Issuu on Google+

JOURNAL OF NEUROTRAUMA 26:2365–2382 (December 2009) ª Mary Ann Liebert, Inc. DOI: 10.1089=neu.2009.0906

Review Articles

Advances in Sport Concussion Assessment: From Behavioral to Brain Imaging Measures Dave Ellemberg,1 Luke C. Henry,2 Steve N. Macciocchi,3 Kevin M. Guskiewicz,4 and Steven P. Broglio 5


Given that the incidence of sports-related concussion is considered to have reached epidemic proportions, in the past 15 years we have witnessed an explosion of research in this field. The purpose of the current review is to compare the results provided by the different assessment tools used in the scientific literature in order to gain a better understanding of the sequelae and recovery following a concussion. Until recently, the bulk of the has literature focused on the immediate outcome in the hours and days post-injury as a means to plan the safest return-to-play strategy. This has led to the development of several assessment batteries that are relatively easy and rapid to administer and that allow for multiple testing sessions. The main conclusion derived from that literature is that cognitive symptoms tend to resolve within 1 week. However, accumulating evidence indicates that cognitive testing should be viewed as one of several complementary tools necessary for a comprehensive assessment of concussion. Including an objective measure of postural stability increases the sensitivity of the return-to-play decision-making process and minimizes the consequences of mitigating factors (e.g., practice effects and motivation) on neuropsychological test results. This is consistent with findings that symptom severity, neuropsychological function, and postural stability do not appear to be related or affected to the same degree after a concussion. Furthermore, recent evidence from brain imaging, including event-related potentials and functional and metabolic imaging, suggest abnormalities in the electrical responses, metabolic balance, and oxygen consumption of neurons that persist several months after the incident. We explain this apparent discrepancy in recovery by suggesting an initial and rapid phase of functional recovery driven by compensatory mechanisms and brain plasticity, which is followed by a prolonged neuronal recovery period during which subtle deficits in brain functioning are present but not apparent to standard clinical assessment tools. Key words: assessment; balance and posture; brain imaging; cognition; concussion; sport



ncreasing attention is being paid to sport-related traumatic brain injury (TBI), or concussion, by the media and scientific community. A search of the PubMed database from 1990 to 1999 for the term ‘‘concussion’’ yields 994 citations. The same search from 2000 through 2008 yields 1175 citations. Much of the recent literature has focused on evaluating and improving the assessment and return-to-play decision-making process. This is of particular importance considering studies that demonstrate persistent effects of multiple concussions in retired professional football athletes, as well as mild cognitive impairment, self-report memory impairments, depression, and earlier onset of Alzheimer’s

disease when compared to the general population (Guskiewicz et al., 2005; Guskiewicz et al., 2007a). As more information is synthesized and the understanding of concussive injury has improved, the definition of concussion has changed. Most recently, the summary and agreement statement of the First International Conference on Concussion in Sport updated the definition and stated: ‘‘Concussion is defined as a complex pathophysiological process affecting the brain, induced by traumatic biomechanical forces’’ (Aubry et al., 2002; McCrory et al., 2009). Injuries fitting this definition are estimated to occur in athletic settings between 1.6 and 3.8 million times annually (Langlois et al., 2006). Many injuries are thought to go unreported, as it typically has no outwardly visible signs, making it difficult to recognize. Thus in many


Department of Kinesiology, and 2Department of Psychology, University of Montre´al, Montre´al, Que´bec, Canada. Shepherd Center and Emory University, Atlanta, Georgia. 4 Department of Exercise and Sport Science, University of North Carolina, Chapel Hill, North Carolina. 5 Department of Kinesiology and Community Health, University of Illinois at Urbana–Champaign, Urbana, Illinois. 3


2366 instances medical personnel rely on self-report by the athlete, but research suggests that over 50% of concussed high school football athletes failed to report their injury to medical personnel (McCrea et al., 2004). An equally complex issue is establishing a time course for safe return to play following injury. The clinician must balance athlete safety, including the risks of a second concussion (Guskiewicz et al., 2003) or catastrophic injury (Cantu, 1995), with the time pressures associated with athletics. Once an athlete is suspected of sustaining a concussion, neuropsychological testing has been suggested to be the cornerstone of the assessment process, as it provides the clinician with objective data for return-to-play decision making (Aubry et al., 2002; McCrory et al., 2009). However, the role of neuropsychological testing as a stand-alone test in the concussion assessment protocol has been questioned (Randolph et al., 2005). As such, cognitive testing should be viewed as one of several complementary tools necessary for a comprehensive assessment of concussion. The concussion assessment protocol should also include a systematic review of symptoms and the evaluation of postural stability (Randolph et al., 2005). Furthermore, recent advances in imaging techniques provide sensitive measures of brain injury and recovery (Boutin et al., 2008; Lovell et al., 2007). Although functional magnetic resonance imaging, event-related potentials, magnetic resonance spectroscopy, and diffusion tensor imaging, have been applied to sport concussion research, their relative novelty has not yet allowed them to make their mark in clinical application. The purpose of the current review is to compare the results provided by the different assessment tools used in the scientific literature to gain a better understanding of the sequelae and functional recovery following a sport concussion. Symptomatology Use of athlete-reported symptomatology as the primary tool for concussion assessment by sports medicine professionals (Notebaert and Guskiewicz, 2005) is supported by the large effect concussion has on physical and cognitive functioning immediately following injury and in the ensuing days (Broglio and Puetz, 2008). The presence of symptoms following sport TBI is typically short lived (Aubry et al., 2002), although persistent symptoms fall under a defined syndrome called post-concussion syndrome (PCS). This syndrome is defined by the Diagnostic and Statistical Manual of Mental Disorders (American Psychiatric Association, 2000) as the presence of concussion-related symptoms for a least 3 months following injury. A discussion of PCS is beyond the scope of this review. A variety of symptom forms have been proposed over the years, with checklists used to indicate the presence or absence of a symptom and scales to grade severity and=or duration. Commonly utilized assessments include the Post Concussion Symptom Scale endorsed by the First International Symposium for Concussion in Sport (Aubry et al., 2002), and the Graded Symptom Checklist recommended by the National Athletic Trainers’ Association (Guskiewicz et al., 2004b). Although there are subtle differences between these and other scales, the items of blurred vision, dizziness, drowsiness, excessive sleeping, fatigue, feeling ‘‘in a fog,’’ feeling ‘‘slowed down,’’ headache, irritability, disorientation, memory problems, nausea, nervousness, decreased concentration, sensi-

ELLEMBERG ET AL. tivity to light, and sensitivity to noise, are commonly included symptoms. The presence of post-concussive symptoms varies widely among individuals, although some symptoms do emerge more commonly than others. For example, headache has been reported to occur in an average of 83% of concussed athletes, while other symptoms, such as dizziness (65% of concussed athletes) and confusion (57% of concussed athletes), are also prevalent, but occur less frequently (Delaney et al., 2002; Guskiewicz et al., 2003; Guskiewicz et al., 2000; McCrory et al., 2000). Notably, the heavy reliance traditionally placed on loss of consciousness (LOC) as a marker of concussion and concussion severity does not seem to be well founded. LOC is observed in fewer than 10% of all injuries (Delaney et al., 2002; Guskiewicz et al., 2003), and clinical outcomes following injury do not appear to be tied to the presence or absence of on-field LOC (Lovell et al., 1999). Other symptoms, such as post-traumatic amnesia, appear to provide greater sensitivity to injury severity, with longer spans of amnesia indicative of a worse outcome (Collins et al., 2003; Erlanger et al., 2003). Symptom recovery appears to occur rapidly in most concussed athletes. In an investigation of concussed collegiate soccer and football athletes, 87–92% reported no symptoms within 3 days of injury, and 95% reported complete symptom resolution within 7 days of injury (Delaney et al., 2002). This is consistent with investigations of young adults finding that recovery occurs within 2–10 days of injury (Broglio et al., 2007a; Collie et al., 2006; Field et al., 2003; Guskiewicz et al., 2003; Macciocchi et al., 2001). Athletes without symptoms immediately following the injury may experience delayed onset of symptoms, and clinicians should be prepared to check for this during serial assessments for at least 3 days after the suspected injury (Guskiewicz et al., 2003). Although professional athletes exhibit notably fewer symptoms when evaluated 1 and 3 days following injury (Pellman et al., 2006), a complete understanding the low symptom reports seen in these athletes has not been elucidated, although job security is speculated as a possible cause. More notable are the differences between men and women in reporting concussion-related symptoms following injury. In many instances women will report experiencing more symptoms than men, with increased reports of somatic symptoms such as headache, fatigue, and dizziness (Broshek et al., 2005; Farace and Alves, 2000). The foundation for gender differences in symptom reporting is not entirely clear, although cultural constructs may result in female athletes being more willing to express their symptoms to medical personnel (Granito, 2002). This is consistent with the finding that female athletes report a more significant number of mild baseline symptoms than male athletes (Covassin et al., 2007, 2003). The evaluation of symptoms associated with sport concussion is quick, cost-efficient, and easy for medical personnel to implement in clinical practice. In many circumstances the symptom evaluation involves asking the injured athlete to indicate the presence or absence of symptoms following a suspected injury. Despite its heavy use in concussion evaluation, however, this method of assessment has inherent weaknesses (Lezak et al., 2004). For example, the presence of symptoms alone may not be indicative of a concussion, as 20% of athletes may experience exercise-induced headaches (McCrory, 1999), and athlete willingness to report symptoms

ADVANCES IN SPORT CONCUSSION ASSESSMENT may not be at its highest when external pressure or a strong desire to return to play is present (McCrea et al., 2004). Furthermore, some athletes report symptoms at rest, justifying the importance of obtaining preseason baseline symptom scores (Lovell et al., 2006; Mailer et al., 2008). Overall, it appears that symptom recovery following concussion diagnosis has been used as a guide for injury recovery, but it is not a definitive return-to-play tool. This protocol is evidenced by the variant recovery patterns noted between symptoms and cognitive function (Broglio et al., 2007b; Fazio et al., 2007). In light of this evidence, symptom evaluation may not reflect the resolution of all post-concussion decrements, and therefore should only be used in combination with other evaluative measures and not as a sole indicator for return to play. The practicality of symptom reports as an indicator of concussion is clear, but further investigative work is needed. What is most needed is a better understanding of how to obtain accurate concussion symptom reports from injured athletes. In addition, revision of the symptom list may be in order. Piland and colleagues (Piland et al., 2003, 2006) noted that nine symptoms may best characterize concussion by removing confounding symptoms, but this scale has not been widely adopted. In addition, clinical guidelines for return to play note that no athlete should return to sport participation while still symptomatic (Guskiewicz et al., 2004b; Kissick and Johnston, 2005). However, recent evidence has shown a clinical improvement in those who participated in moderate activity while still symptomatic (Majerske et al., 2008; Willer and Leddy, 2006). A better understanding of how exercise may increase or decrease recovery from concussive injuries is clearly warranted. Postural Stability Balance plays a vital role in the maintenance of fluid dynamic movement common in sport. Balance is the process of maintaining the center of gravity within the body’s base of support, and many factors enter into the task of controlling balance within this designated area ( Jacobs and Horak, 2007). The system involves a complex network of neural connections and centers that are related by peripheral and central feedback mechanisms. A hierarchy integrating the cerebral cortex, cerebellum, basal ganglia, brainstem, and spinal cord is primarily responsible for controlling voluntary movements (Guyton, 1986; Vander et al., 1990). Postural instability has been identified in pathological conditions such as moderate to severe TBI (Geurts et al., 1996; Ingersoll and Armstrong, 1992; Mallinson and Longridge, 1998; Wober et al., 1993), hemiplegia and craniocerebral injury (Arcan et al., 1977), cerebellar atrophy and ataxia (Mauritz et al., 1979), and whiplash (Mallinson and Longridge, 1998; Rubin et al., 1995). It has been proposed that communication between sensory systems is lost in the majority of these individuals, causing moderate to severe postural instability in either the anterior-posterior direction, medial-lateral direction, or both. In most cases, symptoms such as dizziness, vertigo, tinnitus, lightheadedness, blurred vision, and photophobia, all having visual, vestibular, and=or somatosensory orientation, are reported (Geurts et al., 1996; Ingersoll and Armstrong, 1992; Mallinson and Longridge, 1998; Rubin et al., 1995; Wober et al., 1993).

2367 More recently, balance and postural stability have been studied as objective measures in the evaluation of athletes with acute cerebral concussion. Concussed athletes have demonstrated balance deficits following concussion using both high-tech and clinical methods of assessment. In most cases, decreases in postural stability persisted for up to 3 days following injury in comparison to control subjects, and were most evident when the subjects were standing either on a foam or moving (tilting) surface. Subsequent studies have identified decreases in postural stability for up to 3 days postinjury using the Sensory Organization Test (SOT) on the NeuroCom Smart Balance Master (Guskiewicz et al., 1997, 2001). Using the SOT, Guskiewicz and associates (2001) also found that overall balance performance typically recovers between days 1 and 3 post-injury. These studies identified deficits between concussed and control subjects, especially when visual and support surface conditions were altered. Athletes appear to have sensory interaction and decreased postural control until approximately 3 days following injury. The athletes gradually recover to approximately the scores of matched control subjects by day 10 post-injury. It appears that this deficit is related to a sensory interaction problem, whereby the concussed athlete fails to use their visual and vestibular systems effectively. The integration of visual and vestibular information is essential for the maintenance of equilibrium under certain altered conditions similar to those performed during the SOT (Nashner and Berthoz, 1978; Nashner, 1976; Nashner et al., 1982). If an athlete has difficulty balancing under conditions in which sensory systems have been altered, it can be hypothesized that they are unable to ignore altered environmental conditions and therefore select a motor response based on the altered environmental cues. The SOT requires sophisticated force plate systems that provide a way to challenge and alter information sent to the various sensory systems. While the aforementioned studies suggest that force platform sway measures provide valuable information in making return-to-play decisions following concussion, there is still a question of practicality and accessibility for the sports medicine clinician. In an attempt to provide a more cost-effective, yet quantifiable method of assessing balance in athletes, the Balance Error Scoring System (BESS) was developed by researchers at the University of North Carolina. This clinical balance test can be administered on the sideline (Guskiewicz, 2001). In the absence of sophisticated force plate technology, the use of a quantifiable clinical test battery such as the BESS is recommended. Three different stances (double, single, and tandem) are completed twice, once while on a firm surface and once while on piece of medium-density foam (Airex Balance Pad 81000; for a total of six trials (Fig. 1). Athletes are asked to assume the required stance by placing their hands on the iliac crests, and that upon eye closure the 20-sec test begins. During the single leg stances, subjects are asked to maintain the contralateral limb in 20–308 of hip flexion and 40–508 of knee flexion. The singlelimb stance tests are performed on the non-dominant foot. This same foot is placed towards the rear on the tandem stances. Subjects are told that upon losing their balance, they are to make any necessary adjustments and return to the starting position as quickly as possible. Performance is scored by adding one error point for each error committed (Table 1).



FIG. 1. Balance Error Scoring System (BESS) performed on the firm surface (A–C) and the foam surface (D–F).

Trials are considered to be incomplete if the athlete is unable to sustain the stance position for longer than 5 sec during the entire 20-sec testing period. These trials are assigned a standard maximum error score of 10. Significant correlations between the BESS and force platform sway measures using healthy young adults have been established for five static balance tests (single leg stance-firm surface, tandem stance-firm surface, double leg stance-foam surface, single leg stance-foam surface, and tandem stancefoam surface), with intertester reliability coefficients ranging from .78 to .96 (Riemann et al., 1999). Another study using the BESS identified the best test variations for eliciting postural unsteadiness following concussion. The SOT was also administered to determine if the results of the clinical balance tests paralleled results attained with a force plate system

(Riemann and Guskiewicz, 2000). Significant group differences on day 1 post-injury were revealed using the BESS with the double leg, single leg, and tandem stances on both a firm and foam surface. The results of the SOT composite scores paralleled the results revealed with the clinical balance tests, and were similar to recovery curves reported in previous investigations (Guskiewicz et al., 1996, 1997). Resolution of signs and symptoms recorded across the three post-injury testing sessions appear to coincide with the postural stability recoveries demonstrated by the mild-head-injured subjects. The results revealed greater differences between injured and uninjured subjects when the balance tasks became more challenging, such as by adding a foam surface and narrowing the base of support (Fig. 2). Although the standard Romberg test (double leg, firm surface) has been previously advocated for use in concussion assessment ( Jansen et al., 1982; Thyssen et al., 1982), it fails to objectively identify subtle balance deficits following concussion. Moreover, studies involving the BESS have revealed similar recovery curves (within 3–5 days post-injury) to those seen using sophisticated force plate technology. Currently new assessment paradigms including postural stability assessment in the presence of a cognitive task are being considered. One recent study using gait stability as a measure of posture suggested that concussed individuals may adopt a slower, more conservative gait strategy to maintain balance. Under these conditions, concussed individuals continued to exhibit signs of instability with large center-of-mass deviations that were greater in the presence of a cognitive task; these deviations were significantly greater than in controls under both the single-task and dual-task conditions (Catena et al., 2007). Broglio and associates (2005) studied healthy individuals under dual-task conditions, using only the eyes-opened conditions of the SOT, and found that postural control improved in healthy individuals with the addition of the cognitive task, as healthy individuals appear to be able to divide and focus attention as needed. These studies indicate the possibility of integration of dual tasking measures into the current assessment paradigm, as these measures more closely mimic the cognitive and postural demands of sport.

Table 1. Errors Recorded for Balance Error Scoring System (BESS) Hands lifted off iliac crests Opening eyes Step, stumble, or fall Moving hip into more than 308 of flexion or abduction Lifting forefoot or heel Remaining out of testing position for more than 5 seconds The BESS score is calculated by adding one error point for each error or any combination of errors occurring during one movement

FIG. 2. Error score means (standard deviation) for the three stances on both surfaces for 16 mild-head-injured (MHI) and 16 control subjects on day 1 post-injury (DL, double leg stance; SL, single leg stance; TD, tandem stance; FI, firm surface; FO, foam surface). There were no errors committed by the control group for the DL=FI and DL=FO tests (from Riemann and Guskiewicz, 2000, with permission).

ADVANCES IN SPORT CONCUSSION ASSESSMENT Postural stability assessment, whether done through the use of a force plate or a clinical balance test such as the BESS, is useful in identifying neurological impairment in athletes in the acute post-concussion phase. This impairment typically lasts up to 3–5 days post-injury, but in cases involving visual and vestibular dysfunction, the balance impairment may last weeks or months (Guskiewicz et al., 2001; McCrea et al., 2003). Clinicians should realize that postural stability is only one small piece of a very large puzzle in the assessment of concussion, and that concussion may not necessarily affect the postural control system in every case, nor is postural instability manifest in a consistent manner in every athlete. Paper and Pencil Neuropsychological Testing Clinician-administered neuropsychological assessment has been used to document the impact of concussive injuries for over 30 years and probably longer, as evidenced by Gronwall and Wrightson’s (1975) early work on multiple concussive injuries. In parallel with the initial clinical and empirical interest in sports concussion, which was first apparent in the late 1970s, neuropsychological tests were being used in many clinical research studies that focused on concussions secondary to falls, assaults, and motor vehicle accidents (Barth et al., 1983; Dikmen et al., 1995; Levin et al., 1987). Neuropsychological tests used in these studies were adapted from mainstream neuropsychological practice and typically involved extended testing, often using fixed or flexible batteries that indexed numerous cognitive skills such as intelligence, problem solving, and language, and attention-concentration and memory skills (Dikmen et al., 1995). As sports concussion research became more prevalent, the neuropsychological consequences of concussion became more clearly defined, which resulted in truncating the extensive testing typically used in non-sports populations and early sports concussion studies. The emphasis in sports concussion moved strongly toward assessment of attention, working memory, and information processing speed (Macciocchi et al., 1996), although some researchers continued to use more extensive test batteries (Lovell et al., 1999). At that time, as well as today, there are a large number of clinician-administered tests that can be used to document the impact of sports concussion. Table 2 reviews the psychometrics of a number of instruments that have been used in research and clinical practice, but these tests by no means exhaust the options clinicians and researchers have at their disposal when performing clinical examinations or planning research investigations (Lezak et al., 2004; Strauss et al., 2006). Psychometric characteristics of neuropsychological tests used with concussed athletes The psychometric characteristics of most neuropsychological tests used in sports concussion assessment and research have been examined at length in non-sports populations, but there are few studies that specifically address the reliability, standard error of measurement, practice effect sizes, sensitivity, specificity, and positive predictive value of clinicianadministered neuropsychological tests used in sports populations. While the lack of extensive psychometric data in sports populations may be a concern, clinician-administered pencil-and paper-tests typically have more extensively documented psychometrics than computerized tests (Broglio

2369 Table 2. Ranges of Reliability Coefficients, Standard Error of Measurement, and Practice Effect Sizes for Neuropsychological Tests Commonly Utilized in Concussion Research Test WCST TMT SDMT DST PASAT GPT COWAT HVLT



Practice effect size

.39–.72 .45–.72 .72–.80 .80–.91 .80–.90 .69–.78 .70–.88 .78

8.0–11.9 4.7–5.6 4.5–5.3 .90–.95 3.1–3.9 6.9–8.1 5.1–6.2 .95–2.1

.30–.1.0 .20–.73 .10–.20 .10–.45 .40–1.3 .10–.35 .30–.52 .24–.30

WCST, Wisconsin Card Sort Test; TMT, Trail Making Test; SDMT, Symbol Digit Modalities Test; DST, Digit Span Test; PASAT, Paced Auditory Serial Addition Test; GPT, Grooved Pegboard Test; COWAT, Controlled Oral Word Association Test; HVLT, Hopkins Verbal Learning Test; SEM, standard error of the mean. a Range of SEM based on lower and upper reliability coefficients and normative data for age-, education-, and gender-appropriate comparison groups. References used to gather data for this table: Spreen and Strauss, 1998; Mitrushina et al., 1999; Benedict et al., 1998; WAIS-III=WMS-III Technical Manual, 1997; Heaton et al., 1993; Smith, 1995; McCaffery et al., 2000.

et al., 2007c). The development of computerized tests was in part driven by the desire to increase the reliability and sensitivity of clinician-administered tests, although test developers’ claims of superior psychometrics and the promise of these instruments remains in doubt based on existing research (Broglio et al., 2007c; see below for a review of computerbased cognitive assessments). In any case, even though a number of clinician-administered neuropsychological tests have been employed in research, there is no consensus on what clinician-administered tests alone or in combination are best suited for diagnostic and return-to-play assessments. Issues with the administration of neuropsychological tests to an athletic population While clinician-administered neuropsychological tests are readily available, several problems associated with test application deserve mention. First, clinician-administered testing is labor intensive and requires resources such as trained examiners, which was a significant factor in the move toward computerized test administration over the past 10 years. Second, these tests must be interpreted, which means a neuropsychologist must provide decision rules for test interpretation of clinically meaningful changes, but establishing consistent decision rules is complicated. Changes in neuropsychological test scores over time may be due to factors other than concussion, such as learning problems and fatigue; somatic symptoms such as headache, depression, anxiety, and hyposomnia; and residual effects of alcohol intoxication and=or sub-optimal effort (Hunt et al., 2007). For instance, consider the base rate of headache immediately following concussion. Headache is one of the most common symptoms following concussion in sports (>80%) as well as in general clinical populations (Alves et al., 1993; Macciocchi et al., 1996). One can imagine how headache could affect sleep, which in turn could affect test performance up to several days following injury. One cannot assume that impaired performance on

2370 neuropsychological tests is due to transient impairment secondary to cerebral trauma when other factors such as headache may have a significant direct or indirect effect on test performance. Currently there are no scientifically validated algorithms for clinician-administered test interpretation, which means individual clinicians and researchers use idiosyncratic decision rules, which can lead to variability across individual athletes and research findings (Broglio et al., 2007c). Reliability issues also complicate one’s ability to assess the impact of sports concussion. On the one hand, tests need to be sufficiently reliable, while at the same time they are not so reliable that they are insensitive to the effects of concussion. For instance, tests with high reliability coefficients such as the Digit Span Test typically have low sensitivity. In contrast, the Trail Making Test (TMT) has relatively high sensitivity and has been widely used in clinical settings as well as in research investigations of sports concussion (Collins et al., 2002; Macciocchi et al., 1996; Matser et al., 1999). Unfortunately, the TMT has been shown to have test-retest reliability in the questionable range in some studies (.50–.60), and significant practice effects in others (Macciocchi et al., 1992; Spreen and Strauss, 1998). Reliability problems would be expected to impact sensitivity, specificity, and positive predictive value, all of which are important when using neuropsychological tests to identify and monitor post-concussive changes in cognition. An additional concern involves the susceptibility of neuropsychological instruments to practice effects. Although there is limited literature regarding practice effects, many measures used in studies of concussion have been found to have prominent practice effects (Macciocchi et al., 1992; Spreen and Strauss, 1998). In fact, some tests have practice effect sizes that equal or exceed effects of concussions on those same instruments (McCaffrey et al., 2000). In clinical practice, one solution for large practice effect sizes is the use of alternate forms of the same test, but the extent to which this strategy effectively reduces practice effects is questionable, particularly when tests are administered numerous times over a brief period (Macciocchi et al., 1996, 2001). An alternative approach employed by Hinton-Bayre and colleagues (1999) utilizes multiple pre-injury assessments in order to obtain maximal performance prior to injury, while limiting practice in subsequent post-injury assessments. In this approach, athletes are administered dependent measures several times prior to entering a study. Consequently, athletes’ optimal level of performance is reached prior to injury, and a decrement in performance following injury would reflect change from this optimal level. This methodology has considerable promise because changes in performance would theoretically reflect genuine impairment in neuropsychological functioning postinjury and not psychometric variability. However, a drawback that can limit the application of this strategy is the notable time allotment needed to gain an acceptable baseline assessment. Neuropsychological markers of post-concussion sequelae and recovery Given the documented pathophysiological response to sports concussion (Giza and Hovda, 2001; Jantzen et al., 2004), tests focused on sustained and divided attention, reaction time, visual and auditory processing speed, and working memory are most likely to be sensitive to the effects of con-

ELLEMBERG ET AL. cussion. In fact, the neuropsychological tests administered by clinicians that have been shown to be most sensitive to concussive injuries include the TMT, the Symbol Digit Modalities Test, and the Paced Auditory Serial Addition Test (Broglio et al., 2007c; Collins et al., 1999, 2002; Hinton-Bayre and Geffen, 2002; Pellman et al., 2004). However, the sensitivity and specificity of these instruments varies across studies and seems to some extent to be population-dependent. While many studies reveal a cognitive decrement in the hours and days following even a first concussion, there is no agreement on the duration of cognitive symptoms and the time course of recovery. A series of studies using paper-andpencil tests report that cognitive sequelae rarely persist beyond 2 weeks after a concussion (Echemendia et al., 2001; Guskiewicz, 2001; Macciocchi et al., 2001, 1998; Peterson et al., 2003). In addition to a pre-season baseline test, most protocols tested athletes up to five times during that short period. As noted earlier, despite the use of alternate versions, practice effects likely underestimate impairments caused by the concussion. In fact, some athletes actually perform significantly better during the last testing session than they did on their pre-concussion baseline (Belanger et al., 2005; Echemendia et al., 2001). In addition to a practice effect, some athletes might also have been motivated to perform exceptionally well given that in most protocols return-to-play decisions depended on their test results. When athletes (high school, college, and professional) are tested only once, even up to several months after a first concussion, persistent cognitive deficits are revealed (Downs and Abwender, 2002; Ellemberg et al., 2007; Matser et al., 1999, 1998; Witol and Webbe, 1994). For example, a recent study comparing intercollegiate female athletes suffering their first concussion to a group of agematched non-concussed teammates demonstrated enduring cognitive deficits at least up to 9 months following injury (Ellemberg et al., 2007). Cognitive deficits were apparent on tests that appraised high-level executive functions, such as planning, anticipating, and complex decision making. This suggests that the effects of sport-related concussion may be more enduring than once thought. Overall, clinician-administered tests have psychometric strengths and limitations. Despite 20 years of research on sports concussion, there is no consensus or guidelines on which tests provide clinicians and researchers with the most reliable, sensitive, and specific neuropsychological metrics. The advent of computerized tests has to some extent hindered the development of appropriate clinical decision rules for clinician-administered tests, but clinician-administered tests have been shown to be sensitive to the effects of sports concussion in a large number of studies. Whether these instruments will continue to be used and developed for sports concussion clinical practice and research remains to be seen. Computer Platform Neuropsychological Testing Presently, four computer-based neuropsychological assessments are available for sport concussion assessment: ImPACT (Pittsburgh, PA), Headminder Concussion Resolution Index (CRI) (New York, NY), CogSport (CogState, Melbourne, Australia), and the Automated Neuropsychological Assessment Metric (ANAM) (Center for the Study of Human Operator Performance, The University of Oklahoma, Norman, OK). The length of this review does not permit a detailed

ADVANCES IN SPORT CONCUSSION ASSESSMENT description of each test’s methodology, which have been provided elsewhere (Bleiberg et al., 2000; Erlanger et al., 2002; Iverson et al., 2005; Makdissi et al., 2001). Many of these tests were developed to alleviate problems associated with traditional pen-and-paper based testing, such as baseline administration time, learning effects associated with multiple post-injury assessments, and the need for specialized personnel to interpret results. These computer-based batteries employ multiple sub-tests that evaluate a range of cognitive domains, such as information processing, planning, memory, and switching mental set. Many also include an evaluation of symptoms associated with sport concussion, a review of which has been addressed in a different section of this article. The computer tests can be rapidly administered (20–25 min) to multiple athletes simultaneously, and several forms are available for post-morbid assessments to reduce learning effects, and interpretation of results is commonly automated for the clinical sports medicine staff. These improvements over pencil-and-paper tests have led to their adoption by sports medicine professionals as part of their assessment protocols at all levels of sports, from the intramural athlete through the professional (Ferrara et al., 2001; Notebaert and Guskiewicz, 2005). The computer-based assessments of cognitive performance have been evaluated for their ability to detect post-morbid decrements. For example, when a group of high school athletes was assessed within 3 days of injury, the ImPACT test correctly identified 81.9% of the concussed athletes as having some cognitive impairment or elevated symptom reports (Schatz et al., 2006). This level of sensitivity is slightly higher than that reported in a group of concussed collegiate athletes on the ImPACT (62.5% sensitivity) and the Headminder CRI (78.6% sensitivity), although concussion-related symptoms were not included in the evaluation process (Broglio et al., 2007c). Investigations of ANAM and CogSport sensitivity could not be found. The moderate sensitivity to post-concussion decrements is encouraging, but all athletes should be evaluated on a case-by-case basis. Variables such as previous history, psychological factors, genetics, and methodology appear to play a role in testing outcomes (McCrory et al., 2005b), but in general, computer-based testing shows declines in cognitive performance following injury, with a steady return to baseline in the subsequent days and weeks. Perhaps the most important factor in recovery time is the age of the athlete (Field et al., 2003). Establishing the functional recovery of cognition following concussion in the high school athlete is difficult because of developmental issues occurring in adolescents. Concussed athletes evaluated on the ANAM battery returned to normal functioning on all aspects of the test 1 week post-injury, except for memory, which resolved by day 10 (Sim et al., 2008). A series of investigations implementing the ImPACT test demonstrated impairment on verbal memory and reaction time relative to baseline in high school athletes when tested an average of 5 days post-concussion (Pellman et al., 2006). However, those with grade 1 injuries took a day longer to demonstrate full recovery on the same assessment battery (Lovell et al., 2004a), and a separate investigation found that concussed high school athletes continued to have composite memory impairments at 7 days post-injury (Lovell et al., 2003). Full recovery from sport concussion was apparent 35 days following concussion when concussed and control sub-

2371 jects performed comparably on a cognitive assessment (Lovell et al., 2007). Cognitive functioning in post-morbid young adults shows a similar recovery pattern as their younger counterparts. Evaluations completed within 48 h of sport concussion diagnosis revealed a decrease in the ANAM composite score in 55% of the sample (Guskiewicz et al., 2007c). Follow-up testing was not reported, although concussed military recruits returned to their baseline level of performance on all ANAM variables within 4 days of injury, with the exception of simple reaction time (Warden et al., 2001) Similar trends have been noted when the ImPACT test was implemented in the evaluation of concussed young adults. For example, cognition returned to baseline levels in those without a history of concussion within 5 days post-injury, while those with two or more previous injuries continued to show impaired performance on reaction time and verbal memory (Covassin et al., 2008). Further follow-up assessments were not completed, but separate investigations show prolonged impairment on the same variables when evaluated up to 10 days following diagnosis (Broglio et al., 2007b; Covassin et al., 2008). In all instances, additional test administrations were not given to determine if there was complete restoration of functional cognition. Only one investigation examining the functional recovery on computer-based neuropsychological assessments following sport concussion has been conducted with professional athletes. As part of the National Football League’s investigation of concussion, concussed professional athletes were evaluated the day following injury and again 3 days postinjury. When evaluated on the ImPACT test, the NFL athletes showed declines in verbal and visual memory, reaction time, and processing speed at the initial post-injury assessment, but scores returned to baseline levels by day 3 (Pellman et al., 2006). Figure 3 summarizes the recovery trends indicated by computer-based neuropsychological exams in some of the available studies. Some experts have suggested that the cognitive evaluation should serve as the cornerstone of the concussion assessment process (Aubry et al., 2002), and the rapid adoption and presence of computer-based cognitive evaluations suggests that they have become a key component of the concussion assessment battery. Regardless, surprisingly few studies have been carried out that track recovery in concussed athletes via computer-based assessments. While these tests provide

FIG. 3. Minimum days to recovery as indicated by computer-based neurocognitive assessment. The dotted line indicates the mean minimum recovery (5.9 days) for all settings.

2372 valuable information on the cognitive performance of the concussed athlete, they do not appear to accurately reflect the metabolic recovery of the injured brain. In the investigations reviewed here, athlete age appears to influence recovery, but most high school and collegiate athletes displayed functional cognitive recovery approximately 6 days following a sportrelated concussion, while the professional athlete displayed recovery within 3 days. This falls shy of the 14–28 days of impaired glucose metabolism (Giza and Hovda, 2001) and metabolic imbalance (Vagnozzi et al., 2008) reported in humans. This discrepancy may account for the increased concussion incidence seen when athletes are returned within the first 7–10 days of injury (Guskiewicz et al., 2003). Furthermore, many assessment paradigms call for multiple test administrations in the days following the concussion diagnosis. In one investigation concussed athletes were evaluated on seven occasions within a week of injury, with two assessments occurring within the first 3 h post-diagnosis (McCrea et al., 2003). Improvements on some computer paradigms have been noted in healthy athletes (Bleiberg et al., 2004), leading one to speculate that improvements in concussed athletes may be partially associated with learning effects and not with injury recovery. As such, unless mitigating circumstances are present, clinicians should consider delaying the administration of neuropsychological assessments for the purpose of determining return-to-play status until the athlete is symptom-free (Guskiewicz et al., 2004b). This review does not encompass all of the available literature on cognitive functioning in the concussed athlete. Additional investigations have been completed on the groups of interest examined here, but intramural and collegiate athletes were commonly pooled, thus preventing a separate evaluation of the two groups. It is clear, however, that the use of computer-based assessment for the clinical evaluation of cognitive functioning is well founded at all levels of sport. Some investigators have speculated that their use in the assessment process should be limited (Randolph et al., 2005), and others have shown that they may show state functioning, rather than trait cognitive performance (Broglio et al., 2007a). Regardless, the recovery patterns presented here are representative of group performance, necessitating an individualized approach to each athlete. Electrophysiological Measures The recording of electroencephalograms (EEGs) synchronized with a cognitive or perceptual task is a common research and clinical tool for the diagnosis and management of various brain pathologies, including epilepsy, multiple sclerosis, and the effects of premature birth and concussion (Magnano et al., 2006; Viggiano, 1996; Walls-Esquivel et al., 2007). These electrophysiological techniques assess the integrity of specific brain processes during the performance of cognitive tasks for which behavioral impairments are observed. The main feature of event-related potentials (ERPs) is that they reveal ongoing and covert processing that cannot be fully assessed by behavioral measures. In fact, it is the objectivity, reliability, and relative low cost of ERPs that now makes them a common clinical tool to assess brain injury. The potential benefits of ERPs for the investigation of sportrelated concussion has only been recently explored. Although young, this modality has already made a significant contri-

ELLEMBERG ET AL. bution to our understanding of sport-related concussion. The present section provides the first comparative analysis of this literature in order to highlight its main conclusions and provide a better understanding of its limits. We will systematically review evidence that ERPs are a sensitive measure of symptomatology, the cumulative effects of repeated concussions, and recovery. Post-concussion symptoms ERPs provide a sensitive measure of subtle functional neuronal damage when no clinical symptoms are reported by concussed athletes, and when the results on classical neuropsychological tests are normal. The strongest evidence for this comes from a study by Gosselin and colleagues (2006) that compared results from paper-and-pencil neuropsychological tests (a modified NFL battery; Lovell and Collins, 1998) to those of cognitive evoked potentials in a group of symptomatic concussed athletes, a group of asymptomatic concussed athletes, and a third group of athletes from a noncontact sport without a history of concussion. The concussed athletes were a mixed bag of football, soccer, and hockey players, and the majority of athletes in this group had suffered two or more concussions. The non-concussed athletes were either volleyball or tennis players. This is the only study in the ERP sports literature to include a control group consisting of athletes without a history of concussion that came from a non-contact sport. This is particularly important, as a significant portion of soccer and football players fail to recognize that they suffered symptoms associated with a concussion (Delaney et al., 2002). Compared to the two other groups, the self-reported symptomatic athletes had significantly higher scores on a post-concussion symptom scale. However, no difference was found between the symptomatic and asymptomatic athletes with regard to the total number of concussions sustained (i.e., three to five concussions), the severity of the last concussion, the time elapsed between testing and the last concussion (i.e., 5–15 weeks), and the number of episodes of LOC. Overall, the three groups of athletes had comparable results on the paperand-pencil neuropsychological tests as they did for the reaction time component of the computerized choice reaction time task associated with the ERP paradigm. In contrast, the concussed athletes had significantly lower amplitudes and longer latencies for the P3 component of the ERP compared to the control group, with no difference between the symptomatic and the asymptomatic athletes. In addition to finding abnormal ERPs in asymptomatic concussed athletes, Gosselin and associates (2006), as well as other researchers (Dupuis et al., 2000; Gaetz et al., 2000; Lavoie et al., 2004), found that the severity of self-reported clinical symptoms in the symptomatic athletes were negatively correlated with the amplitude of the P3 component. The ERP task used by Gosselin and colleagues was a modified version of the classical auditory oddball paradigm that was designed to have greater attentional requirements (2006). The oddball paradigm is the most widely used in the ERP literature. In its simplest form, it consists of a choice reaction time task during which the subject is asked to respond to an infrequent stimulus (presented in 10–25% of trials), and to ignore a frequent stimulus. The neurophysiological response associated with each stimulus is a waveform that ap-

ADVANCES IN SPORT CONCUSSION ASSESSMENT pears anytime between 250 and 600 msec after the presentation of the stimulus. This is known as the P3 component. The amplitude of the P3 is said to reflect the amount of attention allocated to the stimulus, while its latency reflects the processing speed associated with stimulus categorization (i.e., frequent versus infrequent stimulus). Two other sets of researchers also found a reduction in the amplitude of the P3 component in concussed athletes with otherwise normal results on neuropsychological tests (Dupuis et al., 2000; Lavoie et al., 2004). However in these cases, only the self-reported symptomatic athletes had abnormal ERPs. The ERPs of the asymptomatic concussed athletes were no different than those of non-concussed athletes who participated in the same contact sport (e.g., football). This different pattern of results could likely be explained by the lack of a control group from a non-contact sport, or because the oddball choice reaction time tasks used in those studies were visual rather than auditory and they had a weaker attentional load. Cumulative effects of multiple concussions ERPs have been used to investigate the possibility of cumulative damage that could result from a history of multiple concussions. The first study to use ERPs as a measure of brain damage in sport-related concussion (Gaetz et al., 2000) compared four groups of junior hockey players: athletes with no history of concussion; athletes who experienced one concussion; athletes who experienced two concussions; and athletes who experienced three or more concussions. The athletes from the injured groups had concussions of comparable severity, corresponding to a grade three concussion, and were tested at least 6 months post-injury. By means of a classical visual oddball task, a significant difference in the latency of the P3 component was found between the no-concussion group and the three-or-more-concussions group. Although not significant, the one- and two-concussions groups had longer P3 latencies than the non-concussion group, but shorter than those of the three-or-more-concussions group. Unfortunately, it is impossible to attribute the findings only to the cumulative effects of the concussions, as clinical symptoms and the time elapsed since the last concussion could also explain part of the results. First, it was reported that the three-or-moreconcussions group had significantly more clinical symptoms than the non-concussion group, while nothing is mentioned about the possibility of clinical symptoms in the one- and twoconcussions groups. Second, we do not know whether the time elapsed since the last concussion was comparable among the three injured groups. The authors only indicate that all participants were tested at least 6 months post-injury, and that the average post-injury period for the three-or-moreconcussions group was 13.2 months. A second study of the cumulative effects of concussions on ERPs controlled for the effect of symptomatology by including only concussed athletes who where asymptomatic (De Beaumont et al., 2007). Specifically, a group of asymptomatic athletes who suffered one concussion, a second group of asymptomatic athletes who experienced two or more concussions, and a third group who never experienced a concussion were tested with a modified visual oddball paradigm combined with a visual search task. The P3 component was significantly reduced for the multiple-concussion group com-

2373 pared to the single-concussion and non-concussed groups. However, this result could be explained at least in part by the important difference in the mean time elapsed between the last concussion and the testing, which was nearly twice as long for the single-concussed group than for the multipleconcussed group. In fact, no correlation between the reduction in P3 amplitude and the number of concussions was found, while there was a nearly significant correlation between time since the last concussion and the attenuation of the P3 component. Post-concussion recovery Although ERP studies provide evidence of neurofunctional deficits that persist at least up to 3 years post-concussion in asymptomatic athletes that suffered from multiple concussions (Broglio et al., 2009), no study has compared the acute and post-acute periods. The only ERP study to investigate the effect of the passage of time since injury is a single case report of an 8-year-old girl (Boutin et al., 2008). Specifically, the longitudinal assessment of the athlete, who suffered a concussion playing soccer, revealed neuropsychological impairments associated with attention at 24 h post-injury that resolved within 22 weeks. In contrast, visual evoked potentials and quantitative EEGs recorded 7 weeks pre-injury, and at 24 h and 7, 22, 32, and 55 weeks post-injury confirmed the presence of cortical impairments up to 1 year post-injury. The results from the spectral analysis of quantitative EEGs indicated an important increase in delta power and a reduction in beta and gamma power at 24 h post-injury. The greater delta activity suggests a reduction in the level of arousal immediately after the concussion, which resolves within 22 weeks. In contrast, the reduction in beta and gamma activity that persisted at 1 year after the concussion suggests that the cortical mechanisms underlying attention and information processing were impaired in this 8-year-old girl. These results are consistent with those of Gosselin and associates (2009), who reported an increase in delta and a reduction in alpha power in a group of concussed athletes who had otherwise normal results on a computerized neuropsychological battery. Taken together, the literature indicates that ERPs are a highly sensitive measure of subtle neurofunctional deficits not detectable by other behavioral methods. It is a non-invasive technique present in most clinical settings that can be rapidly administered. Some protocols can be completed in as little as 15–20 min. Another advantage of this measure is that it is not influenced by internal factors (i.e., downplaying or minimizing cognitive symptoms in order to remain in the game). It is also less affected by motivation and practice than paper-andpencil or computerized neuropsychological tests. Further research is needed to identify the most sensitive ERP paradigm and to create a standardized procedure for clinical testing. Different behavioral tasks have been associated with the online measurement of EEGs to study sportsrelated concussion. Specifically, a visual search paradigm (De Beaumont et al., 2007), a visual stimulus paring paradigm (Gaetz et al., 2000), visual oddball paradigms of varying difficulty (Broglio et al., 2009; Dupuis et al., 2000; Gaetz et al., 2000; Lavoie et al., 2004), and a difficult auditory oddball paradigm (Gosselin et al., 2006) have all been used. Despite important differences in the subject characteristics among the

2374 different studies, there is evidence that tasks with the highest cognitive load are most sensitive to the effects of sport-related concussion. Of the four tasks used to assess asymptomatic athletes, the two with the highest level of difficulty found deficits in these athletes (Broglio et al., 2009; Gosselin et al., 2006), while those with the easier tasks did not detect any problems (Dupuis et al., 2000; Lavoie et al., 2004). Future studies will also need to investigate recovery from sport-related concussion by obtaining a pre-season baseline and repeat measurements up to several years post-injury. Although ERPs are not as perturbed by practice effects as are neuropsychological tests, ERP amplitude is known to be reduced by repeated experience with the same task (Guillaume et al., 2009; Prinzel et al., 2003; Sambeth et al., 2004). The main advantage of the spectral analysis of EEG activity for studying recovery after a sport-related concussion is that because it is not paired with a cognitive task, it is not affected by the practice effects associated with repeated testing. This procedure, which takes as little as 2 min, can easily be added to the ERP paradigm. Neuroimaging Techniques Neuroimaging represents a unique means of discovering the pathophysiological mechanisms and biomarkers that characterize sport concussion. To date, however, the contribution of neuroimaging to the understanding of sports concussion are inconsistent, owing mostly to rapid changes in imaging technology, heterogenous research populations, and a lack of information about the acute post-concussion phase. The following section details the major imaging techniques used in clinical and research practice and their contributions to understanding sport concussion. Anatomical imaging Computed tomography (CT) and magnetic resonance imaging (MRI) can provide information about anatomical and gross structural changes following a concussion. CT is an x-ray-dependent technique that constructs a 3-D image of the brain. Clinically, CT scans can reveal brain lesions, contusions, fractures, and intracranial hemorrhaging. They are widely used in the management of closed-head injuries, particularly within the first 24 h post-injury, though it is generally only specified in cases for which there has been LOC (Livingston et al., 2000; Stein and Ross, 1992; Warren and Bailes, 1998), or persistent symptomatology (Rimal et al., 2007). Research on the utility of CT in sports concussion management is limited, as the only studies available focus on boxers. Though there are instances where lesions are detected, the majority of concussed athletes have negative CT findings with weak predictable outcome validity ( Jordan et al., 1992; Jordan and Zimmerman, 1988; Ross et al., 1987). The lack of consistent CT findings is quite common in the concussion literature as well (Gentry et al., 1988; Groswasser et al., 1987; Han et al., 1984; Newton et al., 1992; Zimmerman et al., 1986). A large study investigating the prevalence of lesions in concussion found that approximately only 16% of scans are positive (Iverson et al., 2000); moreover, patients with positive scans share some common characteristics, chief among them being the presence of intracranial abnormalities, LOC, skull fractures, and lower Glasgow Coma Scale (GCS) and Galveston Orientation and Amnesia Test scores. Though they are

ELLEMBERG ET AL. still used in clinical and emergency settings because of their relative cost effectiveness and wide availability (Toga and Mazziotta, 2002), CT scans have fallen out of favor, particularly in research, because of their limited ability to detect finite lesions and contusions, especially relative to MRI ( Jordan and Zimmerman, 1990; Newton et al., 1992; Snow et al., 1986). MRI is a more sensitive technique for investigating anatomical changes due to its higher resolution, its capacity to image different planes, and because it provides better distinction between tissue types: gray matter, white matter, and cerebrospinal fluid. Typical injuries detected by MRI resulting from sport concussion include small cortical contusions or subdural hematomas, and small white matter hemorrhages (Toga and Mazziotta, 2002), that are generally interpreted to be reflective of diffuse axonal injury (DAI) (Bazarian et al., 2006). Though more effective at detecting abnormalities than CT ( Jordan and Zimmerman, 1990; Newton et al., 1992), MRI has proven inconsistent with only moderate predictive validity in sports concussion ( Jordan and Zimmerman, 1990; Newton et al., 1992), and concussion in general (Barr, 2005; Bazarian et al., 2006; Toga and Mazziotta, 2002). Though its resolution is vastly improved over CT, MRI is still not able to detect lesions in all concussed athletes ( Jordan et al., 1992; Jordan and Zimmerman, 1990), limiting its clinical applicability. Moreover, CT and MRI are unable to provide information about functional alterations in brain function resulting from sports concussion. Diffusion tensor imaging (DTI) exploits differences in water movement through grey and white matter to create an image of the white matter neural pathways and their directionality. DTI’s main utility in neurology is detecting the presence of axonal injury (Toga and Mazziotta, 2002). There is increasing evidence to suggest that DAI is present in TBI and that the extent of the damage is related to the severity of the injury as defined by initial GCS score (Huisman et al., 2004). Similarly, Kraus and associates (2007) investigated TBI across the severity spectrum using DTI and found the degree of DAI to be related to the severity of the injury, with severe TBI patients exhibiting the greatest extent of damage. One of the few studies to focus on concussion found changes in white matter in the corpus callosum up to 5 years post-injury (Inglese et al., 2005). While it is important to note the persistence of injury after such a long period of time, there are very few studies documenting DAI in the acute post-injury phase in concussion; however, studies suggest that damage can be detected within the first week of injury (Miles et al., 2008; Wilde et al., 2008). Understanding DAI in the early phase is crucial to our understanding of how white matter changes over time after a concussion and could provide insight into rehabilitation and recovery. Functional imaging Functional MRI (fMRI) relies on the same principles as MRI, though instead of providing an anatomical picture based on hydrogen protons, it takes advantage of the magnetic properties of hemoglobin. While fMRI can track blood perfusion, the more common paradigm tracks blood oxygenation changes, for which the blood oxygenation leveldependent (BOLD) signal is detected (Toga and Mazziotta, 2002). It is assumed that increased blood flow to a given brain area is related to the cognitive processing inherent to the task

ADVANCES IN SPORT CONCUSSION ASSESSMENT and the subsequent increased metabolic demand. Following injury, decreases in blood flow are therefore speculated to represent an impaired functional capacity. Few studies have specifically targeted sports concussion using fMRI, but each reports dysfunction in concussed athletes (Chen et al., 2007, 2004, 2008b; Jantzen et al., 2004; Lovell et al., 2007). Chen and colleagues (2007, 2004, 2008b) reported functional deficits in working memory in concussed athletes that manifest as reduced activation in the dorsolateral prefrontal cortex, while Jantzen and colleagues (2004) noted an atypical BOLD response on a finger-tapping sequence in parietal and lateral frontal cortical areas. Furthermore, Chen and associates (2007, 2004, 2008b) found that the detectability of an atypical BOLD signal is directly related to the symptomatology experienced by the athlete. Though useful in understanding persistent symptomatology and its covariates (athletes were tested 1–14 months post-concussion), the focus of the studies by Chen and colleagues did not address the acute phase during which deficits, transient though they may be, are most commonly seen in concussed athletes. Lovell and colleagues (2007) scanned concussed athletes in the acute post-concussion phase (1 week post-concussion), and approximately 1 month after injury. Briefly, athletes who displayed hyperactivation on a cognitive task in the acute phase had prolonged recovery times relative to those athletes who demonstrated typical activation in the acute phase. The implication of the findings from Lovell and associates (2007), in concert with those of Chen and colleagues (2007, 2004, 2008b), is that atypical activation in the acute phase is related to recovery time. Though small in scope, the limited fMRI findings in sports concussion are in agreement with those of the other concussion literature (McAllister et al., 1999, 2001a, 2001b), underscoring the link between symptomatology and corresponding changes in functional brain activation. Positron emission tomography (PET) constructs a highly sensitive functional 3-D image of the brain from the emissions of a radio isotope and can directly detect blood flow as well as glucose and oxygen metabolism in the brain. The majority of PET studies have focused on non-sports-related concussion patients with persistent symptomatology, and found that frontotemporal areas are the most consistently impaired regions (Chen et al., 2003; Gross et al., 1996; Ruff et al., 1994; Umile et al., 2002; Varney et al., 2001). Unfortunately, all of these studies were conducted with patients well after the acute injury phase. PET appears to offer reasonable correlation with neuropsychological deficits, but it is difficult to extrapolate these findings to what is seen in the acute phase in sports concussion. Those people who remain diagnostically symptomatic well after suffering an concussion represent a very small portion of the population (3–5%) (McCrea, 2008), and as such may not be the best group upon whom to base conclusions. To our knowledge there have been no PET studies that have focused on sports concussion. This general absence of data makes it difficult to assess the efficacy of PET in concussion diagnosis and management in general, let alone how it pertains to sports concussion research in particular. Metabolic imaging Single-photon emission computed tomography (SPECT) provides information about changes in cerebral blood perfu-

2375 sion following a concussion. SPECT works similarly to PET, as an intravenously injected radioactive ligand accumulates in different brain areas in proportion to the delivery of nutrients to provide an overall picture of regional cerebral blood flow (rCBF) (Toga and Mazziotta, 2002). With respect to concussion, changes in rCBF are moderately correlated with clinical outcome (Bonne et al., 2003; Hofman et al., 2001; Umile et al., 1998), but many of the SPECT studies suffer from the same limitations as the PET research. Most of the studies are carried out in patients with persistent symptomatology at various time points after injury, with a wide range in cause of injury. Despite the variability in participant populations, most SPECT studies find focal hypoperfusion in frontal and temporal cortical areas, as well as in thalamic-basal ganglia areas (Abdel-Dayem et al., 1998, 2000, 1999; Bergsneider et al., 1997; Bonne et al., 2003; Korn et al., 2005; Umile et al., 1998). Magnetic resonance spectroscopy (MRS) images the chemical composition of living tissue. Several compounds can be imaged with MRS, chief among them being creatine, a general energy marker; choline, a marker of neuronal damage and membrane turnover; and N-acetyl aspartate (NAA), a marker of neuronal integrity. MRS is thus able to detect neuronal damage and changes in the chemical make-up of neurons. It is particularly useful in corroborating evidence of DAI as detected using DTI, because damage-related changes to neurons are manifest not only in their physical structure, but also in their composition (Toga and Mazziotta, 2002). In the only two sports-concussion studies, a decrease in NAA was reported, suggesting that there is indeed structural damage in sports concussions despite the negative findings of more traditional imaging techniques (Cimatti, 2006; Vagnozzi et al., 2008). Studies outside of the sports literature have also demonstrated abnormalities in individuals with concussion with otherwise normal-appearing MR scans (Babikian et al., 2006; Govindaraju et al., 2004; Holshouser et al., 2006; Kirov et al., 2007; Shutter et al., 2006). Significantly depressed concentrations of NAA have been measured in concussion despite normal findings on conventional MRI (Cecil et al., 1998; Garnett et al., 2000b), with the greatest reductions seen in injury-prone brain tissues, which typically include frontal areas and grey-white matter junctions. In contrast, levels of myo-inositol were shown to be augmented in concussion (Garnett et al., 2000a). This provides yet another indication of cellular injury, as higher concentrations of this intracellular compound are associated with glial proliferation (Friedman et al., 1998). Though the MRS research is burgeoning and encouraging, more studies in which sports concussion is the focus must be conducted before any conclusions can be made regarding the athlete population. In summary, though neuroimaging has grown in importance in understanding sports concussion, there are certainly more questions than answers at this point. This knowledge gap should not be seen as a weakness of the tools, but rather a testament to the difficulties associated with understanding sports concussion and its sequelae. Questions that lie beyond the anatomical and rest at a cellular level are crucial to our understanding of sports concussions, and as neuroimaging’s precision improves, those questions will be elucidated. Indeed, even as CT and MRI do not detect anatomical changes, other functional techniques including fMRI, PET, and SPECT, are yielding modest results, whereas newer techniques like DTI and MRS have yet to display their full potential in aiding

2376 our understanding of the changes in the concussed athlete’s brain. Discussion There is no dispute that sport-related concussion has immediate consequences for brain function. In the hours and days following injury, concussed athletes have marked decrements in certain aspects of cognitive functioning and postural stability, and they report associated symptoms of headache, dizziness, and confusion. Most studies suggest that athletes return to normal within 1–2 weeks post-injury, as performance on neuropsychological tests returns to baseline within 5–10 days (Lovell et al., 2004b; Sim et al., 2008), deficits in postural stability resolve within 3–5 days (Guskiewicz, 2001), and symptoms dissipate within 3–10 days (Broglio et al., 2007b; Collie et al., 2006; Macciocchi et al., 2001). In contrast, recent evidence from brain imaging studies shows abnormalities in the electrical responses (Gaetz et al., 2000; Gosselin et al., 2006), metabolic balance (Cimatti, 2006; Vagnozzi et al., 2008), and oxygen consumption (Chen et al., 2004; Jantzen et al., 2004) of neurons that persist for several months after the injury. These results are not all that surprising, considering the evidence found of persisting neuropsychological deficits for high-level executive functions in athletes without prior experience with cognitive testing (Downs and Abwender, 2002; Ellemberg et al., 2007), and given the evidence of cognitive impairment in retired professional athletes with a history of sport concussion (Guskiewicz et al., 2005, 2007a). There are possibly two explanations for the discrepancy regarding the findings of post-concussion recovery. As noted previously, the sensitivity of neuropsychological tests is likely reduced by repeated testing within a short period of time (Bleiberg et al., 2004). It is also possible that the pressure associated with athletic performance motivates some individuals to minimize their symptoms or altogether deny their presence (McCrea et al., 2004). Including an objective measure of postural stability increases the sensitivity of the return-toplay decision-making process, and minimizes the consequences of mitigating factors (e.g., practice effects and motivation) on neuropsychological test results. This is consistent with findings indicating that symptom severity, cognitive function, and postural stability do not appear to be related or affected to the same degree after a concussion (Broglio et al., 2007c; Ross et al., 2000). A second possibility, although more speculative, is that recovery takes place in two phases. First, a rapid functional recovery occurs, in which compensatory mechanisms such as the adoption of new strategies and=or functional reorganization via brain plasticity allows the athlete to perform normally on standard clinical assessments. This could be followed by a more prolonged neuronal recovery period, during which subtle deficits in cognitive functioning are present, but are not apparent using standard clinical concussion assessment tools. Athletic trainers and other clinicians need readily accessible, inexpensive, and rapidly administered tests to allow them to make return-to-play decisions that are sensitive enough to protect both the short- and long-term health of the athlete. However, the various assessment tools presented in this article are certainly complementary, as each contributes a different piece of the concussion assessment puzzle. Symptom reporting should first be privileged. Although computerized

ELLEMBERG ET AL. neuropsychological tests have been especially designed for multiple testing during the acute post-concussive phase, it is advantageous to preserve their sensitivity by using them parsimoniously, when other measures are no longer informative. As noted earlier, symptoms like headache, hyposomnia, and depression, which are known to be associated with concussion, can disrupt cognitive performance (Chen et al., 2008a; Guskiewicz et al., 2007b; Hunt et al., 2007). If no symptoms are reported, or when they are no longer reported, athletic trainers and clinicians could turn to the assessment of postural stability using the BESS. The computerized neuropsychological assessment should be considered only when athletes do not report symptoms at rest and under stress, and when they have normal results on the BESS (Guskiewicz et al., 2004a). When used in combination, symptom assessment, balance assessment, and neuropsychological testing provide a sensitivity of over 90% for the identification of concussion (Broglio et al., 2007c). Although there are currently several published sets of return-to-play guidelines, none has been validated, and not all are supported by clinical assessment data (McCrory et al., 2005a). Furthermore, there are no guidelines or recommendations regarding when an athlete should retire from sports. It should also be noted that no universal diagnostic or returnto-play protocol can be applied to all athletes or under all circumstances. For instance, recent work suggests that immediate outcome is worse and recovery longer following concussion in younger athletes (Boutin et al., 2008; Lovell et al., 2003), and in female compared to male athletes (Broshek et al., 2005; Covassin et al., 2007; Ellemberg et al., 2007). Also, although more research is required, it appears likely that the nature of the biomechanical forces exerted during impact influences the severity of the concussion (Ommaya and Gennarelli, 1974; Pellman et al., 2003). Factors like diet, exercise, metabolic dysfunction, and individual characteristics also appear to influence recovery (Fox et al., 2008; Makdissi et al., 2009; Slobounov et al., 2007; Vagnozzi et al., 2008). To date most of the concussion work has focused on adult athletes, and more research is required to determine factors and population characteristics that influence concussion severity and recovery, as well as the sensitivity of the assessment protocol and return-to-play guidelines. Although tremendous strides have been made in concussion assessment in the last two decades, there remain many questions left unanswered. Future research efforts using metabolic and functional brain imaging, as well as human electrophysiology, are needed to clarify the time course of acute functional recovery and of neuronal recovery. Future research using these measures should also be done under conditions of cognitive (e.g., dual-task performance) or physical effort. The consequences of multiple concussions and the effect of timing between subsequent concussions also need to be documented. Furthermore, it will be important to verify if there is a relationship between changes in functional neurochemistry and neuroelectric responses, and symptom reporting, postural stability, and cognitive function in the immediate post-concussion phase. Brain imaging could also be used to compare the effectiveness of various return-to-play protocols. Finally, a better understanding of the neurophysiological and neurometabolic changes associated with sport concussion and their mechanisms of recovery could eventually guide research on potential pharmacological treatments.

ADVANCES IN SPORT CONCUSSION ASSESSMENT Author Disclosure Statement No conflicting financial interests exist. References Abdel-Dayem, H.M., Abu-Judeh, H., Kumar, M., Atay, S., Naddaf, S., El-Zeftawy, H., and Luo, J.Q. (1998). SPECT brain perfusion abnormalities in mild or moderate traumatic brain injury. Clin. Nucl. Med. 23, 309–317. Abu-Judeh, H.H., Parker, R., Aleksic, S., Singh, M.L., Naddaf, S., Atay, S., Kumar, M., Omar, W., El-Zeftawy, H., Luo, J.Q., and Abdel-Dayem, H.M. (2000). SPECT brain perfusion findings in mild or moderate traumatic brain injury. Nucl. Med. Rev. Cent. East. Eur. 3, 5–11. Abu-Judeh, H.H., Parker, R., Singh, M., el-Zeftawy, H., Atay, S., Kumar, M., Naddaf, S., Aleksic, S., and Abdel-Dayem, H.M. (1999). SPET brain perfusion imaging in mild traumatic brain injury without loss of consciousness and normal computed tomography. Nucl. Med. Commun. 20, 505–510. Alves, W., Macciocchi, S.N., and Barth, J.T. (1993). Post concussive symptoms following uncomplicated mild head injury. J. Head Trauma Rehabil. 8, 48–59. American Psychiatric Association. (2000). Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision. American Psychiatric Association: Washington D.C. Arcan, M., Brull, M.A., Najenson, T., and Solzi, P. (1977). FGP assessment of postural disorders during the process of rehabilitation. Scand. J. Rehabil. Med. 9, 165–168. Aubry, M., Cantu, R., Dvorak, J., Graf-Baumann, T., Johnston, K., Kelly, J., Lovell, M., McCrory, P., Meeuwisse, W., and Schamasch, P. (2002). Summary and agreement statement of the First International Conference on Concussion in Sport, Vienna 2001. Recommendations for the improvement of safety and health of athletes who may suffer concussive injuries. Br. J. Sports Med. 36, 6–10. Babikian, T., Freier, M.C., Ashwal, S., Riggs, M.L., Burley, T., and Holshouser, B.A. (2006). MR spectroscopy: predicting long-term neuropsychological outcome following pediatric TBI. J. Magn. Reson. Imaging. 24, 801–811. Barr, M. (2005). The Human Nervous System: An Anatomical Viewpoint, 8th ed. Lippincott Williams & Wilkins: Baltimore. Barth, J.T., Macciocchi, S.N., Giordani, B., Rimel, R., Jane, J.A., and Boll, T.J. (1983). Neuropsychological sequelae of minor head injury. Neurosurgery 13, 529–533. Bazarian, J.J., Blyth, B., and Cimpello, L. (2006). Bench to bedside: evidence for brain injury after concussion—looking beyond the computed tomography scan. Acad. Emerg. Med. 13, 199–214. Belanger, H.G., Curtiss, G., Demery, J.A., Lebowitz, B.K., and Vanderploeg, R.D. (2005). Factors moderating neuropsychological outcomes following mild traumatic brain injury: a meta-analysis. J. Int. Neuropsychological Soc. 11, 215–227. Benedict, R.H.B., Schretlen, D., Groninger, L., and Brandt, J. (1998). Hopkins Verbal Learning Test-Revised: Normative data and analysis of inter-form and test-retest reliability. Clin. Neuropsychol. 12, 43–55. Bergsneider, M., Hovda, D.A., Shalmon, E., Kelly, D.F., Vespa, P.M., Martin, N.A., et al. (1997). Cerebral hyperglycolysis following severe traumatic brain injury in humans: a positron emission tomography study. J. Neurosurg. 86, 241–251. Bleiberg, J., Cernich, A.N., Cameron, K., Sun, W., Peck, K., Ecklund, P.J., Reeves, D., Uhorchak, J., Sparling, M.B., and Warden, D.L. (2004). Duration of cognitive impairment after sports concussion. Neurosurgery 4, 1073–1078.

2377 Bleiberg, J., Kane, R.L., Reeves, D.L., Garmoe, W.S., and Halpern, E. (2000). Factor analysis of computerized and traditional tests used in mild brain injury research. Clin. Neuropsychol. 14, 287–294. Bonne, O., Gilboa, A., Louzoun, Y., Kempf-Sherf, O., Katz, M., Fishman, Y., Ben-Nahum, Z., Krausz, Y., Bocher, M., Lester, H., Chisin, R., and Lerer, B. (2003). Cerebral blood flow in chronic symptomatic mild traumatic brain injury. Psychiatry Res. 124, 141–152. Boutin, D., Lassonde, M., Robert, M., Vanassing, P., and Ellemberg, D. (2008). Neurophysiological assessment prior to and following sports-related concussion during childhood: a case study. Neurocase 14, 239–248. Broglio, S.P., and Puetz, T.W. (2008). The effect of sport concussion on neurocognitive function, self-report symptoms and postural control : a meta-analysis. Sports Med. 38, 53–67. Broglio, S.P., Ferrara, M.S., Macciocchi, S.N., Baumgartner, T.A., and Elliott, R. (2007a). Test-retest reliability of computerized concussion assessment programs. J. Athl. Train. 42, 509– 514. Broglio, S.P., Macciocchi, S.N., and Ferrara, M.S. (2007b). Neurocognitive performance of concussed athletes when symptom free. J. Athl. Train. 42, 504–508. Broglio, S.P., Macciocchi, S.N., and Ferrara, M.S. (2007c). Sensitivity of the concussion assessment battery. Neurosurgery 60, 1050–1057; discussion 1057–1058. Broglio, S.P., Pontifex, M.B., O’Connor, P., and Hillman, C.H. (2009). The persistent effects of concussion on neuroelectic indices of attention. J. Neurotrauma, 26, 1463–1470. Broglio, S.P., Tomporowski, P.D., and Ferrara, M.S. (2005). Balance performance with a cognitive task: a dual-task testing paradigm. Med. Sci. Sports Exerc. 37, 689–695. Broshek, D.K., Kaushik, T., Freeman, J.R., Erlanger, D., Webbe, F., and Barth, J.T. (2005). Sex differences in outcome following sports-related concussion. J. Neurosurg. 102, 856–863. Cantu, R.C. (1995). Second impact syndrome: A risk in any contact sport. Phys. Sportsmed. 38, 53–67. Catena, R.D., van Donkelaar, P., and Chou, L.S. (2007). Cognitive task effects on gait stability following concussion. Exp. Brain Res. 176, 23–31. Cecil, K.M., Lenkinski, R.E., Meaney, D.F., McIntosh, T.K., and Smith, D.H. (1998). High-field proton magnetic resonance spectroscopy of a swine model for axonal injury. J. Neurochem. 70, 2038–2044. Chen, J.K., Johnston, K.M., Collie, A., McCrory, P., and Ptito, A. (2007). A validation of the post concussion symptom scale in the assessment of complex concussion using cognitive testing and functional MRI. J. Neurol. Neurosurg. Psychiatry 78, 1231–1238. Chen, J.K., Johnston, K.M., Frey, S., Petrides, M., Worsley, K., and Ptito, A. (2004). Functional abnormalities in symptomatic concussed athletes: an fMRI study. Neuroimage 22, 68–82. Chen, J.-K., Johnston, K.M., Petrides, M., and Ptito, A. (2008a). Neural substrates of symptoms of depression following concussion in male athletes with persisting postconcussion symptoms. Arch. Gen. Psychiatry 65, 81–89. Chen, J.K., Johnston, K.M., Petrides, M., and Ptito, A. (2008b). Neural substrates of symptoms of depression following concussion in male athletes with persisting postconcussion symptoms. Arch. Gen. Psychiatry 65, 81–89. Chen, S.H., Kareken, D.A., Fastenau, P.S., Trexler, L.E., and Hutchins, G.D. (2003). A study of persistent post-concussion symptoms in mild head trauma using positron emission tomography. J. Neurol. Neurosurg. Psychiatry 74, 326–332.

2378 Cimatti, M. (2006). Assessment of metabolic cerebral damage using proton magnetic resonance spectroscopy in mild traumatic brain injury. J. Neurosurg. Sci. 50, 83–88. Collie, A., Makdissi, M., Maruff, P., Bennell, K., and McCrory, P. (2006). Cognition in the days following concussion: comparison of symptomatic versus asymptomatic athletes. J. Neurosurg. Psychiatry 77, 241–245. Collins, M.W., Grindel, S.H., Lovell, M.R., Dede, D.E., Moser, D.J., Phalin, B.R., Nogle, S., Wasik, M., Cordry, D., Daugherty, K.M., Sears, S.F., Nicolette, G., Indelicato, P., and McKeag, D.B. (1999). Relationship between concussion and neuropsychological performance in college football players. JAMA 282, 964–970. Collins, M.W., Iverson, G.L., Lovell, M.R., McKeag, D.B., Norwig, J., and Maroon, J. (2003). On-field predictors of neuropsychological and symptom deficit following sports-related concussion. Clin. J. Sport Med. 13, 222–229. Collins, M.W., Lovell, M.R., Iverson, G.L., Cantu, R.C., Maroon, J.C., and Field, M. (2002). Cumulative effects of concussion in high school athletes. Neurosurgery 51, 1175–1179; discussion 1180–1171. Covassin, T., Schatz, P., and Swanik, C.B. (2007). Sex differences in neuropsychological function and post-concussion symptoms of concussed collegiate athletes. Neurosurgery 61, 345–350. Covassin, T., Stearne, D., and Elbin, R. (2008). Concussion history and postconcussion neurocognitive performance and symptoms in collegiate athletes. J. Athl. Train. 43, 119–124. Covassin, T., Swanik, C.B., and Sachs, M.L. (2003). Sex differences and the incidence of concussions among collegiate athletes. J. Athl. Train. 38, 238–244. De Beaumont, L., Brisson, B., Lassonde, M., and Jolicoeur, P. (2007). Long-term electrophysiological changes in athletes with a history of multiple concussions. Brain Inj. 21, 631–644. Delaney, J.S., Lacroix, V.J., Leclerc, S., and Johnston, K.M. (2002). Concussions among university football and soccer players. Clin. J. Sport Med. 12, 331–338. Dikmen, S.S., Machamer, J.E., Winn, H.R., and Temkin, N.R. (1995). Neuropsychological outcome at 1-year post head injury. Neuropsychology 59, 80–90. Downs, D.S., and Abwender, D. (2002). Neuropsychological impairments in soccer athletes. J. Sports Med. Phys. Fitness 42, 103–107. Dupuis, F., Johnston, K.M., Lavoie, M., Lepore, F., and Lassonde, M. (2000). Concussions in athletes produce brain dysfunction as revealed by event-related potentials. Neuroreport 11, 4087–4092. Echemendia, R.J., Putukian, M., Mackin, R.S., Julian, L., and Shoss, N. (2001). Neuropsychological test performance prior to and following sports-related mild traumatic brain injury. Clin. J. Sport Med. 11, 23–31. Ellemberg, D., Leclerc, S., Couture, S., and Daigle, C. (2007). Prolonged neuropsychological impairments following a first concussion in female university soccer athletes. Clin. J. Sport Med. 17, 369–374. Erlanger, D., Kaushik, T., Cantu, R., Barth, J.T., Broshek, D.K., Freeman, J.R., and Webbe, F.M. (2003). Symptom-based assessment of the severity of a concussion. J. Neurosurg. 98, 477–484. Erlanger, D.M., Kaushik, T., Broshek, D., Freeman, J., Feldman, D., and Festa, J. (2002). Development and validation of a webbased screening tool for monitoring cognitive status. J. Head Trauma Rehabil. 17, 458–476. Farace, E., and Alves, W.M. (2000). Do women fare worse: a metaanalysis of gender differences in traumatic brain injury outcome. J. Neurosurg. 93, 539–545.

ELLEMBERG ET AL. Fazio, V.C., Lovell, M.R., Pardini, J.E., and Collins, M.W. (2007). The relation between post concussion symptoms and neurocognitive performance in concussed athletes. NeuroRehabilitation 22, 207–216. Ferrara, M.S., McCrea, M., Peterson, C.L., and Guskiewicz, K.M. (2001). A survey of practice patterns in concussion assessment and management. J. Athl. Train. 36, 145–149. Field, M., Collins, M.W., Lovell, M.R., and Maroon, J. (2003). Does age play a role in recovery from sports-related concussion? A comparison of high school and collegiate athletes. J. Pediatr. 142, 546–553. Fox, Z.G., Mihalik, J.P., Blackburn, J.T., Battaglini, C.L., and Guskiewicz, K.M. (2008). Return of postural control to baseline after anaerobic and aerobic exercise protocols. J. Athl. Train. 43, 456–463. Friedman, S.D., Brooks, W.M., Jung, R.E., Hart, B.L., and Yeo, R.A. (1998). Proton MR spectroscopic findings correspond to neuropsychological function in traumatic brain injury. A.J.N.R. Am. J. Neuroradiol. 19, 1879–1885. Gaetz, M., Goodman, D., and Weinberg, H. (2000). Electrophysiological evidence for the cumulative effects of concussion. Brain Inj. 14, 1077–1088. Garnett, M.R., Blamire, A.M., Corkill, R.G., Cadoux-Hudson, T.A., Rajagopalan, B., and Styles, P. (2000a). Early proton magnetic resonance spectroscopy in normal-appearing brain correlates with outcome in patients following traumatic brain injury. Brain 123, 2046–2054. Garnett, M.R., Blamire, A.M., Rajagopalan, B., Styles, P., and Cadoux-Hudson, T.A. (2000b). Evidence for cellular damage in normal-appearing white matter correlates with injury severity in patients following traumatic brain injury: A magnetic resonance spectroscopy study. Brain 123, 1403–1409. Gentry, L.R., Godersky, J.C., Thompson, B., and Dunn, V.D. (1988). Prospective comparative study of intermediate-field MR and CT in the evaluation of closed head trauma. A.J.R. Am. J. Roentgenol. 150, 673–682. Geurts, A.C., Ribbers, G.M., Knoop, J.A., and van Limbeek, J. (1996). Identification of static and dynamic postural instability following traumatic brain injury. Arch. Phys. Med. Rehabil. 77, 639–644. Giza, C.C., and Hovda, D.A. (2001). The neurometabolic cascade of concussion. J. Athl. Train. 36, 228–235. Gosselin, N., Lassonde, M., Petit, D., Leclerc, S., Mongrain, V., Collie, A., and Montplaisir, J. (2009). Sleep following sportrelated concussions. Sleep Med. 10, 35–46. Gosselin, N., Theriault, M., Leclerc, S., Montplaisir, J., and Lassonde, M. (2006). Neurophysiological anomalies in symptomatic and asymptomatic concussed athletes. Neurosurgery 58, 1151–1161; discussion 1151—1161. Govindaraju, V., Gauger, G.E., Manley, G.T., Ebel, A., Meeker, M., and Maudsley, A.A. (2004). Volumetric proton spectroscopic imaging of mild traumatic brain injury. A.J.N.R. Am. J. Neuroradiol. 25, 730–737. Granito, V.J. (2002). Psychological response to athletic injury: Gender differences. Sports Behavior 25, 243–259. Gronwall, D., and Wrightson, P. (1975). Cumulative effect of concussion. Lancet 2, 995–997. Gross, H., Kling, A., Henry, G., Herndon, C., and Lavretsky, H. (1996). Local cerebral glucose metabolism in patients with long-term behavioral and cognitive deficits following mild traumatic brain injury. J. Neuropsychiatry Clin. Neurosci. 8, 324–334. Groswasser, Z., Reider-Groswasser, I., Soroker, N., and Machtey, Y. (1987). Magnetic resonance imaging in head injured

ADVANCES IN SPORT CONCUSSION ASSESSMENT patients with normal late computed tomography scans. Surg. Neurol. 27, 331–337. Guillaume, C., Guillery-Girard, B., Chaby, L., Lebreton, K., Hugueville, L., Eustache, F., and Fiori, N. (2009). The time course of repetition effects for familiar faces and objects: an ERP study. Brain Res. 1248, 149–161. Guskiewicz, K.M., Bruce, S.L., Cantu, R.C., Ferrara, M.S., Kelly, J.P., McCrea, M., Putukian, M., and McLeod, T.C. (2004a). Recommendations on management of sport-related concussion: summary of the National Athletic Trainers’ Association position statement. Neurosurgery 55, 891–895; discussion 896. Guskiewicz, K.M., Bruce, S.L., Cantu, R.C., Ferrara, M.S., Kelly, J.P., McCrea, M., Putukian, M., and Valovich McLeod, T.C. (2004b). National Athletic Trainers’ Association Position Statement: Management of sport-related concussion. J. Athl. Train. 39, 280–297. Guskiewicz, K.M., Marshall, S.W., Bailes, J., McCrea, M., Cantu, R.C., Randolph, C., and Jordan, B.D. (2005). Association between recurrent concussion and late-life cognitive impairment in retired professional football players. Neurosurgery 57, 719– 726; discussion 719–726. Guskiewicz, K.M., Marshall, S.W., Bailes, J., McCrea, M., Harding, H.P. Jr., Matthews, A., Mihalik, J.R., and Cantu, R.C. (2007a). Recurrent concussion and risk of depression in retired professional football players. Med. Sci. Sports Exerc. 39, 903– 909. Guskiewicz, K.M., Marshall, S.W., Bailes, J., McCrea, M., Harding, H.P.J., Matthews, A., Mihalik, J.R., and Cantu, R.C. (2007b). Recurrent concussion and risk of depression in retired professional football players. Med. Sci. Sports Exerc. 39, 903– 909. Guskiewicz, K.M., McCrea, M., Marshall, S.W., Cantu, R.C., Randolph, C., Barr, W., Onate, J.A., and Kelly, J.P. (2003). Cumulative effects associated with recurrent concussion in collegiate football players: the NCAA Concussion Study. JAMA 290, 2549–2555. Guskiewicz, K.M., Mihalik, J.P., Shankar, V., Marshall, S.W., Crowell, D.H., Oliaro, S.M., S.M., Ciocca, M.F., and Hooker, D.N. (2007c). Measurement of head impacts in collegiate football players: relationship between head impact biomechanics and acute clinical outcome after concussion. Neurosurgery 61, 1244–1252; discussion 1252–1243. Guskiewicz, K.M., Perrin, D.H., and Gansneder, B.M. (1996). Effect of mild head injury on postural stability in athletes. J. Athl. Train. 31, 300–306. Guskiewicz, K.M. (2001). Postural stability assessment following concussion: one piece of the puzzle. Clin. J. Sport Med. 11, 182–189. Guskiewicz, K.M., Riemann, B.L., Perrin, D.H., and Nashner, L.M. (1997). Alternative approaches to the assessment of mild head injury in athletes. Med. Sci. Sports Exerc. 29, S213–S221. Guskiewicz, K.M., Ross, S.E., and Marshall, S.W. (2001). Postural stability and neuropsychological deficits after concussion in collegiate athletes. J. Athl. Train. 36, 263–273. Guskiewicz, K.M., Weaver, N.L., Padua, D.A., and Garrett, W.E. Jr. (2000). Epidemiology of concussion in collegiate and high school football players. Am. J. Sports Med. 28, 643–650. Guyton, A. (1986). Textbook of Medical Physiology. W.B. Saunders Co.: Philadelphia. Han, J.S., Kaufman, B., Alfidi, R.J., Yeung, H.N., Benson, J.E., Haaga, J.R., El Yousef, S.J., Clampitt, M.E., Bonstelle, C.T., and Huss, R. (1984). Head trauma evaluated by magnetic resonance and computed tomography: a comparison. Radiology 150, 71–77.

2379 Heaton, R.K., Chelune, G.J., Talley, J.L., Kay, G.G., and Curtiss, G. (1993). Wisconsin Card Sorting Test Manual: Revised and Expanded. Odessa, FL: Psychological Assessment Resources. Hinton-Bayre, A.D., and Geffen, G. (2002). Severity of sportsrelated concussion and neuropsychological test performance. Neurology 59, 1068–1070. Hinton-Bayre, A.D., Geffen, G.M., Geffen, L.B., McFarland, K.A., and Friis, P. (1999). Concussion in contact sports: reliable change indices of impairment and recovery. J. Clin. Exp. Neuropsychol. 21, 70–86. Hofman, P.A., Stapert, S.Z., van Kroonenburgh, M.J., Jolles, J., de Kruijk, J., and Wilmink, J.T. (2001). MR imaging, singlephoton emission CT, and neurocognitive performance after mild traumatic brain injury. A.J.N.R. Am. J. Neuroradiol. 22, 441–449. Holshouser, B.A., Tong, K.A., Ashwal, S., Oyoyo, U., Ghamsary, M., Saunders, D., and Shutter, L. (2006). Prospective longitudinal proton magnetic resonance spectroscopic imaging in adult traumatic brain injury. J. Magn. Reson. Imaging 24, 33–40. Huisman, T.A., Schwamm, L.H., Schaefer, P.W., Koroshetz, W.J., Shetty-Alva, N., Ozsunar, Y., Wu, O., and Sorensen, A.G. (2004). Diffusion tensor imaging as potential biomarker of white matter injury in diffuse axonal injury. A.J.N.R. Am. J. Neuroradiol. 25, 370–376. Hunt, T.N., Ferrara, M.S., Miller, L.S., and Macciocchi, S. (2007). The effect of effort on baseline neuropsychological test scores in high school football athletes. Arch. Clin. Neuropsychol 22, 615–621. Ingersoll, C.D., and Armstrong, C.W. (1992). The effects of closed-head injury on postural sway. Med. Sci. Sports Exerc. 24, 739–743. Inglese, M., Makani, S., Johnson, G., Cohen, B.A., Silver, J.A., Gonen, O., Silver, J.A., Gonen, O., and Grossman, R.I. (2005). Diffuse axonal injury in mild traumatic brain injury: a diffusion tensor imaging study. J. Neurosurg. 103, 298–303. Iverson, G.L., Lovell, M.R., and Collins, M.W. (2005). Validity of ImPACT for measuring processing speed following sportsrelated concussion. J. Clin. Exp. Neuropsychol. 27, 683–689. Iverson, G.L., Lovell, M.R., Smith, S., and Franzen, M.D. (2000). Prevalence of abnormal CT-scans following mild head injury. Brain Inj. 14, 1057–1061. Jacobs, J.V., and Horak, F.B. (2007). Cortical control of postural responses. J. Neural Transmission 114, 1339–1348. Jansen, E.C., Larsen, R.E., and Olesen, M.B. (1982). Quantitative Romberg’s test. Measurement and computer calculation of postural stability. Acta Neurol. Scand. 66, 93–99. Jantzen, K.J., Anderson, B., Steinberg, F.L., and Kelso, J.A. (2004). A prospective functional MR imaging study of mild traumatic brain injury in college football players. A.J.N.R. Am. J. Neuroradiol. 25, 738–745. Jordan, B.D., and Zimmerman, R.D. (1990). Computed tomography and magnetic resonance imaging comparisons in boxers. JAMA 263, 1670–1674. Jordan, B.D., and Zimmerman, R.D. (1988). Magnetic resonance imaging in amateur boxers. Arch. Neurol. 45, 1207–1208. Jordan, B.D., Jahre, C., Hauser, W.A., Zimmerman, R.D., Zarrelli, M., Lipsitz, E.C., Johnson, V., Warren, R.F., Tsairis, P., and Folk, F.S. (1992). CT of 338 active professional boxers. Radiology 185, 509–512. Kirov, I., Fleysher, L., Babb, J.S., Silver, J.M., Grossman, R.I., and Gonen, O. (2007). Characterizing ‘mild’ in traumatic brain injury with proton MR spectroscopy in the thalamus: Initial findings. Brain Inj. 21, 1147–1154.

2380 Kissick, J., and Johnston, K.M. (2005). Return to play after concussion: principles and practice. Clin. J. Sport Med. 15, 426– 431. Korn, A., Golan, H., Melamed, I., Pascual-Marqui, R., and Friedman, A. (2005). Focal cortical dysfunction and bloodbrain barrier disruption in patients with postconcussion syndrome. J. Clin. Neurophysiol. 22, 1–9. Kraus, M.F., Susmaras, T., Caughlin, B.P., Walker, C.J., Sweeney, J.A., and Little, D.M. (2007). White matter integrity and cognition in chronic traumatic brain injury: a diffusion tensor imaging study. Brain 130, 2508–2519. Langlois, J.A., Rutland-Brown, W., and Wald, M.M. (2006). The epidemiology and impact of traumatic brain injury: a brief overview. J. Head Trauma Rehabil. 21, 375–378. Lavoie, M.E., Dupuis, F., Johnston, K.M., Leclerc, S., and Lassonde, M. (2004). Visual p300 effects beyond symptoms in concussed college athletes. J. Clin. Exp. Neuropsychol. 26, 55–73. Levin, H.S., Lippold, S.C., Goldman, A., Handel, S., High, W.M. Jr., Eisenberg, H.M., and Zelitt, D. (1987). Neurobehavioral functioning and magnetic resonance imaging findings in young boxers. J. Neurosurg. 67, 657–667. Lezak, M.D., Howieson, D.B., and Loring, D.W. (2004). Neuropsychological Assessment. Oxford University Press: New York. Livingston, D.H., Lavery, R.F., Passannante, M.R., Skurnick, J.H., Baker, S., Fabian, T.C., Fry, D.E., and Malangoni, M.A. (2000). Emergency department discharge of patients with a negative cranial computed tomography scan after minimal head injury. Ann. Surg. 232, 126–132. Lovell, M.R., and Collins, M.W. (1998). Neuropsychological assessment of the college football player. J. Head Trauma Rehab. 13, 9–29. Lovell, M.R., Collins, M., and Bradley, J. (2004a). Return to play following sports-related concussion. Clin. Sports Med. 23, 421–441, ix. Lovell, M.R., Collins, M.W., Iverson, G.L., Field, M., Maroon, J.C., Cantu, R., Podell, K., Powell, J.W., Belza, M., and Fu, F.H. (2003). Recovery from mild concussion in high school athletes. J. Neurosurg. 98, 296–301. Lovell, M.R., Collins, M.W., Iverson, G.L., Johnston, K.M., and Bradley, J.P. (2004b). Grade 1 or ‘‘ding’’ concussions in high school athletes. Am. J. Sports Med. 32, 47–54. Lovell, M.R., Iverson, G.L., Collins, M.W., McKeag, D., and Maroon, J.C. (1999). Does loss of consciousness predict neuropsychological decrements after concussion? Clin. J. Sport Med. 9, 193–198. Lovell, M.R., Iverson, G.L., Collins, M.W., Podell, K., Johnston, K.M., Pardini, D., Pardini, J., Norwig, J., and Maroon, J.C. (2006). Measurement of symptoms following sports-related concussion: reliability and normative data for the postconcussion scale. Appl. Neuropsychol. 13, 166–174. Lovell, M.R., Pardini, J.E., Welling, J., Collins, M.W., Bakal, J., Lazar, N., Roush, R., Eddy, W.F., and Becker, J.T. (2007). Functional brain abnormalities are related to clinical recovery and time to return-to-play in athletes. Neurosurgery 61, 352– 359; discussion 359–360. Macciocchi, S.N., Barth, J.T., Alves, W., Rimel, R.W., and Jane, J.A. (1996). Neuropsychological functioning and recovery after mild head injury in collegiate athletes. Neurosurgery 39, 510– 514. Macciocchi, S.N., Barth, J.T., and Littlefield, L.M. (1998). Outcome after mild head injury. Clin. Sports Med. 17, 27–36. Macciocchi, S.N., Barth, J.T., Littlefield, L., and Cantu, R.C. (2001). Multiple concussions and neuropsychological func-

ELLEMBERG ET AL. tioning in collegiate football players. J. Athl. Train. 36, 303– 306. Macciocchi, S.N., Fowler, P.C., and Ranseen, J.D. (1992). Trait analyses of the Luria-Nebraska intellectual processes, motor functions, and memory scales. Arch. Clin. Neuropsychol. 7, 541–551. Magnano, I., Aiello, I., and Piras, M.R. (2006). Cognitive impairment and neurophysiological correlates in MS. J. Neurol. Sci. 245, 117–122. Mailer, B.J., Valovich-McLeod, T.C., and Bay, R.C. (2008). Healthy youth are reliable in reporting symptoms on a graded symptom scale. J. Sport Rehabil. 17, 11–20. Majerske, C.W., Mihalik, J.P., Ren, D., Collins, M.W., Reddy, C.C., Lovell, M.R., and Wagner, A.K. (2008). Concussion in sports: postconcussive activity levels, symptoms, and neurocognitive performance. J. Athl. Train. 43, 265–274. Makdissi, M., Collie, A., Maruff, P., Darby, D.G., Bush, A., McCrory, P., and Bennell, K. (2001). Computerised cognitive assessment of concussed Australian Rules footballers. Br. J. Sports Med. 35, 354–360. Makdissi, M., McCrory, P., Ugoni, A., Darby, D., and Brukner, P. (2009). A prospective study of postconcussive outcomes after return to play in Australian football. Am. J. Sports Med. 37, 877–883. Mallinson, A.I., and Longridge, N.S. (1998). Dizziness from whiplash and head injury: differences between whiplash and head injury. Am. J. Otol. 19, 814–818. Matser, J.T., Kessels, A.G.H., Jordan, B.D., Lezak, M.D., and Troost, J. (1998). Chronic traumatic brain injury in professional soccer players. Neurology 51, 791–796. Matser, E.J., Kessels, A.G., Lezak, M.D., Jordan, B.D., and Troost, J. (1999). Neuropsychological impairment in amateur soccer players. JAMA 282, 971–973. Mauritz, K.H., Dichgans, J., and Hufschmidt, A. (1979). Quantitative analysis of stance in late cortical cerebellar atrophy of the anterior lobe and other forms of cerebellar ataxia. Brain 102, 461–482. McAllister, T.W., Saykin, A.J., Flashman, L.A., Sparling, M.B., Johnson, S.C., Guerin, S.J., Mamourian, A.C., Weaver, J.B., and Yanofsky, N. (1999). Brain activation during working memory 1 month after mild traumatic brain injury: a functional MRI study. Neurology 53, 1300–1308. McAllister, T.W., Sparling, M.B., Flashman, L.A., and Saykin, A.J. (2001b). Neuroimaging findings in mild traumatic brain injury. J. Clin. Exp. Neuropsychol. 23, 775–791. McAllister, T.W., Sparling, M.B., Flashman, L.A., Guerin, S.J., Mamourian, A.C., and Saykin, A.J. (2001a). Differential working memory load effects after mild traumatic brain injury. Neuroimage 14, 1004–1012. McCaffrey, R.J., Duff, K., and Westervelt, H.J. (2000). Practitioner’s Guide to Evaluating Change with Neuropsychological Assessment Instruments. Kluwer Academic=Plenum Publishers: New York. McCrea, M., Guskiewicz, K.M., Marshall, S.W., Barr, W., Randolph, C., Cantu, R.C., Onate, J.A., Yang, J., and Kelly, J.P. (2003). Acute effects and recovery time following concussion in collegiate football players: the NCAA Concussion Study. JAMA 290, 2556–2563. McCrea, M., Hammeke, T., Olsen, G., Leo, P., and Guskiewicz, K.M. (2004). Unreported concussion in high school football players: implications for prevention. Clin. J. Sport Med. 14, 13–17. McCrea, M. (2008). Mild Traumatic Brain Injury and Postconcussion Syndrome. Oxford University Press: New York.

ADVANCES IN SPORT CONCUSSION ASSESSMENT McCrory, P., Johnston, K., Meeuwisse, W., Aubry, M., Cantu, R., Dvorak, J., Graf-Baumann, T., Kelly, J., Lovell, M., and Schamasch, P. (2005a). Summary and agreement statement of the 2nd International Conference on Concussion in Sport, Prague 2004. Br. J. Sports Med. 39, 196–204. McCrory, P., Makdissi, M., Davis, G., and Collie, A. (2005b). Value of neuropsychological testing after head injuries in football. Br. J. Sports Med. 39, i58–i63. McCrory, P., Meeuwisse, W., Johnston, K., Dvorak, J., Aubry, M., Molloy, M., and Cantu, R. (2009). Consensus Statement on Concussion in Sport—The 3rd International Conference on Concussion in Sport Held in Zurich, November 2008. PM R 1, 406–420. McCrory, P. (1999). The eighth wonder of the world: the mythology of concussion management. Br. J. Sports Med. 33, 136–137. McCrory, P.R., Ariens, T., and Berkovic, S.F. (2000). The nature and duration of acute concussive symptoms in Australian football. Clin. J. Sport Med. 10, 235–238. Miles, L., Grossman, R.I., Johnson, G., Babb, J.S., Diller, L., and Inglese, M. (2008). Short-term DTI predictors of cognitive dysfunction in mild traumatic brain injury. Brain Inj. 22, 115–122. Mitrushina, M.N., Boone, K.B., and D’Elia, L.F. (1999). Handbook of normative data for neuropsychological assessment. New York: Oxford University Press. Nashner, L., and Berthoz, A. (1978). Visual contribution to rapid motor responses during postural control. Brain Res. 150, 403– 407. Nashner, L.M. (1976). Adapting reflexes controlling the human posture. Exp. Brain Res. 26, 59–72. Nashner, L.M., Black, F.O., and Wall, C. 3rd. (1982). Adaptation to altered support and visual conditions during stance: patients with vestibular deficits. J. Neurosci. 2, 536–544. Newton, M.R., Greenwood, R.J., Britton, K.E., Charlesworth, M., Nimmon, C.C., Carroll, M.J., and Dolke, G. (1992). A study comparing SPECT with CT and MRI after closed head injury. J. Neurol. Neurosurg. Psychiatry 55, 92–94. Notebaert, A.J., and Guskiewicz, K.M. (2005). Current trends in athletic training practice for concussion assessment and management. J. Athl. Train. 40, 320–325. Ommaya, D., and Gennarelli, T. (1974). Cerebral concussion and traumatic unconsciousness: correlation of experimental and clinical observation on blunt head injuries. Brain 97, 633–654. Pellman, E.J., Lovell, M.R., Viano, D.C., and Casson, I.R. (2006). Concussion in professional football: recovery of NFL and high school athletes assessed by computerized neuropsychological testing—Part 12. Neurosurgery 58, 263–274; discussion 263– 274. Pellman, E.J., Lovell, M.R., Viano, D.C., Casson, I.R., and Tucker, A.M. (2004). Concussion in professional football: neuropsychological testing—part 6. Neurosurgery 55, 1290–1303; discussion 1303–1295. Pellman, E.J., Viano, D.C., Tucker, A.M., and Casson, I.R. (2003). Concussion in professional football: location and direction of helmet impacts—Part 2. Neurosurgery 56, 1328–1340. Peterson, C.L., Ferrara, M.S., Mrazik, M., Piland, S., and Elliott, R. (2003). Evaluation of neuropsychological domain scores and postural stability following cerebral concussion in sports. Clin. J. Sport Med. 13, 230–237. Piland, S.G., Motl, R.W., Ferrara, M.S., and Peterson, C.L. (2003). Evidence for the factorial and construct validity of a self-report concussion symptoms scale. J. Athl. Train. 38, 104–112. Piland, S.G., Motl, R.W., Guskiewicz, K.M., McCrea, M., and Ferrara, M.S. (2006). Structural validity of a self-report concussionrelated symptom scale. Med. Sci. Sports Exerc. 38, 27–32.

2381 Prinzel, L.J. 3rd, Freeman, F.G., Scerbo, M.W., Mikulka, P.J., and Pope, A.T. (2003). Effects of a psychophysiological system for adaptive automation on performance, workload, and the event-related potential P300 component. Hum. Factors 45, 601–613. Psychological Corporation. (1997). WAIS-III=WMS-III Technical Manual. San Antonio, TX: Harcourt Brace. Randolph, C., McCrea, M., and Barr, W.B. (2005). Is neuropsychological testing useful in the management of sportrelated concussion? J. Athl. Train. 40, 139–152. Riemann, B.L., and Guskiewicz, K.M. (2000). Effects of mild head injury on postural stability as measured through clinical balance testing. J. Athl. Train. 35, 19–25. Riemann, B.L., Guskiewicz, K., and Shields, E.W. (1999). Relationship between clinical forceplate measures of postural stability. J. Sport Rehabil. 8, 71–82. Rimal, D., Thapa, S.R., Munasinghe, N., and Errington, M. (2007). An unusual presentation of a minor head injury sustained during a game of rugby. Emerg. Med. J. 24, 485–486. Ross, R.J., Casson, I.R., Siegel, O., and Cole, M. (1987). Boxing injuries: neurologic, radiologic, and neuropsychologic evaluation. Clin. Sports Med. 6, 41–51. Ross, S.E., Guskiewicz, K., and Onate, J.A. (2000). Symptomatology following cerebral concussion and its relationship with neuropsychological and postural stability tests (Abstract). J. Athl. Train. 35, S-53. Rubin, A.M., Woolley, S.M., Dailey, V.M., and Goebel, J.A. (1995). Postural stability following mild head or whiplash injuries. Am. J. Otol. 16, 216–221. Ruff, R.M., Crouch, J.A., Troster, A.I., Marshall, L.F., Buchsbaum, M.S., Lottenberg, S., and Somers, L.M. (1994). Selected cases of poor outcome following a minor brain trauma: comparing neuropsychological and positron emission tomography assessment. Brain Inj. 8, 297–308. Sambeth, A., Maes, J.H., Quian Quiroga, R., and Coenen, A.M. (2004). Effects of stimulus repetitions on the event-related potential of humans and rats. Int. J. Psychophysiol. 53, 197– 205. Schatz, P., Pardini, J.E., Lovell, M.R., Collins, M.W., and Podell, K. (2006). Sensitivity and specificity of the ImPACT Test Battery for concussion in athletes. Arch. Clin. Neuropsychol. 21, 91–99. Shutter, L., Tong, K.A., Lee, A., and Holshouser, B.A. (2006). Prognostic role of proton magnetic resonance spectroscopy in acute traumatic brain injury. J. Head Trauma Rehabil. 21, 334– 349. Sim, A., Terryberry-Spohr, L., and Wilson, K.R. (2008). Prolonged recovery of memory functioning after mild traumatic brain injury in adolescent athletes. J. Neurosurg. 108, 511–516. Slobounov, S., Slobounov, E., Sebastianelli, W., Cao, C., and Newell, K. (2007). Differential rate of recovery in athletes after first and second concussion episodes. Neurosurgery 61, 338– 344. Snow, R.B., Zimmerman, R.D., Gandy, S.E., and Deck, M.D. (1986). Comparison of magnetic resonance imaging and computed tomography in the evaluation of head injury. Neurosurgery 18, 45–52. Spreen, O., and Strauss, E. (1998). A Compendium of Neuropsychological Tests. Oxford Univesity Press: New York. Stein, S.C., and Ross, S.E. (1992). Mild head injury: a plea for routine early CT scanning. J. Trauma 33, 11–13. Strauss, E., Sherman, E.M.S., and Spreen, O. (2006). A Compendium of Neuropsychological Tests. Administration, Norms, and Commentary. Oxford University Press: New York.

2382 Thyssen, H.H., Brynskov, J., Jansen, E.C., and Munster-Swendsen, J. (1982). Normal ranges and reproducibility for the quantitative Romberg’s test. Acta Neurol. Scand. 66, 100–104. Toga, A.W., and Mazziotta, J.C. (2002). Brain Mapping: The Methods, 2nd ed. Academic Press: San Diego. Umile, E.M., Plotkin, R.C., and Sandel, M.E. (1998). Functional assessment of mild traumatic brain injury using SPECT and neuropsychological testing. Brain Inj. 12, 577–594. Umile, E.M., Sandel, M.E., Alavi, A., Terry, C.M., and Plotkin, R.C. (2002). Dynamic imaging in mild traumatic brain injury: support for the theory of medial temporal vulnerability. Arch. Phys. Med. Rehabil. 83, 1506–1513. Vagnozzi, R., Signoretti, S., Tavazzi, B., Floris, R., Ludovici, A., Marziali, S., Tarascio, G., Amorini, A.M., Di Pietro, V., Delfini, R., and Lazzarino, G. (2008). Temporal window of metabolic brain vulnerability to concussion: a pilot 1H-magnetic resonance spectroscopic study in concussed athletes—part III. Neurosurgery 62, 1286–1295; discussion 1295–1286. Vander, A., Sherman, J., and Luciano, D. (1990). Human Physiology: The Mechanisms of Body Function, 5th ed. McGraw-Hill: New York. Varney, N.R., Pinkston, J.B., and Wu, J.C. (2001). Quantitative PET findings in patients with posttraumatic anosmia. J. Head Trauma Rehabil. 16, 253–259. Viggiano, M. (1996). Event-related potentials in brain-injured patients with neuropsychological disorders: a review. J. Clin. Exp. Neuropsychol. 18, 631���647. Walls-Esquivel, E., Vecchierini, M.F., Heberle, C., and Wallois, F. (2007). Electroencephalography (EEG) recording techniques and artefact detection in early premature babies. Neurophysiol Clin. 37, 299–309. Warden, D.L., Bleiberg, J., Cameron, K.L., Ecklund, J., Walter, J., Sparling, M.B., Reeves, D., Reynolds, K.Y., and Arciero, R.

ELLEMBERG ET AL. (2001). Persistent prolongation of simple reaction time in sports concussion. Neurology 57, 524–526. Warren, W.L. Jr., and Bailes, J.E. (1998). On the field evaluation of athletic head injuries. Clin. Sports Med. 17, 13–26. Wilde, E.A., McCauley, S.R., Hunter, J.V., Bigler, E.D., Chu, Z., Wang, Z.J., Hanten, G.R., Troyanskaya, M., Yallampalli, R., Li, X., Chia, J., and Levin, H.S. (2008). Diffusion tensor imaging of acute mild traumatic brain injury in adolescents. Neurology 70, 948–955. Willer, B., and Leddy, J.J. (2006). Management of concussion and post-concussion syndrome. Curr. Treat. Options Neurol. 8, 415–426. Witol, A.D., and Webbe, F. (1994). Neuropsychological deficits associated with soccer play. Arch. Clin. Neuropsychol. 9, 104. Wober, C., Oder, W., Kollegger, H., Prayer, L., Baumgartner, C., Wober-Bingol, C., Wimberger, D., Binder, H., and Deecke, L. (1993). Posturographic measurement of body sway in survivors of severe closed head injury. Arch. Phys. Med. Rehabil, 74, 1151–1156. Zimmerman, R.A., Bilaniuk, L.T., Hackney, D.B., Goldberg, H.I., and Grossman, R.I. (1986). Head injury: early results of comparing CT and high-field MR. A.J.R. Am. J. Roentgenol. 147, 1215–1222.

Address correspondence to: Dave Ellemberg, Ph.D. University of Montreal Department of Kinesiology 2100 Edouard Montpetit Montreal, Que´bec H3T 1J4 E-mail:

This article has been cited by: 1. Shruti V Kabadi, Genell D Hilton, Bogdan A Stoica, David N Zapple, Alan I Faden. 2010. Fluid-percussion–induced traumatic brain injury model in rats. Nature Protocols 5:9, 1552-1563. [CrossRef] 2. David W Creighton, Ian Shrier, Rebecca Shultz, Willem H Meeuwisse, Gordon O Matheson. 2010. Return-to-Play in Sport: A Decision-based Model. Clinical Journal of Sport Medicine 20:5, 379-385. [CrossRef]

Advances in Sport Concussion Assessment