Control analysis of the action potential and its propagation in the Hodgkin-Huxley model

[摘要] ENGLISH ABSTRACT: The Hodgkin-Huxley model, created in 1952, was one of the first models incomputational neuroscience and remains the best studied neuronal model todate. Although many other models have a more detailed system descriptionthan the Hodgkin-Huxley model, it nonetheless gives an accurate account ofvarious high-level neuronal behaviours.The fields of computational neuroscience and Systems Biology havedeveloped as separate disciplines for a long time and only fairly recently has theneurosciences started to incorporate methods from Systems Biology. MetabolicControl Analysis (MCA), a Systems Biology tool, has not been used in theneurosciences. This study aims to further bring these two fields together, bytesting the feasibility of an MCA approach to analyse the Hodgkin-Huxleymodel.In MCA it is not the parameters of the system that are perturbed, as inthe more traditional sensitivity analysis, but the system processes, allowing theformulation of summation and connectivity theorems. In order to determineif MCA can be performed on the Hodgkin-Huxley model, we identified allthe discernable model processes of the neuronal system. We performed MCAand quantified the control of the model processes on various high-level timeinvariant system observables, e.g. the action potential (AP) peak, firingthreshold, propagation speed and firing frequency. From this analysis weidentified patterns in process control, e.g. the processes that would causean increase in sodium current, would also cause the AP threshold to lower(decrease its negative value) and the AP peak, propagation speed and firingfrequency to increase. Using experimental inhibitor titrations from literaturewe calculated the control of the sodium channel on AP characteristics andcompared it with control coefficients derived from our model simulation.Additionally, we performed MCA on the model's time-dependent statevariables during an AP. This revealed an intricate linking of the systemvariables via the membrane potential. We developed a method to quantify the contribution of the individual feedback loops in the system. We couldthus calculate the percentage contribution of the sodium, potassium and leakcurrents leading to the observed global change after a system perturbation.Lastly, we compared ion channel mutations to our model simulations andshowed how MCA can be useful in identifying targets to counter the effect ofthese mutations.In this thesis we extended the framework of MCA to neuronal systems andhave successfully applied the analysis framework to quantify the contributionof the system processes to the model behaviour.

[发布机构] Stellenbosch University