Nicola Hodges

Both visual and motor experiences impact action prediction, yet through potentially different mechanisms. Having physical experience with an action is thought to engage motor simulative processes, potentially activating the watcher’s motor system in an effector specific manner, aiding prediction. Leveraging baseball’s unique specialization demands, we assessed pitch discrimination in athletes with predominantly visual experience (hitters, n = 41) and motor experience (pitchers, n = 42; 9 left-handed). Videos of right-handed (RH) pitches, cut at or after ball release, of three different pitches, were used to assess pitch prediction accuracy. Two versions of each video clip were shown; the original RH clips were “flipped” to make the pitcher appear to throw left-handed (LH). Pitchers and hitters had reliable responses and showed high accuracy (~70%) and discriminability. Pitchers were more discriminatory than hitters (d prime) when contrasting two pitch types with the same initial trajectory and speed, but different postural cues (curveballs and changeups). Compared to hitters, pitchers also showed a trend for higher accuracy in “release-point” conditions, where only postural information was available. Accuracy was high on both left and right videos, but only LH pitchers showed a LH video advantage (although at release point, there were effector specific advantages for LH and RH pitchers). Because pitchers did not differ in accuracy from hitters, despite a lack of visual experience, this suggests that their motor experience aided predictions. However, there was only partial support for a simulation explanation (based on effector specificity).

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Changing technique, whereby a permanent strategy is adopted to improve performance or reduce injury risk, is a common practice among sport practitioners. Although the empirical literature is lacking quality evidence and consensus regarding best methods, there are several models and methods suggested; including the Five-A model, error amplification, and continual contrasting of the “old” technique with a new one. My aims with this thesis were to review the technique change literature to help identify commonalities and differences across methods and evaluate if and how these methods are being applied in high-performance sport across a range of practitioner groups and sports. In Study 1, I interviewed fifteen practitioners and in Study 2, I developed an online survey that was completed by thirty-six practitioners, all highly experienced and many working at the highest level of sport. Three practitioner groups were targeted including sport coaches, therapists and strength & conditioning (S&C) coaches and sixteen different sports. In general, there were more similarities than differences across groups; coaches and S&Cs intervened to improve performance, whereas therapists, as well as S&C coaches, intervened to reduce injury risk or regain technique post injury. When intervening, S&Cs and therapists would focus on physical assessments and modifications, often working outside the sport context, then back into it. Coaches would remain within the sport context, though scale back the task difficulty to encourage change. There was little evidence that exaggerating errors, or contrasting between old and new ways, was used to change technique, but practitioners did use error awareness, technique-focused feedback (directing attention both internally and externally) and direct-instruction regarding a desired technique. Despite practitioners reporting that they spent ~55% of their time changing technique, with a success rate of ~60%, many noted challenges associated with technique interventions. There are gaps in knowledge about current evidence-recommended methods, particularly the need to train and evaluate the new technique in competition-like situations. As such, greater efforts should be made by academics to engage in knowledge translation activities to aid practitioner awareness of the various tools that could improve the efficiency and efficacy of technique change interventions.

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There has been an increasing interest in training perceptual skills in sports through video-based methods, particularly in baseball (e.g., baseball pitch recognition). However, there is little empirical evidence related to their reliability and validity, to help guide the efficacy and application of video-based training methods. Here we sought to investigate whether an online task can be used to a) assess perceptual cognitive skills and b) discriminate across age and different skill groups. An online experimental platform was developed to help collect data on baseball specific predictions concerning pitch type and dynamic visual acuity among baseball players (n = 21) and novices (n=14) with low baseball experience (age 13 -22 yr). The baseball prediction task consisted of two different pitchers, three pitch types and three occlusion points (such that ball flight information was progressively removed). Each clip was shown twice. The prediction task was shown to be valid and reliable, discriminating across skill groups and showing reliability across repeated viewings and from the online task to an in-person assessment (n=6). There were, however, differences in reliability and discriminant validity based on the type of pitcher, with one pitcher being responded to more accurately and reliably. The skilled participants showed good discriminability between fastballs and change-ups versus the novice group and there was a trend for better dynamic visual acuity in the skilled group. Due to difficulties in recruitment, the data was mostly based on adult participants, such that further data collection is needed to make conclusions about age-group differences and development of perceptual-cognitive skills in baseball. The current data mostly help to provide baseline data about current stimuli and methods for assessment of perceptual skills in baseball, showing evidence speaking to the validity and reliability of online methods.

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Previous studies have provided evidence consistent with the proposal that people “simulate” observed actions, based on their own motor experiences, to help predict the outcome of others’ actions. This simulation is believed to be based on low-level activation of the observer’s motor system at the time of the decision. In this experiment, we tested how closely people’s motor experiences influence their ability to predict action outcomes and whether these experiences generalize to predicting outcomes of novel stimuli. To do this, we manipulated the experiences (and therefore, the type of internal model formed during physical practice), by asking people to practice throwing darts with or without a wrist weight. Participants were asked to predict outcomes of people throwing under opposite or the same conditions as those experienced during practice. Although we showed evidence that prediction ability is specific to one’s practice experience, this was only seen in people who physically practiced without a weight and not for people who physically practiced with a wrist weight. The contribution of the motor system to these predictive decisions was also assessed by secondary-motor tasks designed to probe motor system involvement during prediction. Although we showed that predicting dart outcomes while wearing a wrist weight aided prediction accuracy, this was only observed in people who physically practiced without a weight. Contrary to previous studies, we were unable to show interference from a secondary, incongruent movement task (light press on a force gauge) after physical practice. Both physical and perceptual practice resulted in improvement in prediction accuracy post-practice, although this was strongest for the no-weight physical practice group. Overall, these data provide evidence that physical practice transfers to improvement in perceptually-driven predictive decisions. However, although the secondary tasks gave some evidence that prediction was dependent on the motor system (when holding a weight), and that the type of motor experience (weight or no-weight) impacts predictive decisions, evidence for motor simulation was not shown. Limits of the current methods are discussed.

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In this thesis I investigate how people adapt manual aiming in novel visual-motor environments and how different adaptation processes (implicit/explicit) depend on feedback type, and existing internal models (action experience). How implicit and explicit processes interact to facilitate accurate performance in adaptation paradigms is debated. One key study concluded that implicit adaptation, driven by error in expected sensory consequences, guided adaptation independent of ‘correct’ strategic/explicit processes (Mazzoni & Krakauer, 2006). We hypothesized that if these processes are independent, later explicit re-adaptation should not influence a previously acquired implicit adaptation (evidenced by unchanged after-effects). In Experiment 1, numeric post-trial knowledge of results (KR) was used to promote explicitly-guided, re-adaptation of an implicit adaptation. Thirty participants gradually adapted aiming movements to a 30° CW visual rotation to achieve implicit adaptation (evidenced by strong after-effects). Participants practiced again with correct or incorrect (+/-15°) KR about cursor endpoint accuracy while still receiving correct cursor feedback. The incorrect KR groups showed the highest variable error, indicative of error-reducing strategic adjustments. Only the +15° error group re-adapted to KR. This resulted in larger after-effects than before KR exposure. If KR engaged only explicit processes, these results would suggest that these processes are interdependent, whereby an (implicit) internal model for aiming was updated by explicit processes, resulting in augmented after-effects. Despite existing evidence suggesting that post-trial KR facilitates only explicit adaptation, we had to test this result in our research design before concluding that the effects of KR were unique to re-adaptation. Therefore, we conducted Experiment 2 to determine whether post-trial KR could be used to update internal models for aiming without previous visual-motor experience. Thirty participants gradually adapted to a 30° CW visual rotation receiving either concurrent or post-trial cursor feedback, or post-trial numeric KR. Although all groups showed after-effects following practice, suggesting implicit adaptation in all feedback conditions, the magnitude of after-effects was smaller for the numeric KR group. From these data we conclude that numeric KR results in both implicit and explicit adaptation and that the relative contributions of these processes to adaptation likely depends on self-attribution of errors and timing of visual feedback.

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Based upon postulates derived from the Developmental Model of Sports Participation (Côté et al., 2012) we tested the effects of domain specific activities (play and practice), as well as sporting diversity during the sampling years, on the development of motivation, passion and skill ratings. The first component of our study required testing predictions that play and diversity during the sampling years (age 5-12 yr) were positively correlated with intrinsic motivation and passion. We questioned elite youth level soccer players (N= 148), across 3 age groups, who were on the pathway towards achieving professional status at the adult level. Overall, we found no significant correlations between play and early sporting diversity during the sampling years with scores of motivation or passion. A small, yet significant positive correlation was observed between accumulated hours in soccer practice and integrated regulation. However, independent analysis of age groups yielded significant negative correlations between hours accumulated in soccer practice and measures of intrinsic motivation (Under 15 yr) and harmonious passion (Under 17 yr). The second study component investigated associations between time spent in soccer activities during the sampling years and across participants’ full careers as well as sporting diversity with coach ratings of skill. For the U17 group, hours accumulated in organized practice were related to creative and overall skill, while accumulated hours in soccer practice were related to technical skill for the U15 group. Moreover, for the U17 group, % accumulated hours in play negatively correlated with technical and overall skill ratings. The youngest group (U13) showed a different pattern of results to the older players, with more hours in play (% and total) related to creative skill. Due to these overall relationships, we conclude that recommendations towards early sporting diversity and more time in deliberate play activities (i.e., individually-led practice or play) should be treated with caution, because they do not inoculate against any hypothesized negative effects of early specialization in sport and are negatively related to predictors of skill (at least for the older players). Follow-up longitudinal analysis is recommended to determine how these practice and motivation variables are related to future success.

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In two experiments, we tested whether non-task related variability, in the form of randomly administered mechanical perturbations during practice, would facilitate the acquisition of a novel two-handed coordination movement. There is considerable evidence in the motor learning literature showing that task-related variability, in the form of practice of variations of a skill or practicing skills in a more variable order, can benefit learning and transfer. Moreover, there is recent evidence that non-task related variability added to the learning process, termed differential learning, is beneficial to learning by simply providing a greater exploration of the dynamic environment. In both experiments, we failed to find evidence to support these predictions about the beneficial effects of non-task related variability. In Experiment 1, when variability was administered after a period of stabilization, and in the presence of performance enhancing feedback (i.e., a Lissajous display), no differences between a control group and a variability (perturbation) group were found in retention. This was despite significant improvements for both groups and evidence that the perturbations worked to increase variability later in practice for the perturbation group. In a second Experiment, we increased the amount of practice, changed the feedback display, and provided variability throughout practice. Despite these changes, externally added, mechanical perturbations added to the movement still failed to aid acquisition, retention or transfer. We conclude that this method of practice, when the variability is externally administered and not dependent on performance, fails to aid acquisition or facilitate long term retention or transfer of new motor skills. Therefore, variability, in and of itself, is not a sufficient variable to bring positive changes in performance and learning, considerations need to be made in regards to the difficulty of the task, the competence of the performer and the specific types of variability, in order to be beneficial.

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It has been suggested that observational practice engages neural mechanisms for movement planning and execution similar to those engaged in physical practice. In three experiments we investigated observational practice during adaptation to a novel visuomotor environment. Participants were tested in the normal visuomotor environment before and after observation, and in the novel environment after observation. In the latter, learning would be seen by immediate performance benefits from watching. In the former, negative after-effects in the normal environment would suggest an updating of internal models based on the visuomotor discordance, arguably a more robust index of learning. In Experiment 1, observers showed benefits in the novel environment, but no after-effects. Because after-effects are believed to be a result of perceived discrepancies between sensory input and predicted sensory consequences, we hypothesised that observational practice might not engage covert simulation involving motor processes to the same degree as initially implied. To more thoroughly test this idea, in Experiment 2 we encouraged more active observation (or simulation) through conditions requiring imagery and error estimation. Despite these manipulations, only actors showed after-effects. In Experiment 3, a group of observers was also passively moved during observation, to determine whether the absence of after-effects was more linked to afferent feedback instead. However, this condition still failed to yield after-effects. A second observer group actively imitated the movements of the actor during observation but this group’s performance was not different from that of passive observers. Because the primary difference between actors and active-observers was the lack of self-generated visual reafference, these results strongly suggest that to update internal models, experiencing visual reafference of one’s own movement is critical. We speculate that learning might have been realized in observers via a more cognitive-strategic route, as compared to actors, based on data across the three experiments showing that observers acquired more accurate explicit knowledge about the direction and size of the visuomotor perturbation, compared to actors. In conclusion, it appears that doing and seeing engage different processes which in the case of visuomotor adaptation, result in different types of learning and learning outcomes for observers and actors.

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