Changes in functional brain networks following sports-related concussion in adolescents

Identification of Concussion Subtypes Based on Intrinsic Brain Activity

Importance

The identification of brain activity-based concussion subtypes at time of injury has the potential to advance the understanding of concussion pathophysiology and to optimize treatment planning and outcomes.

Objective

To investigate the presence of intrinsic brain activity-based concussion subtypes, defined as distinct resting state quantitative electroencephalography (qEEG) profiles, at the time of injury.

Design, Setting, and Participants

In this retrospective, multicenter (9 US universities and high schools and 4 US clinical sites) cohort study, participants aged 13 to 70 years with mild head injuries were included in longitudinal cohort studies from 2017 to 2022. Patients had a clinical diagnosis of concussion and were restrained from activity by site guidelines for more than 5 days, with an initial Glasgow Coma Scale score of 14 to 15. Participants were excluded for known neurological disease or history of traumatic brain injury within the last year. Patients were assessed with 2 minutes of artifact-free EEG acquired from frontal and frontotemporal regions within 120 hours of head injury. Data analysis was performed from July 2021 to June 2023.

Main Outcomes and Measures

Quantitative features characterizing the EEG signal were extracted from a 1- to 2-minute artifact-free EEG data for each participant, within 120 hours of injury. Symptom inventories and days to return to activity were also acquired.

Results

From the 771 participants (mean [SD] age, 20.16 [5.75] years; 432 male [56.03%]), 600 were randomly selected for cluster analysis according to 471 qEEG features. Participants and features were simultaneously grouped into 5 disjoint subtypes by a bootstrapped coclustering algorithm with an overall agreement of 98.87% over 100 restarts. Subtypes were characterized by distinctive profiles of qEEG measure sets, including power, connectivity, and complexity, and were validated in the independent test set. Subtype membership showed a statistically significant association with time to return to activity.

Conclusions and Relevance

In this cohort study, distinct subtypes based on resting state qEEG activity were identified within the concussed population at the time of injury. The existence of such physiological subtypes supports different underlying pathophysiology and could aid in personalized prognosis and optimization of care path.

Functional connectivity, tissue microstructure and T2 at 11.1 Tesla distinguishes neuroadaptive differences in two traumatic brain injury models in rats: A Translational Outcomes Project in NeuroTrauma (TOP-NT) UG3 phase study

The damage caused by contusive traumatic brain injuries (TBIs) is thought to involve breakdown in neuronal communication through focal and diffuse axonal injury along with alterations to the neuronal chemical environment, which adversely affects neuronal networks beyond the injury epicenter(s). In the present study, functional connectivity along with brain tissue microstructure coupled with T2 relaxometry were assessed in two experimental TBI models in rat, controlled cortical impact (CCI) and lateral fluid percussive injury (LFPI). Rats were scanned on an 11.1 Tesla scanner on days 2 and 30 following either CCI or LFPI. Naive controls were scanned once and used as a baseline comparison for both TBI groups. Scanning included functional magnetic resonance imaging (fMRI), diffusion weighted images (DWI), and multi-echo T2 images. fMRI scans were analyzed for functional connectivity across laterally and medially located region of interests (ROIs) across the cortical mantle, hippocampus, and dorsal striatum. DWI scans were processed to generate maps of fractional anisotropy, mean, axial, and radial diffusivities (FA, MD, AD, RD). The analyses focused on cortical and white matter (WM) regions at or near the TBI epicenter. Our results indicate that rats exposed to CCI and LFPI had significantly increased contralateral intra-cortical connectivity at 2 days post-injury. This was observed across similar areas of the cortex in both groups. The increased contralateral connectivity was still observed by day 30 in CCI, but not LFPI rats. Although both CCI and LFPI had changes in WM and cortical FA and diffusivities, WM changes were most predominant in CCI and cortical changes in LFPI. Our results provide support for the use of multimodal MR imaging for different types of contusive and skull-penetrating injury.

Adolescent Sport-Related Concussion and the Associated Neurophysiological Changes: A Systematic Review

BACKGROUND

Sport-related concussion (SRC) has been shown to induce cerebral neurophysiological deficits, quantifiable with electroencephalography (EEG). As the adolescent brain is undergoing rapid neurodevelopment, it is fundamental to understand both the short- and long-term ramifications SRC may have on neuronal functioning. The current systematic review sought to amalgamate the literature regarding both acute/subacute (≤28 days) and chronic (>28 days) effects of SRC in adolescents via EEG and the diagnostic accuracy of this tool.

METHODS

The review was registered within the Prospero database (CRD42021275256). Search strategies were created and input into the PubMed database, where three authors completed all screening. Risk of bias assessments were completed using the Scottish Intercollegiate Guideline Network and Methodological Index for Non-Randomized Studies.

RESULTS

A total of 128 articles were identified; however, only seven satisfied all inclusion criteria. The studies ranged from 2012 to 2021 and included sample sizes of 21 to 81 participants, albeit only ∼14% of the included athletes were females. The studies displayed low-to-high levels of bias due to the small sample sizes and preliminary nature of most investigations. Although heterogeneous methods, tasks, and analytical techniques were used, 86% of the studies found differences compared with control athletes, in both the symptomatic and asymptomatic phases of SRC. One study used raw EEG data as a diagnostic indicator demonstrating promise; however, more research and standardization are a necessity.

CONCLUSIONS

Collectively, the findings highlight the utility of EEG in assessing adolescent SRC; however, future studies should consider important covariates including biological sex, maturation status, and development.

Brain functional connectivity in children with a mild traumatic brain injury: A scoping review

INTRODUCTION

The occurrence of mild traumatic brain injury(mTBI) is estimated at 0,2-0,3% cases annually. Following a mTBI, some children experience persistent symptoms, and functional connectivity(FC) changes may be implicated. However, characteristics of FC have not been widely described in this population. This scoping review aimed to identify and understand the impacts of mTBI on EEG-measured FC in children, provide an overview of the available literature, detail analysis techniques, and describe gaps in the research.

METHODS

PubMed, Web of Science, Medline, Embase, ProQuest and CINAHL were searched up to June 25, 2023, with the terms child, mTBI, EEG, FC, and their synonyms. Ten studies were identified.

RESULTS

Five studies reported significant differences between the mTBI group and controls. In addition to group differences, six studies reported significant variation over time. Brain Network Analysis(BNA), utilized in seven studies, was the primary FC analysis recorded. Two of the five studies that reported significant differences following mTBI utilized the BNA. The other three applied alternative analysis methods.

DISCUSSION

FC assessment based on EEG can identify some differences in children with mTBI. BNA was more useful in following changes over time. Further research is suggested, considering the limited age range and number of retrieved studies.

Sports-Related Concussion Affects Cognitive Function in Adolescents: A Systematic Review and Meta-analysis

BACKGROUND

Rates of sports-related concussion (SRC) are high in adolescents. Ambiguity exists regarding the effect of SRC on cognitive function in adolescents.

PURPOSE

To rigorously examine adolescents' cognitive function after SRC.

STUDY DESIGN

Systematic review and meta-analysis; Level of evidence, 4.

METHODS

Web of Science, Scopus, and PubMed were searched from database inception until September 2021. Studies were included if participants were adolescents aged 13 to 18 years, if the definition of SRC was fully consistent with the Berlin Consensus Statement on Concussion in Sport, if the study included a control group or in-group baseline test, and if the study reported cognitive outcomes (eg, visual memory, processing speed) that could be separately extracted.

RESULTS

A total of 47 studies were included in the systematic review, of which 31 were included in the meta-analysis, representing 8877 adolescents with SRC. Compared with individuals in the non-SRC group, individuals with SRC had worse performance in cognitive function and reported more symptoms not only in the acute phase but also in the prolonged phase (1-6 months after injury) (visual memory: d = -0.21, 95% CI, -0.37 to -0.05, P = .012; executive function: d = -0.56, 95% CI, -1.07 to -0.06, P = .028; and symptoms: d = 1.17, 95% CI, 0.13 to 2.22, P = .028). Lower scores in most of the outcomes of cognitive function were observed at <3 days and at 3 to 7 days, but higher scores for verbal memory (d = 0.10; 95% CI, 0.03 to 0.17; P = .008) and processing speed (d = 0.17; 95% CI, 0.10 to 0.24; P < .001) were observed at 7 to 14 days after SRC relative to baseline. The effects of SRC on cognitive function decreased over time (100% of the variance in reaction time, P < .001; 99.94% of the variance in verbal memory, P < .001; 99.88% of the variance in visual memory, P < .001; 39.84% of the variance in symptoms, P = .042) in control group studies. Study design, participant sex, measurement tools, and concussion history were found to be modulators of the relationship between cognitive function and SRC.

CONCLUSION

This study revealed that adolescent cognitive function is impaired by SRC even 1 to 6 months after injury. Results of this study point to the need for tools to measure cognitive function with multiple parallel versions that have demographically diversiform norms in adolescents. Effective prevention of SRC, appropriate treatment, and adequate evaluation of cognitive function before return to play are needed in adolescent SRC management. Moreover, caution is warranted when using the baseline-to-postconcussion paradigm in return-to-play decisions.

Blink-related EEG oscillations are neurophysiological indicators of subconcussive head impacts in female soccer players: a preliminary study

Introduction

Repetitive subconcussive head impacts can lead to subtle neural changes and functional consequences on brain health. However, the objective assessment of these changes remains limited. Resting state blink-related oscillations (BROs), recently discovered neurological responses following spontaneous blinking, are explored in this study to evaluate changes in BRO responses in subconcussive head impacts.

Methods

We collected 5-min resting-state electroencephalography (EEG) data from two cohorts of collegiate athletes who were engaged in contact sports (SC) or non-contact sports (HC). Video recordings of all on-field activities were conducted to determine the number of head impacts during games and practices in the SC group.

Results

In both groups, we were able to detect a BRO response. Following one season of games and practice, we found a strong association between the number of head impacts sustained by the SC group and increases in delta and beta spectral power post-blink. There was also a significant difference between the two groups in the morphology of BRO responses, including decreased peak-to-peak amplitude of response over left parietal channels and differences in spectral power in delta and alpha frequency range post-blink.

Discussion

Our preliminary results suggest that the BRO response may be a useful biomarker for detecting subtle neural changes resulting from repetitive head impacts. The clinical utility of this biomarker will need to be validated through further research with larger sample sizes, involving both male and female participants, using a longitudinal design.

Neurophysiological Markers to Guide Return to Sport After Sport-Related Concussion

SUMMARY

Sport-related concussion (SRC) has been defined as a subset of mild traumatic brain injury (mTBI), without structural abnormalities, reflecting a functional disturbance. Over the past decade, SRC has gained increasing awareness and attention, which coincides with an increase in incidence rates. Because this injury has been considered one of the most challenging encounters for clinicians, there is a need for objective biomarkers to aid in diagnosis (i.e., presence/severity) and management (i.e., return to sport) of SRC/mTBI.The primary aim of this article was to present state-of-the-art neurophysiologic methods (e.g., electroencephalography, magnetoencephalography, transcranial magnetic stimulation, and autonomic nervous system) that are appropriate to investigate the complex pathophysiological process of a concussion. A secondary aim was to explore the potential for evidence-based markers to be used in clinical practice for SRC management. The article concludes with a discussion of future directions for SRC research with specific focus on clinical neurophysiology.

Long-Term Changes in Brain Connectivity Reflected in Quantitative Electrophysiology of Symptomatic Former National Football League Players

Exposure to repetitive head impacts (RHI) has been associated with long-term disturbances in cognition, mood, and neurobehavioral dysregulation, and reflected in neuroimaging. Distinct patterns of changes in quantitative features of the brain electrical activity (quantitative electroencephalogram [qEEG]) have been demonstrated to be sensitive to brain changes seen in neurodegenerative disorders and in traumatic brain injuries (TBI). While these qEEG biomarkers are highly sensitive at time of injury, the long-term effects of exposure to RHI on brain electrical activity are relatively unexplored. Ten minutes of eyes closed resting EEG data were collected from a frontal and frontotemporal electrode montage (BrainScope Food and Drug Administration-cleared EEG acquisition device), as well as assessments of neuropsychiatric function and age of first exposure (AFE) to American football. A machine learning methodology was used to derive a qEEG-based algorithm to discriminate former National Football League (NFL) players (n = 87, 55.40 ± 7.98 years old) from same-age men without history of RHI (n = 68, 54.94 ± 7.63 years old), and a second algorithm to discriminate former players with AFE <12 years (n = 33) from AFE ≥12 years (n = 54). The algorithm separating NFL retirees from controls had a specificity = 80%, a sensitivity = 60%, and an area under curve (AUC) = 0.75. Within the NFL population, the algorithm separating AFE <12 from AFE ≥12 resulted in a sensitivity = 76%, a specificity = 52%, and an AUC = 0.72. The presence of a profile of EEG abnormalities in the NFL retirees and in those with younger AFE includes features associated with neurodegeneration and the disruption of neuronal transmission between regions. These results support the long-term consequences of RHI and the potential of EEG as a biomarker of persistent changes in brain function.

Concussion Prone Scenarios: A Multi-Dimensional Exploration in Impact Directions, Brain Morphology, and Network Architectures Using Computational Models

While individual susceptibility to traumatic brain injury (TBI) has been speculated, past work does not provide an analysis considering how physical features of an individual's brain (e.g., brain size, shape), impact direction, and brain network features can holistically contribute to the risk of suffering a TBI from an impact. This work investigated each of these features simultaneously using computational modeling and analyses of simulated functional connectivity. Unlike the past studies that assess the severity of TBI based on the quantification of brain tissue damage (e.g., principal strain), we approached the brain as a complex network in which neuronal oscillations orchestrate to produce normal brain function (estimated by functional connectivity) and, to this end, both the anatomical damage location and its topological characteristics within the brain network contribute to the severity of brain function disruption and injury. To represent the variations in the population, we analyzed a publicly available database of brain imaging data and selected five distinct network architectures, seven different brain sizes, and three uniaxial head rotational conditions to study the consequences of 74 virtual impact scenarios. Results show impact direction produces the most significant change in connections across brain areas (structural connectome) and the functional coupling of activity across these brain areas (functional connectivity). Axial rotations were more injurious than those with sagittal and coronal rotations when the head kinematics were the same for each condition. When the impact direction was held constant, brain network architecture showed a significantly different vulnerability across axial and sagittal, but not coronal rotations. As expected, brain size significantly affected the expected change in structural and functional connectivity after impact. Together, these results provided groupings of predicted vulnerability to impact-a subgroup of male brain architectures exposed to axial impacts were most vulnerable, while a subgroup of female brain architectures was the most tolerant to the sagittal impacts studied. These findings lay essential groundwork for subject-specific analyses of concussion and provide invaluable guidance for designing personalized protection equipment.

An interdisciplinary computational model for predicting traumatic brain injury: Linking biomechanics and functional neural networks

The brain is a complex network consisting of neuron cell bodies in the gray matter and their axonal projections, forming the white matter tracts. These neurons are supported by an equally complex vascular network as well as glial cells. Traumatic brain injury (TBI) can lead to the disruption of the structural and functional brain networks due to disruption of both neuronal cell bodies in the gray matter as well as their projections and supporting cells. To explore how an impact can alter the function of brain networks, we integrated a finite element (FE) brain mechanics model with linked models of brain dynamics (Kuramoto oscillator) and vascular perfusion (Balloon-Windkessel) in this study. We used empirical resting-state functional magnetic resonance imaging (MRI) data to optimize the fit of our brain dynamics and perfusion models to clinical data. Results from the FE model were used to mimic injury in these optimized brain dynamics models: injury to the nodes (gray matter) led to a decrease in the nodal oscillation frequency, while damage to the edges (axonal connections/white matter) progressively decreased coupling among connected nodes. A total of 53 cases, including 33 non-injurious and 20 concussive head impacts experienced by professional American football players were simulated using this integrated model. We examined the correlation of injury outcomes with global measures of structural connectivity, neural dynamics, and functional connectivity of the brain networks when using different lesion methods. Results show that injurious head impacts cause significant alterations in global network topology regardless of lesion methods. Changes between the disrupted and healthy functional connectivity (measured by Pearson correlation) consistently correlated well with injury outcomes (AUC≥0.75), although the predictive performance is not significantly different (p>0.05) to that of traditional kinematic measures (angular acceleration). Intriguingly, our lesion model for gray matter damage predicted increases in global efficiency and clustering coefficient with increases in injury risk, while disrupting axonal connections led to lower network efficiency and clustering. When both injury mechanisms were combined into a single injury prediction model, the injury prediction performance depended on the thresholds used to determine neurodegeneration and mechanical tolerance for axonal injury. Together, these results point towards complex effects of mechanical trauma to the brain and provide a new framework for understanding brain injury at a causal mechanistic level and developing more effective diagnostic methods and therapeutic interventions.

A Routine Electroencephalography Monitoring System for Automated Sports-Related Concussion Detection

Cases of concussions in the United States keep increasing and are now up to 2 million to 3 million incidents per year. Although concussions are recoverable and usually not life-threatening, the degree and rate of recovery may vary depending on age, severity of the injury, and past concussion history. A subsequent concussion before full recovery may lead to more-severe brain damage and poorer outcomes. Electroencephalography (EEG) recordings can identify brain dysfunctionality and abnormalities, such as after a concussion. Routine EEG monitoring can be a convenient method for reducing unreported injuries and preventing long-term damage, especially among groups with a greater risk of experiencing a concussion, such as athletes participating in contact sports. Because of the relative availability of EEG compared to other brain-imaging techniques (e.g., functional magnetic resonance imaging), the use of EEG monitoring is growing for various neurological disorders. In this longitudinal study, EEG was analyzed from 4 football athletes before their athletic season and also within 7 days of concussion. Compared to a control group of 4 additional athletes, a concussion was detected with up to 99.5% accuracy using EEG recordings in the Theta-Alpha band. Classifiers that use data from only a subset of the EEG electrodes providing reliable detection are also proposed. The most effective classifiers used EEG recordings from the Central scalp region in the Beta band and over the Temporal scalp region using the Theta-Alpha band. This proof-of-concept study and preliminary findings suggest that EEG monitoring may be used to identify a sports-related concussion occurrence with a high level of accuracy and thus reduce the chance of unreported concussion.

Deep Learning Recurrent Neural Network for Concussion Classification in Adolescents Using Raw Electroencephalography Signals: Toward a Minimal Number of Sensors

Artificial neural networks (ANNs) are showing increasing promise as decision support tools in medicine and particularly in neuroscience and neuroimaging. Recently, there has been increasing work on using neural networks to classify individuals with concussion using electroencephalography (EEG) data. However, to date the need for research grade equipment has limited the applications to clinical environments. We recently developed a deep learning long short-term memory (LSTM) based recurrent neural network to classify concussion using raw, resting state data using 64 EEG channels and achieved high accuracy in classifying concussion. Here, we report on our efforts to develop a clinically practical system using a minimal subset of EEG sensors. EEG data from 23 athletes who had suffered a sport-related concussion and 35 non-concussed, control athletes were used for this study. We tested and ranked each of the original 64 channels based on its contribution toward the concussion classification performed by the original LSTM network. The top scoring channels were used to train and test a network with the same architecture as the previously trained network. We found that with only six of the top scoring channels the classifier identified concussions with an accuracy of 94%. These results show that it is possible to classify concussion using raw, resting state data from a small number of EEG sensors, constituting a first step toward developing portable, easy to use EEG systems that can be used in a clinical setting.

Alterations in the Magnetoencephalography Default Mode Effective Connectivity following Concussion

BACKGROUND AND PURPOSE

Magnetoencephalography is sensitive to functional connectivity changes associated with concussion. However, the directional influences between functionally related regions remain unexplored. In this study, we therefore evaluated concussion-related magnetoencephalography-based effective connectivity changes within resting-state default mode network regions.

MATERIALS AND METHODS

Resting-state magnetoencephalography was acquired for 8 high school football players with concussion at 3 time points (preseason, postconcussion, postseason), as well as 8 high school football players without concussion and 8 age-matched controls at 2 time points (preseason, postseason). Time-series from the default mode network regions were extracted, and effective connectivity between them was computed for 5 different frequency bands. The default mode network regions were grouped into anterior and posterior default mode networks. The combined posterior-to-anterior and anterior-to-posterior effective connectivity values were averaged to generate 2 sets of values for each subject. The effective connectivity values were compared using a repeated measures ANOVA across time points for the concussed, nonconcussed, and control groups, separately.

RESULTS

A significant increase in posterior-to-anterior effective connectivity from preseason to postconcussion (corrected P value = .013) and a significant decrease in posterior-to-anterior effective connectivity from postconcussion to postseason (corrected P value = .028) were observed in the concussed group. Changes in effective connectivity were only significant within the delta band. Anterior-to-posterior connectivity demonstrated no significant change. Effective connectivity in the nonconcussed group and controls did not show significant differences.

CONCLUSIONS

The unidirectional increase in effective connectivity postconcussion may elucidate compensatory processes, invoking use of posterior regions to aid the function of susceptible anterior regions following brain injury. These findings support the potential value of magnetoencephalography in exploring directional changes of the brain network following concussion.

Practice Guideline: Use of Quantitative EEG for the Diagnosis of Mild Traumatic Brain Injury: Report of the Guideline Committee of the American Clinical Neurophysiology Society

SUMMARY

Despite many decades of research, controversy regarding the utility of quantitative EEG (qEEG) for the accurate diagnosis of mild traumatic brain injury (mTBI) remains. This guideline is meant to assist clinicians by providing an expert review of the clinical usefulness of qEEG techniques for the diagnosis of mTBI. This guideline addresses the following primary aim: For patients with or without posttraumatic symptoms (abnormal cognition or behavior), does qEEG either at the time of injury or remote from the injury, as compared with current clinical diagnostic criteria, accurately identify those patients with mTBI (i.e., concussion)? Secondary aims included differentiating between mTBI and other diagnoses, detecting mTBI in the presence of central nervous system medications, and pertinence of statistical methods for measurements of qEEG components. It was found that for patients with or without symptoms of abnormal cognition or behavior, current evidence does not support the clinical use of qEEG either at the time of the injury or remote from the injury to diagnose mTBI (level U). In addition, the evidence does not support the use of qEEG to differentiate mTBI from other diagnoses or detect mTBI in the presence of central nervous system medications, and suitable statistical methods do not exist when using qEEG to identify patients with mTBI. Based upon the current literature review, qEEG remains an investigational tool for mTBI diagnosis (class III evidence).

Recurrent neural network-based acute concussion classifier using raw resting state EEG data

Concussion is a global health concern. Despite its high prevalence, a sound understanding of the mechanisms underlying this type of diffuse brain injury remains elusive. It is, however, well established that concussions cause significant functional deficits; that children and youths are disproportionately affected and have longer recovery time than adults; and that individuals suffering from a concussion are more prone to experience additional concussions, with each successive injury increasing the risk of long term neurological and mental health complications. Currently, the most significant challenge in concussion management is the lack of objective, clinically- accepted, brain-based approaches for determining whether an athlete has suffered a concussion. Here, we report on our efforts to address this challenge. Specifically, we introduce a deep learning long short-term memory (LSTM)-based recurrent neural network that is able to distinguish between non-concussed and acute post-concussed adolescent athletes using only short (i.e. 90 s long) samples of resting state EEG data as input. The athletes were neither required to perform a specific task nor expected to respond to a stimulus during data collection. The acquired EEG data were neither filtered, cleaned of artefacts, nor subjected to explicit feature extraction. The LSTM network was trained and validated using data from 27 male, adolescent athletes with sports related concussion, benchmarked against 35 non-concussed adolescent athletes. During rigorous testing, the classifier consistently identified concussions with an accuracy of > 90% and achieved an ensemble median Area Under the Receiver Operating Characteristic Curve (ROC/AUC) equal to 0.971. This is the first instance of a high-performing classifier that relies only on easy-to-acquire resting state, raw EEG data. Our concussion classifier represents a promising first step towards the development of an easy-to-use, objective, brain-based, automatic classification of concussion at an individual level.

Concussion assessment potentially aided by use of an objective multimodal concussion index

Objective

Prompt, accurate, objective assessment of concussion is crucial as delays can lead to increased short and long-term consequences. The purpose of this study was to derive an objective multimodal concussion index (CI) using EEG at its core, to identify concussion, and to assess change over time throughout recovery.

Methods

Male and female concussed ( N = 232) and control ( N = 206) subjects 13–25 years were enrolled at 12 US colleges and high schools. Evaluations occurred within 72 h of injury, 5 days post-injury, at return-to-play (RTP), 45 days after RTP (RTP + 45); and included EEG, neurocognitive performance, and standard concussion assessments. Concussed subjects had a witnessed head impact, were removed from play for ≥ 5 days using site guidelines, and were divided into those with RTP < 14 or ≥14 days. Part 1 describes the derivation and efficacy of the machine learning derived classifier as a marker of concussion. Part 2 describes significance of differences in CI between groups at each time point and within each group across time points.

Results

Sensitivity = 84.9%, specificity = 76.0%, and AUC = 0.89 were obtained on a test Hold-Out group representing 20% of the total dataset. EEG features reflecting connectivity between brain regions contributed most to the CI. CI was stable over time in controls. Significant differences in CI between controls and concussed subjects were found at time of injury, with no significant differences at RTP and RTP + 45. Within the concussed, differences in rate of recovery were seen.

Conclusions

The CI was shown to have high accuracy as a marker of likelihood of concussion. Stability of CI in controls supports reliable interpretation of CI change in concussed subjects. Objective identification of the presence of concussion and assessment of readiness to return to normal activity can be aided by use of the CI, a rapidly obtained, point of care assessment tool.

Validation of a Machine Learning Brain Electrical Activity-Based Index to Aid in Diagnosing Concussion Among Athletes

IMPORTANCE

An objective, reliable indicator of the presence and severity of concussive brain injury and of the readiness for the return to activity has the potential to reduce concussion-related disability.

OBJECTIVE

To validate the classification accuracy of a previously derived, machine learning, multimodal, brain electrical activity-based Concussion Index in an independent cohort of athletes with concussion.

DESIGN, SETTING, AND PARTICIPANTS

This prospective diagnostic cohort study was conducted at 10 clinical sites (ie, US universities and high schools) between February 4, 2017, and March 20, 2019. A cohort comprising a consecutive sample of 207 athletes aged 13 to 25 years with concussion and 373 matched athlete controls without concussion were assessed with electroencephalography, cognitive testing, and symptom inventories within 72 hours of injury, at return to play, and 45 days after return to play. Variables from the multimodal assessment were used to generate a Concussion Index at each time point. Athletes with concussion had experienced a witnessed head impact, were removed from play for 5 days or more, and had an initial Glasgow Coma Scale score of 13 to 15. Participants were excluded for known neurologic disease or history within the last year of traumatic brain injury. Athlete controls were matched to athletes with concussion for age, sex, and type of sport played.

MAIN OUTCOMES AND MEASURES

Classification accuracy of the Concussion Index at time of injury using a prespecified cutoff of 70 or less (total range, 0-100, where ≤70 indicates it is likely the individual has a concussion and >70 indicates it is likely the individual does not have a concussion).

RESULTS

Of 580 eligible participants with analyzable data, 207 had concussion (124 male participants [59.9%]; mean [SD] age, 19.4 [2.5] years), and 373 were athlete controls (187 male participants [50.1%]; mean [SD] age, 19.6 [2.2] years). The Concussion Index had a sensitivity of 86.0% (95% CI, 80.5%-90.4%), specificity of 70.8% (95% CI, 65.9%-75.4%), negative predictive value of 90.1% (95% CI, 86.1%-93.3%), positive predictive value of 62.0% (95% CI, 56.1%-67.7%), and area under receiver operator characteristic curve of 0.89. At day 0, the mean (SD) Concussion Index among athletes with concussion was significantly lower than among athletes without concussion (75.0 [14.0] vs 32.7 [27.2]; P < .001). Among athletes with concussion, there was a significant increase in the Concussion Index between day 0 and return to play, with a mean (SD) paired difference between these time points of -41.2 (27.0) (P < .001).

CONCLUSIONS AND RELEVANCE

These results suggest that the multimodal brain activity-based Concussion Index has high classification accuracy for identification of the likelihood of concussion at time of injury and may be associated with the return to control values at the time of recovery. The Concussion Index has the potential to aid in the clinical diagnosis of concussion and in the assessment of athletes' readiness to return to play.

Predictive Value of Subacute Heart Rate Variability for Determining Outcome Following Adolescent Concussion

Objective assessments of concussion recovery are crucial for facilitating effective clinical management. However, predictive tools for determining adolescent concussion outcomes are currently limited. Research suggests that heart rate variability (HRV) represents an indirect and objective marker of central and peripheral nervous system integration. Therefore, it may effectively identify underlying deficits and reliably predict the symptomology following concussion. Thus, the present study sought to evaluate the relationship between HRV and adolescent concussion outcomes. Furthermore, we sought to examine its predictive value for assessing outcomes. Fifty-five concussed adolescents (12–17 years old) recruited from a local sports medicine clinic were assessed during the initial subacute evaluation (within 15 days postinjury) and instructed to follow up for a post-acute evaluation. Self-reported clinical and depressive symptoms, neurobehavioral function, and cognitive performance were collected at each timepoint. Short-term HRV metrics via photoplethysmography were obtained under resting conditions and physiological stress. Regression analyses demonstrated significant associations between HRV metrics, clinical symptoms, neurobehavioral function, and cognitive performance at the subacute evaluation. Importantly, the analyses illustrated that subacute HRV metrics significantly predicted diminished post-acute neurobehavioral function and cognitive performance. These findings indicate that subacute HRV metrics may serve as a viable predictive biomarker for identifying underlying neurological dysfunction following concussion and predict late cognitive outcomes.

Recovery of Theta Frequency Oscillations in Rats Following Lateral Fluid Percussion Corresponds With a Mild Cognitive Phenotype

Whether from a fall, sports concussion, or even combat injury, there is a critical need to identify when an individual is able to return to play or work following traumatic brain injury (TBI). Electroencephalogram (EEG) and local field potentials (LFP) represent potential tools to monitor circuit-level abnormalities related to learning and memory: specifically, theta oscillations can be readily observed and play a critical role in cognition. Following moderate traumatic brain injury in the rat, lasting changes in theta oscillations coincide with deficits in spatial learning. We hypothesized, therefore, that theta oscillations can be used as an objective biomarker of recovery, with a return of oscillatory activity corresponding with improved spatial learning. In the current study, LFP were recorded from dorsal hippocampus and anterior cingulate in awake, behaving adult Sprague Dawley rats in both a novel environment on post-injury days 3 and 7, and Barnes maze spatial navigation on post-injury days 8–11. Theta oscillations, as measured by power, theta-delta ratio, peak theta frequency, and phase coherence, were significantly altered on day 3, but had largely recovered by day 7 post-injury. Injured rats had a mild behavioral phenotype and were not different from shams on the Barnes maze, as measured by escape latency. Injured rats did use suboptimal search strategies. Combined with our previous findings that demonstrated a correlation between persistent alterations in theta oscillations and spatial learning deficits, these new data suggest that neural oscillations, and particularly theta oscillations, have potential as a biomarker to monitor recovery of brain function following TBI. Specifically, we now demonstrate that oscillations are depressed following injury, but as oscillations recover, so does behavior.

Pathophysiologic Mechanisms of Concussion, Development of Chronic Traumatic Encephalopathy, and Emerging Diagnostics: A Narrative Review

Pathophysiological mechanisms and cascades take place after a mild traumatic brain injury (mTBI) that can cause long-term sequelae, including chronic traumatic encephalopathy in patients with multiple concurrent TBIs. As diagnostic imaging has become more advanced, microanatomical changes present after mTBI may now be more readily visible. In this narrative review, the authors discuss emerging diagnostics and findings in mTBI through advanced imaging, electroencephalograms, neurophysiologic processes, Q2 biochemical markers, and clinical tissue tests in an effort to help osteopathic physicians to understand, diagnose, and manage the pathophysiology behind mTBI, which is increasingly prevalent in the United States.

Prospective longitudinal investigation shows correlation of event-related potential to mild traumatic brain injury in adolescents

STUDY DESIGN

Prospective longitudinal cohort study.

BACKGROUND

Adolescent athletes may be more susceptible to the long-term effects of mild traumatic brain injury (mTBI). A diagnostic and prognostic neuromarker may optimize management and return-to-activity decision-making in athletes who experience mTBI.

OBJECTIVE

Measure an event-related potential (ERP) component captured with electroencephalography (EEG), called processing negativity (PN), at baseline and post-injury in adolescents who suffered mTBI and determine their longitudinal response relative to healthy controls.

METHODS

Thirty adolescents had EEG recorded during an auditory oddball task at a pre-mTBI baseline session and subsequent post-mTBI sessions. Longitudinal EEG data from patients and healthy controls (n= 77) were obtained from up to four sessions in total and processed using Brain Network Analysis algorithms.

RESULTS

The average PN amplitude in healthy controls significantly decreased over sessions 2 and 3; however, it remained steady in the mTBI group's 2nd (post-mTBI) session and decreased only in sessions 3 and 4. Pre- to post-mTBI amplitude changes correlated with the time interval between sessions.

CONCLUSION

These results demonstrate that PN amplitude changes may be associated with mTBI exposure and subsequent recovery in adolescent athletes. Further study of PN may lead to it becoming a neuromarker for mTBI prognosis and return-to-activity decision-making in adolescents.

Reduced frontopolar brain activation characterizes concussed athletes with balance deficits

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Symptomatic athletes with balance deficits present reduced frontopolar oxygenation during postural control with closed eyes.

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Decreased brain oxygenation in the FPC of symptomatic individuals may characterize the deficit of shifting the focus from visual inputs towards proprioception.

Objectives

Athletes with sport-related concussions (SRC) often demonstrate deficits in postural stability. Lower cerebral blood flow in frontal cortices has been documented in athletes with symptoms after SRC, however, it is unclear if functional brain oxygenation during postural control tasks is reduced in symptomatic athletes after SRC in the same manner. We therefore compared brain oxygenation patterns in frontal cortices of symptomatic and asymptomatic athletes with SRC during postural control tasks with the hypothesis that symptomatic athletes are characterized by reduced functional brain oxygenation during postural control.

Methods

62 concussed athletes (n = 31 symptomatic, n = 31 asymptomatic) were investigated during four postural control tasks with eyes closed versus eyes opened conditions and stable vs. unstable surface conditions. Brain oxygenation was assessed using functional NearInfraRed Spectroscopy (fNIRS) on frontopolar cortices of each hemisphere. Postural sway was measured by the analysis of ground reaction forces.

Results

Symptomatic athletes showed greater postural sway when compared to asymptomatic athletes during postural control, particularly during closed eyes and/or unstable surface conditions. Changes of oxygenated hemoglobin (∆HbO₂) within the left hemispheric frontopolar cortex were significantly reduced in symptomatic athletes when compared to asymptomatic athletes during the eyes closed condition. A stepwise linear regression analysis revealed that self-reported post-concussion symptoms such as headaches and sadness predict decreased brain oxygenation during postural control with closed eyes.

Conclusion

Symptomatic athletes with increased postural sway are characterized by decreased frontopolar brain oxygenation during postural control tasks, particularly during conditions with closed eyes. Because the frontopolar cortex showed to be involved in redistributing executive functions to novel task situations, we conclude that athletes with post-concussion symptoms suffer from a deficit in coordinating postural adjustments to balance control tasks with reduced sensory input.

Disrupted Information Flow in Resting-State in Adolescents With Sports Related Concussion

Children and youths are at a greater risk of concussions than adults, and once injured, take longer to recover. A key feature of concussion is an increase in functional connectivity, yet it remains unclear how changes in functional connectivity relate to the patterns of information flow within resting state networks following concussion and how these relate to brain function. We applied a data-driven measure of directed effective brain connectivity to compare the patterns of information flow in healthy adolescents and adolescents with subacute concussion during the resting state condition. Data from 32 healthy adolescents (mean age =16 years) and 21 concussed adolescents (mean age = 15 years) within 1 week of injury were included in the study. Five minutes of resting state data EEG were collected while participants sat quietly with their eyes closed. We applied the information flow rate to measure the transfer of information between the EEG time series of each individual at different source locations, and therefore between different brain regions. Based on the ensemble means of the magnitude of normalized information flow rate, our analysis shows that the dominant nexus of information flow in healthy adolescents is primarily left lateralized and anterior-centric, characterized by strong bidirectional information exchange between the frontal regions, and between the frontal and the central/temporal regions. In contrast, adolescents with concussion show distinct differences in information flow marked by a more left-right symmetrical, albeit still primarily anterior-centric, pattern of connections, diminished activity along the central-parietal midline axis, and the emergence of inter-hemispheric connections between the left and right frontal and the left and right temporal regions of the brain. We also find that the statistical distribution of the normalized information flow rates in each group (control and concussed) is significantly different. This paper is the first to describe the characteristics of the source space information flow and the effective connectivity patterns between brain regions in healthy adolescents in juxtaposition with the altered spatial pattern of information flow in adolescents with concussion, statistically quantifying the differences in the distribution of the information flow rate between the two populations. We hypothesize that the observed changes in information flow in the concussed group indicate functional reorganization of resting state networks in response to brain injury.

Frequency-Dependent Changes in Resting State Electroencephalogram Functional Networks after Traumatic Brain Injury in Piglets

Traumatic brain injury (TBI) is a major health concern in children, as it can cause chronic cognitive and behavioral deficits. The lack of objective involuntary metrics for the diagnosis of TBI makes prognosis more challenging, especially in the pediatric context, in which children are often unable to articulate their symptoms. Resting state electroencephalograms (EEG), which are inexpensive and non-invasive, and do not require subjects to perform cognitive tasks, have not yet been used to create functional brain networks in relation to TBI in children or non-human animals; here we report the first such study. We recorded resting state EEG in awake piglets before and after TBI, from which we generated EEG functional networks from the alpha (8-12 Hz), beta (16.5-25 Hz), broad (1-35 Hz), delta (1-3.5 Hz), gamma (30-35 Hz), sigma (13-16 Hz), and theta (4-7.5 Hz) frequency bands. We hypothesize that mild TBI will induce persistent frequency-dependent changes in the 4-week-old piglet at acute and chronic time points. Hyperconnectivity was found in several frequency band networks after TBI. This study serves as proof of concept that the study of EEG functional networks in awake piglets may be useful for the development of diagnostic metrics for TBI in children.

Cortical activity and network organization underlying physical and cognitive exertion in active young adult athletes: Implications for concussion

OBJECTIVES

To examine the neurophysiological correlates and brain network organization underlying physical and cognitive exertion in active young adults.

DESIGN

Repeated measures.

METHODS

Thirteen healthy adults completed three exertion tasks in a counterbalanced order: a graded working memory task (anti-saccade and serial addition task (ASAT)), a graded exercise task (cycling on a stationary bicycle) (EX) and a combined graded working memory and exercise task (ASAT+EX). All three tasks were performed under five levels of increasing difficulty. Continuous EEG was recorded in each session. Heart rate, perceived exertion and accuracy on the working memory task were recorded throughout. Power spectrum analysis and graph theoretical analysis was applied to the EEG data.

RESULTS

Heart rate and perceived exertion increased with exercise load and in both the EX only and ASAT+EX tasks. Overall accuracy was equally high for the ASAT and ASAT+EX tasks. Analysis of EEG data showed there was an increase in theta power associated with the ASAT+EX task and increase in functional connectivity in the frontal regions of the brain compared with ASAT only task. Accuracy decreased in the last two blocks when the task was most difficult. This decrease in accuracy was associated with a decrease in theta power and a decrease in functional connectivity.

CONCLUSIONS

Combined physical and mental exertion results in significant changes in perceived exertion, EEG theta power and network organization in healthy adults and will be valuable in revealing residual neurocognitive deficits after sports related concussion.

Resting State Electroencephalography and Sports-Related Concussion: A Systematic Review

Sports-related concussion is associated with a range of short-term functional deficits that are commonly thought to recover within a two-week post-injury period for most, but certainly not all, persons. Resting state electroencephalography (rs-EEG) may prove to be an affordable, accessible, and sensitive method of assessing severity of brain injury and rate of recovery after a concussion. This article presents a systematic review of rs-EEG in sports-related concussion. A systematic review of articles published in the English language, up to June 2017, was retrieved via PsychINFO, Medline, Medline In Process, Embase, SportDiscus, CINAHL, and Cochrane Library, Reviews, and Trials. The following key words were used for database searches: electroencephalography, quantitative electroencephalography, qEEG, cranio-cerebral trauma, mild traumatic brain injury, mTBI, traumatic brain injury, brain concussion, concussion, brain damage, sport, athletic, and athlete. Observational, cohort, correlational, cross-sectional, and longitudinal studies were all included in the current review. Sixteen articles met inclusion criteria, which included data on 504 athletes and 367 controls. All 16 articles reported some abnormality in rs-EEG activity after a concussion; however, the cortical rhythms that were affected varied. Despite substantial methodological and analytical differences across the 16 studies, the current review suggests that rs-EEG may provide a reliable technique to identify persistent functional changes in athletes after a concussion. Because of the varied approaches, however, considerable work is needed to establish a systematic methodology to assess its efficacy as a marker of return-to-play.

Longitudinal Changes in Resting State Connectivity and White Matter Integrity in Adolescents With Sports-Related Concussion

OBJECTIVES

The aim of this study was to investigate alterations in functional connectivity, white matter integrity, and cognitive abilities due to sports-related concussion (SRC) in adolescents using a prospective longitudinal design.

METHODS

We assessed male high school football players (ages 14-18) with (n=16) and without (n=12) SRC using complementary resting state functional MRI (rs-fMRI) and diffusion tensor imaging (DTI) along with cognitive performance using the Immediate Post-Concussive Assessment and Cognitive Testing (ImPACT). We assessed both changes at the acute phase (<7 days post-SRC) and at 21 days later, as well as, differences between athletes with SRC and age- and team-matched control athletes.

RESULTS

The results revealed rs-fMRI hyperconnectivity within posterior brain regions (e.g., precuneus and cerebellum), and hypoconnectivity in more anterior areas (e.g., inferior and middle frontal gyri) when comparing SRC group to control group acutely. Performance on the ImPACT (visual/verbal memory composites) was correlated with resting state network connectivity at both time points. DTI results revealed altered diffusion in the SRC group along a segment of the corticospinal tract and the superior longitudinal fasciculus in the acute phase of SRC. No differences between the SRC group and control group were seen at follow-up imaging.

CONCLUSIONS

Acute effects of SRC are associated with both hyperconnectivity and hypoconnectivity, with disruption of white matter integrity. In addition, acute memory performance was most sensitive to these changes. After 21 days, adolescents with SRC returned to baseline performance, although chronic hyperconnectivity of these regions could place these adolescents at greater risk for secondary neuropathological changes, necessitating future follow-up. (JINS, 2018, 24, 781-792).

Advanced biomarkers of pediatric mild traumatic brain injury: Progress and perils

There is growing public concern about neurodegenerative changes (e.g., Chronic Traumatic Encephalopathy) that may occur chronically following clinically apparent and clinically silent (i.e., sub-concussive blows) pediatric mild traumatic brain injury (pmTBI). However, there are currently no biomarkers that clinicians can use to objectively diagnose patients or predict those who may struggle to recover. Non-invasive neuroimaging, electrophysiological and neuromodulation biomarkers have promise for providing evidence of the so-called "invisible wounds" of pmTBI. Our systematic review, however, belies that notion, identifying a relative paucity of high-quality, clinically impactful, diagnostic or prognostic biomarker studies in the sub-acute injury phase (36 studies on unique samples in 28 years), with the majority focusing on adolescent pmTBI. Ultimately, well-powered longitudinal studies with appropriate control groups, as well as standardized and clearly-defined inclusion criteria (time post-injury, injury severity and past history) are needed to truly understand the complex pathophysiology that is hypothesized (i.e., still needs to be determined) to exist during the acute and sub-acute stages of pmTBI and may underlie post-concussive symptoms.

The Role of Physical Activity in Recovery From Concussion in Youth: A Neuroscience Perspective

BACKGROUND AND PURPOSE

Concussion is a major public health concern and one of the least understood neurological injuries. Children and youth are disproportionally affected by concussion, and once injured, take longer to recover. Current guidelines recommend a period of physical and cognitive rest with a gradual progressive return to activity. Although there is limited high-quality evidence (eg, randomized controlled trials) on the benefit of physical activity and exercise after concussion, most studies report a positive impact of exercise in facilitating recovery after concussion. In this article we characterize the complex and dynamic changes in the brain following concussion by reviewing recent results from neuroimaging studies and to inform physical activity participation guidelines for the management of a younger population (eg, 14-25 years of age) after concussion.

SUMMARY OF KEY POINTS

Novel imaging methods and tools are providing a picture of the changes in the structure and function of the brain following concussion. These emerging results will, in the future, assist in creating objective, evidence-based pathways for clinical decision-making. Until such time, physical therapists should be aware that current neuroimaging evidence supports participation in physical activity after an initial and brief period of rest, and consider how best to incorporate exercise into rehabilitation to enhance recovery following concussion.

RECOMMENDATIONS FOR CLINICAL PRACTICE

It is important that physical therapists understand the neurobiological impact of concussion injury and recovery, and be informed of the scientific rationale for the recommendations and guidelines for engagement in physical activity.Video Abstract available for more insights from the authors (see Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A205).

Imaging in Pediatric Concussion: A Systematic Review

CONTEXT

Pediatric mild traumatic brain injury (mTBI) is a common and poorly understood injury. Neuroimaging indexes brain injury and outcome after pediatric mTBI, but remains largely unexplored.

OBJECTIVE

To investigate the differences in neuroimaging findings in children/youth with mTBI. Measures of behavior, symptoms, time since injury, and age at injury were also considered.

DATA SOURCES

A systematic review was conducted up to July 6, 2016.

STUDY SELECTION

Studies were independently screened by 2 authors and included if they met predetermined eligibility criteria: (1) children/youth (5-18 years of age), (2) diagnosis of mTBI, and (3) use of neuroimaging.

DATA EXTRACTION

Two authors independently appraised study quality and extracted demographic and outcome data.

RESULTS

Twenty-two studies met the eligibility criteria, involving 448 participants with mTBI (mean age = 12.7 years ± 2.8). Time postinjury ranged from 1 day to 5 years. Seven different neuroimaging methods were investigated in included studies. The most frequently used method, diffusion tensor imaging (41%), had heterogeneous findings with respect to the specific regions and tracts that showed group differences. However, group differences were observed in many regions containing the corticospinal tract, portions of the corpus callosum, or frontal white-matter regions; fractional anisotropy was increased in 88% of the studies.

LIMITATIONS

This review included a heterogeneous sample with regard to participant ages, time since injury, symptoms, and imaging methods which prevented statistical pooling/modelling.

CONCLUSIONS

These data highlight essential priorities for future research (eg, common data elements) that are foundational to progress the understanding of pediatric concussion.

Demographic, physical and mental health assessments in the adolescent brain and cognitive development study: Rationale and description

The Adolescent Brain and Cognitive Development (ABCD) Study incorporates a comprehensive range of measures assessing predictors and outcomes related to both mental and physical health across childhood and adolescence. The workgroup developed a battery that would assess a comprehensive range of domains that address study aims while minimizing participant and family burden. We review the major considerations that went into deciding what constructs to cover in the demographics, physical health and mental health domains, as well as the process of selecting measures, piloting and refining the originally proposed battery. We present a description of the baseline battery, as well as the six-month interim assessments and the one-year follow-up assessments. This battery includes assessments from the perspectives of both the parent and the target youth, as well as teacher reports. This battery will provide a foundational baseline assessment of the youth's current function so as to permit characterization of stability and change in key domains over time. The findings from this battery will also be utilized to identify both resilience markers that predict healthy development and risk factors for later adverse outcomes in physical health, mental health, and substance use and abuse.

Changes in brain-behavior relationships following a 3-month pilot cognitive intervention program for adults with traumatic brain injury

Facilitating functional recovery following brain injury is a key goal of neurorehabilitation. Direct, objective measures of changes in the brain are critical to understanding how and when meaningful changes occur, however, assessing neuroplasticity using brain based results remains a significant challenge. Little is known about the underlying changes in functional brain networks that correlate with cognitive outcomes in traumatic brain injury (TBI). The purpose of this pilot study was to assess the feasibility of an intensive three month cognitive intervention program in individuals with chronic TBI and to evaluate the effects of this intervention on brain-behavioral relationships. We used tools from graph theory to evaluate changes in global and local brain network features prior to and following cognitive intervention. Network metrics were calculated from resting state electroencephalographic (EEG) recordings from 10 adult participants with mild to severe brain injury and 11 age and gender matched healthy controls. Local graph metrics showed hyper-connectivity in the right inferior frontal gyrus and hypo-connectivity in the left inferior frontal gyrus in the TBI group at baseline in comparison with the control group. Following the intervention, there was a statistically significant increase in the composite cognitive score in the TBI participants and a statistically significant decrease in functional connectivity in the right inferior frontal gyrus. In addition, there was evidence of changes in the brain-behavior relationships following intervention. The results from this pilot study provide preliminary evidence for functional network reorganization that parallels cognitive improvements after cognitive rehabilitation in individuals with chronic TBI.

What is the difference in concussion management in children as compared with adults? A systematic review

AIM

To evaluate the evidence regarding the management of sport-related concussion (SRC) in children and adolescents. The eight subquestions included the effects of age on symptoms and outcome, normal and prolonged duration, the role of computerised neuropsychological tests (CNTs), the role of rest, and strategies for return to school and return to sport (RTSp).

DESIGN

Systematic review.

DATA SOURCES

MEDLINE (OVID), Embase (OVID) and PsycInfo (OVID).

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Studies were included if they were original research on SRC in children aged 5 years to 18 years, and excluded if they were review articles, or did not focus on childhood SRC.

RESULTS

A total of 5853 articles were identified, and 134 articles met the inclusion criteria. Some articles were common to multiple subquestions. Very few studies examined SRC in young children, aged 5-12 years.

SUMMARY/CONCLUSIONS

This systematic review recommends that in children: child and adolescent age-specific paradigms should be applied; child-validated symptom rating scales should be used; the widespread routine use of baseline CNT is not recommended; the expected duration of symptoms associated with SRC is less than 4 weeks; prolonged recovery be defined as symptomatic for greater than 4 weeks; a brief period of cognitive and physical rest should be followed with gradual symptom-limited physical and cognitive activity; all schools be encouraged to have a concussion policy and should offer appropriate academic accommodations and support to students recovering from SRC; and children and adolescents should not RTSp until they have successfully returned to school, however early introduction of symptom-limited physical activity is appropriate.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO 2016:CRD42016039184.

Mapping the Connectome Following Traumatic Brain Injury

There is a paucity of accurate and reliable biomarkers to detect traumatic brain injury, grade its severity, and model post-traumatic brain injury (TBI) recovery. This gap could be addressed via advances in brain mapping which define injury signatures and enable tracking of post-injury trajectories at the individual level. Mapping of molecular and anatomical changes and of modifications in functional activation supports the conceptual paradigm of TBI as a disorder of large-scale neural connectivity. Imaging approaches with particular relevance are magnetic resonance techniques (diffusion weighted imaging, diffusion tensor imaging, susceptibility weighted imaging, magnetic resonance spectroscopy, functional magnetic resonance imaging, and positron emission tomographic methods including molecular neuroimaging). Inferences from mapping represent unique endophenotypes which have the potential to transform classification and treatment of patients with TBI. Limitations of these methods, as well as future research directions, are highlighted.

Making Waves in the Brain: What Are Oscillations, and Why Modulating Them Makes Sense for Brain Injury

Traumatic brain injury (TBI) can result in persistent cognitive, behavioral and emotional deficits. However, the vast majority of patients are not chronically hospitalized; rather they have to manage their disabilities once they are discharged to home. Promoting recovery to pre-injury level is important from a patient care as well as a societal perspective. Electrical neuromodulation is one approach that has shown promise in alleviating symptoms associated with neurological disorders such as in Parkinson’s disease (PD) and epilepsy. Consistent with this perspective, both animal and clinical studies have revealed that TBI alters physiological oscillatory rhythms. More recently several studies demonstrated that low frequency stimulation improves cognitive outcome in models of TBI. Specifically, stimulation of the septohippocampal circuit in the theta frequency entrained oscillations and improved spatial learning following TBI. In order to evaluate the potential of electrical deep brain stimulation for clinical translation we review the basic neurophysiology of oscillations, their role in cognition and how they are changed post-TBI. Furthermore, we highlight several factors for future pre-clinical and clinical studies to consider, with the hope that it will promote a hypothesis driven approach to subsequent experimental designs and ultimately successful translation to improve outcome in patients with TBI.

Brain Network Activation as a Novel Biomarker for the Return-to-Play Pathway Following Sport-Related Brain Injury

Children and adolescent athletes are at a higher risk for concussion than adults, and also experience longer recovery times and increased associated symptoms. It has also recently been demonstrated that multiple, seemingly mild concussions may result in exacerbated and prolonged neurological deficits. Objective assessments and return-to-play criteria are needed to reduce risk and morbidity associated with concussive events in these populations. Recent research has pushed to study the use of electroencephalography as an objective measure of brain injury. In the present case study, we present a novel approach that examines event-related potentials via a brain network activation (BNA) analysis as a biomarker of concussion and recovery. Specifically, changes in BNA scores, as indexed through this approach, offer a potential indicator of neurological health as the BNA assessment qualitatively and quantitatively indexes the network dynamics associated with brain injury. Objective tools, such as these support accurate and efficient assessment of brain injury and may offer a useful step in categorizing the temporal and spatial changes in brain activity following concussive blows, as well as the functional connectivity of brain networks, associated with concussion.