The evaluation of the correlation between the activations of various organs has great importance. This work investigated the synchronization of the brain and heart responses to different auditory stimuli using complexity-based analysis. We selected three pieces of music based on the difference in the complexity of embedded noise (including white noise, brown noise, and pink noise) in them. We played these pieces of music for 11 subjects (7 M and 4 F) and computed the fractal dimension and sample entropy of EEG signals and R–R time series [as heart rate variability (HRV)]. We found strong correlations ([Formula: see text] in the case of fractal dimension and [Formula: see text] in the case of sample entropy) among the complexities of EEG signals and HRV. This finding demonstrates the synchronization of the brain and heart responses and auditory stimuli from the complexity perspective.
In this work, we investigated the coupling among the activities of the brain and heart versus the changes in auditory stimuli using information-based analysis. Three music were selected based on the difference in their complexity. We applied these auditory stimuli on 11 subjects, and accordingly, computed and compared the Shannon entropy of electroencephalography (EEG) signals and heart rate variability (R–R time series). The results demonstrated a correlation among the alterations of the information contents of EEG signals and R–R time series. This finding shows the coupling between the activities of the brain and heart. This analysis could be expanded to analyze the activities of other organs versus the brain’s reaction in various conditions.
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