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CORRECTION article

Front. Neurosci., 28 November 2023
Sec. Auditory Cognitive Neuroscience
Volume 17 - 2023 | https://doi.org/10.3389/fnins.2023.1283644

Corrigendum: Multi-channel EEG emotion recognition using Residual Graph Attention Neural Network

This article is a correction to:

  1. Multi-channel EEG emotion recognition through residual graph attention neural network

    1. Read original article
\r\nHao Chao Hao Chao*Yiming CaoYiming CaoYongli LiuYongli Liu
  • College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, China

A corrigendum on
Multi-channel EEG emotion recognition through residual graph attention neural network

Chao H, Cao Y and Liu Y (2023). Front. Neurosci. 17:1135850. doi: 10.3389/fnins.2023.1135850

In the published article, there was an error in the Funding statement. The fund name is incorrect and the fund number is missing. The original text is: Programs for Science and Technology Development of Henan province. The correct Funding statement appears below.

Funding

Programs for Science and Technology Development of Henan province No. 222102210078.

The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Keywords: EEG, emotion recognition, residual network, graph attention neural network, feature fusion

Citation: Chao H, Cao Y and Liu Y (2023) Corrigendum: Multi-channel EEG emotion recognition using Residual Graph Attention Neural Network. Front. Neurosci. 17:1283644. doi: 10.3389/fnins.2023.1283644

Received: 26 August 2023; Accepted: 13 November 2023;
Published: 28 November 2023.

Approved by:

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Copyright © 2023 Chao, Cao and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Hao Chao, Y2hhb2hhbzE5ODEmI3gwMDA0MDsxNjMuY29t

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.