Tone-Evoked Sleep Electroencephalographic Slow Oscillations as a Function of Peripheral Rhythms: New Insights Into the Brain-Heart Integration.

Recent studies have shown that acoustic stimulation, a common neuromodulation technique, can enhance slow-wave activity (SWA), which is associated with immune, autonomic nervous system activity and cognitive health benefits. Despite some disagreement, many studies suggest that maximising tone-evoked SWA depends on the timing of the acoustic stimulus in relation to ongoing cortical slow oscillations. Given the close connection between the central and peripheral systems during sleep, particularly at the cortico-cardiac level, we here aimed to examine the overlooked relationship between the timing of stimulation and the dominant cortical and cardiac rhythms. We evaluated the effect of acoustic stimulation in different phases of the EEG slow oscillation (SO; ~0.8 Hz) component of SWA (0.5-4 Hz) and heart rate (HR) low-frequency (LF) (0.04-0.15 Hz) and high-frequency (HF) (0.15-0.4 Hz) oscillations on tone-evoked EEG slow activity and HR profiles. One hundred thirty-three adolescents underwent overnight polysomnography where acoustic tones (80 dB at 1000 Hz for 50 msec) were played with a random 15-30 s interstimulus interval. The analysis was limited to artefact and arousal-free episodes of NREM sleep. Playing acoustic tones in the upstate phases of EEG SOs, upstate phases of HR LF oscillations and downstate phases of HR HF oscillations induced significantly higher peak-to-peak amplitude EEG SOs (110%, 16% and 7%, respectively) (p < 0.001) and HR oscillations (16%, 56% and 25%, respectively) (p < 0.001), produced a greater number of EEG SOs (22%, 12% and 5%, respectively) and increased the SWA (3%, 14% and 3%, respectively) (p < 0.05) in contrast to playing tones in the other phase (downstate phases of EEG SOs, downstate phases of LF oscillations and upstate phases of HR HF oscillations). Our findings reveal complex interactions between the central and peripheral nervous systems in processing external stimuli, leading to significant variations in postcortical and cardiac oscillations. These results have potential implications for developing deep sleep enhancement technologies using adaptive interventions based on multidimensional oscillations.