Harnessing sleep/wake state tracking by olfactory bulb oscillations to perform fully brain-based sleep scoring in mice

It has long been thought that sleep scoring could not be achieved with brain signals alone despite the deep neuromodulatory transformations that accompany sleep state changes. Here we demonstrate using multi-site electrophysiological LFP recordings in freely moving mice that gamma power in the olfactory bulb (OB) allows for clear classification of sleep and wake. Coupled with hippocampal theta activity, it allows the construction of a sleep scoring algorithm that relies on brain activity alone. This method reaches over 90% homology with classical methods based on muscular activity (EMG) and video tracking. Moreover, contrary to EMG, OB gamma power allows correct discrimination between sleep and immobility in ambiguous situations such as fear-related freezing. We use the instantaneous power of hippocampal theta oscillation and OB gamma oscillation to construct a 2D phase-space that is highly robust across mice and days. Dynamic analysis of trajectories within this space yields a novel characterization of sleep/wake and wake/sleep transitions as deeply divergent phenomena. Whereas waking up is a fast and direct transition, falling asleep is best described as stochastic and gradual change. Altogether this methodology opens the avenue for multi-timescale characterization of sleep states with high temporal resolution based on brain signals only.