Abstract
In the realm of neuroscience, brain activity is often characterized by rhythmic oscillations at different frequency bands. These oscillations underlie various cognitive processes and constitutes the basis of communication between populations of neurons. Cross-frequency coupling (CFC) refers to techniques directed to study the interactions between oscillations at different frequencies, providing a more comprehensive view of neural dynamics than traditional measures of connectivity or based on the distribution of the power spectral density. In this paper, we propose a method to explore CFC local patterns in an explainable way, allowing to visualize them over time and to easily identify functional brain areas activated during a task development from the Phase-Amplitude Coupling (PAC) point of view.
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Acknowledgements
This research is part of the PID2022-137461NB-C32, PID2022-137629OA-I00 and PID2022-137451OB-I00 projects, funded by MICIU/AEI/10.13039/501100011033 and by ERDF/EU, as well as UMA20-FEDERJA-086 (Consejería de Economía y Conocimiento, Junta de Andalucía) and by ERDF/EU. Work by D.C.B. is part of the grant FJC2021-048082-I funded by MICIU/AEI/10.13039/501100011033 and by European Union NextGenerationEU/PRTR. Work by I.R.-R. is funded by Plan Andaluz de Investigación, Desarrollo e Innovación (PAIDI), Junta de Andalucía.
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Ortiz, A., Gallego-Molina, N.J., Castillo-Barnes, D., Rodríguez-Rodríguez, I., Górriz, J.M. (2024). Visualizing Brain Synchronization: An Explainable Representation of Phase-Amplitude Coupling. 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_2
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