stdp_dopamine_synapse – Synapse type for dopamine-modulated spike-timing dependent plasticity
=============================================================================================

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

``stdp_dopamine_synapse`` is a connection to create synapses with
dopamine-modulated spike-timing dependent plasticity (used as a
benchmark model in [1]_, based on [2]_). The dopaminergic signal is a
low-pass filtered version of the spike rate of a user-specific pool
of neurons. The spikes emitted by the pool of dopamine neurons are
delivered to the synapse via the assigned volume transmitter. The
dopaminergic dynamics is calculated in the synapse itself.

.. warning::

   This synaptic plasticity rule does not take
   :ref:`precise spike timing <sim_precise_spike_times>` into
   account. When calculating the weight update, the precise spike time part
   of the timestamp is ignored.

Parameters
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=================== ============== ======================================================
**Common properties**
-----------------------------------------------------------------------------------------
 volume_transmitter NodeCollection volume_transmitter collecting the spikes from the
                                   pool of dopamine releasing neurons and transmitting
                                   the spikes to the synapse.
 A_plus              real          Multiplier applied to weight changes caused by
                                   pre-before-post spike pairings. If b (dopamine
                                   baseline concentration) is zero, then A_plus
                                   is simply the multiplier for facilitation (as in the
                                   stdp_synapse model). If b is not zero, then A_plus
                                   will be the multiplier for facilitation only if n - b
                                   is positive, where n is the instantenous dopamine
                                   concentration in the volume transmitter. If n - b is
                                   negative, A_plus will be the multiplier for
                                   depression.
 A_minus             real          Multiplier applied to weight changes caused by
                                   post-before-pre spike pairings. If b (dopamine
                                   baseline concentration) is zero, then A_minus
                                   is simply the multiplier for depression (as in the
                                   stdp_synapse model). If b is not zero, then A_minus
                                   will be the multiplier for depression only if n - b
                                   is positive, where n is the instantenous dopamine
                                   concentration in the volume transmitter. If n - b is
                                   negative, A_minus will be the multiplier for
                                   facilitation.
 tau_plus            ms            STDP time constant for weight changes caused by
                                   pre-before-post spike pairings.
 tau_c               ms            Time constant of eligibility trace
 tau_n               ms            Time constant of dopaminergic trace
 b                   real          Dopaminergic baseline concentration
 Wmin                real          Minimal synaptic weight
 Wmax                real          Maximal synaptic weight
=================== ============== ======================================================

The common properties can only be set by :py:func:`.SetDefaults` and apply
to all instances of the synapse model.

=== ======  =====================================
**Individual properties**
-------------------------------------------------
 c  real    Eligibility trace
 n  real    Neuromodulator concentration
=== ======  =====================================

References
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.. [1] Potjans W, Morrison A, Diesmann M (2010). Enabling functional neural
       circuit simulations with distributed computing of neuromodulated
       plasticity. Frontiers in Computational Neuroscience, 4:141.
       DOI: https://doi.org/10.3389/fncom.2010.00141
.. [2] Izhikevich EM (2007). Solving the distal reward problem through linkage
       of STDP and dopamine signaling. Cerebral Cortex, 17(10):2443-2452.
       DOI: https://doi.org/10.1093/cercor/bhl152

Transmits
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SpikeEvent

See also
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:doc:`Synapse <index_synapse>`, :doc:`Spike-Timing-Dependent Plasticity <index_spike-timing-dependent plasticity>`

Examples using this model
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.. listexamples:: stdp_dopamine_synapse