# Command: tsodyks2_synapse

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Name:

    tsodyks2_synapse - Synapse type with short term plasticity.

Description:

      This synapse model implements synaptic short-term depression and short-term
      facilitation according to [1] and [2]. It solves Eq (2) from [1] and
      modulates U according to eq. (2) of [2].

      This connection merely scales the synaptic weight, based on the spike history
      and the parameters of the kinetic model. Thus, it is suitable for all types
      of synaptic dynamics, that is current or conductance based.

      The parameter A_se from the publications is represented by the
      synaptic weight. The variable x in the synapse properties is the
      factor that scales the synaptic weight.

Parameters:

      The following parameters can be set in the status dictionary:
      U	 double	- probability of release increment (U1) [0,1],
      default=0.5
      u	 double	- Maximum probability of release (U_se) [0,1],
      default=0.5
      x	 double	- current scaling factor of the weight, default=U
      tau_rec   double	- time constant for depression in ms, default=800 ms
      tau_fac   double	- time constant for facilitation in ms, default=0 (off)

Transmits:

    SpikeEvent

Remarks:

      Under identical conditions, the tsodyks2_synapse produces
      slightly lower peak amplitudes than the tsodyks_synapse. However,
      the qualitative behavior is identical. The script
      test_tsodyks2_synapse.py in the examples compares the two synapse
      models.

References:

      [1] Tsodyks, M. V., & Markram, H. (1997). The neural code between neocortical
      pyramidal neurons depends on neurotransmitter release probability.
      PNAS, 94(2), 719-23.
      [2] Fuhrmann, G., Segev, I., Markram, H., & Tsodyks, M. V. (2002). Coding of
      temporal information by activity-dependent synapses. Journal of
      neurophysiology, 87(1), 140-8.
      [3] Maass, W., & Markram, H. (2002). Synapses as dynamic memory buffers.
      Neural networks, 15(2), 155-61.

Author:

    Marc-Oliver Gewaltig, based on tsodyks_synapse by Moritz Helias

FirstVersion:

    October 2011

SeeAlso:

- tsodyks_synapse
- synapsedict
- stdp_synapse
- static_synapse

Source:

    /opt/conda/conda-bld/nest_1510212701067/work/nest-2.14.0/models/tsodyks2_connection.h

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