# Command: synaptic_element

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Name:

    synaptic_element - Contact point element for the dynamic creation
      and deletion of synapses.

Description:

      This class represents synaptic element of a node (like Axonl boutons or
      dendritic spines) used for structural plasticity.
      The synaptic elements represent connection points between two neurons. They
      grow according to a homeostatic growth rule. The dynamics of the
      number of synaptic elements is driven by the average electrical activity of
      the neuron (indirectly measured through the Calcium concentration of the
      node). The probability of two neurons creating a new synapse between them,
      depends on the number of available synaptic elements of each neuron.

Parameters:

      z	 double 	- Current number of synaptic elements. Stored as a
      double variable but the actual usable number of
      synaptic elements is an integer truncated from
      this
      double value. An standard value for the growth of
      a
      synaptic element is around 0.0001 elements/ms.
      continuous	 boolean	- Defines if the number of synaptic elements should
      be treated as a continuous double number or as an
      integer value. Default is false.
      growth_rate	 double 	- The maximum amount by which the synaptic elements
      will
      change between time steps. In elements/ms.
      tau_vacant	 double 	- Rate at which vacant synaptic elements will decay.
      Typical is 0.1 which represents a
      loss of 10% of the vacant synaptic elements each
      time
      the structural_plasticity_update_interval is
      reached by the simulation time.
      growth_curve	 GrowthCurve*	- Rule which defines the dynamics of this
      synaptic element.

References:

      [1] Butz, Markus, Florentin Wörgötter, and Arjen van Ooyen.
      "Activity-dependent structural plasticity." Brain research reviews 60.2
      (2009): 287-305.

      [2] Butz, Markus, and Arjen van Ooyen. "A simple rule for dendritic spine
      and axonal bouton formation can account for cortical reorganization after
      focal retinal lesions." PLoS Comput Biol 9.10 (2013): e1003259.

Author:

    Mikael Naveau, Sandra Diaz

FirstVersion:

    July 2013

SeeAlso:

- GrowthCurve
- SPManager
- SPBuilder
- Node
- ArchivingNode.

Source:

    /opt/conda/conda-bld/nest_1512418852064/work/nest-2.12.0/nestkernel/synaptic_element.h

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