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Table 4 EEG Features Predicting Trial Accuracy in SZ

From: Machine learning identification of EEG features predicting working memory performance in schizophrenia and healthy adults

Location WM stage Frequency Feature Weight
Central Encode gamma −1.169
Frontal Encode gamma −0.916
Central Retrieve beta 0.704
Central Retain theta 1 −0.611
Central Retrieve theta 1 −0.601
Frontal Retrieve gamma −0.600
Central Encode alpha 0.409
Occipital Retrieve theta 1 −0.371
Occipital Retain beta −0.350
Central Baseline theta 1 −0.204
Frontal Retain theta 1 −0.168
Frontal Encode theta 1 −0.032
Frontal Encode theta 2 −0.029
Occipital Retain gamma −0.001
  1. Features extracted by 1-norm SVM to classify correct vs. incorrect trials in SZ. Model based on simultaneous entry of 60 EEG features with correct trials labeled 1 and incorrect labeled −1. All other features weighted at 0