The mission of visual brain-computer interfaces (BCIs) is to enhance information transfer rate (ITR) to reach high speed towards real-life communication. Despite notable progress, noninvasive visual BCIs have encountered a plateau in ITRs, leaving it uncertain whether higher ITRs are achievable. In this study, we investigate the information rate limits of the primary visual channel to explore whether we can and how we should build visual BCI with higher information rate. Using information theory, we estimate a maximum achievable ITR of approximately 63 bits per second (bps) with a uniformly-distributed White Noise (WN) stimulus. Based on this discovery, we propose a broadband WN BCI approach that expands the utilization of stimulus bandwidth, in contrast to the current state-of-the-art visual BCI methods based on steady-state visual evoked potentials (SSVEPs). Through experimental validation, our broadband BCI outperforms the SSVEP BCI by an impressive margin of 7 bps, setting a new record of 50 bps. This achievement demonstrates the possibility of decoding 40 classes of noninvasive neural responses within a short duration of only 0.1 seconds. The information-theoretical framework introduced in this study provides valuable insights applicable to all sensory-evoked BCIs, making a significant step towards the development of next-generation human-machine interaction systems.

翻译：视觉脑机接口（BCI）的使命是提升信息传输速率（ITR），以实现面向现实通信的高速交互。尽管取得了显著进展，无创视觉BCI的ITR已陷入瓶颈，目前尚不明确是否能够达到更高的ITR。本研究通过探究初级视觉通道的信息率极限，揭示了构建更高信息速率视觉BCI的可能性及方法。基于信息论，我们估计出采用均匀分布白噪声（WN）刺激时，最大可实现ITR约为每秒63比特。基于这一发现，我们提出一种宽带白噪声BCI方法，该方法扩展了刺激带宽的利用率，区别于当前基于稳态视觉诱发电位（SSVEP）的最先进视觉BCI技术。通过实验验证，我们的宽带BCI比SSVEP BCI高出7 bps，创下50 bps的新纪录。这一成果证明了在仅0.1秒的短时窗内解码40类无创神经反应的可行性。本研究引入的信息论框架为所有感觉诱发的BCI提供了宝贵见解，向着开发下一代人机交互系统迈出了关键一步。