Giovanni Santostasi1, Roneil Malkani2, Brady Riedner3, Michele Bellesi3, Giulio Tononi3, Ken A Paller4, Phyllis C Zee2. 1. Department of Neurology, Feinberg School of Medicine, Northwestern University, 710 N Lake Shore Drive, 5th floor, Chicago, IL 60611, USA. Electronic address: giovanni.santostasi@northwestern.edu. 2. Department of Neurology, Feinberg School of Medicine, Northwestern University, 710 N Lake Shore Drive, 5th floor, Chicago, IL 60611, USA. 3. Department of Psychiatry, School of Medicine, University of Wisconsin, 6001 Research Park Blvd, Madison, WI 53719, USA. 4. Department of Psychology, Northwestern University, 2029 Sheridan Rd, Evanston, IL 60208, USA.
Abstract
BACKGROUND: A brain-computer interface could potentially enhance the various benefits of sleep. NEW METHOD: We describe a strategy for enhancing slow-wave sleep (SWS) by stimulating the sleeping brain with periodic acoustic stimuli that produce resonance in the form of enhanced slow-wave activity in the electroencephalogram (EEG). The system delivers each acoustic stimulus at a particular phase of an electrophysiological rhythm using a phase-locked loop (PLL). RESULTS: The PLL is computationally economical and well suited to follow and predict the temporal behavior of the EEG during slow-wave sleep. COMPARISON WITH EXISTING METHODS: Acoustic stimulation methods may be able to enhance SWS without the risks inherent in electrical stimulation or pharmacological methods. The PLL method differs from other acoustic stimulation methods that are based on detecting a single slow wave rather than modeling slow-wave activity over an extended period of time. CONCLUSIONS: By providing real-time estimates of the phase of ongoing EEG oscillations, the PLL can rapidly adjust to physiological changes, thus opening up new possibilities to study brain dynamics during sleep. Future application of these methods hold promise for enhancing sleep quality and associated daytime behavior and improving physiologic function.
BACKGROUND: A brain-computer interface could potentially enhance the various benefits of sleep. NEW METHOD: We describe a strategy for enhancing slow-wave sleep (SWS) by stimulating the sleeping brain with periodic acoustic stimuli that produce resonance in the form of enhanced slow-wave activity in the electroencephalogram (EEG). The system delivers each acoustic stimulus at a particular phase of an electrophysiological rhythm using a phase-locked loop (PLL). RESULTS: The PLL is computationally economical and well suited to follow and predict the temporal behavior of the EEG during slow-wave sleep. COMPARISON WITH EXISTING METHODS: Acoustic stimulation methods may be able to enhance SWS without the risks inherent in electrical stimulation or pharmacological methods. The PLL method differs from other acoustic stimulation methods that are based on detecting a single slow wave rather than modeling slow-wave activity over an extended period of time. CONCLUSIONS: By providing real-time estimates of the phase of ongoing EEG oscillations, the PLL can rapidly adjust to physiological changes, thus opening up new possibilities to study brain dynamics during sleep. Future application of these methods hold promise for enhancing sleep quality and associated daytime behavior and improving physiologic function.
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