Think fast, stay healthy? A narrative review of neurocognitive performance and lower extremity injury

BACKGROUND

Lower extremity (LE) injury has been problematic in athletic populations. While previous research has identified biomechanical and neuromuscular risk factors, more recent efforts have determined that neurocognitive performance (NP) may influence LE injury risk.

OBJECTIVES

To describe the present findings pertaining to the relationship between NP and LE injury. This review described potential cerebral neural mechanisms underpinning LE injury with a particular emphasis on the role of vision in sensorimotor integration. Lastly, newer technology such as stroboscopic eyewear, smartboards, and virtual/augmented reality were discussed for their utility in assessing and training NP.

METHODS

Narrative review that described NP and LE injury, as well as plausible mechanisms and training interventions.

RESULTS

NP appears to influence both LE biomechanics and LE injury risk. Athletes with worse NP demonstrated decreased knee flexion and increased frontal plane knee loading compared to better performing athletes. Most studies determined an association between NP and LE injury risk. Visual motor reaction time, processing speed, and working memory appear to be useful NP measures for identifying athletes at risk for LE injury. Various brain regions including the precuneus and lingual gyrus may be implicated as neural signatures for LE injury. While recently developed technology offer promise, far-transfer effects to LE injury risk reduction have yet to be substantially investigated.

CONCLUSIONS

NP should be considered an important component for identifying LE injury risk. Sports scientists and clinicians may consider a variety of assessments and interventions to quantify and train NP in conjunction with previously established protocols.

Reactive Task Performance Under Varying Loads in Division I Collegiate Soccer Athletes

This study was conducted to identify whether team-wide or positional differences exist in simple or choice reactivity of collegiate soccer athletes when completed under various loads. Much research exists surrounding the assessment of reaction time in the general population, but given variations in training, little insight exists surrounding how unique and elite populations may differ based upon performance demands and task translatability to training. Reactive performance was assessed using the Dynavision D2 in 24 female soccer players (19.73 ± 1.05 years old) from a team within a power five conference of the National Collegiate Athletic Association. Evaluated loads included two conditions of simple reactivity (no additional load and with a concurrent lower body motor task) and three conditions of choice reactivity (no additional load, with a concurrent lower body motor task, and prolonged durations). Paired t-tests and ANOVAs were used to identify differences in task performance based upon load and positional group. No significant load-based or positional differences existed in measured simple reaction times. Performances in choice reaction tasks across the team were found to be slower when completed across extended durations (p < 0.0001) and faster when completed concurrent with an added balance task (p = 0.0108), as compared to performance under normal conditions. By assessment of positional differences, goalkeepers tended to be slower than other positions in reactivity during choice tasks, despite no differences existing in simple task performance. Given the unique population utilized herein, measured reactivity in different tasks suggests a strong relation to the training demands of soccer, as well as those of goalkeepers as compared to field positions. Findings suggest that sport and positional demands may be substantial contributors to population- and individual-based reactivity performance.

Test-Retest Reliability, Training, and Detraining Effects Associated With the Dynavision D2™ Mode A Visuomotor Reaction Time Test

CONTEXT

The Dynavision D2™ Mode A test (ModeA) is a 1-minute reaction time (RT) test commonly used in sports science research and clinical rehabilitation. However, there is limited data regarding the effect of repeated testing (ie, training) or subsequent periods of no testing (ie, detraining) on test-retest reliability and RT performance. Therefore, the purpose of this study was to examine the test-retest reliability, training, and detraining effects associated with the D2™ ModeA test.

DESIGN

Repeated measures/reliability.

METHODS

Twenty-four recreationally active men and women completed 15 training sessions consisting of 2 ModeA tests per session (30 tests). The participants were then randomized to either 1 or 2 weeks of detraining prior to completing 15 retraining sessions (30 tests). The training and retraining periods were separated into 10 blocks for analysis (3 tests per block). The number of hits (hits) and the average RT per hit (AvgRT) within each block were used to determine RT performance. Intraclass correlation coefficients, SEM, and minimum difference were used to determine reliability. Repeated-measures analysis of variance/analysis of covariance were used to determine training and detraining effects, respectively.

RESULTS

The ModeA variables demonstrated excellent test-retest reliability (intraclass correlation coefficient2,3 > .93). Significant improvements in hits and AvgRT were noted within training blocks 1 to 5 (P < .05). No further improvements in RT performance were noted between training blocks 6 through 10. There was no effect of detraining period on RT. The RT performance was not different between blocks during retraining.

CONCLUSIONS

It appears that 15 tests are necessary to overcome the training effect and establish reliable baseline performance for the ModeA test. Detraining for 1 to 2 weeks did not impact RT performance. The authors recommend that investigators and clinicians utilize the average of 3 tests when assessing RT performance using the D2 ModeA test.

Topical Review: The Top Five Peripheral Vision Tools in Sport

SIGNIFICANCE

This study summarizes the empirical evidence on the use of peripheral vision for the most-researched peripheral vision tools in sports.

The objective of this review was to explain if and how the tools can be used to investigate peripheral vision usage and how empirical findings with these vision tools might be transferred to sports situations. The data sources used in this study were Scopus, ScienceDirect, and PubMed. We additionally searched the manufacturers' Web pages and used Google Scholar to find full texts that were not available elsewhere. Studies were included if they were published in a peer-reviewed journal, were written in English language, and were conducted in a sports context. From the 10 searched tools, we included the 5 tools with most published studies. In our topical search, we identified 93 studies for the five most-used peripheral vision tools. Surprisingly, none of these studies used eye-tracking methods to control for the use of peripheral vision. Best "passive" control is achieved by tools using (foveal) secondary tasks (Dynavision D2 and Vienna Test System). Best transfer to sports tasks is expected for tools demanding action responses (FitLight, Dynavision D2). Tools are likely to train peripheral monitoring (NeuroTracker), peripheral reaction time (Dynavision D2, Vienna Test System), or peripheral preview (FitLight), whereas one tool did not show any link to peripheral vision processes (Nike SPARQ Vapor Strobe).