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Application of rapid invisible frequency tagging for brain computer interfaces

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 anal...

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Autores principales: Brickwedde, Marion, Bezsudnova, Yulia, Kowalczyk, Anna, Jensen, Ole, Zhigalov, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7615063/
https://www.ncbi.nlm.nih.gov/pubmed/36228894
http://dx.doi.org/10.1016/j.jneumeth.2022.109726
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author Brickwedde, Marion
Bezsudnova, Yulia
Kowalczyk, Anna
Jensen, Ole
Zhigalov, Alexander
author_facet Brickwedde, Marion
Bezsudnova, Yulia
Kowalczyk, Anna
Jensen, Ole
Zhigalov, Alexander
author_sort Brickwedde, Marion
collection PubMed
description 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 magnetoenceph-alography (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.
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spelling pubmed-76150632023-09-08 Application of rapid invisible frequency tagging for brain computer interfaces Brickwedde, Marion Bezsudnova, Yulia Kowalczyk, Anna Jensen, Ole Zhigalov, Alexander J Neurosci Methods Article 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 magnetoenceph-alography (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. 2022-12-01 2022-10-10 /pmc/articles/PMC7615063/ /pubmed/36228894 http://dx.doi.org/10.1016/j.jneumeth.2022.109726 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a BY 4.0 (https://creativecommons.org/licenses/by/4.0/) International license. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
Brickwedde, Marion
Bezsudnova, Yulia
Kowalczyk, Anna
Jensen, Ole
Zhigalov, Alexander
Application of rapid invisible frequency tagging for brain computer interfaces
title Application of rapid invisible frequency tagging for brain computer interfaces
title_full Application of rapid invisible frequency tagging for brain computer interfaces
title_fullStr Application of rapid invisible frequency tagging for brain computer interfaces
title_full_unstemmed Application of rapid invisible frequency tagging for brain computer interfaces
title_short Application of rapid invisible frequency tagging for brain computer interfaces
title_sort application of rapid invisible frequency tagging for brain computer interfaces
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7615063/
https://www.ncbi.nlm.nih.gov/pubmed/36228894
http://dx.doi.org/10.1016/j.jneumeth.2022.109726
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