Fig. 5.

Classification performance, computed as the area under the ROC curve, for a support-vector machine (SVM) trained using 5 s of pre-stimulus data to classify responses and misses. Input features to the classifier were microstate parameters or the theta–alpha ratio, individually or combined. Within each group of grouped scatter box plots, inner boxes represent the standard error of the mean, outer boxes represent the standard deviation. The mean is shown by a yellow line, the median is shown by a green line (where distinct from the mean), and individual participants are shown as dots. Microstate parameters were able to predict responsiveness at an individual trial level across subjects, with a performance similar to that of the theta-alpha ratio