Brain response to luminance-based and motion-based stimulation using intermodulation frequencies
发布时间：2025-04-30
点击次数：
- 发布时间：
- 2025-04-30
- 论文名称：
- Brain response to luminance-based and motion-based stimulation using intermodulation frequencies
- 发表刊物：
- PLoS ONE
- 摘要：
- Steady state visual evoked potential (SSVEP)-based brain computer interface (BCI) has advantages of high information transfer rate (ITR), less electrodes and little training. So it has been widely investigated. However, the available stimulus frequencies are limited by brain responses. Simultaneous modulation of stimulus luminance is a novel method to resolve this problem. In this study, three experiments were devised to gain a deeper understanding of the brain response to the stimulation using inter-modulation frequencies. First, luminance-based stimulation using one to five inter-modulation frequencies was analyzed for the first time. The characteristics of the brain responses to the proposed stimulation were reported. Second, the motion-based stimulation with equal luminance using inter-modulation frequencies was also proposed for the first time. The response of the brain under these conditions were similar to that of luminance-based stimulation which can induce combination frequencies. And an elementary analysis was conducted to explain the reason of the occurrence of combination frequencies. Finally, the online test demonstrated the efficacy of our proposed two stimulation methods for BCI. The average ITRs reached 34.7836 bits/min and 39.2856 bits/min for luminance-based and motion-based stimulation respectively. This study demonstrated that the simultaneous modulation of stimulus luminance could extend to at least five frequencies to induce SSVEP and the brain response to the stimulus still maintained a certain positive correlation with luminance. And not only luminance-based stimulation, but also motion-based stimulation with equal luminance can elicit inter-modulation frequencies to effectively increase the number of targets for multi-class SSVEP.
- 合写作者：
- Xin Zhang, Guanghua Xu, Jun Xie, Xun Zhang
- 是否译文：
- 否
- 发表时间：
- 2017-11-15