Fig. 3

We applied the machine-learning algorithm (Boruta) to find the most influential EEG features accounting for changes in LF results. The algorithm gives an overall index of the importance of each variable with their respective standard errors and a dichotomic evaluation of “important “(green boxes) or “not important” (red boxes). The solid black line represents the mean, the box edges are the first and third quartiles, and the circles are outliers, defined as outside 1.5 times the interquartile range (whiskers) above the upper quartile and below the lower quartile