For the statistical analysis, we used Generalized Estimating Equations, which is based on the maximum likelihood and which uses Wald’s chi-square test (Wald χ2) to identify the effect of the variable on the generalized linear model, with Bonferroni test as the post hoc test.

We tested the goodness of fit for scale response for both model types, linear and gamma with log link, and we chose the model with the smallest value of the quasi-likelihood under the independence model criterion. For all analyses tested, the gamma model had the best fit. First, we count the number of coefficients (events) classified as such for each WCC strength category. Still, we analyzed HR and SF at different speeds considering the SF as the locomotor task frequency. As the speeds were fixed, they were used as a categorical variable. To investigate if the CLS emerged spontaneously, the speed was the factor and all WCC coefficients for each pair of temporal series (ECG-VL and ECG-GM), at each speed, were considered the dependent variable. Finally, we investigated the entrainment frequencies and the center frequency of the VL (SEMGMNF-VL) and the center frequency of the GM (SEMGMNF-GM) as dependent variables for each WCC strength category.

A posteriori power analysis was performed to confirm a minimum power of 0.8 using the software GLIMMPSE (Munjal et al., 2014).

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