Automatized online prediction of slow-wave peaks during non-rapid eye movement sleep in young and old individuals: Why we should not always rely on amplitude thresholds

Abstract

Brain-state-dependent stimulation during slow-wave sleep is a promising tool for the treatment of psychiatric and neurodegenerative diseases. A widely used slow-wave prediction algorithm required for brain-state-dependent stimulation is based on a specific amplitude threshold in the electroencephalogram. However, due to decreased slow-wave amplitudes in aging and psychiatric conditions, this approach might miss many slow-waves because they do not fulfill the amplitude criterion. Here, we compared slow-wave peaks predicted via an amplitude-based versus a multidimensional approach using a topographical template of slow-wave peaks in 21 young and 21 older healthy adults. We validate predictions against the gold-standard of offline detected peaks. Multidimensionally predicted peaks resemble the gold-standard regarding spatiotemporal dynamics but exhibit lower peak amplitudes. Amplitude-based prediction, by contrast, is less sensitive, less precise and - especially in the older group - predicts peaks that differ from the gold-standard regarding spatiotemporal dynamics. Our results suggest that amplitude-based slow-wave peak prediction might not always be the ideal choice. This is particularly the case in populations with reduced slow-wave amplitudes, like older adults or psychiatric patients. We recommend the use of multidimensional prediction, especially in studies targeted at populations other than young and healthy individuals.

Keywords: acoustic stimulation; aging; amplitude; slow-wave prediction; slow-wave sleep; topographic maps.