Key papers about NEURON

"The NEURON simulation environment" (overviewforhbtnn2e.pdf)
by Hines & Carnevale. Preprint of an "executive summary" published as
Hines, M.L. and Carnevale, N.T. The NEURON simulation environment. In: The Handbook of Brain Theory and Neural Networks, 2nd ed, edited by M.A. Arbib. Cambridge, MA: MIT Press, 2003, pp. 769-773.
Read this to learn why you should use NEURON.
"The NEURON simulation environment"
An earlier paper with the same title, expanded from our first article in Neural Computation. Full of useful information for NEURON newbies.
"NEURON: a tool for neuroscientists"
by Hines & Carnevale. Powerful strategies for improving spatiotemporal accuracy while preserving computational efficiency.
1. The d_lambda criterion, a simple but very effective method for specifying the spatial grid.
2. Variable order / variable timestep integration with CVODE.
"Expanding NEURON's repertoire of mechanisms with NMODL"
by Hines & Carnevale.
"Efficient discrete event simulation of spiking neurons in NEURON"
a PDF of our poster from the 2002 SFN Meeting that describes the three classes of integrate-and-fire ("artificial") neuron models that are built into NEURON.
"Translating network models to parallel hardware in NEURON"
by Hines and Carnevale. This paper should be read by anyone who intends to develop a network model, regardless of whether they intend to use serial or parallel hardware to run simulations.