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 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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Publication Details

Journal
Proceedings of the ... International Florida Artificial Intelligence Research Society Conference
Published
2025-05-14
DOI
https://doi.org/10.32473/flairs.38.1.138973
Primary Topic
Neuroscience, Education and Cognitive Function
Type
article
Field-Weighted Citation Impact
0.00
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article

Single-trial Neural Congruency: Paving the Way towards Single-trial EEG Analysis in Dyslexia research

Christoforos Christoforou, Timothy C. Papadopoulos
Proceedings of the ... International Florida Artificial Intelligence Research Society Conference
Neuroscience, Education and Cognitive Function
article

Single-trial Neural Congruency: Paving the Way towards Single-trial EEG Analysis in Dyslexia research

Christoforos Christoforou, Timothy C. Papadopoulos
article en

Abstract

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.

Proceedings of the ... International Florida Artificial Intelligence Research Society ConferenceVol. 38
Openalex Percentile: Top 77%
Neuroscience, Education and Cognitive Function
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