Mental fatigue in central-field and peripheral-field steady-state visually evoked potential and its effects on event-related potential responses

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Abstract

The steady-state visually evoked potential (SSVEP) is a natural response of the brain to visual stimulation at specific frequencies and is used widely for electroencephalography-based brain–computer interface (BCI) systems. Although the SSVEP is useful for its high level of decoding accuracy, visual fatigue from the repetitive visual flickering is an unavoidable problem. In addition, hybrid BCI systems that combine the SSVEP with the event-related potential (ERP) have been proposed recently. These hybrid BCI systems would improve the decoding accuracy; however, the competing effect by simultaneous presentation of the visual stimulus could possibly supervene the signal in the hybrid system. Nevertheless, previous studies have not sufficiently reported these problems of visual fatigue with SSVEP stimuli or the competing effect in the SSVEP+ERP system. In this study, two different experiments were designed to explore our claims. The first experiment evaluated the visual fatigue level and decoding accuracy for the different types of SSVEP stimuli, which were the peripheral-field SSVEP (pSSVEP) and the central-field SSVEP (cSSVEP). We report that the pSSVEP could reduce the visual fatigue level by avoiding direct exposure of the eye-retina to the flickering visual stimulus, while also delivering a decoding accuracy comparable to that of cSSVEP. The second experiment was designed to examine the competing effect of the SSVEP stimuli on ERP performance and vice versa. To do this, the visual stimuli of ERP and SSVEP were presented simultaneously as part of the BCI speller layout. We found a clear competing effect wherein the evoked brain potentials were influenced by the SSVEP stimulus and the band power at the target frequencies was also decreased significantly by the ERP stimuli. Nevertheless, these competing effects did not lead to a significant loss in decoding accuracy; their features preserved sufficient information for discriminating a target class. Our work is the first to evaluate the visual fatigue and competing effect together, which should be considered when designing BCI applications. Furthermore, our findings suggest that the pSSVEP is a viable substitution for the cSSVEP because of its ability to reduce the level of visual fatigue while maintaining a minimal loss of decoding accuracy.

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