title: Improving N1 classification by grouping EEG trials with phases of pre-stimulus EEG oscillations.
abstract: A reactive brain-computer interface using electroencephalography (EEG) relies on the classification of evoked ERP responses. As the trial-to-trial variation is evitable in EEG signals, it is a challenge to capture the consistent classification features distribution. Clustering EEG trials with similar features and utilizing a specific classifier adjusted to each cluster can improve EEG classification. In this paper, instead of measuring the similarity of ERP features, the brain states during image stimuli presentation that evoked N1 responses were used to group EEG trials. The correlation between momentary phases of pre-stimulus EEG oscillations and N1 amplitudes was analyzed. The results demonstrated that the phases of time-frequency points about 5.3 Hz and 0.3 s before the stimulus onset have significant effect on the ERP classification accuracy. Our findings revealed that N1 components in ERP fluctuated with momentary phases of EEG. We also further studied the influence of pre-stimulus momentary phases on classification of N1 features. Results showed that linear classifiers demonstrated outstanding classification performance when training and testing trials have close momentary phases. Therefore, this gave us a new direction to improve EEG classification by grouping EEG trials with similar pre-stimulus phases and using each to train unit classifiers respectively.
authors: College of Information Science and Technology, Beijing Normal University, No.19, Xinjiekouwai Street, Beijing, 100875 China.
authors: Li
authors: L
authors: Han
authors: College of Information Science and Technology, Beijing Normal University, No.19, Xinjiekouwai Street, Beijing, 100875 China.
authors: Zhang
authors: Z
authors: Liang
authors: College of Information Science and Technology, Beijing Normal University, No.19, Xinjiekouwai Street, Beijing, 100875 China.
authors: Zhang
authors: Z
authors: Jiacai
authors: National Key Lab of Cognitive Neuroscience and Learning, Beijing Normal University, No.19, Xinjiekouwai Street, Beijing, 100875 China.
authors: Wang
authors: W
authors: Changming
authors: College of Information Science and Technology, Beijing Normal University, No.19, Xinjiekouwai Street, Beijing, 100875 China ; National Key Lab of Cognitive Neuroscience and Learning, Beijing Normal University, No.19, Xinjiekouwai Street, Beijing, 100875 China.
authors: Yao
authors: Y
authors: Li
authors: College of Information Science and Technology, Beijing Normal University, No.19, Xinjiekouwai Street, Beijing, 100875 China.
authors: Wu
authors: W
authors: Xia
authors: College of Information Science and Technology, Beijing Normal University, No.19, Xinjiekouwai Street, Beijing, 100875 China.
authors: Guo
authors: G
authors: Xiaojuan
keywords: EEG; LDA; N1; Phase; Wavelets