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Neuroscience, Biomechanics, and Risks of Concussion in the Developing Brain

Over the past 30 years, a number of experimental models of traumatic brain injury (TBI) have been developed to study various aspects of TBI in humans. This area of research originally focused on adult animal models of moderate to severe brain injuries, and these models have significantly contributed to our understanding of the biomechanics and neurochemical changes that occur after TBI. More recently, research efforts have focused on animal models of mild TBI (mTBI) and concussions, but only a few studies have addressed age and sex differences in injuries of this severity. TBI of any severity in the developing brain is complicated by ongoing cerebral maturation. The goal of this chapter is to (1) summarize the normal changes that occur with brain maturation; (2) explain the biomechanics involved in generating brain injuries of a range of severities; (3) summarize what is known about the neurochemical and metabolic changes that occur after concussions; and (4) describe risk factors for concussions in youth. In the section on the biomechanics of concussion, the committee responds to the portion of its charge concerning physical and biological thresholds for concussive injury.

NORMAL BRAIN DEVELOPMENT

The human brain is a complex system of connections that continues to be refined and reshaped throughout an individual’s lifespan. During development, rapid changes in synapses, myelination, and metabolism occur, with the brain achieving adult-like connections by the mid-20s (see Figure 2-1). The changes in both the structural architecture and the func-



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2 Neuroscience, Biomechanics, and Risks of Concussion in the Developing Brain Over the past 30 years, a number of experimental models of traumatic brain injury (TBI) have been developed to study various aspects of TBI in humans. This area of research originally focused on adult animal models of moderate to severe brain injuries, and these models have significantly contributed to our understanding of the biomechanics and neurochemical changes that occur after TBI. More recently, research efforts have focused on animal models of mild TBI (mTBI) and concussions, but only a few studies have addressed age and sex differences in injuries of this severity. TBI of any severity in the developing brain is complicated by ongoing ce- rebral maturation. The goal of this chapter is to (1) summarize the normal changes that occur with brain maturation; (2) explain the biomechanics involved in generating brain injuries of a range of severities; (3) summarize what is known about the neurochemical and metabolic changes that occur after concussions; and (4) describe risk factors for concussions in youth. In the section on the biomechanics of concussion, the committee responds to the portion of its charge concerning physical and biological thresholds for concussive injury. NORMAL BRAIN DEVELOPMENT The human brain is a complex system of connections that continues to be refined and reshaped throughout an individual’s lifespan. During development, rapid changes in synapses, myelination, and metabolism oc- cur, with the brain achieving adult-like connections by the mid-20s (see Figure 2-1). The changes in both the structural architecture and the func- 55

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56 SPORTS-RELATED CONCUSSIONS IN YOUTH FIGURE 2-1 Profiles of parameters of human brain development and the estimated age ranges for research animal models. This figure illustrates the timing of changes in the number of brain synapses, cerebral blood flow, and metabolism (blue) and in brain myelination (green). The colored bars below the figure reflect the ap- proximated human age equivalent of the rat (blue) and pig (green) based on species specific developmental profiles. SOURCE: Adapted from Casey et al., 2005. tional organization of the brain reflect a dynamic interplay of progressive and regressive events that occur simultaneously as the developing individual interacts with the environment. Although total brain size is about 90 per- cent of adult size by age 6 years, the brain continues to undergo dynamic changes throughout adolescence and into young adulthood (Yakovlev and Lecours, 1967). Current neuroimaging methods do not have the resolution to delineate the processes that underlie the observed developmental changes beyond observations of the brain’s gray and white matter subcomponents. The techniques do, however, allow for assessment of functional sequelae of concussions and, together with animal models, suggest that the developing brain responds differently to concussion than does the mature brain (Choe et al., 2012; Shrey et al., 2011).

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NEUROSCIENCE, BIOMECHANICS, AND RISKS OF CONCUSSION 57 Synaptic Density Brain cells communicate with each other through synapses, which are dynamic points of contact between cells where chemicals called neu- rotransmitters are transferred. During brain development there are dra- matic changes in the number of synapses in the brain, with different regions of the brain developing at different rates and times (Bourgeois et al., 1994; Huttenlocher and Dabholkar, 1997). There is a dramatic increase in the number of synapses during the first few years of life. This production of synapses is followed by a prolonged period of synaptic pruning that, based on an individual’s experiences, eliminates weaker synaptic contacts while retaining and strengthening the stronger connections. This pruning process occurs earlier in the auditory and visual cortex (by approximately 12 years of age), than in areas of the prefrontal cortex, which plays a role in executive functions such as problem solving and decision making (by approximately 18 years of age) (Bourgeois et al., 1994; Huttenlocher and Dabholkar, 1997). Gray and White Matter Gray and white matter are two major components of the central ner- vous system (CNS), which includes the brain and the spinal cord. Gray matter is associated with processing and cognition, while white matter is involved in coordinating communication between different brain regions. Longitudinal studies using magnetic resonance imaging (MRI) to map the developmental time-course of structural changes in the normal brain indi- cate that increases in white matter are linear throughout childhood and ad- olescence and continue well into young adulthood. In contrast, the growth in gray matter volume shows an inverted U-shaped course, first increasing during the first few years of life and then decreasing during adolescence (Giedd, 2004; Giedd et al., 1999, 2012; Gogtay et al., 2004; Sowell et al., 2004). These changes do not occur uniformly throughout an individual’s development. The primary sensorimotor regions mature during early ado- lescence, while parietal and prefrontal regions, which are important for at- tention and working memory, have a more protracted development, lasting into young adulthood (Gogtay et al., 2004; Sowell et al., 2004). In general, regions of cortical gray matter (parietal, frontal, and temporal) develop earlier in females than in males during adolescence (Giedd et al., 2012). Concussions and other head injuries can result in changes to the integrity of gray and white matter.

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58 SPORTS-RELATED CONCUSSIONS IN YOUTH Cerebral Blood Flow and Glucose Metabolism In parallel with the structural changes that occur with brain develop- ment, there are changes in cerebral glucose metabolism and cerebral blood flow (CBF), which refers to the blood supply to the brain. Normal CBF at birth is lower than the adult rate of 50ml/min/100g (Chiron et al., 1992). Blood flow rates increase rapidly during the first year of life and are 50 to 80 percent higher than flow rates in adults by the time a child is 5 to 6 years of age. CBF rates then decrease gradually during childhood and adoles- cence, reaching adult values when an individual is between 15 and 19 years of age. CBF varies with age and sex (Tontisirin et al., 2007; Udomphorn et al., 2008; Vavilala et al., 2005), with adolescents and adult females showing greater middle cerebral artery flow rates than male adults (Bakker et al., 2004; Vavilala et al., 2002a). Given that cerebral substrate supply and utilization are linked, it is not surprising that the developmental profile of cerebral glucose uptake mirrors that of CBF in both animals and humans (Nehlig et al., 1989). Positron emission tomography (PET) has been used to image the regional changes in glucose uptake of the normal developing brain. This research shows that the overall cerebral metabolic rate of glucose consumption (CMRglc) at birth are 30 percent lower than they are for adults and that glucose up- take increases sharply after birth to peak at approximately 4 years of age (Chugani, 1998). CMRglc plateaus at 50-60 µmol/min/100g between 4 and 10 years, followed by a decline in glucose uptake until the uptake reaches adult rates by the age of 16 to 18 years. Changes in CBF, cerebral metabolic rates for oxygen, and CMRglc mirror one another as they peak during early childhood and gradually de- crease to adult levels (Udomphorn et al., 2008). CBF is coupled to glucose metabolism, partial pressure of carbon dioxide, partial pressure of oxygen, and blood viscosity (Len and Neary, 2011). Several studies have demon- strated that females from 4 to 8 years of age and between 10 and 16 years of age show greater middle cerebral artery and basilar artery blood flow velocities relative to males of the same age (Tontisirin et al., 2007; Vavilala et al., 2005). Compared with adults, youth ages 12 to 17 years show lower autoregulation of blood flow and higher blood flow velocities (Vavilala et al., 2002b). While evidence in the literature sufficiently demonstrates the existence of age and sex differences in the maturation of these couplings, it is also clear that much more research needs to be done to understand the extent and significance of these differences in regard to how they affect cerebral response to concussions and other brain injuries.

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NEUROSCIENCE, BIOMECHANICS, AND RISKS OF CONCUSSION 59 Behavioral Changes Sleep patterns change dramatically during brain maturation. The aver- age sleep duration for infants is 12.7 hours and for toddlers is 11.9 hours (Galland et al., 2012). Sleep duration is influenced by the start of school at- tendance, which begins around 5 or 6 years of age. The average sleep dura- tion gradually decreases from approximately 10.5 hours during elementary school (5- to 10-year-olds) to about 9.3 hours during middle school (11- to 13-year-olds) (Iglowstein et al., 2003). During adolescence, biological sleep patterns shift toward later times for both sleeping and waking (Malone, 2011). Although the optimal sleep duration for adolescents is about 9 hours each night (Carskadon et al., 2004), the average high schooler (14- to 18-year-olds) gets between 6 and 8 hours of sleep each night, largely due to early school start times and wake-inducing activities (e.g., social and aca- demic activities) that interfere with sleep. This reduction in sleep coincides with the period of adolescent cortical synaptic pruning. The possibility of interactive factors at work, with changes in sleep altering cognitive, linguis- tic, and emotional behaviors, should be considered when identifying sleep and cognitive impairments in youths following a concussion. Adolescence is also a period of brain development that is marked by an increase in risk behaviors and addiction. The prefrontal cortex is important in executive decision making, the regulation of emotions, and the assess- ment of risk and reward (Bechara et al., 2000; Kelley et al., 2004; Romer, 2010; Spear, 2010). Protracted development of the prefrontal cortex may contribute to an increase in risk-taking behaviors in adolescence (Bava and Tapert, 2010; Casey and Jones, 2010; Dayan et al., 2010; Pharo et al., 2011). Such behaviors may include those that result in increased risk of injury. Compared with previous generations, today’s youth, due to an earlier average age of puberty (Biro et al., 2010), may have a greater mis- match between the propensity to engage in risk taking (which arises with the onset of puberty) and behavioral inhibition (which is associated with development of the prefrontal cortex). BIOMECHANICS OF CONCUSSION The biomechanics of TBI (including concussions) is defined broadly as the interrelationships among the forces experienced during impact, head and neck movements, stiffness of the tissue that composes the head/neck complex, deformation of structures at the macroscopic and microscopic level, and the biological responses to the various loading conditions im- posed on the head. The biological responses may be structural (torn vessels and axons) or functional (changes in blood flow or neurological status), and they may be immediate or delayed.

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60 SPORTS-RELATED CONCUSSIONS IN YOUTH Understanding the biomechanics of sports-related concussions in youth requires knowledge about what head and neck movements and applied forces occur in an array of sporting environments, how the developing head and neck mechanical and biological properties change with age and gender, how mechanical responses change during development, and how tissue deformations or changes in physiology (e.g., CBF, metabolism) produced by these motions and forces may directly or indirectly cause a concussion. This information plays a pivotal role in understanding risk factors and designing practices and equipment to reduce the incidence of concussions in sports. The studies employed for biomechanics investigations typically include direct measurements of loading conditions and responses in hu- mans, animals, and anthropomorphic surrogates (i.e., crash test dummies); visualization of tissue responses to prescribed loads in order to characterize the responses of complex geometries or composite structures; mechanical property testing of individual components in order to identify changes with age; computational models to predict how tissues will deform during impact or rapid head rotations; and identification of the time-course of cell or tissue responses to specified deformations in order to define thresholds associated with various types of injuries. Note that blast injuries are typi- cally associated with exposure to extremely rapid pressure waves that cause rapid expansion and contraction of brain tissue as they pass through the brain; the biomechanics and characteristics of these types of brain injuries are distinct from most brain injuries that occur in sporting environments (Holbourn, 1945; Ommaya et al., 1971), and they will not be discussed further in this section. Non-blast-related impacts to the head that occur in the military setting may be governed by similar mechanics as those on the athletic field, however, and the concepts discussed in the following section are applicable. Understanding the relationships between biomechanics and concussions in the developing brain is an essential step in creating protective devices to reduce the incidence of sports-related concussion and in developing rule changes aimed at reducing individuals’ exposure to hazardous conditions. This section summarizes the range of experimental platforms used to study brain injury, what has been learned from these studies about how brain injuries occur, and the many gaps in our understanding of how concussions occur in a youth sports environment. Overview of Common Experimental Platforms for Understanding the Biomechanics of Traumatic Brain Injury Investigators can use human data obtained in the field during sporting events to help understand what scenarios cause concussion. Typically, a sen- sor affixed to a helmet or a mouthpiece is used to measure the magnitude,

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NEUROSCIENCE, BIOMECHANICS, AND RISKS OF CONCUSSION 61 direction, and type (i.e., linear, rotational, centroidal, or non-centroidal) of head motion (see, for example, Camarillo et al., 2013; Crisco et al., 2010; Daniel et al., 2012; Rowson and Duma, 2013; Rowson et al., 2012). These sensors do not usually measure head impact forces directly (for an exception, see Ouckama and Pearsall, 2011), but rather they measure the head’s movement (acceleration or velocity) in response to an impact. The mechanical data recorded by the sensors are correlated with clinical assess- ments of injuries sustained on the sport field. However, such human data are influenced by equipment design limitations. For example, some devices are unable to measure actual head movements because of slipping between head and sensor, some cannot measure linear motions independently from angular motions or only report motion in a single plane of motion or a composite, and some sensors have errors or measurement variability that exceed reasonable standards. The human data may also be limited by inaccuracies in self-reports of concussions and difficulties in adequately adjusting for varying histories of previous impact exposures. Furthermore, the lack of control over the direction, extent, and number of head move- ments each subject experiences impedes the ability to determine whether the person-to-person variability in outcome measures is attributable to differences in impact forces or head motions or to differences in sex, age, and previous history of head injuries. As the current obstacles related to biomechanical measurements are addressed and objective clinical measures of concussion are improved, human data collected from on-field settings will play an increasingly valuable role in understanding what biomechanical conditions or predisposing factors contribute to concussions. In 2012 the U.S. Army began using sensors to collect data on the effects of blasts on the body, including the mechanisms that lead to concussions and other traumatic brain injury in soldiers. Results are not yet published (Hoffman, 2012). To obtain kinematic information in more controlled settings, human- like anthropomorphic surrogates (i.e., crash test dummies) and laboratory- based studies are used to reenact film and witness accounts of sports-related events in order to estimate the forces of impact and head movements (kine- matics). Surrogates and humans are also used to document the kinematics associated with non-injurious activities (Feng et al., 2010; Funk et al., 2011; Lloyd et al., 2011), which are important for identifying both tolerable and injurious kinematic conditions. It is important to note that surrogates measure only kinematic responses and that at this time, in the absence of accepted tolerance values, surrogates cannot be used to predict or measure concussions or tissue distortions. Instead, results obtained using surrogates must be correlated with animal studies, autopsy reports, and patient re- cords to infer biological responses to kinematic loading conditions or with computational models to infer tissue deformations resulting from a head

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62 SPORTS-RELATED CONCUSSIONS IN YOUTH rotation or impact. A final issue is that there are few surrogates for youth and no surrogate has been validated as representative of human responses in sports settings, where kinematic conditions are often considerably lower than in car crashes. Computational models are used to estimate the tissue distortions and stresses that may result from the kinematics of a rapid head motion or head impact, but they are valuable for understanding mechanics only when they use life-like tissue stiffnesses. Brain and skull tissue stiffnesses are available for young children (infants and toddlers) and adults (Coats and Margulies, 2006; Elkin et al., 2010; Kaster et al., 2011; Prange and Margulies, 2002; Prevost et al., 2011), but there are few data for older youth. As is the case with surrogates, computational models cannot be used to directly mea- sure concussion or axonal injury, skull fracture, or vessel rupture; instead, predicted deformations or stresses from the model must be compared to published tissue-specific thresholds in order to infer injury. An important point is that early data have demonstrated that the brain tissue distortions and stresses in the skull that are associated, respectively, with axonal injury and skull fracture are smaller in young children than in adults (Coats and Margulies, 2006; Ibrahim et al., 2010; Raghupathi and Margulies, 2002; Robbins and Wood, 1969), but there are no concussion tissue threshold data for older youth. It is important to note that, typically, biomechanical thresholds of injury correspond to the risk of acute injury. Rarely is biomechanics used to develop injury thresholds for long-term consequences, repeated expo- sures, or predisposing biological conditions. The physiological response to an initial injury may continue for days or weeks (see discussion on the neurochemistry of concussion later in this chapter), potentially creating a prolonged period when the brain may respond differently to a second event (discussed in Chapter 5). It is unknown whether deformation injury thresh- olds for previously injured tissue, which may be hypoxic or metabolically compromised, are lower than for normally functioning tissue. Research at the intersection of biomechanics and physiology is required before inves- tigators can predict whether a subsequent head rotation or impact after a concussion may be more damaging than a single event. Another common application of computational models is to simulate the head response to an impact and, if human data for that event are known, to use the model’s estimates of tissue distortions to infer tissue deforma- tions that may be associated with brain injury (Kimpara and Iwamoto, 2012; Kleiven, 2007; Takhounts et al., 2008). This indirect prediction of brain injury is hampered by the drawbacks described above and, given that brain injury is now understood to be heterogeneous, by the challenge of defining the critical deformations associated with various types and sever- ity of the specific brain injury of interest (Saatman et al., 2008). Previous

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NEUROSCIENCE, BIOMECHANICS, AND RISKS OF CONCUSSION 63 biomechanics studies have linked tissue deformations to a spectrum of brain injuries and have demonstrated that deformation thresholds are age- and injury-specific and that the magnitude and rate of the distortion required to rupture a blood vessel are different from those required to injure an axon or cause a concussion (Coats et al., 2012; Monson et al., 2003; Smith et al., 1999; Zhu et al., 2006). It is widely accepted that smaller deforma- tions may be associated with brief functional changes (deficits in synaptic transmission, signaling pathways, and membrane permeability; see Meaney and Smith, 2011) and that larger deformations may cause permanent struc- tural changes (Cater et al., 2006; Elkin and Morrison, 2007). Thus, tissue distortions and the rates of tissue deformation associated with concussion (with no lingering neural or vascular structural changes visible in radiologi- cal imaging or pathology) are probably lower than those for more severe brain injuries (Gennarelli et al., 2003), so it is inappropriate to rely on a single threshold for all head injuries. Moreover, it is unknown whether a concussion is produced when a critical proportion of the entire brain expe- riences deformation above a threshold level or whether only certain brain locations must be exposed to deformation (King et al., 2003; Ommaya and Gennarelli, 1974). Furthermore, the research community has not reached a consensus regarding whether the most appropriate injury thresholds should be defined as an average value, a threshold associated with zero injury risk, or one associated with some modest acceptable chance of injury. For com- parison, in automotive safety, vehicles and restraint systems are designed so that body regions experience mechanical loads below a threshold value associated with a chance of moderate to serious injury of anywhere from 15 to 50 percent (Kleinberger et al., 1998). Each of these gaps in knowledge about concussion thresholds limits the ability of computational models to predict whether a concussion would occur from a specific head rotation or impact. However, when appropriate and acceptable tissue thresholds spe- cific to concussions in youth are determined in the future, computational models of the human head will be powerful platforms to identify dominant and secondary factors that contribute to the biomechanics of concussion, to integrate future data regarding synergistic effects of biology and biome- chanics, and to develop rational guidelines for protective equipment. Presently, because human data and computational models are limited, researchers use alternative idealized experimental preparations such as ani- mals, tissues, and isolated cells to create controllable settings with similar predisposing conditions among subjects and reproducible mechanical loads. Animal models are useful for measuring physiological responses (e.g., re- flexes, blood flow, tissue oxygen content, metabolic derangements); injuries to the vessels, axons, and neural cell bodies; and changes in motor, memory, learning, and behavioral aptitudes at prescribed time-points after injury. Although they are the best substitute for humans, there are four chal-

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64 SPORTS-RELATED CONCUSSIONS IN YOUTH lenges in using animal models to understand sports-related concussion youth. First, human concussion includes changes in mental status without a loss of consciousness, and no metrics have been developed to assess these subtle alterations in animals immediately after injury. Thus, the definition of brain injury in an animal model includes loss of consciousness, often accompanied with demonstrable changes in axon structure or function, appearance of hemorrhages, or longer-term alterations in neurological func- tion. Because concussions may not be associated with axonal injury, hemor- rhage, and loss of consciousness, animal models, even those of mTBI, most commonly involve more severe brain injuries than concussion. Second, informative injury models need to mimic the injuries seen in sporting envi- ronments (Wall and Shani, 2008), yet most brain injury models create focal hemorrhagic cortical lesions caused by direct impact to the skull or exposed brain (Xiong et al., 2013), while the human concussed brain is more com- monly associated with distributed white matter alterations (Benson et al., 2007; Kraus et al., 2007). Third, most models use adult animals, and, given the developmental differences described earlier in this chapter, extensions to youth should be made with caution. Fourth, animal models most commonly involve mice and rats but have also included ovine, porcine, and nonhu- man primate models (Browne et al., 2011; Durham et al., 2000; Finnie et al., 2012; Gennarelli et al., 1981, 1982; Viano et al., 2012). Recent reports indicate that rodents have limited fidelity to human genomic and proteomic responses, injury time-courses, and gray and white brain matter distribu- tion (Duhaime et al., 2006; Seok et al., 2013), which implies that there are challenges in applying what is learned about injury in the developing rodent brain to the human child. Despite these four substantial challenges, animal models are a valuable tool for understanding how head impacts and sudden head movements translate to brain deformations and how brain deforma- tions result in a spectrum of brain injuries, from mild to severe. What Has Been Learned About How Traumatic Brain Injuries Occur Using the tools described above, researchers have determined that with or without a helmet, when the head contacts a stationary or moving object there is a rapid change in velocity and a possible deformation of the skull. Skull deformation may produce a local contusion or hemorrhage if the deformations of the tissues exceed their injury thresholds. When the prop- erties of the contact surfaces are softer or allow sliding or deformation, the rate of velocity change (acceleration or deceleration, depending on whether the velocity is increasing or decreasing) is lower. Similarly, if there is no head contact but only body contact (e.g., in a tackle), the deceleration of the moving head is usually lower than when the head is contacted directly. After the initial rapid change in velocity caused by impact to the head

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NEUROSCIENCE, BIOMECHANICS, AND RISKS OF CONCUSSION 65 or body, the subsequent motion of the head is influenced by the location of that initial point of contact and the interaction between the head, neck, and body. There are three possible kinematic responses to head contact. First, if the contact is directed through the center of mass of the brain (i.e., is centroidal), there may be linear motion and no rotation of the head (e.g., a weight dropping down onto the top of the head or a blow to the back of the head that moves the ears and nose forward without neck flexion or exten- sion). Animal studies have shown that these purely linear motions produce little brain motion or distortion and no concussion (Hardy et al., 2001; Ommaya and Gennarelli, 1974; Ommaya et al., 1971). However, most often the contact force is not directed centroidally through the brain, a situ- ation that is referred to as a non-centroidal impact. After a non-­ entroidal c contact, the head may rotate without a linear motion (e.g., shaking the head “no”). This purely rotational motion produces a distortion of the brain’s neural and vascular structures within the skull because the brain is softer than the skull and loosely coupled to the skull. More commonly, though, a head impact produces a change in head velocity that is associated with both linear acceleration and rotation of the head. This combined rotational and linear motion may occur because the contact is glancing (further away from the rotation center) or the body continues to move after the head is restrained by the contact surface or the head bounces or rebounds after contact. For these combined rotation/linear head responses, computational simulations have illuminated the relationship between the location of the head impact, the kinematic responses of the head (linear and rotational accelera­ions), and the predicted brain tissue deformations (Aare et al., t 2004; Kleiven, 2007; Post et al., 2011). Specifically, for those unusual instances when the head impact is through the center of mass of the head, linear acceleration correlates with the rotational acceleration response and the average deformation response in the brain. In these situations, linear ac- celeration is a reasonable surrogate for the brain tissue distortion response. By contrast, in the more common non-centroidal head impacts, linear and rotational accelerations are not correlated significantly, and the rotational acceleration component of the head response correlates most strongly with the average and peak brain deformations. Thus, for the most common head contact events, the linear acceleration component does not describe all of the brain’s deformation response, and therefore when used alone, is not a robust predictor of injury risk. Internal structures of the head, such as the falx cerebri and tentorium, influence how the brain moves within the skull and may cause local brain regions with very high deformations only in certain directions of head rotation, so that sagittal and coronal rotations may produce more severe injuries in primates at lower accelerations and velocities (Gennarelli et al., 1982). In addition, animal and human studies have shown a general

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