Neurons make use of their complex cellular and intracellular architecture to process and guide electrical and biochemical signals. To study this structure-function interplay, computational methods are detremental, since many parameters are not directly accessible in an experimental setting. This also means that the detailed three-dimensional morphology of cells and organelles needs to be included in modeling and simulation, which results in complex-domain problems, described by systems of coupled, nonlinear, partial differential equations. We have developed numerical discretization methods and fast solvers to address this general type of biological problem set, with a focus on optimal weak scalability on High Performance Computing infrastructures. We present some of the important biological problems revolving around cellular calcium signaling, coupled to electrical models, and the use of our NeuroBox Toolbox and the multiphysics platform uG4 to solve such ultrastructural 3D neuron models. Selected results show how neurons are capable of using their (intra)cellular architecture to fine-tune their response to exterior/network input.