.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/twoneurons.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_examples_twoneurons.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_twoneurons.py:


Two neuron example
------------------

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----

 Run this example as a Jupyter notebook:

  .. card::
    :width: 25%
    :margin: 2
    :text-align: center
    :link: https://lab.ebrains.eu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fnest%2Fnest-simulator-examples&urlpath=lab%2Ftree%2Fnest-simulator-examples%2Fnotebooks%2Fnotebooks%2Ftwoneurons.ipynb&branch=main
    :link-alt: JupyterHub service

    .. image:: https://nest-simulator.org/TryItOnEBRAINS.png


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   :padding: 0 0 2 0

   .. grid-item::
     :class: sd-text-muted
     :margin: 0 0 3 0
     :padding: 0 0 3 0
     :columns: 4

     See :ref:`our guide <run_jupyter>` for more information and troubleshooting.

----


This script simulates two connected pre- and postsynaptic neurons.
The presynaptic neuron receives a constant external current,
and the membrane potential of both neurons are recorded.

See Also
~~~~~~~~

:doc:`one_neuron`

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First, we import all necessary modules for simulation, analysis and plotting.
Additionally, we set the verbosity to suppress info messages and reset
the kernel.

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.. code-block:: Python


    import matplotlib.pyplot as plt
    import nest
    import nest.voltage_trace

    nest.set_verbosity("M_WARNING")
    nest.ResetKernel()


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Second, we create the two neurons and the recording device.

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.. code-block:: Python


    neuron_1 = nest.Create("iaf_psc_alpha")
    neuron_2 = nest.Create("iaf_psc_alpha")
    voltmeter = nest.Create("voltmeter")


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Third, we set the external current of neuron 1.

.. GENERATED FROM PYTHON SOURCE LINES 58-61

.. code-block:: Python


    neuron_1.I_e = 376.0


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Fourth, we connect neuron 1 to neuron 2.
Then, we connect a voltmeter to the two neurons.
To learn more about the previous steps, please check out the
:doc:`one neuron example <one_neuron>`.

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.. code-block:: Python


    weight = 20.0
    delay = 1.0

    nest.Connect(neuron_1, neuron_2, syn_spec={"weight": weight, "delay": delay})
    nest.Connect(voltmeter, neuron_1)
    nest.Connect(voltmeter, neuron_2)


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Now we simulate the network using ``Simulate``, which takes the
desired simulation time in milliseconds.

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.. code-block:: Python


    nest.Simulate(1000.0)


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Finally, we plot the neurons' membrane potential as a function of
time.

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.. code-block:: Python


    nest.voltage_trace.from_device(voltmeter)
    plt.show()


.. _sphx_glr_download_auto_examples_twoneurons.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: twoneurons.ipynb <twoneurons.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: twoneurons.py <twoneurons.py>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_