NEURON is designed for empirically-based neural modeling of biological neurons and networks, and is particularly well-suited for use by experimentalists. NEURON also handles models of artificial spiking neurons, which are simulated using an extremely efficient discrete event method. Network models may contain any combination of biophysical and artificial spiking model cells. More than 2000 scientific publications have reported work performed with NEURON (see the list of publications at http://www.neuron.yale.edu/neuron/static/bib/usednrn.html).
NEURON runs on all leading computational platforms from workstations and PCs (UNIX/Linux/macOS and MSWindows) to supercomputers. Simulations can take advantage of parallel hardware ranging from multiple core PCs and Macs through workstation clusters and massively parallel supercomputer hardware.
NEURON was created by Michael Hines and John Moore at Duke University, and Michael has been in charge of its active maintenance, development, and extension ever since. It uses an open source development model to help meet the evolving needs of neuroscientists, and is available free of charge from http://www.neuron.yale.edu.