1. EEG-based classification accuracy for across- and within-expression discrimination of facial identity with temporally cumulative data (50–650 ms after stimulus onset).
EEG-based classification accuracy for across- and within-expression discrimination of facial identity with temporally cumulative data (50–650 ms after stimulus onset). Accuracy corresponding to neutral and happy faces are separately shown for (A) group-based ERP data and (B) single-participant data (i.e., pattern classification was conducted individually for each participant and, then, its results averaged across participants). The plots display (A) the results of permutation tests (red solid and dash lines indicate average accuracy and 99% confidence intervals estimated with 103 permutations) and (B) the distribution of single-participant data (green and purple solid lines indicate medians, boxes represent 1st and 3rd quartiles, whiskers represent minimum and maximum accuracy values, points represent individual participants’ values and red solid lines indicate chance-level discrimination).
Dan Nemrodov et al. eNeuro 2018;5:ENEURO
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