Welcome to the NEST Simulator documentation! ============================================ .. grid:: :gutter: 2 .. grid-item:: .. grid:: 1 1 1 1 :gutter: 2 .. grid-item:: 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. .. grid-item:: .. button-ref:: tutorials_guides :ref-type: ref :shadow: :color: primary Start exploring NEST .. grid-item:: .. grid:: 1 1 1 1 :gutter: 2 .. grid-item-card:: .. carousel:: :show_indicators: :show_fade: :show_dark: :data-bs-ride: carousel .. figure:: static/img/network_model_sketch_mesocircuit.png Create spatially structured networks .. figure:: static/img/astrocyte_interaction.png Inspect neuron and astrocyte interactions .. figure:: static/img/hpc_benchmark_connectivity.svg Test perfomance and benchmarks .. figure:: static/img/pong_sim.gif Simulate a game of PONG with NEST .. figure:: static/img/gapjunctions.png Explore synapse types like gap junctions .. grid-item:: .. button-ref:: pynest_examples :ref-type: ref :color: info :align: center :shadow: Discover all our examples! How NEST works --- The Big Picture ---------------------------------- .. grid:: .. grid-item:: .. raw:: html .. grid:: .. grid-item:: A NEST simulation is created with input from :doc:`stimulation devices `, :doc:`neuron models `, and :doc:`synapse models `, along with :ref:`connection rules `. You can choose what data to record with :doc:`recording devices `. After simulation, the output is ready for analysis with NEST's built in :py:mod:`.raster_plot` and :py:mod:`.voltage_trace` modules or external tools such as :doc:`Elephant `. You can find these components in NEST or you can implement your own custom models and extend NEST's functionalities using :doc:`NESTML ` and the :doc:`NEST extension module `, respectively. Check out our wide-ranging list of :doc:`network model ` examples. .. toctree:: :caption: USAGE :hidden: :glob: Install Tutorials and Guides Examples Models Python API ref_material/glossary benchmark_results Cite NEST License .. toctree:: :caption: COMMUNITY :hidden: :glob: Contact us Contribute What's new? NEST Homepage Acknowledgments .. toctree:: :caption: RELATED PROJECTS :hidden: NEST Desktop NESTML NESTGPU