Command: iaf_neuron

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Name:
 iaf_neuron - Leaky integrate-and-fire neuron model.

Description:

  iaf_neuron is an implementation of a leaky integrate-and-fire model
  with alpha-function shaped synaptic currents. Thus, synaptic currents
  and the resulting post-synaptic potentials have a finite rise time. 
  The threshold crossing is followed by an absolute refractory period
  during which the membrane potential is clamped to the resting potential.

  The subthreshold membrane potential dynamics are given by [3]

  dV_m/dt = - ( V_m - E_L ) / tau_m + I_syn(t) / C_m + I_e / C_m

  where I_syn(t) is the sum of alpha-shaped synaptic currents

  I_syn(t) = Sum[w_j alpha(t-t_j) for t_j in input spike times]

  w_j is the synaptic weight of the connection through which the spike
  at time t_j arrived. Each individual alpha-current is given by

  alpha(t) = e * t/tau_s * e^{-t/tau_s} * Heaviside(t)

  alpha(t=tau_s) == 1 is the maximum of the alpha-current.

  The linear subthresold dynamics is integrated by the Exact
  Integration scheme [1]. The neuron dynamics is solved on the time
  grid given by the computation step size. Incoming as well as emitted
  spikes are forced to that grid.  

  An additional state variable and the corresponding differential
  equation represents a piecewise constant external current.

  The general framework for the consistent formulation of systems with
  neuron like dynamics interacting by point events is described in
  [1].  A flow chart can be found in [2].

  Critical tests for the formulation of the neuron model are the
  comparisons of simulation results for different computation step
  sizes. sli/testsuite/nest contains a number of such tests.
  
  The iaf_neuron is the standard model used to check the consistency
  of the nest simulation kernel because it is at the same time complex
  enough to exhibit non-trivial dynamics and simple enough to compute
  relevant measures analytically.


Parameters:
 

  The following parameters can be set in the status dictionary.

  V_m        double - Membrane potential in mV 
  E_L        double - Resting membrane potential in mV. 
  C_m        double - Capacity of the membrane in pF
  tau_m      double - Membrane time constant in ms.
  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.
  tau_syn    double - Rise time of the excitatory synaptic alpha function in ms.
  I_e        double - Constant external input current in pA.

Note:
  tau_m != tau_syn is required by the current implementation to avoid a
  degenerate case of the ODE describing the model [1]. For very similar values,
  numerics will be unstable.
 
References:
  [1] Rotter S & Diesmann M (1999) Exact simulation of time-invariant linear
      systems with applications to neuronal modeling. Biologial Cybernetics
      81:381-402.
  [2] Diesmann M, Gewaltig M-O, Rotter S, & Aertsen A (2001) State space 
      analysis of synchronous spiking in cortical neural networks. 
      Neurocomputing 38-40:565-571.
  [3] Morrison A, Straube S, Plesser H E, & Diesmann M (2007) Exact subthreshold 
      integration with continuous spike times in discrete time neural network 
      simulations. Neural Computation 19:47-79.

Sends:
 SpikeEvent

Receives:
 SpikeEvent, CurrentEvent, DataLoggingRequest
      
Author:
  September 1999, Diesmann, Gewaltig
SeeAlso:iaf_psc_alpha testsuite::test_iaf
Source:
 /home/abuild/rpmbuild/BUILD/nest-2.4.1/models/iaf_neuron.h

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