Application of rapid invisible frequency tagging for brain computer interfaces

Marion Brickwedde*, Yulia Bezsudnova, Anna Kowalczyk, Ole Jensen, Alexander Zhigalov

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Article number109726
Number of pages8
JournalJournal of Neuroscience Methods
Early online date10 Oct 2022
Publication statusPublished - 1 Dec 2022

Bibliographical note

© 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (

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


  • Brain-computer interface
  • Rapid-invisible frequency tagging
  • Covert attention
  • Magnetoencephalography
  • Eye-tracking


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