Nonlinear brain-heart interactions in children with focal epilepsy assessed by mutual information of EEG and heart rate variability

Network physiology is a recent approach describing the human body as an integrated network composed of several organ systems which continuously interact to produce healthy and diseased states. In this work, we apply the network physiology paradigm to study dynamical interactions between EEG activity and heart rate variability in children suffering from focal epilepsy. We aim to study the characteristics of brainheart coupling between, before, and after seizures to better understand the physiological mechanisms underlying seizure onset in the pre-ictal phase and the recovery of normal autonomic function in the post-ictal phase. In perspective, linking the dynamic information of brain-heart can provide useful information for a better seizure prediction. EEG and ECG data were recorded in 10 patients with focal epilepsy. After removal of baseline drift and muscle artifacts, the variability of heart rate and brain activity were measured extracting R-R intervals from the ECG and computing the spectral power of the EEG. 143 synchronous time series of 300 points were obtained in 4 different time windows (10 min and 10 sec before and after the seizure) and analyzed computing the cross-correlation coefficient (CC) and the mutual information (MI). A statistically significant increase of MI was observed just after seizure episodes (pvalue equal to 0.04, 10s before vs 10s after distributions, electrode O2), while a recovery of the baseline value was obtained 10 minutes after the episodes. This trend was found for several other EEG electrodes (Fp2, F3, F8, T3, C4, T4). On the contrary, CC did not change significantly across time windows. These results suggest that focal seizures are associated with an increased brain-heart coupling which is noticeable after seizure termination only in terms of mutual information. We conclude that focal epilepsy in childhood is associated with nonlinear brain-heart interaction mechanisms.