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Exploring the Predictability of EEG Signals Timed with the Heartbeat: A Model-Based Approach for the Temporal and Spatial Characterization of the Brain Dynamics

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MEDICON’23 and CMBEBIH’23 (MEDICON 2023, CMBEBIH 2023)

Part of the book series: IFMBE Proceedings ((IFMBE,volume 93))

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Abstract

This study aims to provide a temporal and spatial characterization of the human brain activity related to the cardiac cycle in terms of regularity of the brain wave amplitudes measured from electroencephalographic (EEG) signals. To achieve this objective, linear autoregressive models are employed to characterize time-series of the spectral power extracted from EEG signals, timed with the heartbeat, by using a measure of predictability. The analysis is performed on four different time-series acquired on healthy subjects in a resting state and describing the EEG spectral content over the whole frequency spectrum and within the \(\theta \), \(\alpha \) and \(\beta \) bands. Our results indicate predictability values with targeted activations in the frontal and parieto-occipital brain regions, which reflect regular amplitude modulations of the brain waves at rest, and could be linked to the cortical processing of the heartbeat.

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Acknowledgement

This study was supported by SiciliAn MicronanOTecH Research And Innovation CEnter “SAMOTHRACE” (MUR, PNRR-M4C2, ECS 00000022). V.R.V. is sup ported by the project “Sensoristica intelligente, infrastrutture e modelli gestion ali per la sicurezza di soggetti fragili” (4FRAILTY) funded by MIUR, PON R &I grant ARS01 00345, CUP B76G18000220005, and R.P. is partially supported by the European Social Fund (ESF)-Complementary Operational Programme (POC) 2014/2020 of the Sicily Region.

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Authors and Affiliations

  1. Department of Engineering, University of Palermo, Palermo, Italy

    Valeria Rosalia Vergara, Chiara Bara, Riccardo Pernice, Luca Faes & Yuri Antonacci

  2. Department of Psychological, Health and Territorial Sciences, “G. d’Annunzio” University of Chieti-Pescara, Chieti, Italy

    Andrea Zaccaro

  3. Department of Neuroscience, Imaging and Clinical Sciences, “G. d’Annunzio” University of Chieti-Pescara, Chieti, Italy

    Francesca Ferri

  4. Institute for Advanced Biomedical Technologies, ITAB, “G. d’Annunzio” University of Chieti-Pescara, Chieti, Italy

    Francesca Ferri

Authors
  1. Valeria Rosalia Vergara
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  2. Chiara Bara
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  3. Riccardo Pernice
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  4. Andrea Zaccaro
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  5. Francesca Ferri
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  6. Luca Faes
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  7. Yuri Antonacci
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Corresponding author

Correspondence to Valeria Rosalia Vergara .

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Editors and Affiliations

  1. Verlab Research Institute for Biomedical Engineering, Medical Devices, and Artificial Intelligence, Sarajevo, Bosnia and Herzegovina

    Almir Badnjević

  2. Verlab Research Institute for Biomedical Engineering, Medical Devices, and Artificial Intelligence, Sarajevo, Bosnia and Herzegovina

    Lejla Gurbeta Pokvić

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Vergara, V.R. et al. (2024). Exploring the Predictability of EEG Signals Timed with the Heartbeat: A Model-Based Approach for the Temporal and Spatial Characterization of the Brain Dynamics. In: Badnjević, A., Gurbeta Pokvić, L. (eds) MEDICON’23 and CMBEBIH’23. MEDICON CMBEBIH 2023 2023. IFMBE Proceedings, vol 93. Springer, Cham. https://doi.org/10.1007/978-3-031-49062-0_15

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  • DOI: https://doi.org/10.1007/978-3-031-49062-0_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-49061-3

  • Online ISBN: 978-3-031-49062-0

  • eBook Packages: EngineeringEngineering (R0)

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