Spatio-temporal dynamics of spontaneous neural activity during the transition from slow oscillations to an awake-like state in isolated cortical networks.

Abstract

Slow oscillations (SO) of neural activity occur spontaneously in the neocortex during functionally disconnected brain states, such as deep anaesthesia or slow-wave sleep. These consist in a near-1-Hz alternation of high- (Up) and low-responsive (Down) periods, and spatially propagate as a travelling wave. During the tran- sition towards wakefulness, globally synchronous SO break down, giving rise to asynchronous awake-like states or micro-arousals. There is currently a shortage of quantitative techniques to detect such state transitions in neurophysiological record- ings. Notably, the disentanglement of non-stationary oscillatory signals embedded in background colour noise bears significant challenges. Thus, the emergence of asynchrony from the SO is poorly understood; in particular, the role of the local cortical network in orchestrating this transition spatially. We devised a new statistical procedure based on the time-frequency decomposi- tion of multivariate signals to investigate the network activity dynamics during this liminal regime. Our method, built upon an original mathematical framework, pro- poses a new normalisation of the wavelet power components that allows quantifying the level of asynchronicity at every given instant. We then applied the novel methodology to extracellular, multi-electrode-array recordings on acute brain slices. These slices exhibited robust SO and were subse- quently subjected to neurochemical modulations for eliciting asynchronous awake- like states, emulating a transitional awaking regime. Our analyses show how, on the brink of wakefulness, an excited SO-like activity cohabits with periods of near- asynchrony. Their spatio-temporal interplay depends on the structure of the cortical network: the cortical layer dictates the firing rate intensity, while the cortical col- umn sustains and confines the oscillation. Furthermore, we found that the surges of asynchrony are spatio-temporally correlated, suggesting that the switch from synchrony to asynchrony pervades the whole network. Overall, our findings reveal for the first time that the local circuits have the mechanisms for alternating spontaneously between synchronous and asynchronous states, confirming the recently attributed role of the cortex in the transitions be- tween sleep and wakefulness. Also importantly, our methodological approach en- ables future investigations on state transitions in a variety of neurophysiological contexts.