Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

M phase phosphorylation of the epigenetic regulator UHRF1 regulates its physical association with the deubiquitylase USP7 and stability.

Proceedings of the National Academy of Sciences of the United States of America·2012

Same author

Biosynthesis of ethyl oleate, a primer pheromone, in the honey bee (Apis mellifera L.).

Insect biochemistry and molecular biology·2012

Same author

Co-delivery strategies based on multifunctional nanocarriers for cancer therapy.

Current drug metabolism·2012

Same author

Efficacy of gemifloxacin for the treatment of experimental Staphylococcus aureus keratitis.

Journal of ocular pharmacology and therapeutics : the official journal of the Association for Ocular Pharmacology and Therapeutics·2012

Same author

Expression profile analysis of the polygalacturonase-inhibiting protein genes in rice and their responses to phytohormones and fungal infection.

Plant cell reports·2012

Same author

Characterizing natural dissolved organic matter in a freshly submerged catchment (Three Gorges Dam, China) using UV absorption, fluorescence spectroscopy and PARAFAC.

Water science and technology : a journal of the International Association on Water Pollution Research·2012

Same journal

Analysis of End-Tidal CO2 Variability During Plateau Waves Episodes: An Information Theoretic Approach<sup></sup>.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025

Same journal

AI and Tomosynthesis for Breast Cancer Molecular Subtyping: A step toward precision medicine<sup></sup>.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025

Same journal

Towards Sustainable Protein Recovery from Biological Waste: Assessing Polyethersulfone-based Microfiltration.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025

Same journal

Analysis of the cardiovascular response to standardized polymicrobial peritonitis experimental model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025

Same journal

Automated Wrist Ultrasound Image Bone Enhancement and Segmentation Using Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025

Same journal

A Deep Learning approach for Depressive Symptoms assessment in Parkinson's disease patients using facial videos.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025

See all related articles

Search research articles

Related Experiment Video

Updated: Oct 10, 2025

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

EEG-based Emotion Recognition Using Graph Convolutional Network with Learnable Electrode Relations.

Ming Jin, Hao Chen, Zhunan Li

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|December 11, 2021

Summary

This summary is machine-generated.

This study introduces a novel Graph Convolutional Network (GCN) with learnable electrode relations (LR-GCN) for more accurate electroencephalography (EEG) based emotion recognition. The method automatically learns optimal brain connections, significantly improving performance.

More Related Videos

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Published on: June 26, 2012

Related Experiment Videos

Last Updated: Oct 10, 2025

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Published on: June 26, 2012

Area of Science:

Neuroscience
Computer Science
Artificial Intelligence

Background:

Electroencephalography (EEG) is crucial for emotion recognition in affective computing.
Graph Convolutional Networks (GCNs) show promise but rely on subjective adjacency matrices for electrode relationships.
Optimizing electrode relationships is key for enhancing GCN performance in emotion recognition tasks.

Purpose of the Study:

To develop a Graph Convolutional Network (GCN) with automatically learned electrode relationships (LR-GCN) for improved EEG-based emotion recognition.
To address the limitations of empirical and subjective adjacency matrix settings in existing GCN models.
To enhance the accuracy and reliability of emotion recognition by extracting task-relevant brain connectivity patterns.

Main Methods:

Proposed a novel LR-GCN model that learns the adjacency matrix automatically through self-attention and gradient propagation.
Utilized self-attention mechanisms for forward updating the Laplacian matrix.
Employed gradient propagation for backward updating the adjacency matrix to optimize electrode relationships.

Main Results:

The LR-GCN model achieved superior emotion recognition accuracy compared to methods using fixed or feature-based adjacency matrices.
Subject-dependent experiments on the SEED database yielded high accuracies: 94.72% (DE features) and 85.24% (PSD features).
Visualization of the learned Laplacian matrix revealed enhanced brain connections associated with vision, hearing, and emotion processing.

Conclusions:

The proposed LR-GCN effectively learns electrode relationships, leading to significant improvements in EEG-based emotion recognition.
Automatic learning of brain connectivity patterns offers a more objective and effective approach than traditional methods.
The findings highlight the potential of adaptive GCNs for understanding complex brain dynamics in affective computing.