Dynamical criticality during induction of anesthesia in human ECoG recordings

In this work we analyze electro-corticography (ECoG) recordings in human sub- jects as they are anesthetized. We hypothesize that the decrease in responsiveness that defines anesthesia induction is concomitant with the stabilization of neuronal dynamics. To test this hypothesis, we performed a moving vector autoregressive analysis and quantified stability of neuronal dynamics using eigenmode decompo- sition of the autoregressive matrices, independently fitted to short sliding temporal windows. Consistent with the hypothesis we show that while the subject is awake, many modes of oscillations of neuronal activity are found at the edge of instabil- ity, but as the subject becomes anesthetized the fitted dynamics becomes more damped. Analysis of eigenmode distributions in the awake and anesthetized brain revealed statistically significant stabilization not present in surrogate data. Sta- bility analysis thus offer a novel way of quantifying changes in neuronal activity that characterize loss of consciousness induced by general anesthetics. Specifically, our analysis suggests that the effect of the anesthetic procedure is to damp out high frequency activity while still allowing for low frequency modes to perform a function.