- "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.