sinusoidal_gamma_generator – Generates sinusoidally modulated gamma spike trains
================================================================================

Description
+++++++++++

``sinusoidal_gamma_generator`` generates sinusoidally modulated gamma spike
trains. By default, each target of the generator will receive a different
spike train.

The instantaneous rate of the process is given by

.. math::

 f(t) = \mathrm{rate} + \mathrm{amplitude} \cdot \sin \left(
    2 \pi \cdot \mathrm{frequency} \cdot t + \mathrm{phase} \cdot
    \frac{\pi}{180} \right)

.. note::

   - The gamma generator requires
     :math:`0 \leq \mathrm{amplitude} \leq \mathrm{rate}`.
   - The state of the generator is reset on calibration.
   - The generator does not support precise spike timing.
   - You can use the multimeter to sample the rate of the generator.
   - The generator will create different trains if run at different
     temporal resolutions.

By default, the generator sends a different spike train to each of its
targets. If ``individual_spike_trains`` is set to ``False`` using either
:py:func:`.SetDefaults` or :py:func:`.CopyModel` before a generator node
is created, the generator will send the same spike train to all of its targets.

.. include:: ../models/stimulation_device.rst

rate
    Mean firing rate in spikes/second. Default: ``0.0``.

amplitude
    Firing rate modulation amplitude in spikes/second. Default: ``0.0``.

frequency
    Modulation frequency in Hz. Default: ``0.0``.

phase
    Modulation phase in degree [0-360]. Default: ``0.0``.

order
    Gamma order (>= 1). Default: ``1``.

individual_spike_trains
    See note above. Default: ``True``.

See also [1]_.

Setting parameters from a stimulation backend
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The parameters in this stimulation device can be updated with input
coming from a stimulation backend. The data structure used for the
update holds one value for each of the parameters mentioned above.
The indexing is as follows:

 0. frequency
 1. phase
 2. order
 3. rate
 4. amplitude
 5. individual_spike_trains

Receives
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DataLoggingRequest

Sends
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SpikeEvent

References
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.. [1] Barbieri et al. (2001). Construction and analysis of non-Poisson
       stimulus-response models of neural spiking activity. Journal of
       Neuroscience Methods, 105:25-3.
       DOI: https://doi.org/10.1016/S0165-0270(00)00344-7

See also
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:doc:`Device <index_device>`, :doc:`Generator <index_generator>`

Examples using this model
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.. listexamples:: sinusoidal_gamma_generator