatic brain injury (TBI) and subtle alterations in brain connectivity associated with TBI. Structural connectivity (SC) can be measured using diffusion tensor imaging to evaluate white matter integrity, whereas functional connectivity (FC) can be studied by examining functional correlations within or between functional networks. In this study, the alterations of SC and FC were assessed for TBI patients, with and without chronic symptoms (TBIcs/TBIncs), compared with a healthy control group (CG). The correlation between global SC and FC was significantly increased for both TBI groups compared with CG. SC was significantly lower in the TBIcs group compared with CG, and FC changes were seen in the TBIncs group compared with CG. When comparing TBI groups, FC differences were observed in the TBIcs group compared with the TBIncs group. These observations show that the presence of chronic symptoms is associated with a distinct pattern of SC and FC changes including the atrophy of the SC and a mixture of functional hypoconnectivity and hyperconnectivity, as well as loss of segregation of functional networks.

Characteristics of the Structural Connectivity in Patients with Brain Injury and Chronic Health Symptoms: A Pilot Study

Diffusion properties from diffusion tensor imaging (DTI) are exquisitely sensitive to white matter abnormalities incurred during traumatic brain injury (TBI), especially for those patients with chronic post-TBI symptoms such as headaches, dizziness, fatigue, etc. The evaluation of structural and functional connectivity using DTI has become a promising method for identifying subtle alterations in brain connectivity associated with TBI that are otherwise not visible with conventional imaging. This study assessed whether TBI patients with (n = 17) or without (n = 16) chronic symptoms (TBIcs/TBIncs) exhibit any changes in structural connectivity (SC) and mean fractional anisotropy (mFA) of intra- and inter-hemispheric connections when compared to a control group (CG) (n = 13). Reductions in SC and mFA were observed for TBIcs compared to CG, but not for TBIncs. More connections were found to have mFA reductions than SC reductions. On the whole, SC is dominated by ipsilateral connections for all the groups after the comparison of contralateral and ipsilateral connections. More contra-ipsi reductions of mFA were found for TBIcs than TBIncs compared to CG. These findings suggest that TBI patients with chronic symptoms not only demonstrate decreased global and regional mFA but also reduced structural network connectivity.

Structural and functional connectivity of the whole brain and subnetworks in individuals with mild traumatic brain injury: predictors of patient prognosis

JOURNAL/nrgr/04.03/01300535-202407000-00035/figure1/v/2023-11-20T171125Z/r/image-tiff

Patients with mild traumatic brain injury have a diverse clinical presentation, and the underlying pathophysiology remains poorly understood. Magnetic resonance imaging is a non-invasive technique that has been widely utilized to investigate neurobiological markers after mild traumatic brain injury. This approach has emerged as a promising tool for investigating the pathogenesis of mild traumatic brain injury. Graph theory is a quantitative method of analyzing complex networks that has been widely used to study changes in brain structure and function. However, most previous mild traumatic brain injury studies using graph theory have focused on specific populations, with limited exploration of simultaneous abnormalities in structural and functional connectivity. Given that mild traumatic brain injury is the most common type of traumatic brain injury encountered in clinical practice, further investigation of the patient characteristics and evolution of structural and functional connectivity is critical. In the present study, we explored whether abnormal structural and functional connectivity in the acute phase could serve as indicators of longitudinal changes in imaging data and cognitive function in patients with mild traumatic brain injury. In this longitudinal study, we enrolled 46 patients with mild traumatic brain injury who were assessed within 2 weeks of injury, as well as 36 healthy controls. Resting-state functional magnetic resonance imaging and diffusion-weighted imaging data were acquired for graph theoretical network analysis. In the acute phase, patients with mild traumatic brain injury demonstrated reduced structural connectivity in the dorsal attention network. More than 3 months of follow-up data revealed signs of recovery in structural and functional connectivity, as well as cognitive function, in 22 out of the 46 patients. Furthermore, better cognitive function was associated with more efficient networks. Finally, our data indicated that small-worldness in the acute stage could serve as a predictor of longitudinal changes in connectivity in patients with mild traumatic brain injury. These findings highlight the importance of integrating structural and functional connectivity in understanding the occurrence and evolution of mild traumatic brain injury. Additionally, exploratory analysis based on subnetworks could serve a predictive function in the prognosis of patients with mild traumatic brain injury.

Attention Please! Unravelling the Link Between Brain Network Connectivity and Cognitive Attention Following Acquired Brain Injury: A Systematic Review of Structural and Functional Measures

Traumatic brain injury (TBI) and stroke are the most common causes of acquired brain injury (ABI), annually affecting 69 million and 15 million people, respectively. Following ABI, the relationship between brain network disruption and common cognitive issues including attention dysfunction is heterogenous. Using PRISMA guidelines, we systematically reviewed 43 studies published by February 2023 that reported correlations between attention and connectivity. Across all ages and stages of recovery, following TBI, greater attention was associated with greater structural efficiency within/between executive control network (ECN), salience network (SN), and default mode network (DMN) and greater functional connectivity (fc) within/between ECN and DMN, indicating DMN interference. Following stroke, greater attention was associated with greater structural connectivity (sc) within ECN; or greater fc within the dorsal attention network (DAN). In childhood ABI populations, decreases in structural network segregation were associated with greater attention. Longitudinal recovery from TBI was associated with normalization of DMN activity, and in stroke, normalization of DMN and DAN activity. Results improve clinical understanding of attention-related connectivity changes after ABI. Recommendations for future research include increased use of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) to measure connectivity at the point of care, standardized attention and connectivity outcome measures and analysis pipelines, detailed reporting of patient symptomatology, and casual analysis of attention-related connectivity using brain stimulation.

Neuroimaging Correlates of Functional Outcome Following Pediatric TBI

Neuroimaging plays an important role in assessing the consequences of TBI across the postinjury period. While identifying alterations to the brain is important, associating those changes to functional, cognitive, and behavioral outcomes is an essential step to establishing the value of advanced neuroimaging for pediatric TBI. Here we highlight research that has revealed links between advanced neuroimaging and outcome after TBI and point to opportunities where neuroimaging could expand our ability to prognosticate and potentially uncover opportunities to intervene.

Structural networking of the developing brain: from maturation to neurosurgical implications

Modern neuroscience agrees that neurological processing emerges from the multimodal interaction among multiple cortical and subcortical neuronal hubs, connected at short and long distance by white matter, to form a largely integrated and dynamic network, called the brain "connectome." The final architecture of these circuits results from a complex, continuous, and highly protracted development process of several axonal pathways that constitute the anatomical substrate of neuronal interactions. Awareness of the network organization of the central nervous system is crucial not only to understand the basis of children's neurological development, but also it may be of special interest to improve the quality of neurosurgical treatments of many pediatric diseases. Although there are a flourishing number of neuroimaging studies of the connectome, a comprehensive vision linking this research to neurosurgical practice is still lacking in the current pediatric literature. The goal of this review is to contribute to bridging this gap. In the first part, we summarize the main current knowledge concerning brain network maturation and its involvement in different aspects of normal neurocognitive development as well as in the pathophysiology of specific diseases. The final section is devoted to identifying possible implications of this knowledge in the neurosurgical field, especially in epilepsy and tumor surgery, and to discuss promising perspectives for future investigations.

Randomized clinical trial on the effects of a computerized cognitive training for pediatric patients with acquired brain injury or congenital malformation

Both acquired injuries and congenital malformations often cause lifelong disabilities in children, with a significant impact on cognitive abilities. Remote computerized cognitive training (CCT) may be delivered in ecological settings to favour rehabilitation continuity. This randomized clinical trial (RCT) evaluated the efficacy of an 8-week multi-domain, home-based CCT in a sample of patients aged 11-16 years with non-progressive acquired brain injury (ABI), brain tumor (BT) and congenital brain malformation (CBM). Following a stepped-wedge research design, patients were randomized into two groups: Training-first group, which started the CCT immediately after baseline assessment and Waiting-first group, which started the CCT after a period of time comparable to that required by the training (8 weeks). Post-training and long-term (6 months) changes were assessed. Both groups improved on visual-spatial working memory after the CCT, with benefits maintained after 6 months, while no other changes in cognitive or psychological measures were found. These findings suggest that a multi-domain CCT can generate benefits in visual-spatial working memory, in accordance with data from extant literature reporting that computer games heavily engage visuo-spatial abilities. We speculate that is tapping on the same cognitive ability with a prolonged training that may generate the greatest change after a CCT.

Altered longitudinal structural connectome in paediatric mild traumatic brain injury: an Advancing Concussion Assessment in Paediatrics study

Advanced diffusion-weighted imaging techniques have increased understanding of the neuropathology of paediatric mild traumatic brain injury (i.e. concussion). Most studies have examined discrete white-matter pathways, which may not capture the characteristically subtle, diffuse and heterogenous effects of paediatric concussion on brain microstructure. This study compared the structural connectome of children with concussion to those with mild orthopaedic injury to determine whether network metrics and their trajectories across time post-injury differentiate paediatric concussion from mild traumatic injury more generally. Data were drawn from of a large study of outcomes in paediatric concussion. Children aged 8-16.99 years were recruited from five paediatric emergency departments within 48 h of sustaining a concussion (n = 360; 56% male) or mild orthopaedic injury (n = 196; 62% male). A reliable change score was used to classify children with concussion into two groups: concussion with or without persistent symptoms. Children completed 3 T MRI at post-acute (2-33 days) and/or chronic (3 or 6 months, via random assignment) post-injury follow-ups. Diffusion-weighted images were used to calculate the diffusion tensor, conduct deterministic whole-brain fibre tractography and compute connectivity matrices in native (diffusion) space for 90 supratentorial regions. Weighted adjacency matrices were constructed using average fractional anisotropy and used to calculate global and local (regional) graph theory metrics. Linear mixed effects modelling was performed to compare groups, correcting for multiple comparisons. Groups did not differ in global network metrics. However, the clustering coefficient, betweenness centrality and efficiency of the insula, cingulate, parietal, occipital and subcortical regions differed among groups, with differences moderated by time (days) post-injury, biological sex and age at time of injury. Post-acute differences were minimal, whereas more robust alterations emerged at 3 and especially 6 months in children with concussion with persistent symptoms, albeit differently by sex and age. In the largest neuroimaging study to date, post-acute regional network metrics distinguished concussion from mild orthopaedic injury and predicted symptom recovery 1-month post-injury. Regional network parameters alterations were more robust and widespread at chronic timepoints than post-acutely after concussion. Results suggest that increased regional and local subnetwork segregation (modularity) and inefficiency occurs across time after concussion, emerging after post-concussive symptom resolve in most children. These differences persist up to 6 months after concussion, especially in children who showed persistent symptoms. While prognostic, the small to modest effect size of group differences and the moderating effects of sex likely would preclude effective clinical application in individual patients.

Structural-functional connectivity bandwidth predicts processing speed in mild traumatic brain Injury: A multiplex network analysis

An emerging body of work has revealed alterations in structural (SC) and functional (FC) brain connectivity following mild TBI (mTBI), with mixed findings. However, these studies seldom integrate complimentary neuroimaging modalities within a unified framework. Multilayer network analysis is an emerging technique to uncover how white matter organization enables functional communication. Using our novel graph metric (SC-FC Bandwidth), we quantified the information capacity of synchronous brain regions in 53 mild TBI patients (46 females; age mean = 40.2 years (y), σ = 16.7 (y), range: 18-79 (y). Diffusion MRI and resting state fMRI were administered at the acute and chronic post-injury intervals. Moreover, participants completed a cognitive task to measure processing speed (30 Seconds and Counting Task; 30-SACT). Processing speed was significantly increased at the chronic, relative to the acute post-injury intervals (p = <0.001). Nonlinear principal components of direct (t = -1.84, p = 0.06) and indirect SC-FC Bandwidth (t = 3.86, p = <0.001) predicted processing speed with a moderate effect size (R2 = 0.43, p < 0.001), while controlling for age. A subnetwork of interhemispheric edges with increased SC-FC Bandwidth was identified at the chronic, relative to the acute mTBI post-injury interval (pFDR = 0.05). Increased interhemispheric SC-FC Bandwidth of this network corresponded with improved processing speed at the chronic post-injury interval (partial r = 0.32, p = 0.02). Our findings revealed that mild TBI results in complex reorganization of brain connectivity optimized for maximum information flow, supporting improved cognitive performance as a compensatory mechanism. Moving forward, this measurement may complement clinical assessment as an objective marker of mTBI recovery.

Abnormal structural and functional network topological properties associated with left prefrontal, parietal, and occipital cortices significantly predict childhood TBI-related attention deficits: A semi-supervised deep learning study

Introduction

Traumatic brain injury (TBI) is a major public health concern in children. Children with TBI have elevated risk in developing attention deficits. Existing studies have found that structural and functional alterations in multiple brain regions were linked to TBI-related attention deficits in children. Most of these existing studies have utilized conventional parametric models for group comparisons, which have limited capacity in dealing with large-scale and high dimensional neuroimaging measures that have unknown nonlinear relationships. Nevertheless, none of these existing findings have been successfully implemented to clinical practice for guiding diagnoses and interventions of TBI-related attention problems. Machine learning techniques, especially deep learning techniques, are able to handle the multi-dimensional and nonlinear information to generate more robust predictions. Therefore, the current research proposed to construct a deep learning model, semi-supervised autoencoder, to investigate the topological alterations in both structural and functional brain networks in children with TBI and their predictive power for post-TBI attention deficits.

Methods

Functional magnetic resonance imaging data during sustained attention processing task and diffusion tensor imaging data from 110 subjects (55 children with TBI and 55 group-matched controls) were used to construct the functional and structural brain networks, respectively. A total of 60 topological properties were selected as brain features for building the model.

Results

The model was able to differentiate children with TBI and controls with an average accuracy of 82.86%. Functional and structural nodal topological properties associated with left frontal, inferior temporal, postcentral, and medial occipitotemporal regions served as the most important brain features for accurate classification of the two subject groups. Post hoc regression-based machine learning analyses in the whole study sample showed that among these most important neuroimaging features, those associated with left postcentral area, superior frontal region, and medial occipitotemporal regions had significant value for predicting the elevated inattentive and hyperactive/impulsive symptoms.

Discussion

Findings of this study suggested that deep learning techniques may have the potential to help identifying robust neurobiological markers for post-TBI attention deficits; and the left superior frontal, postcentral, and medial occipitotemporal regions may serve as reliable targets for diagnosis and interventions of TBI-related attention problems in children.

Processing efficiency in pediatric cancer survivors: A review and operationalization for outcomes research and clinical utility

OBJECTIVE

Childhood cancer and cancer-related treatments disrupt brain development and maturation, placing survivors at risk for cognitive late effects. Given that assessment tools vary widely across researchers and clinicians, it has been daunting to identify distinct patterns in outcomes across diverse cancer types and to implement systematic neurocognitive screening tools. This review aims to operationalize processing efficiency skill impairment-or inefficient neural processing as measured by working memory and processing speed abilities-as a worthwhile avenue for continued study within the context of childhood cancer.

METHODS

A comprehensive literature review was conducted to examine the existing research on cognitive late effects and biopsychosocial risk factors in order to conceptualize processing efficiency skill trends in childhood cancer survivors.

RESULTS

While a frequently reported pattern of neurobiological (white matter) and cognitive (working memory and processing speed) disruption is consistent with processing efficiency skill impairment, these weaknesses have not yet been fully operationalized in this population. We offer a theoretical model that highlights the impacts of a host of biological and environmental factors on the underlying neurobiological substrates of cancer survivors that precede and may even predict long-term cognitive outcomes and functional abilities following treatment.

CONCLUSION

The unified construct of processing efficiency may be useful in assessing and communicating neurocognitive skills in both outcomes research and clinical practice. Deficits in processing efficiency may serve as a possible indicator of cognitive late effects and functional outcomes due to the unique relationship between processing efficiency skills and neurobiological disruption following cancer treatment. Continued research along these lines is crucial for advancing childhood cancer outcomes research and improving quality of life for survivors.

Structural connectome differences in pediatric mild traumatic brain and orthopedic injury

Sophisticated network‐based approaches such as structural connectomics may help to detect a biomarker of mild traumatic brain injury (mTBI) in children. This study compared the structural connectome of children with mTBI or mild orthopedic injury (OI) to that of typically developing (TD) children. Children aged 8–16.99 years with mTBI (n = 83) or OI (n = 37) were recruited from the emergency department and completed 3T diffusion MRI 2–20 days postinjury. TD children (n = 39) were recruited from the community and completed diffusion MRI. Graph theory metrics were calculated for the binarized average fractional anisotropy among 90 regions. Multivariable linear regression and linear mixed effects models were used to compare groups, with covariates age, hemisphere, and sex, correcting for multiple comparisons. The two injury groups did not differ on graph theory metrics, but both differed from TD children in global metrics (local network efficiency: TD > OI, mTBI, d = 0.49; clustering coefficient: TD < OI, mTBI, d = 0.49) and regional metrics for the fusiform gyrus (lower degree centrality and nodal efficiency: TD > OI, mTBI, d = 0.80 to 0.96; characteristic path length: TD < OI, mTBI, d = −0.75 to −0.90) and in the superior and middle orbital frontal gyrus, paracentral lobule, insula, and thalamus (clustering coefficient: TD > OI, mTBI, d = 0.66 to 0.68). Both mTBI and OI demonstrated reduced global and regional network efficiency and segregation as compared to TD children. Findings suggest a general effect of childhood injury that could reflect pre‐ and postinjury factors that can alter brain structure. An OI group provides a more conservative comparison group than TD children for structural neuroimaging research in pediatric mTBI.

The Connectomes: Methods of White Matter Tractography and Contributions of Resting State fMRI

A comprehensive mapping of the structural and functional circuitry of the brain is a major unresolved problem in contemporary neuroimaging research. Diffusion-weighted and functional MRI have provided investigators with the capability to assess structural and functional connectivity in-vivo, driven primarily by methods of white matter tractography and resting-state fMRI, respectively. These techniques have paved the way for the construction of the functional and structural connectomes, which are quantitative representations of brain architecture as neural networks, comprised of nodes and edges. The connectomes, typically depicted as matrices or graphs, possess topological properties that inherently characterize the strength, efficiency, and organization of the connections between distinct brain regions. Graph theory, a general mathematical framework for analyzing networks, can be implemented to derive metrics from the connectomes that are sensitive to changes in brain connectivity associated with age, sex, cognitive function, and disease. These quantities can be assessed at either the global (whole brain) or local levels, allowing for the identification of distinct regional connectivity hubs and associated localized brain networks, which together serve crucial roles in establishing the structural and functional architecture of the brain. As a result, structural and functional connectomes have each been employed to study the brain circuitry underlying early brain development, neuroplasticity, developmental disorders, psychopathology, epilepsy, aging, neurodegenerative disorders, and traumatic brain injury. While these studies have yielded important insights into brain structure, function, and pathology, a precise description of the innate relationship between functional and structural networks across the brain remains unachieved. To date, connectome research has merely scratched the surface of potential clinical applications and related characterizations of brain-wide connectivity. Continued advances in diffusion and functional MRI acquisition, the delineation of functional and structural networks, and the quantification of neural network properties in specific brain regions, will be invaluable to future progress in neuroimaging science.

Topological Aberrance of Structural Brain Network Provides Quantitative Substrates of Post-Traumatic Brain Injury Attention Deficits in Children

Background: Traumatic brain injury (TBI)-induced attention deficits are among the most common long-term cognitive consequences in children. Most of the existing studies attempting to understand the neuropathological underpinnings of cognitive and behavioral impairments in TBI have utilized heterogeneous samples and resulted in inconsistent findings. The current research proposed to investigate topological properties of the structural brain network in children with TBI and their relationship with post-TBI attention problems in a more homogeneous subgroup of children who had severe post-TBI attention deficits (TBI-A). Materials and Methods: A total of 31 children with TBI-A and 35 group-matched controls were involved in the study. Diffusion tensor imaging-based probabilistic tractography and graph theoretical techniques were used to construct the structural brain network in each subject. Network topological properties were calculated in both global level and regional (nodal) level. Between-group comparisons among the topological network measures and analyses for searching brain-behavioral were all corrected for multiple comparisons using Bonferroni method. Results: Compared with controls, the TBI-A group showed significantly higher nodal local efficiency and nodal clustering coefficient in left inferior frontal gyrus and right transverse temporal gyrus, whereas significantly lower nodal clustering coefficient in left supramarginal gyrus and lower nodal local efficiency in left parahippocampal gyrus. The temporal lobe topological alterations were significantly associated with the post-TBI inattentive and hyperactive symptoms in the TBI-A group. Conclusion: The results suggest that TBI-related structural re-modularity in the white matter subnetworks associated with temporal lobe may play a critical role in the onset of severe post-TBI attention deficits in children. These findings provide valuable input for understanding the neurobiological substrates of post-TBI attention deficits, and have the potential to serve as quantitatively measurable criteria guiding the development of more timely and tailored strategies for diagnoses and treatments to the affected individuals. Impact statement This study provides a new insight into the neurobiological substrates associated with post-traumatic brain injury attention deficits (TBI-A) in children, by evaluating topological alterations of the structural brain network. The results demonstrated that relative to group-matched controls, the children with TBI-A had significantly altered nodal local efficiency and nodal clustering coefficient in temporal lobe, which strongly linked to elevated inattentive and hyperactive symptoms in the TBI-A group. These findings suggested that white matter structural re-modularity in subnetworks associated with temporal lobe may serve as quantitatively measurable biomarkers for early prediction and diagnosis of post-TBI attention deficits in children.

Network-level functional topological changes after mindfulness-based cognitive therapy in mood dysregulated adolescents at familial risk for bipolar disorder: a pilot study

BACKGROUND

Given that psychopharmacological approaches routinely used to treat mood-related problems may result in adverse outcomes in mood dysregulated adolescents at familial risk for bipolar disorder (BD), Mindfulness-Based Cognitive Therapy for Children (MBCT-C) provides an alternative effective and safe option. However, little is known about the brain mechanisms of beneficial outcomes from this intervention. Herein, we aimed to investigate the network-level neurofunctional effects of MBCT-C in mood dysregulated adolescents.

METHODS

Ten mood dysregulated adolescents at familial risk for BD underwent a 12-week MBCT-C intervention. Resting-state functional magnetic resonance imaging (fMRI) was performed prior to and following MBCT-C. Topological metrics of three intrinsic functional networks (default mode network (DMN), fronto-parietal network (FPN) and cingulo-opercular network (CON)) were investigated respectively using graph theory analysis.

RESULTS

Following MBCT-C, mood dysregulated adolescents showed increased global efficiency and decreased characteristic path length within both CON and FPN. Enhanced functional connectivity strength of frontal and limbic areas were identified within the DMN and CON. Moreover, change in characteristic path length within the CON was suggested to be significantly related to change in the Emotion Regulation Checklist score.

CONCLUSIONS

12-week MBCT-C treatment in mood dysregulated adolescents at familial risk for BD yield network-level neurofunctional effects within the FPN and CON, suggesting enhanced functional integration of the dual-network. Decreased characteristic path length of the CON may be associated with the improvement of emotion regulation following mindfulness training. However, current findings derived from small sample size should be interpreted with caution. Future randomized controlled trials including larger samples are critical to validate our findings.

Challenges and opportunities for neuroimaging in young patients with traumatic brain injury: a coordinated effort towards advancing discovery from the ENIGMA pediatric moderate/severe TBI group

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.

Training-Induced Neural Plasticity in Youth: A Systematic Review of Structural and Functional MRI Studies

Experience-dependent neural plasticity is high in the developing brain, presenting a unique window of opportunity for training. To optimize existing training programs and develop new interventions, it is important to understand what processes take place in the developing brain during training. Here, we systematically review MRI-based evidence of training-induced neural plasticity in children and adolescents. A total of 71 articles were included in the review. Significant changes in brain activation, structure, microstructure, and structural and functional connectivity were reported with different types of trainings in the majority (87%) of the studies. Significant correlation of performance improvement with neural changes was reported in 51% of the studies. Yet, only 48% of the studies had a control condition. Overall, the review supports the hypothesized neural changes with training while at the same time charting empirical and methodological desiderata for future research.

Neuroplasticity in children and adolescents in response to treatment intervention: A systematic review of the literature

The purpose of the present study was to conduct a systematic review of the literature, adhering to PRISMA guidelines, regarding evidence of neuroplasticity in children and adolescents in response to cognitive or sensory-motor interventions. Twenty-eight studies employing seven different types of neuroimaging techniques were included in the review. Findings revealed that significant variability existed across the 28 studies with regard to the clinical populations examined, type of interventions employed, neuroimaging methods, and the type of neuroimaging data included in the studies. Overall, results supported that experience-dependent interventions were associated with neuroplastic changes among children and adolescents in both neurotypical and clinical populations. However, it remains unclear whether these molecular neuroplastic changes, including the degree and direction of those differences, were the direct result of the intervention. Although the findings are encouraging, methodological limitations of the studies limit clinical utility of the results. Future studies are warranted that rigorously define the construct of neuroplasticity, establish consistent protocols across measurement techniques, and have adequate statistical power. Lastly, studies are needed to identify the functional and structural neuroplastic mechanisms that correspond with changes in cognition and behavior in child and adolescent samples.

Frontostriatal White Matter Integrity Relations with "Cool" and "Hot" Self-Regulation after Pediatric Traumatic Brain Injury

Traumatic brain injury (TBI) produces microstructural damage to white matter pathways connecting neural structures in pre-frontal and striatal regions involved in self-regulation (SR). Dorsal and ventral frontostriatal pathways have been linked to cognitive ("cool") and emotional ("hot") SR, respectively. We evaluated the relation of frontostriatal pathway fractional anisotropy (FA) 2 months post-TBI on cool and hot SR assessed 7 months post-TBI. Participants were 8-15 years of age, including children with uncomplicated mild TBI (mTBI; n = 24), more severe TBI (complicated-mild, moderate, severe [cms]TBI; n = 60), and typically developing (TD) children (n = 55). Diffusion tensor tractography was used to map frontostriatal pathways. Cool SR included focused and sustained attention performance, and parent-reported attention, whereas hot SR included risk-taking performance and parent-reported emotional control. Multivariate general linear models showed that children with cmsTBI had greater parent-reported cool and hot SR difficulties and lower dorsal and ventral FA than TD children. Focused attention, risk taking, and emotional control correlated with FA of specific dorsal and ventral pathways; however, only the effect of TBI on focused attention was mediated by integrity of dorsal pathways. Results suggest that frontostriatal FA may serve as a biomarker of risk for SR difficulties or to assess response to interventions targeting SR in pediatric TBI and in broader neurodevelopmental populations.

Implementation of an attention training programme with a sample of children who have sustained traumatic brain injuries in South Africa: A pilot study

This pilot study evaluated the feasibility of implementing an attention-training programme for children who have sustained moderate-to-severe traumatic brain injuries (TBIs) in a South African context. We compared the performance on the programme of children with TBI (TBI Intervention Group) to children who had been diagnosed with Attention Deficit Hyperactivity Disorder (ADHD Intervention Group), a TBI Art group and a TBI No-intervention Group (n=5 in each group) in this preliminary study. Children in the two Intervention Groups participated in the "Pay Attention!" programme for 45 minutes twice a week for 12 weeks. All children were aged 6-8 years and underwent neuropsychological testing pre- and post-intervention. Behavioural data were collected from parents. Children in the ADHD Intervention Group showed individual clinically significant attentional improvements on measures of the Conners' Continuous Performance Test II using the Reliable Change Index (≥ 2.58 SD). Despite mixed results, the pilot study demonstrates that implementing a cognitive rehabilitation programme in South Africa is feasible and necessary, despite limited infrastructure and access to resources.

Traumatic Brain Injury Severity in a Network Perspective: A Diffusion MRI Based Connectome Study

Traumatic brain injury (TBI) is often characterized by alterations in brain connectivity. We explored connectivity alterations from a network perspective, using graph theory, and examined whether injury severity affected structural connectivity and modulated the association between brain connectivity and cognitive deficits post-TBI. We performed diffusion imaging network analysis on chronic TBI patients, with different injury severities and healthy subjects. From both global and local perspectives, we found an effect of injury severity on network strength. In addition, regions which were considered as hubs differed between groups. Further exploration of graph measures in the determined hub regions showed that efficiency of six regions differed between groups. An association between reduced efficiency in the precuneus and nonverbal abstract reasoning deficits (calculated using actual pre-injury scores) was found in the controls but was lost in TBI patients. Our results suggest that disconnection of network hubs led to a less efficient network, which in turn may have contributed to the cognitive impairments manifested in TBI patients. We conclude that injury severity modulates the disruption of network organization, reflecting a "dose response" relationship and emphasize the role of efficiency as an important diagnostic tool to detect subtle brain injury specifically in mild TBI patients.

Predicting Concussion Outcome by Integrating Finite Element Modeling and Network Analysis

Concussion is a significant public health problem affecting 1.6-2.4 million Americans annually. An alternative to reducing the burden of concussion is to reduce its incidence with improved protective equipment and injury mitigation systems. Finite element (FE) models of the brain response to blunt trauma are often used to estimate injury potential and can lead to improved helmet designs. However, these models have yet to incorporate how the patterns of brain connectivity disruption after impact affects the relay of information in the injured brain. Furthermore, FE brain models typically do not consider the differences in individual brain structural connectivities and their purported role in concussion risk. Here, we use graph theory techniques to integrate brain deformations predicted from FE modeling with measurements of network efficiency to identify brain regions whose connectivity characteristics may influence concussion risk. We computed maximum principal strain in 129 brain regions using head kinematics measured from 53 professional football impact reconstructions that included concussive and non-concussive cases. In parallel, using diffusion spectrum imaging data from 30 healthy subjects, we simulated structural lesioning of each of the same 129 brain regions. We simulated lesioning by removing each region one at a time along with all its connections. In turn, we computed the resultant change in global efficiency to identify regions important for network communication. We found that brain regions that deformed the most during an impact did not overlap with regions most important for network communication (Pearson's correlation, ρ = 0.07; p = 0.45). Despite this dissimilarity, we found that predicting concussion incidence was equally accurate when considering either areas of high strain or of high importance to global efficiency. Interestingly, accuracy for concussion prediction varied considerably across the 30 healthy connectomes. These results suggest that individual network structure is an important confounding variable in concussion prediction and that further investigation of its role may improve concussion prediction and lead to the development of more effective protective equipment.

Longitudinal Neuroimaging in Pediatric Traumatic Brain Injury: Current State and Consideration of Factors That Influence Recovery

Traumatic brain injury (TBI) is a leading cause of death and disability for children and adolescents in the U.S. and other developed and developing countries. Injury to the immature brain varies greatly from that of the mature, adult brain due to numerous developmental, pre-injury, and injury-related factors that work together to influence the trajectory of recovery during the course of typical brain development. Substantial damage to brain structure often underlies subsequent functional limitations that persist for years following pediatric TBI. Advances in neuroimaging have established an important role in the acute management of pediatric TBI, and magnetic resonance imaging (MRI) techniques have a particular relevance for the sequential assessment of long-term consequences from injuries sustained to the developing brain. The present paper will discuss the various factors that influence recovery and review the findings from the present neuroimaging literature to assess altered development and long-term outcome following pediatric TBI. Four MR-based neuroimaging modalities have been used to examine recovery from pediatric TBI longitudinally: (1) T1-weighted structural MRI is sensitive to morphological changes in gray matter volume and cortical thickness, (2) diffusion-weighted MRI is sensitive to changes in the microstructural integrity of white matter, (3) MR spectroscopy provides a sensitive assessment of metabolic and neurochemical alterations in the brain, and (4) functional MRI provides insight into the functional changes that occur as a result of structural damage and typical developmental processes. As reviewed in this paper, 13 cohorts have contributed to only 20 studies published to date using neuroimaging to examine longitudinal changes after TBI in pediatric patients. The results of these studies demonstrate considerable heterogeneity in post-injury outcome; however, the existing literature consistently shows that alterations in brain structure, function, and metabolism can persist for an extended period of time post-injury. With larger sample sizes and multi-site cooperation, future studies will be able to further examine potential moderators of outcome, such as the developmental, pre-injury, and injury-related factors discussed in the present review.

Longitudinal structural connectomic and rich-club analysis in adolescent mTBI reveals persistent, distributed brain alterations acutely through to one year post-injury

The diffuse nature of mild traumatic brain injury (mTBI) impacts brain white-matter pathways with potentially long-term consequences, even after initial symptoms have resolved. To understand post-mTBI recovery in adolescents, longitudinal studies are needed to determine the interplay between highly individualised recovery trajectories and ongoing development. To capture the distributed nature of mTBI and recovery, we employ connectomes to probe the brain’s structural organisation. We present a diffusion MRI study on adolescent mTBI subjects scanned one day, two weeks and one year after injury with controls. Longitudinal global network changes over time suggests an altered and more ‘diffuse’ network topology post-injury (specifically lower transitivity and global efficiency). Stratifying the connectome by its back-bone, known as the ‘rich-club’, these network changes were driven by the ‘peripheral’ local subnetwork by way of increased network density, fractional anisotropy and decreased diffusivities. This increased structural integrity of the local subnetwork may be to compensate for an injured network, or it may be robust to mTBI and is exhibiting a normal developmental trend. The rich-club also revealed lower diffusivities over time with controls, potentially indicative of longer-term structural ramifications. Our results show evolving, diffuse alterations in adolescent mTBI connectomes beginning acutely and continuing to one year.

Cognitive Training in Young Patients With Traumatic Brain Injury: A Fixel-Based Analysis

Background. Traumatic brain injury (TBI) is associated with altered white matter organization and impaired cognitive functioning. Objective. We aimed to investigate changes in white matter and cognitive functioning following computerized cognitive training. Methods. Sixteen adolescents with moderate-to-severe TBI (age 15.6 ± 1.8 years, 1.2-4.6 years postinjury) completed the 8-week BrainGames program and diffusion weighted imaging (DWI) and cognitive assessment at time point 1 (before training) and time point 2 (after training). Sixteen healthy controls (HC) (age 15.6 ± 1.8 years) completed DWI assessment at time point 1 and cognitive assessment at time point 1 and 2. Fixel-based analyses were used to examine fractional anisotropy (FA), mean diffusivity (MD), and fiber cross-section (FC) on a whole brain level and in tracts of interest. Results. Patients with TBI showed cognitive impairments and extensive areas with decreased FA and increased MD together with an increase in FC in the body of the corpus callosum and left superior longitudinal fasciculus (SLF) at time point 1. Patients improved significantly on the inhibition measure at time point 2, whereas the HC group remained unchanged. No training-induced changes were observed on the group level in diffusion metrics. Exploratory correlations were found between improvements on verbal working memory and reduced MD of the left SLF and between increased performance on an information processing speed task and increased FA of the right precentral gyrus. Conclusions. Results are indicative of positive effects of BrainGames on cognitive functioning and provide preliminary evidence for neuroplasticity associated with cognitive improvements following cognitive intervention in TBI.

Exploratory relationships between cognitive improvements and training induced plasticity in hippocampus and cingulum in a rat model of mild traumatic brain injury: a diffusion MRI study

Traumatic brain injury (TBI) is a major cause of long-term cognitive deficits, even in mild TBI patients. Computerized cognitive training can help alleviate complaints and improve daily life functioning of TBI patients. However, the underlying biological mechanisms of cognitive training in TBI are not fully understood. In the present study, we utilised for the first time a touchscreen cognitive training system in a rat model of mild TBI. Moreover, we wanted to examine whether the beneficial effects of a cognitive training are task-dependent and selective in their target. Specifically, we examined the effect of two training tasks, i.e. the Paired Associate Learning (PAL) task targeting spatial memory functioning and 5-Choice Continuous Performance (5-CCP) task loading on attention and inhibition control, on the microstructural organization of the hippocampus and cingulum, respectively, using diffusion tensor imaging (DTI). Our findings revealed that the two training protocols induced similar effects on the diffusion MRI metrics. Further, in the TBI groups who received training microstructural organization in the hippocampus and cingulum improved (as denoted by increases in fractional anisotropy), while a worsening (i.e., increases in mean diffusivity and radial diffusivity) was found in the TBI control group. In addition, these alterations in diffusion MRI metrics coincided with improved performance on the training tasks in the TBI groups who received training. Our findings show the potential of DTI metrics as reliable measure to evaluate cognitive training in TBI patients and to facilitate future research investigating further improvement of cognitive training targeting deficits in spatial memory and attention.

Bridging the gap: Mechanisms of plasticity and repair after pediatric TBI

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.

The structural connectome in traumatic brain injury: A meta-analysis of graph metrics

Although recent structural connectivity studies of traumatic brain injury (TBI) have used graph theory to evaluate alterations in global integration and functional segregation, pooled analysis is needed to examine the robust patterns of change in graph metrics across studies. Following a systematic search, 15 studies met the inclusion criteria for review. Of these, ten studies were included in a random-effects meta-analysis of global graph metrics, and subgroup analyses examined the confounding effects of severity and time since injury. The meta-analysis revealed significantly higher values of normalised clustering coefficient (gö=ö1.445, CI=[0.512, 2.378], pö=ö0.002) and longer characteristic path length (gö=ö0.514, CI=[0.190, 0.838], pö=ö0.002) in TBI patients compared with healthy controls. Our findings suggest that the TBI structural network has shifted away from the balanced small-world network towards a regular lattice. Therefore, these graph metrics may be useful markers of neurocognitive dysfunction in TBI. We conclude that the pattern of change revealed by our analysis should be used to guide hypothesis-driven research into the role of graph metrics as diagnostic and prognostic biomarkers.

Structural Connectivity Related to Persistent Symptoms After Mild TBI in Adolescents and Response to Aerobic Training: Preliminary Investigation

OBJECTIVE

To quantify structural connectivity abnormalities in adolescents with mild traumatic brain injury (mTBI) and to investigate connectivity changes following aerobic training using graph theory and diffusion tensor imaging tractography.

SETTING

Outpatient research setting.

PARTICIPANTS

Twenty-two children (age: 15.83 ± 1.77 years, 10 females) with 4 to 16 weeks of persistent symptoms after mTBI and a matched healthy comparison group.

DESIGN

Randomized clinical trial of aerobic training and stretching comparison combined with case-control comparison.

MAIN MEASURES

(1) Five global network measures: global efficiency (Eglob), mean local efficiency, modularity, normalized clustering coefficient (γ), normalized characteristic path length (λ), and small-worldness (σ). (2) The self-reported Post-Concussion Symptom Inventory score.

RESULTS

At initial enrollment, adolescents with mTBI had significantly lower Eglob and higher γ, λ, and σ (all P < .05) than healthy peers. After the intervention, significantly increased Eglob and decreased λ (both P < .05) were found in the aerobic training group. Improvement in Post-Concussion Symptom Inventory scores was significantly correlated with the Eglob increase and λ decrease in the aerobic training and λ decrease in the stretching comparison group (all P < .05).

CONCLUSION

This pilot study showed initial evidence that structural connectivity analysis was sensitive to brain network abnormalities and may serve as an imaging biomarker in children with persistent symptoms after mTBI.

Impaired rich club and increased local connectivity in children with traumatic brain injury: Local support for the rich?

Recent evidence has shown the presence of a "rich club" in the brain, which constitutes a core network of highly interconnected and spatially distributed brain regions, important for high-order cognitive processes. This study aimed to map the rich club organization in 17 young patients with moderate to severe TBI (15.71 ± 1.75 years) in the chronic stage of recovery and 17 age- and gender-matched controls. Probabilistic tractography was performed on diffusion weighted imaging data to construct the edges of the structural connectomes using number of streamlines as edge weight. In addition, the whole-brain network was divided into a rich club network, a local network and a feeder network connecting the latter two. Functional outcome was measured with a parent questionnaire for executive functioning. Our results revealed a significantly decreased rich club organization (p values < .05) and impaired executive functioning (p < .001) in young patients with TBI compared with controls. Specifically, we observed reduced density values in all three subnetworks (p values < .005) and a reduced mean strength in the rich club network (p = .013) together with an increased mean strength in the local network (p = .002) in patients with TBI. This study provides new insights into the nature of TBI-induced brain network alterations and supports the hypothesis that the local subnetwork tries to compensate for the biologically costly subnetwork of rich club nodes after TBI.

Neuroimaging of the Injured Pediatric Brain: Methods and New Lessons

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.

Diffusion MRI in pediatric brain injury

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.

The structural connectome of children with traumatic brain injury

This study aimed to investigate the impact of mild to severe pediatric TBI on the structural connectome. Children aged 8-14 years with trauma control (TC) injury (n = 27) were compared to children with mild TBI and risk factors for complicated TBI (mild^RF+ , n = 20) or moderate/severe TBI (n = 16) at 2.8 years post-injury. Probabilistic tractography on diffusion tensor imaging data was used in combination with graph theory to study structural connectivity. Functional outcome was measured using neurocognitive tests and parent and teacher questionnaires for behavioral functioning. The results revealed no evidence for an impact of mild^RF+ TBI on the structural connectome. In contrast, the moderate/severe TBI group showed longer characteristic path length (P = 0.022, d = 0.82) than the TC group. Furthermore, longer characteristic path length was related to poorer intelligence and poorer working memory in children with TBI. In conclusion, children have abnormal organization of the structural connectome after moderate/severe TBI, which may be implicated in neurocognitive dysfunction associated with pediatric TBI. These findings should be interpreted in the context of our exploratory analyses, which indicate that the definition and weighting of connectivity (e.g., streamline density, fractional anisotropy) influence the properties of the reconstructed connectome and its sensitivity to the impact and outcome of pediatric TBI. Hum Brain Mapp 38:3603-3614, 2017. © 2017 Wiley Periodicals, Inc.