Search results for "brain-heart interactions"
showing 3 items of 3 documents
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…
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,…
Synergistic and Redundant Brain-Heart Information in Patients with Focal Epilepsy
2020
In this work, partial information decomposition (PID) was applied to the time series of heart rate and EEG amplitude variability to investigate the dynamical interactions in brain-heart coupling before and after epileptic seizures. From ECG and EEG signals collected on 23 children suffering from focal epilepsy, the RR intervals and the EEG variance at ipsilateral and contralateral temporal electrodes were computed in four different time windows before and after the seizures. Static PID was used to obtain redundant, unique and synergistic components of the total information shared between the series of RR and EEG variance. Results highlight, in the progression from preictal to postictal stat…