Estimating and approaching maximum information rate of noninvasive visual brain-computer interface

TL;DR

This paper estimates the maximum information transfer rate of noninvasive visual BCIs using information theory, proposes a broadband stimulus approach, and demonstrates a new record of 50 bps in experimental validation.

Contribution

It introduces an information-theoretical framework to estimate ITR limits and develops a broadband WN BCI that surpasses previous methods in speed.

Findings

Maximum achievable ITR estimated at 63 bps with white noise stimulus

Broadband WN BCI outperforms SSVEP-based BCI by 7 bps

Achieved decoding of 40 classes within 0.1 seconds

Abstract

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.