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Welcome to the NEST Simulator documentation!

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NEST is a simulator for spiking neural network models that focuses on the dynamics, size and structure of neural systems rather than on the exact morphology of individual neurons.

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NEST is used in computational neuroscience to model and study behavior of large networks of neurons. The models describe single neuron and synapse behavior and their connections. Different mechanisms of plasticity can be used to investigate artificial learning and help to shed light on the fundamental principles of how the brain works.

NEST is ideal for networks of spiking neurons of any size, and scales flexibly from running on your laptop to high-performance computing systems involving hundreds of compute nodes.

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It can be used to simulate small and large-scale models of information processing e.g. in the visual or auditory cortex of mammals, odels of network activity dynamics, e.g. laminar cortical networks or balanced random networks, and supports many models of learning and plasticity.

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