| Contents |
| Since the 1950s, there have been a steadily maturing theory for model-based control of systems, as well as a steadily improving computational neuroscience demonstrating models with increasing fidelity to the biophysics and dynamics of neuronal systems. We have recently demonstrated that there is an emergent unification between seizures and spreading depression (the physiology of migraine auras), derived by improving the biophysical modeling and introducing conservation principles into an extension of the Hodgkin-Huxley equations. Such models represent nodes within neuronal graph directed networks. The topology of how such nodes are connected determines the structural observability and controllability of neuronal systems, which is highly dependent upon the presence of symmetries in such connectivity. We discuss the implications of nodal dynamics and topology on strategies for closed-loop control of neuronal systems. |
|