Installing NEST is (literally) as simple as typing
pip3 install nest-simulator
Or check out our other installation options
quick links
import nest
neurons = nest.Create("iaf_psc_alpha", 10000, {
"V_m": nest.random.normal(-5.0),
"I_e": 1000.0
})
input = nest.Create("noise_generator", params={
"amplitude": 500.0
})
nest.Connect(input, neurons, syn_spec={'synapse_model': 'stdp_synapse'})
spikes = nest.Create("spike_recorder", params={
'record_to': 'ascii',
'label': 'excitatory_spikes'
})
nest.Connect(neurons, spikes)
nest.Simulate(100.0)
nest.raster_plot.from_device(spikes, hist=True)
plt.show()
NEST is one among a set of awesome tools and resources for researchers in neuroscience, robotics, and beyond. If you're looking for ways to analyze your results, compare with other simulators, or want to use a graphical user interface, we have some ideas for you. See our list of related projects.
Did you use NEST in your research? Please cite us! You can also access logo for posters and presentations here.
All model implementations and simulation algorithms in NEST are thoroughly tested and highly optimized. We employ a modern development process, continuous integration, and code reviews to ensure that the NEST code is rock solid at all times. If you want the gritty details and find out how it's done come to the dark side! See our developer facing documentation.