Statistical analysis
hand dexterity
REGRESSION, CONTRACTION
To ensure the homogeneity between groups regarding age, chopsticks frequency and ability, and hand dexterity, a two-sample t-test was conducted for each variable. In addition, we also tested the balance of the two groups in terms of baseline performance by submitting the S1 scores of GA, FL, and MD to a two-sample t-test.The performance scores were baseline corrected (subtracting the S1 scores from the performance scores at each session). Subsequently, single-sample t-tests were employed to evaluate whether groups exhibited a significant learning rate (contrasting the baseline-corrected scores at S6 against 0), and two-sample t-tests to evaluate whether the extent of the learning rate was different across the two groups (contrasting between groups the baseline-corrected scores at S6).Moving to the EMG analysis, two sample t-tests were conducted to ensure that the initial EMG scores did not differ between groups. Furthermore, three Repeated Measures ANOVAs (one for each muscle) were applied on the average contraction amplitude, with Time as a within-subject factor and Group as a between-subjects factor. The similarity was analyzed to evaluate whether our participants approached the muscular pattern of the model during the training. In case of significant effects, direct comparisons were performed within each group via paired t-tests to explore the differences between the initial (S1) and the final (S6) values. As a note, three subjects had instability of one of the EMG electrodes (1 OP in AOT, 1 OP in CTRL, 1 ADM in CTRL) during the recording. Thus, they have not been included in the relative analyses.Finally, linear regression analyses were performed to evaluate whether the behavioral amelioration could be explained by the EMG parameters found to be modulated over the training. We standardized the behavioral improvement scores to weigh the absolute increase over the average performance using the formula (Δ = (S6 − S1)/(S6 + S1)). As similarity was already expressed as a percentage, it was enough to compute the difference between the initial and final values (Δ = S6 − S1) to obtain a standardized metric of the convergence toward the model.The linear regression analyses followed three different hypotheses:The initial level of similarity could determine the initial behavioral performance. Should this be the case, the similarity would act as a determinant of the current dexterity of the participant;The initial level of similarity could determine the behavioral improvement over the training. Should this be the case, the similarity would act as a determinant of the subject's potential for learning;The gain in similarity over the training could explain the behavioral improvement over the training. Should this be the case, the degree of convergence toward the model would act as a determinant for the extent of learning.Considering that the reach-to-place action is composed of different phases (Reaching, Holding, and Transport) and involves different muscles (OP, FDI, and ADM), we repeated the linear regression analysis separately for each phase and muscle, thus weighting the phase- and muscle-specificity in sustaining the behavioral outcome. Given that the number of comparisons here increased to 9, we applied a False Discovery Rate procedure