# Command: iaf_cond_alpha_mc

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Name:

    iaf_cond_alpha_mc - PROTOTYPE Multi-compartment conductance-based leaky
      integrate-and-fire neuron model.

Description:

      THIS MODEL IS A PROTOTYPE FOR ILLUSTRATION PURPOSES. IT IS NOT YET
      FULLY TESTED. USE AT YOUR OWN PERIL!

      iaf_cond_alpha_mc is an implementation of a multi-compartment spiking
      neuron using IAF dynamics with conductance-based synapses. It serves
      mainly to illustrate the implementation of multicompartment models in
      NEST.

      The model has three compartments: soma, proximal and distal dendrite,
      labeled as s, p, and d, respectively. Compartments are connected through
      passive conductances as follows

      C_m.s d/dt V_m.s = ...	- g_sp ( V_m.s	- V_m.p )

      C_m.p d/dt V_m.p = ...	- g_sp ( V_m.p	- V_m.s )	- g_pd ( V_m.p	- V_m.d )

      C_m.d d/dt V_m.d = ...		- g_pd ( V_m.d	- V_m.p )

      A spike is fired when the somatic membrane potential exceeds threshold,
      V_m.s >= V_th. After a spike, somatic membrane potential is clamped to
      a reset potential, V_m.s == V_reset, for the refractory period. Dendritic
      membrane potentials are not manipulated after a spike.

      There is one excitatory and one inhibitory conductance-based synapse
      onto each compartment, with alpha-function time course. The alpha
      function is normalised such that an event of weight 1.0 results in a
      peak current of 1 nS at t = tau_syn. Each compartment can also receive
      current input from a current generator, and an external (rheobase)
      current can be set for each compartment.

      Synapses, including those for injection external currents, are addressed through
      the receptor types given in the receptor_types entry of the state dictionary.
      Note that in contrast to the single-compartment iaf_cond_alpha model, all
      synaptic weights must be positive numbers!

Parameters:

      The following parameters can be set in the status dictionary. Parameters
      for each compartment are collected in a sub-dictionary; these sub-dictionaries
      are called "soma", "proximal", and "distal", respectively. In the list below,
      these parameters are marked with an asterisk.

      V_m*	 double	- Membrane potential in mV
      E_L*	 double	- Leak reversal potential in mV.
      C_m*	 double	- Capacity of the membrane in pF
      E_ex*	 double	- Excitatory reversal potential in mV.
      E_in*	 double	- Inhibitory reversal potential in mV.
      g_L*	 double	- Leak conductance in nS;
      tau_syn_ex*  double	- Rise time of the excitatory synaptic alpha function in ms.
      tau_syn_in*  double	- Rise time of the inhibitory synaptic alpha function in ms.
      I_e*	 double	- Constant input current in pA.

      g_sp	 double	- Conductance connecting soma and proximal dendrite, in nS.
      g_pd	 double	- Conductance connecting proximal and distal dendrite, in
      nS.
      t_ref	 double	- Duration of refractory period in ms.
      V_th	 double	- Spike threshold in mV.
      V_reset	 double	- Reset potential of the membrane in mV.

      Example:
      See examples/nest/mc_neuron.py.

      Remark:
      This is a prototype for illustration which has undergone only limited testing.
      Details of the implementation and user-interface will likely change.
      USE AT YOUR OWN PERIL!

Require:

    HAVE_GSL

Receives:

    SpikeEvent, CurrentEvent, DataLoggingRequest

Sends:

    SpikeEvent

References:

      Meffin, H., Burkitt, A. N., & Grayden, D. B. (2004). An analytical
      model for the large, fluctuating synaptic conductance state typical of
      neocortical neurons in vivo. J.  Comput. Neurosci., 16, 159-175.

      Bernander, O ., Douglas, R. J., Martin, K. A. C., & Koch, C. (1991).
      Synaptic background activity influences spatiotemporal integration in
      single pyramidal cells.  Proc. Natl. Acad. Sci. USA, 88(24),
      11569-11573.

Author:

    Plesser

SeeAlso:

- iaf_cond_alpha

Source:

    /opt/conda/conda-bld/nest_1512418773968/work/nest-2.14.0/models/iaf_cond_alpha_mc.h

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