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ORIGINAL RESEARCH article

Front. Neurosci.
Sec. Neuroscience Methods and Techniques
Volume 18 - 2024 | doi: 10.3389/fnins.2024.1434444

Who is WithMe? EEG features for attention in a visual task, with auditory and rhythmic support

Provisionally accepted
Renata Turkes Renata Turkes 1*Steven Mortier Steven Mortier 1Jorg De Winne Jorg De Winne 2Dick Botteldooren Dick Botteldooren 2Paul Devos Paul Devos 2Steven Latre Steven Latre 1Tim Verdonck Tim Verdonck 1
  • 1 University of Antwerp, Antwerp, Belgium
  • 2 Ghent University, Ghent, East Flanders, Belgium

The final, formatted version of the article will be published soon.

    The study of attention has been pivotal in advancing our comprehension of cognition. The goal of this study is to investigate which EEG data representations or features are most closely linked to attention, and to what extent they can handle the cross-subject variability. We explore the features obtained from the univariate time series from a single EEG channel, such as time domain features and recurrence plots, as well as representations obtained directly from the multivariate time series, such as global field power or functional brain networks. To address the cross-subject variability in EEG data, we also investigate persistent homology features that are robust to different types of noise. The performance of the different EEG representations is evaluated with the Support Vector Machine (SVM) accuracy on the WithMe data derived from a modified digit span experiment, and is benchmarked against baseline EEG-specific models, including a deep learning architecture known for effectively learning task-specific features.

    Keywords: EEG, visual attention, Auditory support, rhythmic support, topological data analysis

    Received: 17 May 2024; Accepted: 30 Oct 2024.

    Copyright: © 2024 Turkes, Mortier, De Winne, Botteldooren, Devos, Latre and Verdonck. 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) or licensor 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: Renata Turkes, University of Antwerp, Antwerp, Belgium

    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.