Multi-domain feature of event-related potential extracted by nonnegative tensor factorization: 5 vs. 14 electrodes EEG data

12Citations
Citations of this article
16Readers
Mendeley users who have this article in their library.
Get full text

Abstract

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.

Cite

CITATION STYLE

APA

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

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free