Reduced computational modelling of Kölliker-Fuse contributions to breathing patterns in Rett syndrome

Reduced computational models are used to test effects of loss of inhibition to the Kölliker-Fuse nucleus (KFn). Three reduced computational models that simulate eupnoeic and vagotomized respiratory rhythms are considered. All models exhibit the emergence of respiratory perturbations associated with Rett syndrome as inhibition to the KFn is diminished. Simulations suggest that application of 5-HT_1A agonists can mitigate the respiratory pathology. The three models can be distinguished and tested based on their predictions about connections and dynamics within the respiratory circuit and about effects of perturbations on certain respiratory neuron populations.

Rett syndrome (RTT) is a developmental disorder that can lead to respiratory disturbances featuring prolonged apnoeas of variable durations. Determining the mechanisms underlying these effects at the level of respiratory neural circuits would have significant implications for treatment efforts and would also enhance our understanding of respiratory rhythm generation and control. While experimental studies have suggested possible factors contributing to the respiratory patterns of RTT, we take a novel computational approach to the investigation of RTT, which allows for direct manipulation of selected system parameters and testing of specific hypotheses. Specifically, we present three reduced computational models, developed using an established framework, all of which successfully simulate respiratory outputs across eupnoeic and vagotomized conditions. All three models show that loss of inhibition to the Kölliker-Fuse nucleus reproduces the key respiratory alterations associated with RTT and, as suggested experimentally, that effects of 5-HT_1A agonists on the respiratory neural circuit suffice to alleviate this respiratory pathology. Each of the models makes distinct predictions regarding the neuronal populations and interactions underlying these effects, suggesting natural directions for future experimental testing.