Modeling regional changes in dynamic stability during sleep and wakefulness.

Abstract

Global brain states are frequently placed within a unidimensional continuum by correlational studies, ranging from states of deep unconsciousnessto ordinarywakefulness. An alternative is their multidimensional and mechanistic characterization in terms of different cognitive capacities, using computational models toreproduce the underlying neural dynamics. We explore this alternative by introducing a semi-empirical model linking regional activation and long-range functionalconnectivity in the different brain states visited during the natural wake-sleep cycle. Our model combines functional magnetic resonance imaging (fMRI) data,in vivoestimates of structural connectivity, and anatomically-informed priors to constrain the independent variation of regional activation. The bestfit to empirical data wasachieved using priors based on functionally coherent networks, with the resulting model parameters dividing the cortex into regions presenting opposite dynamicalbehavior. Frontoparietal regions approached a bifurcation from dynamics at afixed point governed by noise, while sensorimotor regions approached a bifurcationfrom oscillatory dynamics. In agreement with human electrophysiological experiments, sleep onset induced subcortical deactivation with low correlation, which wassubsequently reversed for deeper stages. Finally, we introduced periodic forcing of variable intensity to simulate external perturbations, and identified the key regionsrelevant for the recovery of wakefulness from deep sleep. Our model represents sleep as a state with diminished perceptual gating and the latent capacity for globalaccessibility that is required for rapid arousals. To the extent that the qualitative characterization of local dynamics is exhausted by the dichotomy between unstableand stable behavior, our work highlights how expanding the model parameter space can describe states of consciousness in terms of multiple dimensions with in-terpretations given by the choice of anatomically-informed priors