EEG decoding for effects of visual joint attention training on ASD patients with interpretable and lightweight convolutional neural network

Jianling Tan ¹, Yichao Zhan ², Yi Tang ¹

⁰Department of Biomedical Engineering, Chongqing University of Posts and Telecommunications, Chongqing, 400065 China.

Cognitive Neurodynamics +

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June 3, 2024

View abstract on PubMed

Summary

Joint attention training enhances social cognitive abilities in autism spectrum disorder (ASD). This study used EEGNet to show improved brain responses, particularly in the parietal lobe, after training for individuals with ASD.

Area Of Science

Neuroscience
Cognitive Science
Developmental Psychology

Background

Visual joint attention is crucial for social and language development in humans.
Individuals with autism spectrum disorder (ASD) often exhibit deficits in visual joint attention.
EEGNet is an effective model for decoding electroencephalogram (EEG) signals, but its application in ASD attentional training is underexplored.

Purpose Of The Study

To investigate the effectiveness of joint attention training in improving visual attention in individuals with ASD.
To utilize EEGNet and saliency mapping to decode P300 signals and visualize cognitive changes during visual attention tasks in ASD patients.

Main Methods

EEGNet was employed to decode P300 signals elicited during a joint attention training paradigm.
Saliency map analysis was used to visualize the spatial and temporal patterns of brain activity.
P300 signal characteristics, including latency and classification contribution, were analyzed before and after training in social and non-social scenarios.

Main Results

The parietal lobe, particularly the Pz electrode, showed significant contribution to EEG classification.
The time window of 300-500 ms, peaking around 300 ms, was most critical for EEG classification.
Joint attention training enhanced gradient contribution at 300 ms specifically in social scenarios.
Increased training led to a forward shift in P300 latency in social, but not non-social, scenarios for ASD patients.

Conclusions

Joint attention training can effectively improve cognitive abilities related to social characteristics in individuals with ASD.
EEGNet and saliency mapping provide valuable insights into the neural mechanisms underlying attentional improvements in ASD.
The findings highlight the potential of targeted interventions to enhance social responsiveness in autism spectrum disorder.

Keywords:

Autism spectrum disorder EEGNet Electroencephalogram Feature visualization Joint attention training