Design Considerations for the Attenuation of Translational and Rotational Accelerations in American Football Helmets.

Participants in American football experience repetitive head impacts that induce negative changes in neurocognitive function over the course of a single season. This study aimed to quantify the transfer function connecting the force input to the measured output acceleration of the helmet system to provide a comparison of the impact attenuation of various modern American football helmets. Impact mitigation varied considerably between helmet models and with location for each helmet model. The current data indicate that helmet mass is a key variable driving force attenuation, however flexible helmet shells, helmet shell cutouts, and more compliant padding can improve energy absorption.

Mitigating the Consequences of Subconcussive Head Injuries.

Subconcussive head injury represents a pathophysiology that spans the expertise of both clinical neurology and biomechanical engineering. From both viewpoints, the terms injury and damage, presented without qualifiers, are synonymously taken to mean a tissue alteration that may be recoverable. For clinicians, concussion is evolving from a purely clinical diagnosis to one that requires objective measurement, to be achieved by biomedical engineers. Subconcussive injury is defined as subclinical pathophysiology in which underlying cellular- or tissue-level damage (here, to the brain) is not severe enough to present readily observable symptoms. Our concern is not whether an individual has a (clinically diagnosed) concussion, but rather, how much accumulative damage an individual can tolerate before they will experience long-term deficit(s) in neurological health. This concern leads us to look for the history of damage-inducing events, while evaluating multiple approaches for avoiding injury through reduction or prevention of the associated mechanically induced damage.

Distribution of Head Acceleration Events Varies by Position and Play Type in North American Football.

OBJECTIVE: The goal of this pilot study was to evaluate the number of head acceleration events (HAEs) based on position, play type, and starting stance. DESIGN: Prospective cohort study. SETTING: Postcollegiate skill development camp during practice sessions and 1 exhibition game. PARTICIPANTS: Seventy-eight male adult North American football athletes. INDEPENDENT VARIABLES: A position was assigned to each participant, and plays in the exhibition game were separated by play type for analysis. During the exhibition game, video data were used to determine the effects of the starting position ("up" in a 2-point stance or "down" in a 3- or 4-point stance) on the HAEs experienced by players on the offensive line. MAIN OUTCOME MEASURES: Peak linear acceleration and number of HAEs greater than 20 g (g = 9.81 m/s2) were measured using an xPatch (X2 Biosystems, Seattle, WA). RESULTS: Four hundred thirty-seven HAEs were recorded during practices and 272 recorded during the exhibition game; 98 and 52 HAEs, the greatest number of HAEs by position in the game, were experienced by the offensive and defensive linemen, respectively. Linebackers and tight ends experienced high percentages of HAEs above 60 g. Offensive line players in a down stance had a higher likelihood of sustaining a HAE than players in an up stance regardless of the type of play (run vs pass). CONCLUSIONS: Changing the stance of players on the offensive line and reducing the number of full-contact practices will lower HAEs.

Evaluation of Impulse Attenuation by Football Helmets in the Frequency Domain.

Design of helmets used in contact sports has been driven by the necessity of preventing severe head injuries. Manufacturing standards and pass or fail grading systems ensure protective headgear built to withstand large impacts, but design standards do no account for impacts resulting in subconcussive episodes and the effects of cumulative impacts on its user. Thus, it is important to explore new design parameters, such as the frequency-domain measures of transmissibility and mechanical impedance that are based on energy absorption from a range of impact loads. Within the experimentally determined frequency range of interest (FROI), transmissibilities above unity were found in the 0-40 Hz range with the magnitude characteristics varying considerably with impact location. A similar variability with location was observed for the mechanical impedance, which ranged from 9 N/m to 50 N/m. Additional research is required to further understand how changes in the components or materials of the components will affect the performance of helmets, and how they may be used to reduce both transmissibility and dynamic impedance.

Uncovering multi-site identifiability based on resting-state functional connectomes.

Multi-site studies are becoming important to increase statistical power, enhance generalizability, and to improve the likelihood of pooling relevant subgroups together-activities which are otherwise limited by the availability of subjects or funds at a single site. Even with harmonized imaging sequences, site-dependent variability can mask the advantages of these multi-site studies. The aim of this study was to assess multi-site reproducibility in resting-state functional connectivity "fingerprints", and to improve identifiability of functional connectomes. The individual fingerprinting of functional connectivity profiles is promising due to its potential as a robust neuroimaging biomarker with which to draw single-subject inferences. We evaluated, on two independent multi-site datasets, individual fingerprints in test-retest visit pairs within and across two sites and present a generalized framework based on principal component analysis to improve identifiability. Those principal components that maximized differential identifiability of a training dataset were used as an orthogonal connectivity basis to reconstruct the individual functional connectomes of training and validation sets. The optimally reconstructed functional connectomes showed a substantial improvement in individual fingerprinting of the subjects within and across the two sites and test-retest visit pairs relative to the original data. A notable increase in ICC values for functional edges and resting-state networks were also observed for reconstructed functional connectomes. Improvements in identifiability were not found to be affected by global signal regression. Post-hoc analyses assessed the effect of the number of fMRI volumes on identifiability and showed that multi-site differential identifiability was for all cases maximized after optimal reconstruction. Finally, the generalizability of the optimal set of orthogonal basis of each dataset was evaluated through a leave-one-out procedure. Overall, results demonstrate that the data-driven framework presented in this study systematically improves identifiability in resting-state functional connectomes in multi-site studies.

The Use of an Electrophysiological Brain Function Index in the Evaluation of Concussed Athletes.

OBJECTIVE: To evaluate the effectiveness of the electroencephalographic (EEG) Brain Function Index (BFI) for characterizing sports-related concussive injury and recovery. PARTICIPANTS: Three hundred fifty-four (354) male contact sport high school and college athletes were prospectively recruited from multiple locations over 6 academic years of play (244 control baseline athletes and 110 athletes with a concussion). METHODS: Using 5 to 10 minutes of eyes closed resting EEG collected from frontal and frontotemporal regions, a BFI was computed for all subjects and sessions. Group comparisons were performed to test for the significance of the difference in the BFI score between the controls at baseline and athletes with a concussion at several time points. RESULTS: There was no significant difference in BFI between athletes with a concussion at baseline (ie, prior to injury) and controls at baseline (P = .4634). Athletes with a concussion, tested within 72 hours of injury, exhibited significant differences in BFI compared with controls (P = .0036). The significant differences in BFI were no longer observed at 45 days following injury (P = .19). CONCLUSION: Controls and athletes with a concussion exhibited equivalent BFI scores at preseason baseline. The concussive injury (measured within 72 hours) significantly affected brain function reflected in the BFI in the athletes with a concussion. The BFI of the athletes with a concussion returned to levels seen in controls by day 45, suggesting recovery. The BFI may provide an important objective marker of concussive injury and recovery.

Longitudinal changes in resting state fMRI brain self-similarity of asymptomatic high school American football athletes.

American football has become the focus of numerous studies highlighting a growing concern that cumulative exposure to repetitive, sports-related head acceleration events (HAEs) may have negative consequences for brain health, even in the absence of a diagnosed concussion. In this longitudinal study, brain functional connectivity was analyzed in a cohort of high school American football athletes over a single play season and compared against participants in non-collision high school sports. Football athletes underwent four resting-state functional magnetic resonance imaging sessions: once before (pre-season), twice during (in-season), and once 34-80 days after the contact activities play season ended (post-season). For each imaging session, functional connectomes (FCs) were computed for each athlete and compared across sessions using a metric reflecting the (self) similarity between two FCs. HAEs were monitored during all practices and games throughout the season using head-mounted sensors. Relative to the pre-season scan session, football athletes exhibited decreased FC self-similarity at the later in-season session, with apparent recovery of self-similarity by the time of the post-season session. In addition, both within and post-season self-similarity was correlated with cumulative exposure to head acceleration events. These results suggest that repetitive exposure to HAEs produces alterations in functional brain connectivity and highlight the necessity of collision-free recovery periods for football athletes.

Neural correlates of adaptation in freely-moving normal hearing subjects under cochlear implant acoustic simulations.

Neurobiological correlates of adaptation to spectrally degraded speech were investigated with fMRI before and after exposure to a portable real-time speech processor that implements an acoustic simulation model of a cochlear implant (CI). The speech processor, in conjunction with isolating insert earphones and a microphone to capture environment sounds, was worn by participants over a two week chronic exposure period. fMRI and behavioral speech comprehension testing were conducted before and after this two week period. After using the simulator each day for 2h, participants significantly improved in word and sentence recognition scores. fMRI shows that these improvements came accompanied by changes in patterns of neuronal activation. In particular, we found additional recruitment of visual, motor, and working memory areas after the perceptual training period. These findings suggest that the human brain is able to adapt in a short period of time to a degraded auditory signal under a natural learning environment, and gives insight on how a CI might interact with the central nervous system. This paradigm can be furthered to investigate neural correlates of new rehabilitation, training, and signal processing strategies non-invasively in normal hearing listeners to improve CI patient outcomes.

How challenges in auditory fMRI led to general advancements for the field.

In the early years of fMRI research, the auditory neuroscience community sought to expand its knowledge of the underlying physiology of hearing, while also seeking to come to grips with the inherent acoustic disadvantages of working in the fMRI environment. Early collaborative efforts between prominent auditory research laboratories and prominent fMRI centers led to development of a number of key technical advances that have subsequently been widely used to elucidate principles of auditory neurophysiology. Perhaps the key imaging advance was the simultaneous and parallel development of strategies to use pulse sequences in which the volume acquisitions were "clustered," providing gaps in which stimuli could be presented without direct masking. Such sequences have become widespread in fMRI studies using auditory stimuli and also in a range of translational research domains. This review presents the parallel stories of the people and the auditory neurophysiology research that led to these sequences.

Event segmentation in a visual language: neural bases of processing American Sign Language predicates.

Motion capture studies show that American Sign Language (ASL) signers distinguish end-points in telic verb signs by means of marked hand articulator motion, which rapidly decelerates to a stop at the end of these signs, as compared to atelic signs (Malaia and Wilbur, in press). Non-signers also show sensitivity to velocity in deceleration cues for event segmentation in visual scenes (Zacks et al., 2010; Zacks et al., 2006), introducing the question of whether the neural regions used by ASL signers for sign language verb processing might be similar to those used by non-signers for event segmentation. The present study investigated the neural substrate of predicate perception and linguistic processing in ASL. Observed patterns of activation demonstrate that Deaf signers process telic verb signs as having higher phonological complexity as compared to atelic verb signs. These results, together with previous neuroimaging data on spoken and sign languages (Shetreet et al., 2010; Emmorey et al., 2009), illustrate a route for how a prominent perceptual-kinematic feature used for non-linguistic event segmentation might come to be processed as an abstract linguistic feature due to sign language exposure.

Euclidean Distance Approximations From Replacement Product Graphs.

We introduce a new chamfering paradigm, locally connecting pixels to produce path distances that approximate Euclidean space by building a small network (a replacement product) inside each pixel. These " RE -grid graphs" maintain near-Euclidean polygonal distance contours even in noisy data sets, making them useful tools for approximation when exact numerical solutions are unobtainable or impractical. The RE -grid graph creates a modular global architecture with lower pixel-to-pixel valency and simplified topology at the cost of increased computational complexity due to its internal structure. We present an introduction to chamfering replacement products with a number of case study examples to demonstrate the potential of these graphs for path-finding in high frequency and low resolution image spaces which motivate further study. Possible future applications include morphology, watershed segmentation, halftoning, neural network design, anisotropic image processing, image skeletonization, dendritic shaping, and cellular automata.

Metabolomic response to collegiate football participation: Pre- and Post-season analysis.

Contact sports participation has been shown to have both beneficial and detrimental effects on health, however little is known about the metabolic sequelae of these effects. We aimed to identify metabolite alterations across a collegiate American football season. Serum was collected from 23 male collegiate football athletes before the athletic season (Pre) and after the last game (Post). Samples underwent nontargeted metabolomic profiling and 1131 metabolites were included for univariate, pathway enrichment, and multivariate analyses. Significant metabolites were assessed against head acceleration events (HAEs). 200 metabolites changed from Pre to Post (P < 0.05 and Q < 0.05); 160 had known identity and mapped to one of 57 pre-defined biological pathways. There was significant enrichment of metabolites belonging to five pathways (P < 0.05): xanthine, fatty acid (acyl choline), medium chain fatty acid, primary bile acid, and glycolysis, gluconeogenesis, and pyruvate metabolism. A set of 12 metabolites was sufficient to discriminate Pre from Post status, and changes in 64 of the 200 metabolites were also associated with HAEs (P < 0.05). In summary, the identified metabolites, and candidate pathways, argue there are metabolic consequences of both physical training and head impacts with football participation. These findings additionally identify a potential set of objective biomarkers of repetitive head injury.

Coupling between cerebrovascular oscillations and CSF flow fluctuations during wakefulness: An fMRI study.

It is commonly believed that cerebrospinal fluid (CSF) movement is facilitated by blood vessel wall movements (i.e., hemodynamic oscillations) in the brain. A coherent pattern of low frequency hemodynamic oscillations and CSF movement was recently found during non-rapid eye movement (NREM) sleep via functional MRI. This finding raises other fundamental questions: 1) the explanation of coupling between hemodynamic oscillations and CSF movement from fMRI signals; 2) the existence of the coupling during wakefulness; 3) the direction of CSF movement. In this resting state fMRI study, we proposed a mechanical model to explain the coupling between hemodynamics and CSF movement through the lens of fMRI. Time delays between CSF movement and global hemodynamics were calculated. The observed delays between hemodynamics and CSF movement match those predicted by the model. Moreover, by conducting separate fMRI scans of the brain and neck, we confirmed the low frequency CSF movement at the fourth ventricle is bidirectional. Our finding also demonstrates that CSF movement is facilitated by changes in cerebral blood volume mainly in the low frequency range, even when the individual is awake.

Normalized Brain Tissue-Level Evaluation of Volumetric Changes of Youth Athletes Participating in Collision Sports.

Observations of short-term changes in the neural health of youth athletes participating in collision sports (e.g., football and soccer) have highlighted a need to explore potential structural alterations in brain tissue volumes for these persons. Studies have shown biochemical, vascular, functional connectivity, and white matter diffusivity changes in the brain physiology of these athletes that are strongly correlated with repetitive head acceleration exposure. Here, research is presented that highlights regional anatomical volumetric measures that change longitudinally with accrued subconcussive trauma. A novel pipeline is introduced that provides simplified data analysis on standard-space template to quantify group-level longitudinal volumetric changes within these populations. For both sports, results highlight incremental relative regional volumetric changes in the subcortical cerebrospinal fluid that are strongly correlated with head exposure events greater than a 50-G threshold at the short-term post-season assessment. Moreover, longitudinal regional gray matter volumes are observed to decrease with time, only returning to baseline/pre-participation levels after sufficient (5-6 months) rest from collision-based exposure. These temporal structural volumetric alterations are significantly different from normal aging observed in sex- and age-matched controls participating in non-collision sports. Future work involves modeling repetitive head exposure thresholds with multi-modal image analysis and understanding the underlying physiological reason. A possible pathophysiological pathway is presented, highlighting the probable metabolic regulatory mechanisms. Continual participation in collision-based activities may represent a risk wherein recovery cannot occur. Even when present, the degree of the eventual recovery remains to be explored, but has strong implications for the well-being of collision-sport participants.

A preliminary model of football-related neural stress that integrates metabolomics with transcriptomics and virtual reality.

Research suggests contact sports affect neurological health. This study used permutation-based mediation statistics to integrate measures of metabolomics, neuroinflammatory miRNAs, and virtual reality (VR)-based motor control to investigate multi-scale relationships across a season of collegiate American football. Fourteen significant mediations (six pre-season, eight across-season) were observed where metabolites always mediated the statistical relationship between miRNAs and VR-based motor control ( p S o b e l p e r m ≤ 0.05; total effect > 50%), suggesting a hypothesis that metabolites sit in the statistical pathway between transcriptome and behavior. Three results further supported a model of chronic neuroinflammation, consistent with mitochondrial dysfunction: (1) Mediating metabolites were consistently medium-to-long chain fatty acids, (2) tricarboxylic acid cycle metabolites decreased across-season, and (3) accumulated head acceleration events statistically moderated pre-season metabolite levels to directionally model post-season metabolite levels. These preliminary findings implicate potential mitochondrial dysfunction and highlight probable peripheral blood biomarkers underlying repetitive head impacts in otherwise healthy collegiate football athletes.

Reproducibility of fMRI activations associated with auditory sentence comprehension.

The reproducibility of three different aspects of fMRI activations-namely binary activation maps, effect size and spatial distribution of local maxima-was evaluated for an auditory sentence comprehension task with high attention demand on a group of 17 subjects that were scanned on five different occasions. While in the scanner subjects were asked to listen to a series of six short everyday sentences from the CUNY sentence test. Comprehension and attention to the stimuli were monitored after each listen condition epoch by having subjects answer a series of multiple-choice questions. Statistical maps of activation for the listen condition were computed at three different levels: overall results for all imaging sessions, group-level/single-session results for each of the five imaging occasions, and single-subject/single-session results computed for each subject and each scanning occasion independently. The experimental task recruited a distributed bilateral network with processing nodes located in the lateral temporal cortex, inferior frontal cortex, medial BA6, medial occipital cortex and subcortical structures such as the putamen and the thalamus. Reproducibility of these activations at the group level was high (83.95% of the imaged volume was consistently classified as active/inactive across all five imaging sessions), indicating that sites of neuronal activity associated with auditory comprehension can reliably be detected with fMRI in healthy subjects, across repeated measures after group averaging. At the single-subject level reproducibility ranged from moderate to high, although no significant differences were found on behavioral measures across subjects or sessions. This result suggests that contextual differences-i.e., those specific to each imaging session, can modulate our ability to detect fMRI activations associated with speech comprehension in individual subjects.

Effects of combining field strengths on auditory functional MRI group analysis: 1.5T and 3T.

PURPOSE: To evaluate effects of combining functional magnetic resonance imaging (fMRI) data acquired from different field strengths on group analysis as a function of the number of subjects at each field strength. MATERIALS AND METHODS: In all, 28 subjects (18 at 3T) participated in an auditory task of passively listening to a 0.75s segment of jazz music in an event-related design. Results of single-subject analysis were combined to create all possible subject combinations for a group size of eight subjects from each of the 3T and 1.5T pools, comprising subject mixtures of (3T/1.5T) 0/8, 2/6, 4/4, 6/2, and 8/0. Group analysis performance of each subject permutation was measured by receiver operating characteristic (ROC) curves and activation overlap maps. RESULTS: While area under ROC curves, extent of activation in the gold standard region, and reliability of activation increased with the number of 3T subjects, marginal gain decreased. ROC performance overlap across mixtures was observed, indicating that some combinations of subjects markedly outperformed others. For detection of activation, 4/4 was arguably the minimum mixture level that was comparable to 3T-only group results. CONCLUSION: Inclusion of 1.5T data does not necessarily reduce the validity of group analysis. Lower field strength data was found only to limit detection power, but did not affect specificity. Within the limits of realignment error, these results should also extend to group longitudinal analyses of subject mixtures from different field strengths.

Development of subject-specific geometric spine model through use of automated active contour segmentation and kinematic constraint-limited registration.

This paper describes the development of a patient-specific spine model through use of active contour segmentation and registration of intraoperative imaging of porcine vertebra augmented with kinematic constraints. The geometric active contours are fully automated and lead to a discrete representation of the image segmentation results. After determining errors within the segmentations, application of reliability theory allows the selection of active contour parameters to obtain best-fit segmentations from a stack of 2D images. The segmented images are then used in conjunction with C-arm fluoroscope images to simulate the result of intraoperative patient-specific model registration including patient and/or structure motion between preoperative and intraoperative scans. The results are validated through comparison of the error within the patient-specific model generated through use of the C-arm images with a model acquired directly from MRI images of the spine after motion. The results are applicable to the development of a wide variety of patient-specific geometric and biomechanical models.

Using carpet plots to analyze transit times of low frequency oscillations in resting state fMRI.

A "carpet plot" is a 2-dimensional plot (time vs. voxel) of scaled fMRI voxel intensity values. Low frequency oscillations (LFOs) can be successfully identified from BOLD fMRI and used to study characteristics of neuronal and physiological activity. Here, we evaluate the use of carpet plots paired with a developed slope-detection algorithm as a means to study LFOs in resting state fMRI (rs-fMRI) data with the help of dynamic susceptibility contrast (DSC) MRI data. Carpet plots were constructed by ordering voxels according to signal delay time for each voxel. The slope-detection algorithm was used to identify and calculate propagation times, or "transit times", of tilted vertical edges across which a sudden signal change was observed. We aim to show that this metric has applications in understanding LFOs in fMRI data, possibly reflecting changes in blood flow speed during the scan, and for evaluating alternative blood-tracking contrast agents such as inhaled CO2. We demonstrate that the propagations of LFOs can be visualized and automatically identified in a carpet plot as tilted lines of sudden intensity change. Resting state carpet plots produce edges with transit times similar to those of DSC carpet plots. Additionally, resting state carpet plots indicate that edge transit times vary at different time points during the scan.

A novel method of quantifying hemodynamic delays to improve hemodynamic response, and CVR estimates in CO2 challenge fMRI.

Elevated carbon dioxide (CO2) in breathing air is widely used as a vasoactive stimulus to assess cerebrovascular functions under hypercapnia (i.e., "stress test" for the brain). Blood-oxygen-level-dependent (BOLD) is a contrast mechanism used in functional magnetic resonance imaging (fMRI). BOLD is used to study CO2-induced cerebrovascular reactivity (CVR), which is defined as the voxel-wise percentage BOLD signal change per mmHg change in the arterial partial pressure of CO2 (PaCO2). Besides the CVR, two additional important parameters reflecting the cerebrovascular functions are the arrival time of arterial CO2 at each voxel, and the waveform of the local BOLD signal. In this study, we developed a novel analytical method to accurately calculate the arrival time of elevated CO2 at each voxel using the systemic low frequency oscillations (sLFO: 0.01-0.1 Hz) extracted from the CO2 challenge data. In addition, 26 candidate hemodynamic response functions (HRF) were used to quantitatively describe the temporal brain reactions to a CO2 stimulus. We demonstrated that our approach improved the traditional method by allowing us to accurately map three perfusion-related parameters: the relative arrival time of blood, the hemodynamic response function, and CVR during a CO2 challenge.