Remediating Phonological Deficits in Dyslexia with Brain-Computer Interfaces

BCIs offer science-based interfaces for human enhancement, enabling people to improve cognitive skills that may be difficult for them to learn. Here, we design a non-invasive EEG-BCI relying on auditory inputs and visual feedback to optimise brain patterns related to phonology (speech-sound) and reading deficits in children with dyslexia. Drawing from a decade of dyslexia neuroscience research on perceptive ‘temporal sampling’ along with computational modelling of EEG collected from over 100 children, we engineered a decoder for online BCI control. We designed an engaging interface aimed at teaching children how to self-regulate neural oscillatory patterns related to phonological difficulties in dyslexia, using a range of ideas derived from competition-winning motor imagery paradigms to BCIs for aircraft control.