Command: tsodyks_synapse

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Name:
 tsodyks_synapse - Synapse type with short term plasticity.

Description:
   This synapse model implements synaptic short-term depression and short-term facilitation
   according to [1]. In particular it solves Eqs (3) and (4) from this paper in an
   exact manner.

   Synaptic depression is motivated by depletion of vesicles in the readily releasable pool
   of synaptic vesicles (variable x in equation (3)). Synaptic facilitation comes about by
   a presynaptic increase of release probability, which is modeled by variable U in Eq (4).
   The original interpretation of variable y is the amount of glutamate concentration in
   the synaptic cleft. In [1] this variable is taken to be directly proportional to the
   synaptic current caused in the postsynaptic neuron (with the synaptic weight w as a
   proportionality constant). In order to reproduce the results of [1] and to use this
   model of synaptic plasticity in its original sense, the user therefore has to ensure
   the following conditions:

   1.) The postsynaptic neuron must be of type iaf_psc_exp or iaf_tum_2000, because
   these neuron models have a postsynaptic current which decays exponentially.

   2.) The time constant of each tsodyks_synapse targeting a particular neuron
   must be chosen equal to that neuron's synaptic time constant. In particular that means
   that all synapses targeting a particular neuron have the same parameter tau_psc.

   However, there are no technical restrictions using this model of synaptic plasticity
   also in conjunction with neuron models that have a different dynamics for their synaptic
   current or conductance. The effective synaptic weight, which will be transmitted
   to the postsynaptic neuron upon occurrence of a spike at time t is u(t)*x(t)*w, where
   u(t) and x(t) are defined in Eq (3) and (4), w is the synaptic weight specified upon
   connection.
   The interpretation is as follows: The quantity u(t)*x(t) is the release probability
   times the amount of releasable synaptic vesicles at time t of the presynaptic neuron's
   spike, so this equals the amount of transmitter expelled into the synaptic cleft.
   The amount of transmitter than relaxes back to 0 with time constant tau_psc of the
   synapse's variable y.
   Since the dynamics of y(t) is linear, the postsynaptic neuron can reconstruct from the
   amplitude of the synaptic impulse u(t)*x(t)*w the full shape of y(t).
   The postsynaptic neuron, however, might choose to have a synaptic current that is not
   necessarily identical to the concentration of transmitter y(t) in the synaptic cleft.
   It may realize an arbitrary postsynaptic effect depending on y(t).

Parameters:
 
     The following parameters can be set in the status dictionary:
     Us         double - maximum probability of realease [0,1]
     tau_pscs   double - time constants of synaptic current in ms
     tau_facs   double - time constant for facilitation in ms
     tau_recs   double - time constant for depression in ms
     xs         double - initial fraction of synaptic vesicles in the readily releasable pool [0,1]
     ys         double - initial fraction of synaptic vesicles in the synaptic cleft [0,1]

References:
   [1] Tsodyks, Uziel, Markram (2000) Synchrony Generation in Recurrent Networks
       with Frequency-Dependent Synapses. Journal of Neuroscience, vol 20 RC50

Transmits:
 SpikeEvent
       
FirstVersion:
 March 2006
Author:
 Moritz Helias
SeeAlso:synapsedict stdp_synapse static_synapse iaf_psc_exp iaf_tum_2000
Source:
 /home/abuild/rpmbuild/BUILD/nest-2.4.1/models/tsodyks_connection.h

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