Key result
Cardiac activity influences the predictive information of EEG dynamics differently across various phases of the cardiac cycle, as measured by the variability of local Information Storage.
Why the study?
Cortical processing of the heartbeat is usually investigated via the Heartbeat Evoked Potential, prompting the exploration of an alternative approach based on variability in the predictability of brain dynamics induced by the heartbeat.
Observational (n=18)
No
Local Information Storage (IS) analysis of simultaneous EEG and ECG signals reveals that cardiac activity dynamically influences cortical predictability across different phases of the cardiac cycle.
Cardiac phase may confound EEG measures; leaves open validation for clinical monitoring or prognostication.
Objective Brain-heart interactions involve bidirectional effects produced by bottom-up input at each heartbeat, and top-down neural regulatory responses of the brain. While the cortical processing of the heartbeat is usually investigated through the analysis of the Heartbeat Evoked Potential, in this study we propose an alternative approach based on the variability in the predictability of the brain dynamics induced by the heartbeat. Methods In a group of eighteen subjects in whom simultaneous recording of the electroencephalogram (EEG) and electrocardiogram was performed in a resting-state, we analyzed the temporal profile of the local Information Storage (IS) to detect changes in the regularity of EEG signals in time windows associated with different phases of the cardiac cycle at rest. Results The average values of the local IS were significantly higher in the parieto-occipital areas of the scalp, suggesting an activation of the Default Mode Network, regardless of the cardiac cycle phase. In contrast, the variability of the local IS showed marked differences across the cardiac cycle phases. Conclusion Our results suggest that cardiac activity influences the predictive information of EEG dynamics differently in the various phases of the cardiac cycle. Significance The variability of local IS measures can represent a useful index to identify spatio-temporal dynamics within the neurocardiac system, which generally remain overlooked by the more widely employed global measures.
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Barà et al. (2023) conducted an observational in Healthy (n=18). Cardiac cycle phases vs. Whole cardiac cycle was evaluated on Mean and variability (SD) of local Information Storage (IS) in EEG signals. Cardiac activity influences the predictive information of EEG dynamics differently across various phases of the cardiac cycle, as measured by the variability of local Information Storage.
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