Welcome to the NEST Simulator documentation!

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 learning and help to shed light on the fundamental principles of how the brain works.

NEST offers convenient and efficient commands to define and connect large networks, ranging from algorithmically determined connections to data-driven connectivity. Create connections between neurons using numerous synapse models from STDP to gap junctions.

How NEST works — The Big Picture

A NEST simulation is created with input from stimulation devices, neuron models, and synapse models, along with connection rules. You can choose what data to record with recording devices. After simulation, the output is ready for analysis with NEST’s built in raster_plot and voltage_trace modules or external tools such as Elephant.

You can find these components in NEST or you can implement your own custom models and extend NEST’s functionalities using NESTML and the NEST extension module, respectively. Check out our wide-ranging list of network model examples.