Ma, Yan and Tang, Yiou and Zeng, Yang and Ding, Tao and Liu, Yifu (2023) An N400 identification method based on the combination of Soft-DTW and transformer. Frontiers in Computational Neuroscience, 17. ISSN 1662-5188
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Abstract
As a time-domain EEG feature reflecting the semantic processing of the human brain, the N400 event-related potentials still lack a mature classification and recognition scheme. To address the problems of low signal-to-noise ratio and difficult feature extraction of N400 data, we propose a Soft-DTW-based single-subject short-distance event-related potential averaging method by using the advantages of differentiable and efficient Soft-DTW loss function, and perform partial Soft-DTW averaging based on DTW distance within a single-subject range, and propose a Transformer-based ERP recognition classification model, which captures contextual information by introducing location coding and a self-attentive mechanism, combined with a Softmax classifier to classify N400 data. The experimental results show that the highest recognition accuracy of 0.8992 is achieved on the ERP-CORE N400 public dataset, verifying the effectiveness of the model and the averaging method.
Item Type: | Article |
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Subjects: | Open Research Librarians > Medical Science |
Depositing User: | Unnamed user with email support@open.researchlibrarians.com |
Date Deposited: | 27 Mar 2023 09:02 |
Last Modified: | 06 Mar 2024 04:25 |
URI: | http://stm.e4journal.com/id/eprint/471 |