Changes in EEG and ECG signal connectivity during tilt table testing in healthy young adults without syncope

Tilt table testing (TTT) has been used for over fifty years in clinical and basic medicine to study the adaptation of heart rate and blood pressure to changes in body position. In the area of ​​studying local features of electroencephalogram (EEG) and electrocardiogram (ECG) signal synchronization, there is a lack of research devoted to the precise quantitative mathematical analysis of electrophysiological signals recorded during TTT. Furthermore, most studies related to brain activity analysis focus on the development of syncope.

This study analyzed electrophysiological signals (EEG and ECG) in 19 healthy men. The TTT procedure was performed in a gentle mode with a slight elevation (45°) of the volunteers after 15 min of horizontal positioning. This procedure eliminated the risk of syncope. Time-frequency analysis of the EEG was performed using a continuous wavelet transform. Synchronization of electrophysiological signals in the brain and cardiac activity was assessed using wavelet bicoherence, assessed pairwise between ECG and EEG signals.

EEG activity in the brain remained unchanged before and after verticalization of the volunteers. Heart rate increased, on average, from 1.0 to 1.05 Hz in the horizontal position to 1.3-1.4 Hz in the vertical position (p < 0.005). Significant changes in synchronization were demonstrated before and after verticalization of the volunteers. Most interesting is the increase in ECG and EEG synchronization in the low-frequency range [0.25; 0.75] Hz in response to the tilt table test. Such changes in synchronization can be interpreted in the context of the activation of the human body's adaptive responses during this test.

This study results provide a basis for understanding the physiological relationship between the cardiovascular system and brain activity during the standing position test (SPT) without syncope. These results suggest that low-frequency (below the baseline heart rate) components of P-QRS-T complex variability may be a promising approach for studying neurocardiac interactions.