Abstract
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.
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References
Fricke T et al (2015) Brain control of horizontal airplane motion-a comparison of two approaches. In: AIAA atmospheric flight mechanics conference
Edelman BJ et al (2019) Noninvasive neuroimaging enhances continuous neural tracking for robotic device control. Sci Robot 4(31):eaaw6844
Goswami U (2022) Theories of developmental dyslexia. In: Skeide M (ed) The Cambridge handbook of dyslexia and dyscalculia. Cambridge University Press, pp 5–24
Breteler MH et al (2010) Improvements in spelling after QEEG-based neurofeedback in dyslexia: a randomized controlled treatment study. Appl Psychophysiol Biofeedback 35(1):5–11
Vanutelli ME, Lucchiari C, Antonietti A (2021) Using neurofeedback to restore inter-hemispheric imbalance: a study protocol for adults with dyslexia. Front Psychol:5158
Carrera Arias FJ, Molinaro N, Lizarazu M (2021) Real-time EEG neurofeedback as a tool to improve neural entrainment to speech. bioRxiv:2021.04.19.440176
Di Liberto GM et al (2018) Atypical cortical entrainment to speech in the right hemisphere underpins phonemic deficits in dyslexia. Neuroimage 175:70–79
Goswami U et al (2002) Amplitude envelope onsets and developmental dyslexia: a new hypothesis. Proc Natl Acad Sci 99(16):10911–10916
Goswami U (2011) A temporal sampling framework for developmental dyslexia. Trends Cognitive Sci 15(1):3–10
Goswami U (2015) Sensory theories of developmental dyslexia: three challenges for research. Nat Rev Neurosci 16(1):43–54
Goswami U (2022) Language acquisition and speech rhythm patterns: an auditory neuroscience perspective. Royal Society Open Science
Power AJ et al (2016) Neural encoding of the speech envelope by children with developmental dyslexia. Brain Lang 160:1–10
Power AJ et al (2013) Neural entrainment to rhythmic speech in children with developmental dyslexia. Front Hum Neurosci 7:777
Araújo J et al (2022) Atypical cortical encoding of speech identifies children with Dyslexia versus Developmental Language Disorder. bioRxiv:2022.10.26.513864
Ortiz A et al (2020) Dyslexia diagnosis by eeg temporal and spectral descriptors: an anomaly detection approach. Int J Neural Syst 30(07):2050029
Ortiz A et al (2020) Dyslexia detection from EEG signals using SSA component correlation and convolutional neural networks. Springer International Publishing, Cham
Gallego-Molina NJ et al (2022) Complex network modelling of EEG band coupling in dyslexia: an exploratory analysis of auditory processing and diagnosis. Knowl Based Syst:108098
Blankertz B et al (2007) Optimizing spatial filters for robust EEG single-trial analysis. IEEE Signal Process Mag 25(1):41–56
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Araújo, J., Simons, B.D., Goswami, U. (2024). Remediating Phonological Deficits in Dyslexia with Brain-Computer Interfaces. In: Guger, C., Allison, B., Rutkowski, T.M., Korostenskaja, M. (eds) Brain-Computer Interface Research. SpringerBriefs in Electrical and Computer Engineering. Springer, Cham. https://doi.org/10.1007/978-3-031-49457-4_2
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