Enhancing EEG-based attachment style prediction: unveiling the impact of feature domains

Enhancing EEG-based attachment style prediction: unveiling the impact of feature domains

IntroductionAttachment styles are crucial in human relationships and have been explored through neurophysiological responses and EEG data analysis. This study investigates the potential of EEG data in predicting and differentiating secure and insecure attachment styles, contributing to the understan...

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Bibliographic Details
Main Authors: Ilan Laufer, Dor Mizrahi, Inon Zuckerman
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-01-01
Series:Frontiers in Psychology
Subjects:
EEG data analysis
attachment styles
machine learning
feature domains
neurophysiological responses
Online Access:https://www.frontiersin.org/articles/10.3389/fpsyg.2024.1326791/full

Internet

https://www.frontiersin.org/articles/10.3389/fpsyg.2024.1326791/full

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