Fig. 2.

Accuracy of subject identification for Pearson, geodesic, and linear classifier approaches as a function of the number of available runs available for training when (a) BOLD, (b) HbO, (c) HbR, and (d) HbT signals are used separately. The condition “All” refers to the case in which one run was used for testing and the remaining runs were used for training. Due to the pruning criteria, the number of runs per participant varied from three to five for BOLD and four to six for fNIRS. Each distribution depicts all observed results in detail (300 values in total). In each violin plot, the white circle represents the median, and shaded regions indicate the first and third quartiles (as a typical boxplot). The horizontal lines indicate the accuracy values obtained across all trials, and their lengths are proportional to the frequency of each obtained accuracy within the distribution.