Background: The quantification of functional brain–heart interplay (BHI) through analysis of the dynamics of the central and autonomic nervous systems provides effective biomarkers for cognitive, emotional, and autonomic state changes. Several computational models have been proposed to estimate BHI, focusing on a single sensor, brain region, or frequency activity. However, no models currently provide a directional estimation of such interplay at the organ level. Objective: This study proposes an analysis framework to estimate BHI that quantifies the directional information flow between whole–brain and heartbeat dynamics. Methods: System–wise directed functional estimation is performed through an ad-hoc symbolic transfer entropy implementation, which leverages on EEG-derived microstate series and on partition of heart rate variability series. The proposed framework is validated on two different experimental datasets: the first investigates the cognitive workload performed through mental arithmetic and the second focuses on an autonomic maneuver using a cold pressor test (CPT). Results: The experimental results highlight a significant bidirectional increase in BHI during cognitive workload with respect to the preceding resting phase and a higher descending interplay during a CPT compared to the preceding rest and following recovery phases. These changes are not detected by the intrinsic self entropy of isolated cortical and heartbeat dynamics. Conclusion: This study corroborates the literature on the BHI phenomenon under these experimental conditions and the new perspective provides novel insights from an organ–level viewpoint. Significance: A system–wise perspective of the BHI phenomenon may provide new insights into physiological and pathological processes that may not be completely understood at a lower level/scale of analysis.

Nervous–system–wise Functional Estimation of Directed Brain–Heart Interplay through Microstate Occurrences

Catrambone V.;Valenza G.
Ultimo
2023-01-01

Abstract

Background: The quantification of functional brain–heart interplay (BHI) through analysis of the dynamics of the central and autonomic nervous systems provides effective biomarkers for cognitive, emotional, and autonomic state changes. Several computational models have been proposed to estimate BHI, focusing on a single sensor, brain region, or frequency activity. However, no models currently provide a directional estimation of such interplay at the organ level. Objective: This study proposes an analysis framework to estimate BHI that quantifies the directional information flow between whole–brain and heartbeat dynamics. Methods: System–wise directed functional estimation is performed through an ad-hoc symbolic transfer entropy implementation, which leverages on EEG-derived microstate series and on partition of heart rate variability series. The proposed framework is validated on two different experimental datasets: the first investigates the cognitive workload performed through mental arithmetic and the second focuses on an autonomic maneuver using a cold pressor test (CPT). Results: The experimental results highlight a significant bidirectional increase in BHI during cognitive workload with respect to the preceding resting phase and a higher descending interplay during a CPT compared to the preceding rest and following recovery phases. These changes are not detected by the intrinsic self entropy of isolated cortical and heartbeat dynamics. Conclusion: This study corroborates the literature on the BHI phenomenon under these experimental conditions and the new perspective provides novel insights from an organ–level viewpoint. Significance: A system–wise perspective of the BHI phenomenon may provide new insights into physiological and pathological processes that may not be completely understood at a lower level/scale of analysis.
2023
Catrambone, V.; Valenza, G.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1177692
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