NEURON was initially developed to handle models of individual cells or parts of cells, in which complex membrane properties and extended geometry play important roles (Hines 1989; 1993; 1995). However, as the research interests of experimental and theoretical neuroscientists evolved, NEURON has been revised to meet their changing needs. Since the early 1990s it has been used to model networks of biological neurons (e.g. Destexhe et al. 1993; Lytton et al. 1997; Sohal et al. 2000). This work stimulated the development of powerful strategies that increase the convenience and efficiency of creating, managing, and exercising such models (Destexhe et al. 1994; Lytton 1996; Hines and Carnevale 2000). Increasing research activity on networks of spiking neurons (e.g. Riecke et al. 1997; Maass and Bishop 1999) prompted further enhancements to NEURON, such as inclusion of an event delivery system and development of the NetCon (network connection) class (see Chapter 10).

Consequently, since the latter 1990s, NEURON has been capable of efficient simulations of networks that may include biophysical neuron models and/or artificial spiking neurons.