Fig. 3: Characterization of high-gamma activity (HGA) and low-frequency signals (LFS) during silent-speech attempts.

a 10-fold cross-validated classification accuracy on silently attempted NATO code words when using HGA alone, LFS alone, and both HGA+LFS simultaneously. Classification accuracy using only LFS is significantly higher than using only HGA, and using both HGA+LFS results in significantly higher accuracy than either feature type alone (**P = 4.71 × 10⁻⁴, z = 3.78 for each comparison, two-sided Wilcoxon Rank-Sum test with 3-way Holm-Bonferroni correction). Chance accuracy is 3.7%. Each boxplot corresponds to n = 10 cross-validation folds (which are also plotted as dots) and depicts the median as a center line, quartiles as bottom and top box edges, and the minimum and maximum values as whiskers (except for data points that are 1.5 times the interquartile range). b–e Electrode contributions. Electrodes that appear larger and more opaque provide more important features to the classification model. b, c Show contributions associated with HGA features using a model trained on HGA alone (b) vs using the combined LFS + HGA feature set (c). d, e depict contributions associated with LFS features using a model trained on LFS alone (d) vs the combined LFS + HGA feature set (e). f Histogram of the minimum number of principal components (PCs) required to explain more than 80% of the total variance, denoted as σ², in the spatial dimension for each feature set over 100 bootstrap iterations. The number of PCs required were significantly different for each feature set (***P < 0.0001, P-values provided in Table S5, two-sided Wilcoxon Rank-Sum test with 3-way Holm-Bonferroni correction). g Histogram of the minimum number of PCs required to explain more than 80% of the variance in the temporal dimension for each feature set over 100 bootstrap iterations (***P < 0.0001, P-values provided in Table S6, two-sided Wilcoxon Rank-Sum test with 3-way Holm-Bonferroni correction, *P < 0.01 two-sided Wilcoxon Rank-Sum test with 3-way Holm-Bonferroni correction). h Effect of temporal smoothing on classification accuracy. Each point represents the median, and error bars represent the 99% confidence interval around bootstrapped estimations of the median. Data to recreate all panels are provided as a Source Data file.