As nonnegative tensor factorization (NTF) is particularly useful for the problem of underdetermined linear transform model, we performed NTF on the EEG data recorded from 14 electrodes to extract the multi-domain feature of N170 which is a visual event-related potential (ERP), as well as 5 typical electrodes in occipital-temporal sites for N170 and in frontal-central sites for vertex positive potential (VPP) which is the counterpart of N170, respectively. We found that the multi-domain feature of N170 from 5 electrodes was very similar to that from 14 electrodes and more discriminative for different groups of participants than that of VPP from 5 electrodes. Hence, we conclude that when the data of typical electrodes for an ERP are decomposed by NTF, the estimated multi-domain feature of this ERP keeps identical to its counterpart extracted from the data of all electrodes used in one ERP experiment. © 2012 Springer-Verlag.
CITATION STYLE
Cong, F., Phan, A. H., Astikainen, P., Zhao, Q., Hietanen, J. K., Ristaniemi, T., & Cichocki, A. (2012). Multi-domain feature of event-related potential extracted by nonnegative tensor factorization: 5 vs. 14 electrodes EEG data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7191 LNCS, pp. 502–510). https://doi.org/10.1007/978-3-642-28551-6_62
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