EEG-Based Auditory Attention Detection and Its Possible Future Applications for Passive BCI

Abstract

The ability to discriminate and attend one specific sound source in a complex auditory environment is a fundamental skill for efficient communication. Indeed, it allows us to follow a family conversation or discuss with a friend in a bar. This ability is challenged in hearing-impaired individuals and more precisely in those with a cochlear implant (CI). Indeed, due to the limited spectral resolution of the implant, auditory perception remains quite poor in a noisy environment or in presence of simultaneous auditory sources. Recent methodological advances allow now to detect, on the basis of neural signals, which auditory stream within a set of multiple concurrent streams an individual is attending to. This approach, called EEG-based auditory attention detection (AAD), is based on fundamental research findings demonstrating that, in a multi speech scenario, cortical tracking of the envelope of the attended speech is enhanced compared to the unattended speech. Following these findings, other studies showed that it is possible to use EEG/MEG (Electroencephalography/Magnetoencephalography) to explore auditory attention during speech listening in a Cocktail-party-like scenario. Overall, these findings make it possible to conceive next-generation hearing aids combining customary technology and AAD. Importantly, AAD has also a great potential in the context of passive BCI, in the educational context as well as in the context of interactive music performances. In this mini review, we firstly present the different approaches of AAD and the main limitations of the global concept. We then expose its potential applications in the world of non-clinical passive BCI.

Neural tracking to go: auditory attention decoding and saliency detection with mobile EEG

“…Based on this finding, methods have been developed to decode the attended speaker within multi-speaker environments (Ding andSimon 2012, Alickovic et al 2019). This offers opportunities for promising future applications in assistive devices (Slaney et al 2020) such as neuro-steered hearing aids (Geirnart et al 2021b) or other brain-computer interfaces (Belo et al 2021), especially in complex, uncontrolled natural auditory scenes. However, so far, these methods have been tested exclusively inside the lab, under controlled conditions.…”

Exploring Auditory Attention Using EEG

“…The system we aim to comprehend and identify is the human brain. Despite the complexity of our dynamic brain, linear models, trained on provided input and recorded output, have been proven to perform well in auditory experiments [7,10,19,51].…”

Cortical linear encoding and decoding of sounds: Similarities and differences between naturalistic speech and music listening

“…Such linear modelling techniques can also lead, in addition to research purposes, to concrete applications and brain–computer interfaces. Stimulus reconstruction, through backward modelling, could be used for cortical auditory attention decoding (AAD) (Alickovic et al, 2019; Belo et al, 2021; Geirnaert et al, 2021). The AAD application could be implemented in hearing aids, hearing‐assistive devices or even consumer audio products (headphones or earbuds) (Belo et al, 2021; Geirnaert et al, 2021).…”