stdp_synapse_facetshw_hom – Synapse type for spike-timing dependent plasticity using homogeneous parameters
===========================================================================================================

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

``stdp_facetshw_synapse`` is a connector to create synapses with spike-timing
dependent plasticity (as defined in [1]_).
This connector is a modified version of ``stdp_synapse``.
It includes constraints of the hardware developed in the FACETS (BrainScaleS)
project [2]_, [3]_, as for example, 4-bit weight resolution, sequential updates of groups
of synapses and reduced symmetric nearest-neighbor spike pairing scheme. For
details see [3]_.
The modified spike pairing scheme requires the calculation of ``tau_minus_``
within this synapse and not at the neuron site via ``Kplus_`` like in
``stdp_synapse_hom``.

.. 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.

The synapse IDs are assigned to each synapse in an ascending order (0,1,2,
...) according their first presynaptic activity and is used to group synapses
that are updated at once. It is possible to avoid activity dependent synapse
ID assignments by manually setting the no_synapses and the synapse_id(s)
before running the simulation. The weights will be discretized after the
first presynaptic activity at a synapse.

Parameters
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======================= =========== ===========================================
**Common properties**
-------------------------------------------------------------------------------
 tau_plus               ms          Time constant of STDP window, causal branch
 tau_minus_stdp         ms          Time constant of STDP window, anti-causal
                                    branch
 Wmax                   real        Maximum allowed weight
 no_synapses            integer     Total number of synapses
 synapses_per_driver    integer     Number of synapses updated at once
 driver_readout_time    real        Time for processing of one synapse row
                                    (synapse line driver)
 readout_cycle_duration real        Duration between two subsequent
                                    updates of same synapse (synapse line
                                    driver)
 lookuptable_0          list of     Three look-up tables (LUT)
                        integers
 lookuptable_1          list of
                        integers
 lookuptable_2          list of
                        integers
 configbit_0            list of     Configuration bits for evaluation
                        integers    function. For details see code in
                                    function ``eval_function_`` and [4]_
                                    (configbit[0]=e_cc, ..[1]_=e_ca,
                                    ..[2]_=e_ac, ..[3]=e_aa).
                                    Depending on these two sets of
                                    configuration bits weights are updated
                                    according LUTs (out of three: (1,0),
                                    (0,1), (1,1)). For (0,0) continue
                                    without reset.
 configbit_1            list of
                        integers
 reset_pattern          list of     Configuration bits for reset behavior.
                        integers    Two bits for each LUT (reset causal
                                    and acausal). In hardware only (all
                                    false; never reset) or (all true;
                                    always reset) is allowed.
======================= =========== ===========================================

Common properties can only be set on the synapse model using
:py:func:`.SetDefaults`.

============  ======= =====================================================
**Individual properties**
---------------------------------------------------------------------------
 a_causal     real    Causal and anti-causal spike pair accumulations
 a_acausal    real
 a_thresh_th  real    Two thresholds used in evaluation function
                      No common property, because variation of analog
                      synapse circuitry can be applied here
 a_thresh_tl  real
 synapse_id   integer Synapse ID, used to assign synapses to groups (synapse
                      drivers)
============  ======= =====================================================

Transmits
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SpikeEvent

References
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.. [1] Morrison A, Diesmann M, Gerstner W (2008). Phenomenological models of
       synaptic plasticity based on spike-timing. Biological Cybernetics,
       98:459-478. DOI: https://doi.org/10.1007/s00422-008-0233-1
.. [2] Schemmel J, Gruebl A, Meier K, Mueller E (2006). Implementing synaptic
       plasticity in a VLSI spiking neural network model. In Proceedings of the
       2006 International Joint Conference on Neural Networks, pp.1--6,
       IEEE Press. DOI: https://doi.org/10.1109/IJCNN.2006.246651
.. [3] Pfeil T, Potjans TC, Schrader S, Potjans W, Schemmel J, Diesmann M,
       Meier K (2012). Is a 4-bit synaptic weight resolution enough? -
       constraints on enabling spike-timing dependent plasticity in
       neuromorphic hardware. Frontiers in Neuroscience 6(90).
       DOI: https://doi.org/10.3389/fnins.2012.00090
.. [4] Friedmann, S. in preparation

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