Date Awarded


Document Type


Degree Name

Doctor of Philosophy (Ph.D.)


Applied Science


Christopher A Del Negro

Committee Member

Leah B Shaw

Committee Member

Cheng Ly


Breathing is the rhythmic motor behavior which maintains homeostasis by driving gas exchange between our blood and the atmosphere. This behavior is essential for life in all terrestrial mammals. This behavior involves two distinct but coupled rhythms: the inspiratory rhythm, the normal breathing rhythm that occurs on the order of seconds, and the sigh rhythm, which produces large amplitude breaths that occur on the order of minutes and maintain pulmonary function. The rhythm for both behaviors and their control originates in a specialized neuronal region of the ventral medulla called the preBötzinger complex (preBötC). While we know the anatomical region that generates these behaviors, the mechanism by which they are generated remains the subject of debate. We used a suite of experiments that utilized transgenic mouse models to falsify a long-standing theory that auto-rhythmic neurons are essential in generating the inspiratory rhythm. Concurrently, we developed a mathematical model which predicts the sigh rhythm emerges due to intracellular calcium oscillation. These findings have led us to investigate the inspiratory rhythm as an emergent network property. This dissertation investigates the underlying network structure of the preBötC by modeling its constituent neurons using a spiking model. The network is driven by neurons that fire stochastically, but none are intrinsically autorhythmic properties. First, we show that synaptic topology influences the ability of a network to form burstlets, a phenomenon that underlies inspiratory rhythmogenesis, the ability of a network to trigger network excitation exogenously, and the robustness of network function. We were able to recapitulate several experimental findings with our model and show that an Erdős–Rényi network with log-normally distributed synaptic weights provides the highest fidelity. Finally, we implement intracellular calcium oscillations within the consitutent neurons of the network to create the first spiking model of the preBötC that can produce burstlets and sighs. This model could help explain respiratory pathologies, such as opioid-induced respiratory depression, and provide insights the other brain rhythmics.




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