Tom Maudrich1,2, Hannah Kandt1, Patrick Ragert1,2, Rouven Kenville1,2. 1. Department of Movement Neuroscience, Faculty of Sport Science, Leipzig University, Leipzig, Saxony, Germany. 2. Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Saxony, Germany.
Abstract
Besides simple movement sequences, precise whole-body motor sequences are fundamental for top athletic performance. It has long been questioned whether athletes have an advantage when learning new whole-body motor sequences. In a previous study, we did not find any superior learning or transfer effects of strength and endurance athletes in a complex whole-body serial reaction time task (CWB-SRTT). In the present study, we aimed to extend this research by increasing the overlap of task requirements between CWB-SRTT and a specific sports discipline. For this purpose, we assessed differences between football players and non-athletes during motor sequence learning using CWB-SRTT. 15 non-athletes (CG) and 16 football players (FG) performed the CWB-SRTT over 2 days separated by one week. Median reaction times and movement times were analyzed as well as differences in sequence-specific CWB-SRTT learning rates and retention. Our findings did not reveal any differences in sequence-specific or non-sequence-specific improvement, nor retention rates between CG and FG. We speculate that this might relate to a predominately cognitive-induced learning effect during CWB-SRTT which negates the assumed motor advantage of the football players.
Besides simple movement sequences, precise whole-body motor sequences are fundamental for top athletic performance. It has long been questioned whether athletes have an advantage when learning new whole-body motor sequences. In a previous study, we did not find any superior learning or transfer effects of strength and endurance athletes in a complex whole-body serial reaction time task (CWB-SRTT). In the present study, we aimed to extend this research by increasing the overlap of task requirements between CWB-SRTT and a specific sports discipline. For this purpose, we assessed differences between football players and non-athletes during motor sequence learning using CWB-SRTT. 15 non-athletes (CG) and 16 football players (FG) performed the CWB-SRTT over 2 days separated by one week. Median reaction times and movement times were analyzed as well as differences in sequence-specific CWB-SRTT learning rates and retention. Our findings did not reveal any differences in sequence-specific or non-sequence-specific improvement, nor retention rates between CG and FG. We speculate that this might relate to a predominately cognitive-induced learning effect during CWB-SRTT which negates the assumed motor advantage of the football players.
There is an ongoing debate about the extent to which specific athletic performance capabilities exhibited during participation in a given sport-related activity translate to superior motor performance in an unrelated motor scenario. Previous research indicates that such transfer effects (motor transfer) depend on the degree of similarity between the domain of athletic expertise and the new task to be performed [1, 2]. Such positive motor transfer has already been demonstrated in baseball players [1], Karate athletes [3], as well as basketball and field hockey players [4] during a variety of simple motor tasks. However, the effect is absent once the new task shows little to no overlap with the domain of athletic expertise [2, 5]. To date, few studies exist on motor transfer abilities of athletes in motor sequence learning. Notably, musicians demonstrate improved learning performance in related fine motor sequence and tapping tasks compared to non-musicians [6, 7], potentially supporting the idea of expertise-induced motor transfer in such tasks.Precise coordination of motor sequences plays a fundamental role in the process of acquiring and mastering everyday motor tasks as well as athletic performance. Basic motor skills such as typing a phone number, as well as the quality of complex athletic movements, depend on the ability to manifest specific motor sequences [8]. Motor sequence learning is typically investigated using serial reaction time tasks (SRTT) for upper or lower extremities. During SRTT, participants are presented with spatially separated visual stimuli. Participants must respond as accurately and as quickly as possible with a motor action, e.g., pressing a button, corresponding to the sequence of the presented stimuli. Performance of motor sequence learning is measured by the proportion of correct responses and the reaction time to the presented visual cues. Consequently, SRTT performance relies on the successful integration of motor and cognitive processes. SRTT designs combine sequence blocks (fixed order of stimuli) with randomized blocks (random order of stimuli) to investigate sequential and non-sequential parts during the motor learning process [9].As an extension of the conventional SRTT, which is mainly applied in simple movement tasks, we introduced a complex whole-body SRTT (CWB-SRTT) [10]. Initial evidence demonstrated that the brains of non-athletes functionally reorganize during learning of CWB-SRTT [10]. A subsequent study examined baseline differences in initial performance during CWB-SRTT as well as learning rates between athletes (endurance and strength athletes) and non-athletes during two days of CWB-SRTT training [11]. The results of this study did not show any differences in initial performance or learning rates between athletes and non-athletes. Accordingly, a transfer effect of basic motor abilities from strength and endurance athletes on CWB-SRTT performance could not be demonstrated. The task specificity of the CWB-SRTT was pointed out as a possible explanation for these results. Although endurance and strength athletes internalize specific movement patterns within their many years of training, these patterns are distinguishable from the typical motor actions of the CWB-SRTT. This discrepancy between the typical motor actions of strength and endurance athletes and the necessary motor actions within the CWB-SRTT possibly accounts for the lack of motor transfer effects.To more accurately assess the possibility of positive motor transfer on motor sequence learning, the intersection between the movement patterns of athletes and those required in the CWB-SRTT must be expanded. Fundamentally, the CWB-SRTT places demands on the serial reaction ability of the lower extremities in a whole-body compound movement. Athletes from several sports can be considered as potential study populations, however, based on their requirement profiles, the largest motor-related intersection lies with football. In football, offensive, as well as defensive game decisions, are realized in the range of a few hundredths of a second via motor actions of the lower extremities [12]. Accordingly, reaction time is an important determinant of football performance [12]. Several studies illustrate this by demonstrating that the cognitive processing of soccer players, in the form of improved reaction times during general motor inhibition tasks [13] as well as faster stimulus processing times and improved attentional performance [14], is increased compared to control groups. Furthermore, the motor related overlap between CWB-SRTT and football performance, i.e., the rapid, goal-directed activation of the lower extremities, is considerably high. In sum, football players might therefore hold an advantage in learning a novel sensorimotor task such as the CWB-SRTT.Consequently, the purpose of this study was to examine the difference between football players and non-athletes during CWB-SRTT performance on two separate days to investigate potential motor transfer of football skills when learning a new motor skill using CWB-SRTT. Based on the outlined body of research, we hypothesized improved initial performance as well as improved learning and retention rates for football players compared to non-athletes.
Materials and methods
Ethical approval
This study was supported by the local ethics committee of Leipzig University (ref. nr. 287/18-ek). According to the Declaration of Helsinki, all subjects provided written informed consent to participate in the study.
Participants
A total of 31 participants (15 female, 16 male; age (mean ± standard deviation): 23.0 ± 2.6 years) were enrolled in the present study, recruited through a public advertisement based on the following inclusion criteria: age 18–35 years & neurologically healthy. Participants were separated into two groups according to their participation in organized football training: a non-athlete control group (CG; n = 15; age: 22.3 ± 2.6 years) and a football group (FG; n = 16; age: 23.6 ± 2.6 years). As non-athletes were considered those participants with an upper limit of 3 hrs of general physical exercise a week (2.0 ± 1.4 hrs). Non-athletes did not participate in a specific sport in an organized manner apart from general recreational activities (e.g., running, fitness and cycling). FG had to regularly undergo at least 3 organized football training sessions during an average week (6.3 ± 1.8 hrs). All football players in this study had to have participated in organized training for at least two years. This critical value was exceeded by FG (17.3 ± 3.9 years). Handedness and footedness of all participants were assessed using the Edinburgh Handedness Inventory [15] and the Waterloo Footedness Questionnaire Revised [16], respectively. An overview of demographic and laterality variables is presented in Table 1.
Table 1
Overview of participant characteristics.
Variable
Football group (FB)
Control group (CG)
Sign. Mann-Whitney
Sample size
n = 16
n = 15
-
Gender (male/female)
8/8
8/7
-
Age (years)
23.56 ± 2.6
22.3 ± 2.6
p = 0.134
Handedness
70.00 ± 42.4
76.00 ± 40.8
p = 0.440
Footedness
5.44 ± 8.6
11.00 ± 7.1
p = 0.065
Training years
17.25 ± 3.9
7.33 ± 4.7
p < 0.001*
Training/week (hrs)
6.28 ± 1.8
2.00 ± 1.4
p < 0.001*
All values are expressed as mean ± standard deviation. Group differences were tested with pairwise Mann-Whitney U tests.
*Significant differences between groups (p < 0.05).
All values are expressed as mean ± standard deviation. Group differences were tested with pairwise Mann-Whitney U tests.*Significant differences between groups (p < 0.05).
Experimental procedure
Participants performed a whole-body sensorimotor skill task, the CWB-SRTT, on two separate days with one week of rest in between sessions, with the measurements of one participant taking place at comparable daytimes. FG and CG completed 15 consecutive sequence blocks and one random block before and one random block after all sequence blocks on each day (Fig 1A). This leads to a total of 204 motor responses for each experimental day. The CWB-SRTT lasted 15 minutes, with 15-second inter-block rest intervals.
Fig 1
Sensorimotor skill learning using a complex whole-body serial reaction time task (CWB-SRTT).
(A) A general overview of the study. Football players (FG) and non-athlete control participants (CG) completed CWB-SRTT on two days separated by a week. On each day participants performed 15 learning sequences (L1-L15; L16-L30), as well as one random sequence before and after the learning sequences (R1, R2, R3, R4). (B) A target cue displayed on any of four squares on a monitor situated 2 meters in front of the participant indicated the plate to be stepped on. (C) The participants’ starting positions during the CWB-SRTT. The target plates were spaced by 0.5 m in both the lateral and longitudinal directions. All plates on the left side had to be operated with the left foot, and all plates on the right side had to be operated with the right foot. The number of plates in each position is related to a number in the learning sequence (1: front left; 2: front right; 3: back left; 4: back right). (D) The fixed learning sequence during all learning blocks appeared in the following order: 2-3-2-4-1-3-1-4-3-4-2-1. This figure was created with Biorender.com.
Sensorimotor skill learning using a complex whole-body serial reaction time task (CWB-SRTT).
(A) A general overview of the study. Football players (FG) and non-athlete control participants (CG) completed CWB-SRTT on two days separated by a week. On each day participants performed 15 learning sequences (L1-L15; L16-L30), as well as one random sequence before and after the learning sequences (R1, R2, R3, R4). (B) A target cue displayed on any of four squares on a monitor situated 2 meters in front of the participant indicated the plate to be stepped on. (C) The participants’ starting positions during the CWB-SRTT. The target plates were spaced by 0.5 m in both the lateral and longitudinal directions. All plates on the left side had to be operated with the left foot, and all plates on the right side had to be operated with the right foot. The number of plates in each position is related to a number in the learning sequence (1: front left; 2: front right; 3: back left; 4: back right). (D) The fixed learning sequence during all learning blocks appeared in the following order: 2-3-2-4-1-3-1-4-3-4-2-1. This figure was created with Biorender.com.
Sensorimotor skill learning: complex whole-body serial reaction time task (CWB-SRTT)
In this study, a four-directional CWB-SRTT for the lower extremities was used as a model of whole-body sensorimotor skill learning. The CWB-SRTT has been shown to robustly induce motor learning in two of our previous experiments [10, 11]. The main aspects of CWB-SRTT are illustrated in Fig 1, as well as briefly described below. For a detailed description of CWB-SRTT, please refer to Mizuguchi et al. (2019) [10]. In general terms, CWB-SRTT requires participants to step on one of four target plates as quickly as possible in response to visual stimuli. During performance, stimuli are presented in randomized or fixed orders to enable the analysis of sequence-specific and non-sequence-specific learning. For this study, we analyzed reaction time and movement time. The time between the onset of the visual stimulus and the raising of the response foot from one of the middle plates was used to determine reaction time. The time difference between lifting the response foot from the middle plate and making initial contact with one of the target plates was used to determine movement time. Median values of reaction and movement times were computed separately over each performed sequence block, resulting in 17 reaction and 17 movement times (2 random and 15 learning blocks) per experimental day and participant.
Statistical analyses
All statistical analyses were performed using JASP (Version 0.16, JASP Team 2020). The normality of reaction and movement times was assessed and confirmed by Shapiro-Wilk testing (α = 0.05). Demographic variables, Handedness/Footedness variables, and RECALL variables were not normally distributed. To compare these variables between FG and CG, non-parametric Mann-Whitney U tests were used.To check whether the initial performance differed between FG and CG, reaction and movement times at the first random sequence on day 1 (R1) were compared using independent-sample t-tests.For each experimental day, separate repeated-measures ANOVAs with the between-subject factor GROUP (FG, CG) and within-subject factor SEQUENCE (17 sequences) were used to evaluate sensorimotor skill learning within and between groups for reaction and movement times separately. A Greenhouse-Geisser correction was implemented when the sphericity assumption was violated.On both days, the time difference between the last random sequence and the last learning sequence was calculated separately to assess sequence-specific improvements in reaction and movement times (day 1: R2-L15, day 2: R4-L30). Independent-sample t-tests were used to check for differences in learning rates between FG and CG.The time difference between the first random sequence and the last random sequence on day 1 (R2-R1) and day 2 (R4-R3) was used to assess non-sequence-specific improvements in reaction and movement times separately. Again, these parameters were compared between groups using independent-sample t-tests.Furthermore, we compared reaction times and movement times at the last learning sequence on day 1 (L15) and the first learning sequence on day 2 (L16) using a repeated-measures ANOVA with the between-subject factor GROUP (NAG, AG) and the within-subject factor SEQUENCE (L15, L16) to assess the retention of sequence-specific performance within and between groups.We further computed the Spearman’s rank correlation coefficients between the sequence-specific improvements on day 1 and RECALL1 as well as between sequence-specific improvements on day 2 and RECALL2 for reaction and movement times separately to assess if the sequence-specific improvement was related to the number of recalled items.For the separate repeated-measures ANOVAs investigating reaction time or movement time on day 1 and day 2 the statistical threshold was Bonferroni adjusted to p < 0.025 to account for multiple comparisons. For all further analyses, the statistical threshold was set at p < 0.05. Effect sizes were expressed either using Cohen’s d for t-tests, the rank-biserial correlation for Mann-Whitney U tests, or partial eta squared (ηp2) for ANOVAs.
Results
No significant differences in terms of age (W = 158.0, p = 0.134, rbiserial = 0.317), handedness (W = 100.5, p = 0.440, rbiserial = -0.163) and footedness (W = 73.0, p = 0.065, rbiserial = -0.392) were observed between FG and CG. However, groups significantly differed in the number of training years (W = 229.0, p < 0.001, rbiserial = 0.908) and the amount of training performed during an average week (W = 240.0, p < 0.001, rbiserial = 1.000).Initial performance in reaction times did not differ between FG and CG (t(29) = -1.371, p = 0.181, d = -0.493). Furthermore, initial movement times were not different between groups (t(29) = -1.508, p = 0.142, d = -0.542).Repeated measures ANOVA indicated a significant effect for SEQUENCE (F(6.196, 176.693) = 9.915, p < 0.001, ηp2 = .255) on median reaction times during day 1 (see Fig 2A). However, no significant effect was found for GROUP (F(1, 29) = 1.209, p = 0.281, ηp2 = .040) and no significant interaction effect GROUP×SEQUENCE was observed (F(6.196, 176.693) = 0.451, p = 0.849, ηp2 = .015).
Fig 2
Results of complex whole-body serial reaction time task (CWB-SRTT).
(A) For the control group (CG) and the football group (FG), a line graph showing CWB-SRTT learning for reaction times on day 1 and day 2 is shown. The average reaction times for each conducted sequence are displayed. The error bars represent the 95% confidence interval of the mean. Random sequences are indicated by black points. (B) A line graph depicting CWB-SRTT learning for movement times on day 1 and day 2 for the control group (CG) and the football group (FG). The mean movement times for each executed sequence are displayed. The error bars represent the 95% confidence interval of the mean. Random sequences are indicated by black points. This figure was created with Biorender.com.
Results of complex whole-body serial reaction time task (CWB-SRTT).
(A) For the control group (CG) and the football group (FG), a line graph showing CWB-SRTT learning for reaction times on day 1 and day 2 is shown. The average reaction times for each conducted sequence are displayed. The error bars represent the 95% confidence interval of the mean. Random sequences are indicated by black points. (B) A line graph depicting CWB-SRTT learning for movement times on day 1 and day 2 for the control group (CG) and the football group (FG). The mean movement times for each executed sequence are displayed. The error bars represent the 95% confidence interval of the mean. Random sequences are indicated by black points. This figure was created with Biorender.com.A similar relation was observed for reaction times on day 2. A repeated-measures ANOVA revealed a significant effect for SEQUENCE (F(5.752, 166.806) = 16.546, p < 0.001, ηp2 = .363), while no such effect could be observed for GROUP (F(1, 29) = 2.964, p = 0.096, ηp2 = .093) and GROUP×SEQUENCE (F(5.752, 166.806) = 1.876, p = 0.091, ηp2 = .061; see Fig 2A).For movement times (see Fig 2B), repeated measures ANOVA revealed a significant effect for SEQUENCE on day 1 (F(6.330, 183.569) = 4.030, p < 0.001, ηp2 = .122) and day 2 (F(5.502, 159.562) = 5.502, p = 0.001, ηp2 = .078). Again, no significant effect was found for GROUP on day 1 (F(1, 29) = 2.477, p = 0.126, ηp2 = .079) or day 2 (F(1, 29) = 0.987, p = 0.329, ηp2 = .033) and no significant interaction effect GROUP×SEQUENCE was observed on day 1 (F(6.330, 183.569) = 1.235, p = 0.289, ηp2 = .041) or day 2 (F(5.502, 159.562) = 0.839, p = 0.533, ηp2 = .028).For sequence specific improvement in reaction times, no differences were found on day 1 (84.00 ms vs. 59.33 ms; t(29) = 0.836, p = 0.410, d = 0.301) and on day 2 (125.94 ms vs. 124.33 ms; t(29) = 0.043, p = 0.966, d = 0.016) between FG and CG. Furthermore, no differences in non-sequence-specific reaction time improvement were found between FG and CG on day 1 (3.78 ms vs. -26.47 ms; t(29) = 1.371, p = 0.181, d = 0.493) and day 2 (-3.13 ms vs. 24.40 ms; t(29) = -1.150, p = 0.259, d = -0.413).Regarding sequence specific improvement in movement times, no differences were found on day 1 (-9.63 ms vs. 5.50 ms; t(29) = -1.855, p = 0.074, d = -0.667) and on day 2 (-4.72 ms vs. -0.90 ms; t(29) = -0.314, p = 0.756, d = -0.113) between FG and CG. Furthermore, no differences in non-sequence-specific movement time improvement were found between FG and CG on day 1 (-32.41 ms vs. -19.67 ms; t(29) = -0.859, p = 0.397, d = -0.309) and day 2 (-19.47 ms vs. -33.83 ms; t(29) = 1.039, p = 0.307, d = 0.373).In terms of retention of sequence-specific performance in reaction times from day 1 to day 2, repeated-measures ANOVA revealed a significant effect for SEQUENCE (F(1, 29) = 7.510, p = 0.010, ηp2 = .206). Post-hoc comparison showed that reaction times during L16 on day 2 were significantly higher compared to reaction times during L15 on day 1 (mean difference (MD) = -43.89 ms, SE = 16.02, p = 0.010, d = -.492). However, there was no significant effect for GROUP (F(1, 29) = 0.146, p = 0.706, ηp2 = .005) and no significant interaction effect GROUP×SEQUENCE (F(1, 29) = 0.605, p = 0.443, ηp2 = .020), indicating that groups showed no difference in the degree of retention.A similar relation was observed for retention of sequence-specific performance in movement times from day 1 to day 2. Repeated-measures ANOVA revealed a significant effect for SEQUENCE (F(1, 29) = 21.254, p < 0.001, ηp2 = .423). Post-hoc comparison showed that reaction times during L16 on day 2 were significantly higher compared to response times during L15 on day 1 (mean difference (MD) = -31.82 ms, SE = 6.90, p < 0.001, d = -.828). No significant effect for GROUP (F(1, 29) = 2.817, p = 0.104, ηp2 = .089) and no significant interaction effect GROUP×SEQUENCE (F(1, 29) = 0.119, p = 0.733, ηp2 = .004) was observed, again indicating that groups showed no difference in the degree of retention.FB and CG did not differ in the number of correctly recalled sequence items on day 1 (W = 152.5, p = 0.200, rbiserial = 0.271) or day 2 (W = 127.5.0, p = 0.775, rbiserial = 0.063). Interestingly however, Spearman rank correlation between sequence-specific improvements in reaction times on day 1 and RECALL1 (rs = 0.465, p = 0.008, 95% CI [0.133, 0.703]) as well as sequence-specific improvements in reaction times on day 2 an RECALL2 (rs = 0.698, p < 0.001, 95% CI [0.177, 0.726]) showed a significant positive relationship when both groups were pooled (see Fig 3). When both groups were separated, FG did not show a significant correlation on day 1 (rs = 0.380, p = 0.147, 95% CI [-0.143, 0.737]) but on day 2 (rs = 0.710, p = 0.002, 95% CI [0.330, 0.892]), whereas CG showed significant correlations both on day 1 (rs = 0.616, p = 0.0015, 95% CI [0.151, 0.858]) and day 2 (rs = 0.662, p = 0.007, 95% CI [0.226, 0.877]).
Fig 3
Positive association between the number of correctly recalled items of the CWB-SRTT learning sequence and sequence-specific improvement in reaction times.
Spearman rank-correlation between sequence recall and sequence-specific improvement in reaction times for the pooled sample on day 1 and day 2. Furthermore, these correlations were calculated separately for FG and CG on each learning day. This figure was created with Biorender.com.
Positive association between the number of correctly recalled items of the CWB-SRTT learning sequence and sequence-specific improvement in reaction times.
Spearman rank-correlation between sequence recall and sequence-specific improvement in reaction times for the pooled sample on day 1 and day 2. Furthermore, these correlations were calculated separately for FG and CG on each learning day. This figure was created with Biorender.com.However, this observation could not be confirmed for movement times on day 1 (rs = -0.025, p = 0.894, 95% CI [-0.376, 0.332]) or day 2 (rs = -0.115, p = 0.537, 95% CI [0.177, 0.726]).
Discussion
In the present study, we aimed to investigate potential motor transfer effects on complex serial reaction time task performance by comparing football players (FG) and non-athletes (CG) in their ability to perform and learn a complex whole-body serial reaction time task (CWB-SRTT). We analyzed both movement and reaction times separately to disentangle potential modulations underlying CWB-SRTT performance. When comparing CG and FG, initial reaction and movement times did not differ significantly between groups. Furthermore, there were no differences in sequence-specific or non-sequence-specific improvements between CG with FG. Analysis of learning rates between CG and FG did not reveal any significant differences between groups at either day 1 or day 2 for both movement and reaction time. Although we found a significant effect for SEQUENCE on retention rates of movement and reaction times, we were unable to demonstrate a significant interaction between GROUP and SEQUENCE. These results suggest that there were no significant differences in retention rates between groups. FG and CG did not differ in the number of correctly recalled test items. However, when pooling FG and CG, correlation analysis revealed a significant positive correlation between the number of correctly recalled items and sequence-specific improvement in reaction times but not movement times on both training days.Given the similarity between football-typical movement patterns and motor requirements of the CWB-SRTT [12], we expected better initial performance of FG. Although FG reaction and movement times were faster compared to CG, these differences were not significant. Accordingly, we did not observe motor transfer effects of football-specific performance on initial CWB-SRTT performance. In general, athletes of various sports disciplines exhibit better reaction times, when compared to non-athletes [17, 18]. However, and in line with the present findings, such differences are closely related to task familiarity [19, 20]. Therefore, although the similarities between football-specific movement patterns and the CWB-SRTT are present in terms of rapid motor actions and reactions of lower extremities, the requirements potentially differ in terms of visuomotor information integration [10]. For this reason, a possible explanation for the lack of significant differences in initial performance is that both groups were naïve to the task. CWB-SRTT does contain motor elements that resemble those of football. Nevertheless, the task performed here is not a typical component of football training regimes. One might argue that the level of expertise plays a substantial role in potential motor transfer effects on initial CWB-SRTT performance. We consider this unlikely since it was shown that football players with different competition levels do not significantly differ in reaction times [21]. Contrasting results exist, but only concerning reaction time in general motor inhibition tasks [13]. On average, reaction and movement times of FG were ~25 ms faster compared to CG. Both reaction and movement times have a considerable impact on athletic performance, as both measures are closely related to overall sensorimotor capacity [22]. Therefore, it is not surprising that FG showed faster reaction and movement times compared to CG. An additional factor that might affect motor transfer is the variability of training schedules [23]. Training variability has previously been shown to have a positive effect on motor transfer in motor sequence learning tasks [24]. However, it is difficult to retrospectively quantify the degree of variability in training regimes of athletes with extensive training backgrounds. In our study, CG trained nonspecifically for 7 years at a maximum workload of 2 hours per week whereas FG trained football-specifically for 17 years at a workload of 6.2 hours per week. In future studies, it seems to be of interest to modulate the variability of a specific training program within longitudinal designs to uncover the influence of variability on motor transfer.Both groups improved their movement times and reaction times during CWB-SRTT on day 1 and day 2. This is in line with previous findings for simple SRTT paradigms (Moisello et al., 2009) [8] as well as for CWB-SRTT (Maudrich et al., 2021) [11]. Similar to our study comparing strength and endurance athletes to healthy controls during CWB-SRTT, we did not detect significant differences in sequence-specific improvements when comparing movement times and reaction times between both groups on either day. Therefore, and contrary to our hypothesis, football players do not show significantly better learning rates in CWB-SRTT compared to non-athletes. Sequence-specific learning is closely associated with the amount of accurately recalled items within the motor sequence [23]. Knowledge of the sequence of items improves response times, as the associated increases in declarative knowledge lead to better anticipation of subsequent stimuli [25]. In our study, both groups did not differ in the amount of correctly recalled items. Interestingly, correlation analyses revealed a significant relationship between the number of correctly recalled items and sequence-specific improvements in reaction time, but not movement time, when both groups were pooled together. An exception was FG, which failed to show this relationship on day 1, but did so on day 2. Based on these results, it can be assumed that improvements in reaction times observed in both groups are predominately related to the proficiency of item recall. Since such a relationship could not be replicated for movement times, we speculate that the observed improvements are predominately cognitive. Sequence-specific improvements in participants might therefore reflect adaptations in the cognitive domain rather than adaptations in the motor domain [10]. Although the initially lower reaction and movement times suggest an inherent motor advantage of FG, this may have been negated by predominantly cognitive-induced improvements during learning of CWB-SRTT as observed in this study. This could account for the lack of differences in sequence-specific improvements between groups as, although the motor overlap between CWB-SRTT and football-specific movement patterns is high, the cognitive overlap, i.e., stimuli-response relationships is potentially low. Recent results demonstrate that non-sport-specific training in a visuomotor task improves cognitive but not sport-specific motor performance within such tasks [26]. Furthermore, unspecific training of general motor skills appears to improve complex motor performance in football players compared to sport-specific training [27]. Thus, despite the fact that gross motor skills are an integral part of sport-specific skill development [28, 29], the environment in which such skills are acquired is crucial to the development of adaptive strategies for adequate regulation of perception and action [26, 30].For non-sequence-specific learning, we did not find differences between CG and FG. Similar to previous research, this may be caused by the structure of sequence and random blocks within the CWB-SRTT. While participants complete multiple identical sequence blocks, the possibility of a transfer from implicit to explicit learning strategies might increase [23]. As implicit learning has been demonstrated to be more effective concerning motor transfer to a novel sequence when compared to explicit learning [31], it is an important aspect to monitor during SRTT. However, no differences were found concerning the number of recalled items on day 1 and day 2 between groups. Therefore, implicit and explicit learners were equally distributed between CG and FG. It seems of value to monitor sequence recall after each block to obtain the time point at which correct item recall is present for the first time, although this might inadvertently induce explicit learning. In any case, future studies should address this aspect to better disentangle the underlying processes of CWB-SRTT learning.
Conclusion
With this study, we extend previous findings on motor transfer effects by showing that football players and non-athletes show no differences in their ability to learn a novel motor sequence using CWB-SRTT. Although faster reaction and movement times were observed among football players compared to non-athletes prior to training, differences between groups were not statistically significant. Furthermore, sequence-specific and non-sequence-specific improvements after learning did not differ between groups. We hypothesize that this might be due to the fact that there did not appear to be any substantial transfer of cognitive-motor football skill to learning the novel movement sequence of the CWB-SRTT. The study of motor transfer effects in complex whole-body movements is important for both recreational and competitive sports. It is often beneficial when a newly learned skill can be applied outside of the specific context in which it was acquired. Furthermore, physical education still wavers between early specialization and general education. In this context, investigating the scope of validity as well as the determinants of motor transfer seems to be a promising approach. Future studies should attempt to extend our research to different tasks and athlete populations to uncover possible principles and mechanisms of motor transfer effects.31 May 2022
PONE-D-22-02272
Whole-Body Sensorimotor Skill Learning in Football Players: No Evidence for Motor Transfer Effects
PLOS ONE
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Comments to the Author1. Is the manuscript technically sound, and do the data support the conclusions?The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes********** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes********** 3. Have the authors made all data underlying the findings in their manuscript fully available?The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes********** 4. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: No********** 5. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: Specific comments, suggestions, and questions are referenced to manuscript line numbers:27-28: Does the phrase “increasing the overlap of motor demands between CWB-SRTT and an athlete group” mean that you were attempting to more closely match the demands of the CWB-SRTT with those imposed by participation in football (i.e., soccer)? If so, “motor demands” are characteristics of the sport activity. The “athlete group” does not possess motor demands.33: Replace “as well as” with “nor” for consistency with “did not reveal any differences…”39: The term “motor transfer” needs to be more clearly defined. An “athlete advantage over non-athletes when learning” does not define motor transfer.49-50: The first sentence of the manuscript seems incomplete and is a bit unclear. Don’t you mean “the extent to which specific athlete performance capabilities exhibited during participation in a given sport-related activity translate to superior motor performance in a somewhat different activity”? The content of the sentence that follows seems to indicate that is what you intend to convey.64-65: The extent to which a person has learned a motor sequence could be determined without consideration of response speed (i.e., proportion of correct motor responses). Are you suggesting that faster reaction is an indicator of superior motor sequence learning?85-86: Redundant content. The is no need to repeat the information presented in prior text.90: “Athletes from several sports can be considered as potential study populations…”91-93, 100-101: Football (i.e., soccer) involves execution of motor sequences that are highly unpredictable, which leads to implicit learning of innumerable combinations, rather than explicit learning of specific sequences. This distinction between football performance in a competitive environment and th27-28: Does the phrase “increasing the overlap of motor demands between CWB-SRTT and an athlete group” mean that you were attempting to more closely match the demands of the CWB-SRTT with those imposed by participation in football (i.e., soccer)? If so, “motor demands” are characteristics of the sport activity. The “athlete group” does not possess motor demands.33: Replace “as well as” with “nor” for consistency with “did not reveal any differences…”39: The term “motor transfer” needs to be more clearly defined. An “athlete advantage over non-athletes when learning” does not define motor transfer.49-50: The first sentence of the manuscript seems incomplete and is a bit unclear. Don’t you mean “the extent to which specific athlete performance capabilities exhibited during participation in a given sport-related activity translate to superior motor performance in a somewhat different activity”? The content of the sentence that follows seems to indicate that is what you intend to convey.64-65: The extent to which a person has learned a motor sequence could be determined without consideration of response speed (i.e., proportion of correct motor e nature of the CWB-SRTT needs to be emphasized. Furthermore, references to “motor actions, motor transfer, and motor skill” fail to acknowledge the complex “cognitive-motor” integration process that is required for efficient performance of whole-body movement sequences.147-160: Apparently, 12 movements were performed during each “block” (Lines 129-131), which are also referred to as “learning sequences” and “random sequences” in the Figure 1 legend. I interpret this to mean that a total of 204 movements were performed during the Day 1 and Day 2 sessions. This information should be provided.171: Why wasn’t a Bonferroni alpha-level correction used for multiple comparisons (i.e., 2 separate ANOVAs for reaction time and movement time)?280: Delete the word “Both” at the beginning of the sentence.284: I suggest replacing the phrase “comparably large intersection between” with “similarity between…”286: I suggest replacing the word “lower” (which could be interpreted as a negative finding) with “faster…”294: Specify “a possible explanation for the lack of significant differences…”304: I suggest replacing the word “lower” (which could be interpreted as a negative finding) with “faster…”318-319: The preceding content did not clearly provide an explanation for why you expected football players to demonstrate better learning rates for than non-athletes for a specific sequence of movement cues. I fail to see the relevance of sequence-specific learning to the high degree of uncertainty about the complex motor actions that will need to be rapidly executed in a competitive sport environment.330-337: I agree that the sequence-specific improvements probably represent a cognitive adaptation in memory processes, but “sensorimotor processes” are not distinct from cognitive processes. The content of this sentence implies that the cognitive domain is distinct from the sensorimotor domain.355: I suggest replacing the phrase “In any way” with “In any case…”360-361: The content of this sentence is very confusing. Suggested rewording: “Although faster reaction and movement times were observed among football players compared to non-athletes prior to training, differences between groups were not statistically significant for either random or sequence-specific movement cues.”362-363: Suggested rewording for greater clarity: “There did not appear to be any substantial transfer of cognitive-motor football skill to learning the novel movement sequences of the CWB-SRTT.”********** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.If you choose “no”, your identity will remain anonymous but your review may still be made public.Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: Yes: Gary B. Wilkerson[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.3 Jun 2022Response to ReviewersAdditional Editor Comments:Dear authors,I approached 21 potential reviewers, but found only one willing to provide an assessment of the paper. Therefore I took a careful look at the manuscript myself and feel confident to go forward with only 1 review. The paper is well structured and describes a well conducted study. There are a few points that could be explained in more detail, but generally the paper is publishable.One suggestion I have, would be a more detailed description of the control group. What sport were they doing and on what level?Our response: Thank you for this suggestion. We added this information:“Non-athletes did not participate in a specific sport in an organized manner apart from general recreational activities (e.g., running, fitness and cycling).” (lines 114-115)Please also address the points of the other reviewer carefully.Reviewers' comments:Reviewer #1: Specific comments, suggestions, and questions are referenced to manuscript line numbers:27-28: Does the phrase “increasing the overlap of motor demands between CWB-SRTT and an athlete group” mean that you were attempting to more closely match the demands of the CWB-SRTT with those imposed by participation in football (i.e., soccer)? If so, “motor demands” are characteristics of the sport activity. The “athlete group” does not possess motor demands.Our response: Thank you for pointing this out. We changed the sentence accordingly.“In the present study, we aimed to extend this research by increasing the overlap of task requirements between CWB-SRTT and a specific sports discipline.” (lines 25-26)33: Replace “as well as” with “nor” for consistency with “did not reveal any differences…”Our response: Done.39: The term “motor transfer” needs to be more clearly defined. An “athlete advantage over non-athletes when learning” does not define motor transfer.Our response: You are correct. We defined motor transfer more clearly.“Motor transfer refers to the transferability of a specific motor skill to different motor tasks” (line 38)49-50: The first sentence of the manuscript seems incomplete and is a bit unclear. Don’t you mean “the extent to which specific athlete performance capabilities exhibited during participation in a given sport-related activity translate to superior motor performance in a somewhat different activity”? The content of the sentence that follows seems to indicate that is what you intend to convey.Our response: Again, you are correct. Your suggestion makes this part clearer.“There is an ongoing debate about the extent to which specific athletic performance capabilities exhibited during participation in a given sport-related activity translate to superior motor performance in an unrelated motor scenario.” (lines 47-49)64-65: The extent to which a person has learned a motor sequence could be determined without consideration of response speed (i.e., proportion of correct motor responses). Are you suggesting that faster reaction is an indicator of superior motor sequence learning?64-65: The extent to which a person has learned a motor sequence could be determined without consideration of response speed (i.e., proportion of correct motor e nature of the CWB-SRTT needs to be emphasized. Furthermore, references to “motor actions, motor transfer, and motor skill” fail to acknowledge the complex “cognitive-motor” integration process that is required for efficient performance of whole-body movement sequences.Our response: Thank you for this comment. Indeed, faster reaction times is not the only indicator of motor sequence learning. Successful sequence learning is also determined by the proportion of correct motor responses. We refined the statement accordingly.“During SRTT, participants are presented with spatially separated visual stimuli. Participants must respond as accurately and as quickly as possible with a motor action, e.g., pressing a button, corresponding to the sequence of the presented stimuli. Performance of motor sequence learning is measured by the proportion of correct responses and the reaction time to the presented visual cues. Consequently, SRTT performance relies on the successful integration of motor and cognitive processes.” (lines 62-67)85-86: Redundant content. The is no need to repeat the information presented in prior text.Our response: We deleted this redundancy.90: “Athletes from several sports can be considered as potential study populations…”Our response: Changes were made accordingly.91-93, 100-101: Football (i.e., soccer) involves execution of motor sequences that are highly unpredictable, which leads to implicit learning of innumerable combinations, rather than explicit learning of specific sequences. This distinction between football performance in a competitive environment and thOur response: Unfortunately, parts of this comment are missing in the revision letter. However, we think that this comment relates to another comment of yours (318-319: The preceding content did not clearly provide an explanation for why you expected football players to demonstrate better learning rates for than non-athletes for a specific sequence of movement cues. I fail to see the relevance of sequence-specific learning to the high degree of uncertainty about the complex motor actions that will need to be rapidly executed in a competitive sport environment.). We hope that our answer to the latter comment (318-319) also clarifies concerns raised here.147-160: Apparently, 12 movements were performed during each “block” (Lines 129-131), which are also referred to as “learning sequences” and “random sequences” in the Figure 1 legend. I interpret this to mean that a total of 204 movements were performed during the Day 1 and Day 2 sessions. This information should be provided.Our response: This information was added to the experimental procedure.“FG and CG completed 15 consecutive sequence blocks and one random block before and one random block after all sequence blocks on each day (Figure 1A). This leads to a total of 204 motor responses for each experimental day.” (lines 128-130)171: Why wasn’t a Bonferroni alpha-level correction used for multiple comparisons (i.e., 2 separate ANOVAs for reaction time and movement time)?Our response: You are correct, this has to be done. We corrected this point in the manuscript. However, all results remain the same.“For the separate repeated-measures ANOVAs investigating reaction time or movement time on day 1 and day 2 the statistical threshold was Bonferroni adjusted to p < 0.025 to account for multiple comparisons.” (lines 190-192)280: Delete the word “Both” at the beginning of the sentence.Our response: Done.284: I suggest replacing the phrase “comparably large intersection between” with “similarity between…”Our response: This was done.286: I suggest replacing the word “lower” (which could be interpreted as a negative finding) with “faster…”Our response: Done.294: Specify “a possible explanation for the lack of significant differences…”Our response: Done.304: I suggest replacing the word “lower” (which could be interpreted as a negative finding) with “faster…”Our response: Done.318-319: The preceding content did not clearly provide an explanation for why you expected football players to demonstrate better learning rates for than non-athletes for a specific sequence of movement cues. I fail to see the relevance of sequence-specific learning to the high degree of uncertainty about the complex motor actions that will need to be rapidly executed in a competitive sport environment.Our response: You are correct that sequence-specific learning and complex, unpredictable sporting demands such as those in football initially appear unrelated.However, the initial challenges of CWB-SRTT are also classified as "unpredictable" up to the point of recognizing a sequence, i.e., the transfer from implicit to explicit learning (Robertson, 2007). The idea behind our hypothesis derives rather from the overlap of the motor component of the task, i.e., the rapid, goal-directed activation of the lower extremities. Especially due to the unpredictability in the football context, football players show a superior repertoire of movement patterns and thus motor ability in this point, which, as hypothesized, could manifest itself in a positive learning performance within the CWB-SRTT. We specified this point in the manuscript where we mention our hypothesis of the study.“In football, offensive, as well as defensive game decisions, are realized in the range of a few hundredths of a second via motor actions of the lower extremities (Vijayendra and Neelam, 2020). Accordingly, reaction time is an important determinant of football performance (Vijayendra and Neelam, 2020). Several studies illustrate this by demonstrating that the cognitive processing of soccer players, in the form of improved reaction times during general motor inhibition tasks (Verburgh et al., 2014) as well as faster stimulus processing times and improved attentional performance (Vestberg et al., 2017), is increased compared to control groups. Furthermore, the motor related overlap between CWB-SRTT and football performance, i.e., the rapid, goal-directed activation of the lower extremities, is considerably high. In sum, football players might therefore hold an advantage in learning a novel sensorimotor task such as the CWB-SRTT.”Consequently, the purpose of this study was to examine the difference between football players and non-athletes during CWB-SRTT performance on two separate days to investigate potential motor transfer of football skills when learning a new motor skill using CWB-SRTT. Based on the outlined body of research, we hypothesized improved initial performance as well as improved learning and retention rates for football players compared to non-athletes.“ (lines 88-101)330-337: I agree that the sequence-specific improvements probably represent a cognitive adaptation in memory processes, but “sensorimotor processes” are not distinct from cognitive processes. The content of this sentence implies that the cognitive domain is distinct from the sensorimotor domain.Our response: We agree that the term „sensorimotor domain” is slightly misleading as cognitive processes are implied in this term. Therefore, to more accurately describe our findings we changed it to “motor domain” in this specific passage. Our line of argumentation relates to the fact that the motor component, i.e., movement patterns of the lower extremity, shows considerable similarity concerning CWB-SRTT and football performance. As you correctly pointed out the cognitive demands of CWB-SRTT and football in a competitive sports environment differ.“Sequence-specific improvements in participants might therefore reflect adaptations in the cognitive domain rather than adaptations in the motor domain (Mizuguchi et al., 2019). Although the initially lower reaction and movement times suggest an inherent motor advantage of FG, this may have been negated by predominantly cognitive-induced improvements during learning of CWB-SRTT as observed in this study. This could account for the lack of differences in sequence-specific improvements between groups as, although the motor overlap between CWB-SRTT and football-specific movement patterns is high, the cognitive overlap, i.e., stimuli-response relationships is potentially low.” (lines 330-337)355: I suggest replacing the phrase “In any way” with “In any case…”Our response: Done.360-361: The content of this sentence is very confusing. Suggested rewording: “Although faster reaction and movement times were observed among football players compared to non-athletes prior to training, differences between groups were not statistically significant for either random or sequence-specific movement cues.”Our response: Thank you for the suggestion. We used it to improve the wording of this sentence.„Although faster reaction and movement times were observed among football players compared to non-athletes prior to training, differences between groups were not statistically significant. Furthermore, sequence-specific and non-sequence-specific improvements after learning did not differ between groups.” (lines 358-361)362-363: Suggested rewording for greater clarity: “There did not appear to be any substantial transfer of cognitive-motor football skill to learning the novel movement sequences of the CWB-SRTT.”Our response: Thank you. We changed the sentence accordingly.“We hypothesize that this might be due to the fact that there did not appear to be any substantial transfer of cognitive-motor football skill to learning the novel movement sequence of the CWB-SRTT.” (lines 361-363)Submitted filename: Response_rev1.docxClick here for additional data file.30 Jun 2022Whole-body sensorimotor skill learning in football players: No evidence for motor transfer effectsPONE-D-22-02272R1Dear Dr. Maudrich,We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.An invoice for payment will follow shortly after the formal acceptance. 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Authors: Nobuaki Mizuguchi; Tom Maudrich; Rouven Kenville; Daniel Carius; Dennis Maudrich; Arno Villringer; Patrick Ragert Journal: Neuroimage Date: 2019-04-25 Impact factor: 6.556
Authors: Damiano Formenti; Alessio Rossi; Tindaro Bongiovanni; Francesco Campa; Luca Cavaggioni; Giampietro Alberti; Stefano Longo; Athos Trecroci Journal: Int J Environ Res Public Health Date: 2021-02-18 Impact factor: 3.390