# Response coupling with an auxiliary neural signal for enhancing brain signal detection

## TL;DR

This paper introduces a new method to improve brain-computer interfaces by combining brain signals with an auxiliary signal to enhance detection accuracy.

## Contribution

The novel 'response coupling' method pairs error-related potentials with SSVEPs to improve BCI signal detection and reliability.

## Key findings

- Response coupling significantly improves detection accuracy of ErrPs in parietal and occipital regions.
- SSVEPs' phase-locking properties enable unsupervised rejection of suboptimal data, increasing BCI reliability.

## Abstract

Brain-computer interfaces (BCIs) offer an implicit, non-linguistic communication channel between users and machines. Despite their potential, BCIs are far from becoming a mainstream communication modality like text and speech. While non-invasive BCIs, such as Electroencephalography, are favored for their ease of use, their broader adoption is limited by challenges related to signal noise, artifacts, and variability across users. In this paper, we propose a novel method called response coupling, aimed at enhancing brain signal detection and reliability by pairing a brain signal with an artificially induced auxiliary signal and leveraging their interaction. Specifically, we use error-related potentials (ErrPs) as the primary signal and steady-state visual evoked potentials (SSVEPs) as the auxiliary signal. SSVEPs, known for their phase-locked responses to rhythmic stimuli, are selected because rhythmic neural activity plays a critical role in sensory and cognitive processes, with evidence suggesting that reinforcing these oscillations can improve neural performance. By exploring the interaction between these two signals, we demonstrate that response coupling significantly improves the detection accuracy of ErrPs, especially in the parietal and occipital regions. This method introduces a new paradigm for enhancing BCI performance, where the interaction between a primary and an auxiliary signal is harnessed to enhance the detection performance. Additionally, the phase-locking properties of SSVEPs allow for unsupervised rejection of suboptimal data, further increasing BCI reliability.