Single-trial Neural Congruency: Paving the Way towards Single-trial EEG Analysis in Dyslexia research
Understanding the relationship between neural activations and cognitive factors in reading disorders, such as dyslexia, is a key goal in developmental neuroscience. Despite advancements in computational methods for extracting neural components at the aggregate, inter-subject variability in EEG sign...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
LibraryPress@UF
2025-05-01
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| Series: | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| Online Access: | https://journals.flvc.org/FLAIRS/article/view/138973 |
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| Summary: | Understanding the relationship between neural activations and cognitive factors in reading disorders, such as dyslexia, is a key goal in developmental neuroscience. Despite advancements in computational methods for extracting neural components at the aggregate, inter-subject variability in EEG signals make it challenging to perform across-group single-trial analysis on the neural mechanisms associated with reading disorders. Our contribution focuses on using the Neural-Congruency framework to address the issue of inter-subject variability in EEG data, which allows for single-trial analysis across groups of dyslexic and control participants. Preliminary results demonstrate the feasibility of this approach, highlighting its potential to deepen our understanding of the neural mechanisms underlying reading disorders. By providing a more granular and accurate analysis of neural activations, this study lays the groundwork for improved diagnostic and intervention strategies for dyslexia.
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| ISSN: | 2334-0754 2334-0762 |