.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/ignore_and_spike_mechanism.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_ignore_and_spike_mechanism.py>`
        to download the full example code.

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

.. _sphx_glr_auto_examples_ignore_and_spike_mechanism.py:


Ignore-and-spike mechanism example
-----------------------------------

.. only:: html

----

 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%2Fignore_and_spike_mechanism.ipynb&branch=main
    :link-alt: JupyterHub service

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


.. grid:: 1 1 1 1
   :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 demonstrates the ignore-and-spike mechanism, which causes
a neuron to spike at defined intervals with a specified initial offset,
ignoring spikes from its internal dynamics.

Two neurons are simulated: one with the ignore-and-spike mechanism enabled
and one without. Both receive the same external current, and their spike
times are recorded and compared.

.. GENERATED FROM PYTHON SOURCE LINES 36-39

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

.. GENERATED FROM PYTHON SOURCE LINES 39-46

.. code-block:: Python


    import matplotlib.pyplot as plt
    import nest

    nest.verbosity = nest.VerbosityLevel.WARNING
    nest.ResetKernel()


.. GENERATED FROM PYTHON SOURCE LINES 47-48

Second, we set the simulation resolution.

.. GENERATED FROM PYTHON SOURCE LINES 48-51

.. code-block:: Python


    nest.set(resolution=0.1)


.. GENERATED FROM PYTHON SOURCE LINES 52-56

Third, we create two neurons and a spike recorder.
The first neuron uses the ignore-and-spike mechanism to fire at regular
intervals (every 10 ms, starting at 5 ms). The second neuron behaves
normally, responding to its internal dynamics.

.. GENERATED FROM PYTHON SOURCE LINES 56-69

.. code-block:: Python


    nrn_regular = nest.Create("iaf_psc_delta")
    nrn_ignore_spike = nest.Create(
        "iaf_psc_delta",
        params=dict(
            ignore_and_spike=True,
            ignore_and_spike_offset=5.0,
            ignore_and_spike_interval=10.0,
        ),
    )

    spike_recorder = nest.Create("spike_recorder")


.. GENERATED FROM PYTHON SOURCE LINES 70-73

Fourth, we set the same external current for both neurons.
Without the ignore-and-spike mechanism, this would cause irregular spiking
based on the neuron's membrane dynamics.

.. GENERATED FROM PYTHON SOURCE LINES 73-77

.. code-block:: Python


    nrn_regular.I_e = 400.0
    nrn_ignore_spike.I_e = 400.0


.. GENERATED FROM PYTHON SOURCE LINES 78-79

Fifth, we connect both neurons to the spike recorder.

.. GENERATED FROM PYTHON SOURCE LINES 79-83

.. code-block:: Python


    nest.Connect(nrn_regular, spike_recorder)
    nest.Connect(nrn_ignore_spike, spike_recorder)


.. GENERATED FROM PYTHON SOURCE LINES 84-85

Now we simulate the network for 100 ms.

.. GENERATED FROM PYTHON SOURCE LINES 85-88

.. code-block:: Python


    nest.Simulate(100.0)


.. GENERATED FROM PYTHON SOURCE LINES 89-92

Finally, we retrieve the spike times and plot them as a raster plot.
The neuron with ignore-and-spike enabled should show perfectly regular
spikes at 5, 15, 25, 35, ... ms, regardless of the external input.

.. GENERATED FROM PYTHON SOURCE LINES 92-114

.. code-block:: Python


    events = spike_recorder.get("events")
    senders = events["senders"]
    times = events["times"]

    fig, ax = plt.subplots(figsize=(6, 2))
    fig.subplots_adjust(left=0.3, right=0.95)

    ax.scatter(times, senders, marker="|", color="#3455B4", s=300)
    ax.set_xlabel("Time (ms)")
    ax.set_yticks([nrn_regular.global_id, nrn_ignore_spike.global_id])
    ax.set_yticklabels(["Regular neuron", "Ignore-and-spike\nneuron"], ha="center")
    ax.tick_params(axis="y", pad=50)
    ax.set_xticks(range(0, 105, 5))
    ax.set_xlim(0, 100)
    ax.set_ylim(0.5, 2.5)
    ax.spines[["top", "right"]].set_visible(False)
    ax.grid(True, alpha=0.3)

    fig.tight_layout()

    plt.show()


.. _sphx_glr_download_auto_examples_ignore_and_spike_mechanism.py:

.. only:: html

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

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

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

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

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

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: ignore_and_spike_mechanism.zip <ignore_and_spike_mechanism.zip>`


.. only:: html

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

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