Single neurone models: oversimple, complex and reduced

Abstract

The single neurone stands in the midst of a controversy among modelers. Some believe that its details are functionally superfluous when the neurone operates in a large network, and very simple models can be used to represent the input/output characteristics of neurones. Others claim that the unique morphology and electrical properties of neurones do play an important role. Complicated models of neurones are developed to reveal how the various kinds of 'neurone-ware' (dendrites, spines, axons, membrane channels and synapses) create a computationally powerful unit. Various models are discussed, including new carefully reduced models that retain essential features of more complex models. Such intermediate models will play a central role in our efforts to understand information processing in large neuronal networks.