One of the most distinguishing features of nerve cells is the vast morphological diversity of their input regions, that is, their dendrites. These range from bulbous structures, with only small protrusions, to large tree-like arborizations. The diversity of nerve cells is further augmented by a continuously increasing number of types of voltage-dependent conductances in dendrites that might alter the postsynaptic signals in a pronounced way. Moreover, intracellular factors such as Ca2+ link electrical activity with biochemical processes, and can induce short and long-term changes in responsiveness. This complexity of neurons in general, and the uniqueness of each cell type, sharply contrasts with the comparatively simple and uniform design principle of the integrate-and-fire units of so-called neuronal net models. This raises the question of which particular structural and physiological details of nerve cells really matter for the performance of neuronal circuits. An answer to this basic problem of computational neurobiology might be given only if the task of the neurons and circuits is known. This review illustrates how the problem can be approached particularly well in sensory interneurons. The functional significance of sensory interneurons can often be assessed more easily than that of central nerve cells because of their vicinity to the sensory surface.