Marc-Oliver Gewaltig and Markus Diesmann, "NEST (Neural Simulation Tool)", Scholarpedia Encyclopedia of Computational Neuroscience, online, pp. 11204, 2007.

The Neural Simulation Tool NEST is a computer program for simulating large heterogeneous networks of point neurons or neurons with a small number of compartments. NEST is best suited for models that focus on the dynamics, size, and structure of neural systems rather than on the detailed morphological and biophysical properties of individual neurons. Examples are: * Models of sensory processing e.g. in the visual or auditory cortex of mammals. * Models of network activity dynamics, e.g. in laminar cortical networks or random balanced networks. * Models of spike-synchronization in feed-forward networks such as Synfire Chains. * Learning and plasticity in models of sensory processing. NEST is developed by the NEST Initiative, a contract-based collaboration between several academic and industrial research institutes, and is available free of charge as source code.