An athletic approach to studying perception-action integration: Does sport-specific training, and the impact of injury, influence how individuals visually guide navigation?
Bibliographic record
Abstract
The objective of this thesis was to investigate perception-action integration capabilities of individuals during a choice navigation task. This task assessed navigation strategies in open space while individuals avoided colliding with two vertical obstacles that created a body-scaled, horizontal gap, at three varying obstacle distances from the starting location (3m, 5m, 7m). The two studies completed in this thesis employed the same paradigm to assess the hypothesized group differences. Gaze behaviours and kinematics of navigation strategies were compared between: 1) athletes specifically trained in navigating in open space versus non-athletes; and 2) athletes with post-concussion syndrome (PCS) versus non-concussed, specifically trained athletes. Specifically trained athletes have been identified as demonstrating more successful perception-action integration in discrete motor tasks related to their sport (Mann et al., 2007; Vickers, 2007). However, whether these abilities translate to the continuous motor task of obstacle avoidance in open space was unknown. The purpose of Study 1 was to identify the influence of sport-specific training on navigating in open space (i.e. navigational strategies of large field sport athletes) compared to age-matched, non-athletes. It was hypothesized that specifically-trained athletes would demonstrate fewer, longer fixations, suggesting a more successful perception-action integration strategy (as defined by Mann et al., 2007), and would employ more sport-specific navigation strategies than non-athletes by maintaining their straight trajectory toward the goal (Fajen & Warren, 2003). Athletes were found to make fewer, longer fixations than non-athletes. However, no differences were observed between navigation strategies of the two groups, nor were any kinematic measures found to differ between groups. It can be concluded that athletes and non-athletes differentially obtain visual information to perform the same actions, suggesting that athletes and non-athletes differentially perform perception-action integration when navigating in open space. Future studies are required to identify sport-specific nuances of navigation (moving obstacles, running) to better identify athletic-related navigation strategies.\nAlthough athletic training can enhance perception-action integration strategies, sport-related injuries can hinder this process. Following a concussion, individuals experience deficits of perception-action integration that persist well beyond 30 days of recovery, post-concussion (Baker and Cinelli, 2014; Slobounov et al., 2006). These perception-action integration deficits may also exist in individual with postconcussion syndrome (PCS). The purpose of the Study 2 was to identify whether perception-action integration deficits persist with the persistent physical symptoms of concussion characteristic of PCS. The current study revealed that athletes with PCS did not differ from non-concussed athletes on any measure of visual fixation strategy, nor were they found to differ on any kinematic measure assessed. These findings suggest that in the context of the current paradigm, athletes with PCS have no perception-action integration deficit. In that, athletes with PCS may have adapted perception-action integration strategies to navigate with equal efficiency as a specifically-trained group of athletes or that the paradigm was not sensitive enough to identify these differences. Such findings suggest that more research is required to assess what, if any, perception-action integration deficits persist with persisting physical symptoms of PCS to better benefit rehabilitative procedures and outcomes for these individuals.\nTogether, these studies add to what was previously known about perception-action integration, as it relates to navigation. Both studies assessed perception-action integration in unique populations that add to understanding of behavioural dynamics in the sport setting. Study 1 builds on a line of research assessing affordance theory and behavioural dynamics in sport (Fajen, Riley, & Turvey, 2008). The findings of this study suggest that although navigation strategies did not differ between specifically trained athletes and non-athletes, visual search strategies employed in task did. Such findings add to the understanding that sport-specific training influences perception-action integration, through our understanding of how athletes obtain visual information to perform actions. This thesis did not identify perception-action integration deficits in athletes with PCS. These findings suggest that the individuals in the present study likely adapted to their injury as they demonstrated equal ability in gaze and navigation strategies to specifically-trained athletes. As such, further research is required to assess the cognitive, motor, and sensory-motor deficits that may persist with the persisting physical symptoms of PCS. As individuals with PCS do not demonstrate similar visuomotor integration deficits as individuals with acute concussions (Baker & Cinelli, 2014), such individuals must be assessed and researched as a separate population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".