Application of rapid invisible frequency tagging for brain computer interfaces

Abstract

BACKGROUND: Brain-computer interfaces (BCI) based on steady-state visual evoked potentials (SSVEPs/SSVEFs) are among the most commonly used BCI systems. They require participants to covertly attend to visual objects flickering at specified frequencies. The attended location is decoded online by analysing the power of neuronal responses at the flicker frequency. NEW METHOD: We implemented a novel rapid invisible frequency-tagging technique, utilizing a state-of-the-art projector with refresh rates of up to 1440 Hz. We flickered the luminance of visual objects at 56 and 60 Hz, which was invisible to participants but produced strong neuronal responses measurable with magnetoencephalography (MEG). The direction of covert attention, decoded from frequency-tagging responses, was used to control an online BCI PONG game. RESULTS: Our results show that seven out of eight participants were able to play the pong game controlled by the frequency-tagging signal, with average accuracies exceeding 60 %. Importantly, participants were able to modulate the power of the frequency-tagging response within a 1-second interval, while only seven occipital sensors were required to reliably decode the neuronal response. COMPARISON WITH EXISTING METHODS: In contrast to existing SSVEP-based BCI systems, rapid frequency-tagging does not produce a visible flicker. This extends the time-period participants can use it without fatigue, by avoiding distracting visual input. Furthermore, higher frequencies increase the temporal resolution of decoding, resulting in higher communication rates. CONCLUSION: Using rapid invisible frequency-tagging opens new avenues for fundamental research and practical applications. In combination with novel optically pumped magnetometers (OPMs), it could facilitate the development of high-speed and mobile next-generation BCI systems.

Publication DOI: https://doi.org/10.1016/j.jneumeth.2022.109726
Divisions: College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
College of Engineering & Physical Sciences > School of Engineering and Technology
Additional Information: © 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Funding information: The work was supported by the following funding: a James S. McDonnell Foundation Understanding Human Cognition Collaborative Award, United States of America (grant number 220020448), the Wellcome Trust Investigator Award in Science, United Kingdom (grant number 207550), a BBSRC grant, United Kingdom (BB/R018723/1) as well as the Royal Society Wolfson Research Merit Award, United Kingdom.
Uncontrolled Keywords: Brain-computer interface,Rapid-invisible frequency tagging,Covert attention,Magnetoencephalography,Eye-tracking
Publication ISSN: 1872-678X
Last Modified: 22 Feb 2024 08:15
Date Deposited: 13 Jun 2023 15:47
Full Text Link:
Related URLs: https://www.sci ... 2527?via%3Dihub (Publisher URL)
PURE Output Type: Article
Published Date: 2022-12-01
Published Online Date: 2022-10-10
Accepted Date: 2022-10-08
Authors: Brickwedde, Marion
Bezsudnova, Yulia
Kowalczyk, Anna
Jensen, Ole
Zhigalov, Alexander (ORCID Profile 0000-0002-3359-5093)

Download

[img]

Version: Published Version

License: Creative Commons Attribution

| Preview

Export / Share Citation


Statistics

Additional statistics for this record