Data from: Harnessing olfactory bulb oscillations to perform fully brain-based sleep-scoring and real-time monitoring of anesthesia depth

Real-time tracking of vigilance states related to both sleep or
anaesthesia has been a goal for over a century. However, sleep scoring
cannot currently be performed with brain signals alone, despite the deep
neuromodulatory transformations that accompany sleep state changes.
Therefore, at heart, the operational distinction between sleep and wake is
that of immobility and movement, despite numerous situations in which this
one-to-one mapping fails. Here we demonstrate, using local field potential
(LFP) recordings in freely moving mice, that gamma (50–70 Hz) power in the
olfactory bulb (OB) allows for clear classification of sleep and wake,
thus providing a brain-based criterion to distinguish these two vigilance
states without relying on motor activity. Coupled with hippocampal theta
activity, it allows the elaboration of a sleep scoring algorithm that
relies on brain activity alone. This method reaches over 90% homology with
classical methods based on muscular activity (electromyography [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 throughout time, across individual mice and mouse
strains, and under classical drug treatment. Dynamic analysis of
trajectories within this space yields a novel characterisation of
sleep/wake transitions: whereas waking up is a fast and direct transition
that can be modelled by a ballistic trajectory, falling asleep is best
described as a stochastic and gradual state change. Finally, we
demonstrate that OB oscillations also allow us to track other vigilance
states. Non-REM (NREM) and rapid eye movement (REM) sleep can be
distinguished with high accuracy based on beta (10–15 Hz) power. More
importantly, we show that depth of anaesthesia can be tracked in real time
using OB gamma power. Indeed, the gamma power predicts and anticipates the
motor response to stimulation both in the steady state under constant
anaesthetic and dynamically during the recovery period. Altogether, this
methodology opens the avenue for multi-timescale characterisation of brain
states and provides an unprecedented window onto levels of vigilance.