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bioRxiv · 10.1101/2022.05.09.491156

Application of rapid invisible frequency tagging for brain computer interfaces

Brickwedde, M.·Bezsudnova, Y.·Kowalczyk, A.·Jensen, O.·Zhigalov, A.
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Abstract

BackgroundBrain-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 in real-time by analysing the power of neuronal responses at the flicker frequency. New methodWe 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 a real-time BCI PONG game. ResultsOur 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 methodsIn 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. ConclusionUsing 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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Brickwedde, M., Bezsudnova, Y., Kowalczyk, A., Jensen, O., Zhigalov, A.. 2022-05-10. Application of rapid invisible frequency tagging for brain computer interfaces. https://doi.org/10.1101/2022.05.09.491156

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