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Modelling the brain response to arbitrary visual stimulation patterns for a flexible high-speed Brain-Computer Interface

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  • Sebastian Nagel
  • Martin Spüler

Abstract

Visual evoked potentials (VEPs) can be measured in the EEG as response to a visual stimulus. Commonly, VEPs are displayed by averaging multiple responses to a certain stimulus or a classifier is trained to identify the response to a certain stimulus. While the traditional approach is limited to a set of predefined stimulation patterns, we present a method that models the general process of VEP generation and thereby can be used to predict arbitrary visual stimulation patterns from EEG and predict how the brain responds to arbitrary stimulation patterns. We demonstrate how this method can be used to model single-flash VEPs, steady state VEPs (SSVEPs) or VEPs to complex stimulation patterns. It is further shown that this method can also be used for a high-speed BCI in an online scenario where it achieved an average information transfer rate (ITR) of 108.1 bit/min. Furthermore, in an offline analysis, we show the flexibility of the method allowing to modulate a virtually unlimited amount of targets with any desired trial duration resulting in a theoretically possible ITR of more than 470 bit/min.

Suggested Citation

  • Sebastian Nagel & Martin Spüler, 2018. "Modelling the brain response to arbitrary visual stimulation patterns for a flexible high-speed Brain-Computer Interface," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-16, October.
    • Handle: RePEc:plo:pone00:0206107
    DOI: 10.1371/journal.pone.0206107
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    References listed on IDEAS

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    1. Yonghui Liu & Qingguo Wei & Zongwu Lu, 2018. "A multi-target brain-computer interface based on code modulated visual evoked potentials," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-17, August.
    2. Jordy Thielen & Philip van den Broek & Jason Farquhar & Peter Desain, 2015. "Broad-Band Visually Evoked Potentials: Re(con)volution in Brain-Computer Interfacing," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-22, July.
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