Principles of Computational Modelling in Neuroscience

So far, we have been discussing how to model accurately the electrical and chemical properties of neurons and how these cells interact within the networks of cells forming the nervous system. The existence of a correct structure is essential for proper functioning of the nervous system, and we now discuss modelling of the development of the nervous system. Most existing models of developmental processes are not as widely accepted as, for example, the Hodgkin–Huxley model of nerve impulse propagation. They are designed on the basis of usually unverified assumptions to test a particular theory for neural development. Our aim is to cast light on the different types of issues that arise when constructing a model of development through discussing several case examples of models applied to particular neural developmental phenomena. We look at models constructed at the levels of individual neurons and of ensembles of nerve cells.