Closed-loop auditory stimulation targeting alpha and theta oscillations during REM sleep induces phase-dependent power and frequency changes

Background Alpha and theta oscillations characterize the waking human electroencephalogram (EEG) and can be modulated by closed-loop auditory stimulation (CLAS). These oscillations also occur during rapid eye movement (REM) sleep, but whether they can be modulated by CLAS is not known. Objective Investigate whether CLAS can modulate alpha and theta oscillations during REM sleep in a targeted phase-dependent manner. Methods We recorded high-density EEG during an extended overnight sleep period in 18 healthy young adults. Auditory stimulation was delivered during both phasic and tonic REM sleep in alternating 6 s ON and 6 s OFF windows. During the ON windows, stimuli were phase-locked to four orthogonal phases of ongoing alpha or theta oscillations detected in a frontal electrode (Fz). Results During ON windows, the four orthogonal phases of ongoing alpha and theta oscillations were targeted with high accuracy. Alpha and theta CLAS induced phase-dependent changes in power and frequency at the target location. Frequency-specific effects were observed for alpha trough (speeding up) and rising (slowing down) and theta trough (speeding up) conditions. These phase-dependent changes of CLAS were observed during both REM sleep substages, even though the amplitude evoked by auditory stimuli which were not phase-locked was very much reduced in phasic compared to tonic REM sleep. Conclusions This study provides evidence that faster REM sleep rhythms can be modulated by CLAS in a phase-dependent manner. This offers a new approach to investigate how modulation of REM sleep oscillations affects the contribution of this vigilance state to brain function. Highlights - REM sleep alpha and theta oscillations can be modulated using phase-locked CLAS - Phase-dependent changes in power and frequency are observed in the target area - Phase-dependent modulation occurs in phasic and tonic REM sleep Graphical Abstract