Search results for " brain-heart interactions"

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Predictability decomposition detects the impairment of brain-heart dynamical networks during sleep disorders and their recovery with treatment

2016

This work introduces a framework to study the network formed by the autonomic component of heart rate variability (cardiac process η ) and the amplitude of the different electroencephalographic waves (brain processes δ , θ , α , σ , β ) during sleep. The framework exploits multivariate linear models to decompose the predictability of any given target process into measures of self-, causal and interaction predictability reflecting respectively the information retained in the process and related to its physiological complexity, the information transferred from the other source processes, and the information modified during the transfer according to redundant or synergistic interaction betwee…

Autonomic nervous system; Brain-heart interactions; Delta sleep electroencephalogram; Granger causality; Heart rate variability; Synergy and redundancy; Mathematics (all); Engineering (all); Physics and Astronomy (all)General MathematicsGeneral Physics and AstronomyElectroencephalography01 natural sciencesSynergy and redundancy03 medical and health sciencesPhysics and Astronomy (all)0302 clinical medicineEngineering (all)0103 physical sciencesMedicineHeart rate variabilityAutonomic nervous systemMathematics (all)Predictability010306 general physicsHeart rate variabilityCardiac processmedicine.diagnostic_testbusiness.industryGeneral EngineeringHealthy subjectsBrainArticlesAutonomic nervous systemDelta sleep electroencephalogramSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaGranger causalityBrain-heart interactionSleep (system call)businessNeuroscience030217 neurology & neurosurgery
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Mutual Information Analysis of Brain-Heart Interactions in Epileptic Children

2021

In this work we apply the network physiology paradigm to retrieve information from central and autonomic nervous systems before focal epileptic seizure, represented respectively by electroencephalogram (EEG) signals and R-R intervals (RRI), and investigate on the presence and strength of brain-heart interactions by computing mutual information (MI) measures. Statistical significance of MI values was tested through surrogate time series generated with the random shuffle approach. Our results suggest that the proposed method for aligning signals representing brain and heart activity measured with different sampling rates, is capable of revealing coupling between RRI representing heart system,…

Signal processingmedicine.diagnostic_testbusiness.industryTotal frequencySpectral densityPattern recognitionMutual informationHeart activityElectroencephalographyEpilepsy seizure EEG R-R intervals mutual information brain-heart interactionsSettore ING-INF/06 - Bioingegneria Elettronica E InformaticamedicineArtificial intelligenceEpileptic seizuremedicine.symptombusinessMathematics
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