Imagined Speech and Visual Imagery as Intuitive Paradigms for Brain-Computer Interfaces

TL;DR

This study compares neural dynamics of imagined speech and visual imagery in EEG data, highlighting their potential for brain-computer interface applications and emphasizing the importance of personalized calibration.

Contribution

It provides a detailed analysis of brain synchronization patterns in imagined speech and visual imagery, advancing understanding of their suitability for non-invasive BCI systems.

Findings

Visual imagery shows higher PLV in visual cortex

Imagined speech exhibits consistent synchronization in language regions

Personalized calibration improves BCI performance

Abstract

Brain-computer interfaces (BCIs) have shown promise in enabling communication for individuals with motor impairments. Recent advancements like brain-to-speech technology aim to reconstruct speech from neural activity. However, decoding communication-related paradigms, such as imagined speech and visual imagery, using non-invasive techniques remains challenging. This study analyzes brain dynamics in these two paradigms by examining neural synchronization and functional connectivity through phase-locking values (PLV) in EEG data from 16 participants. Results show that visual imagery produces higher PLV values in visual cortex, engaging spatial networks, while imagined speech demonstrates consistent synchronization, primarily engaging language-related regions. These findings suggest that imagined speech is suitable for language-driven BCI applications, while visual imagery can complement BCI systems for users with speech impairments. Personalized calibration is crucial for optimizing BCI performance.