Abstract
Heart Rate Variability (HRV) is a measure of the variation in time between successive heartbeats, reflecting the influence of the autonomic nervous system on the heart. It can provide insights into the balance between sympathetic and parasympathetic activity. The relationship between autonomic nervous system function, specifically parasympathetic activity, and certain learning disorders, including dyslexia, is currently under study. In this paper, we propose the use of explainable techniques to explore the relationships between HRV markers and local functional brain activity, estimated by cross-frequency coupling (CFC) from electroencephalography (EEG) signals recorded while auditory stimuli were applied to 7-year-old children. We analyze EEG data to examine the phase-to-phase brainwave coupling and use machine learning tools such as XGBoost and Shapley values to reveal brain regions that most contribute to different HRV features, with a focus on parasympathetic activity. Our findings suggest that HRV features related to stress can explain differential activations in the auditory cortex (Brodmann areas 39 and 40) during auditory stimulation in dyslexic children.
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Acknowledgements
This research is part of the PID2022-137461NB-C32, PID2022-137629OA-I00 and PID2022-137451OB-I00 projects, funded by the MICIU/AEI/10.13039/501100011033 and by ESF+ as well as UMA20-FEDERJA-086 (Consejería de Economía y Conocimiento, Junta de Andalucía) and by European Regional Development Funds (ERDF), as well as the BioSiP (TIC-251) research group and Univerisity of Málaga (UMA). This research is also part of the TIC251-G-FEDER project, funded by ERDF/EU. Marco A. Formoso grant PRE2019-087350 is funded by MICIU/AEI/10.13039/501100011033 by “ESF Investing in your future”. Ignacio Rodriguez-Rodríguez is funded by Plan Andaluz de Investigación, Desarrollo e Innovación (PAIDI), Junta de Andalucía.
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Formoso, M.A., Gallego-Molina, N.J., Ortiz, A., Rodríguez-Rodríguez, I., Giménez, A. (2024). Explainable Exploration of the Interplay Between HRV Features and EEG Local Connectivity Patterns in Dyslexia. In: Ferrández Vicente, J.M., Val Calvo, M., Adeli, H. (eds) Artificial Intelligence for Neuroscience and Emotional Systems. IWINAC 2024. Lecture Notes in Computer Science, vol 14674. Springer, Cham. https://doi.org/10.1007/978-3-031-61140-7_5
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