Date of Award


Degree Type


Degree Name

Doctor of Philosophy (PhD)

Graduate Group


First Advisor

Alexander Proekt

Second Advisor

Diego Contreras


General anesthetics are a class of drugs with diverse molecular mechanisms that cause a state of unconsciousness. Generally, anesthetics are thought to exert this effect by co- opting endogenous sleep pathways within the brain, and activity patterns recorded during anesthesia resemble those recorded during natural sleep. Monitors of anesthetic depth take advantage of the relationship between brain activity patterns and anesthetic concentration to define a depth of exposure. Recovery from anesthetic-induced unconsciousness is typically assumed to be a passive, linear process that relies upon elimination of drug from the body. However, it has been shown that activity patterns undergo discrete transitions between several distinct brain states under anesthesia. Furthermore, the brain exhibits a resistance to recovery of consciousness during emergence from anesthesia. Together, these results show that emergence cannot be explained by drug elimination alone.

In this dissertation, we present evidence to suggest that stochastic fluctuations between distinct brain states account for this resistance to emergence. Furthermore, we show evidence to suggest that local cortical interactions are the principal organizing mechanism that gives rise to the brain states and state transitions recorded under general anesthesia. This mechanism is distinct from those known to drive state transitions during natural sleep. During sleep, broadly projecting modulatory pathways engage neurons throughout the thalamocortical network in coherent activity patterns and state transitions. Here, we demonstrate local heterogeneity in activity patterns and transition times within the cortex. Furthermore, our results indicate that, despite there being only weak coupling between activity patterns and transition times between different cortical regions, this coupling is sufficient to give rise to global brain states.

Altogether, the work presented in this dissertation indicates that the nature of oscillations within the cortex is strongly influenced by local interactions. This finding suggests that the mechanisms thought to give rise to state transitions during sleep are not the same as those that give rise to transitions under anesthesia. This finding that local interactions are potentially a stronger organizing mechanism for cortical activity than previously appreciated has important implications for anesthetic monitoring, clinical sleep disorders, and our basic understanding of thalamocortical activity patterns.

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