# Command: iaf_psc_exp_ps

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Name:

    iaf_psc_exp_ps - Leaky integrate-and-fire neuron
      with exponential postsynaptic currents; canoncial implementation;
      bisectioning method for approximation of threshold crossing.

Description:

      iaf_psc_exp_ps is the "canonical" implementation of the leaky
      integrate-and-fire model neuron with exponential postsynaptic currents
      that uses the bisectioning method to approximate the timing of a threshold
      crossing [1,2]. This is the most exact implementation available.

      The canonical implementation handles neuronal dynamics in a locally
      event-based manner with in coarse time grid defined by the minimum
      delay in the network, see [1,2]. Incoming spikes are applied at the
      precise moment of their arrival, while the precise time of outgoing
      spikes is determined by bisectioning once a threshold crossing has
      been detected. Return from refractoriness occurs precisely at spike
      time plus refractory period.

      This implementation is more complex than the plain iaf_psc_exp
      neuron, but achieves much higher precision. In particular, it does not
      suffer any binning of spike times to grid points. Depending on your
      application, the canonical application with bisectioning may provide
      superior overall performance given an accuracy goal; see [1,2] for
      details. Subthreshold dynamics are integrated using exact integration
      between events [3].

Parameters:

      The following parameters can be set in the status dictionary.
      E_L	 double	- Resting membrane potential in mV.
      C_m	 double	- Capacitance of the membrane in pF.
      tau_m	 double	- Membrane time constant in ms.
      tau_syn_ex   double	- Excitatory synaptic time constant in ms.
      tau_syn_in   double	- Inhibitory synaptic time constant in ms.
      t_ref	 double	- Duration of refractory period in ms.
      V_th	 double	- Spike threshold in mV.
      I_e	 double	- Constant input current in pA.
      V_min	 double	- Absolute lower value for the membrane potential in mV.
      V_reset	 double	- Reset value for the membrane potential in mV.

Receives:

    SpikeEvent, CurrentEvent, DataLoggingRequest

Sends:

    SpikeEvent

Remarks:

      If tau_m is very close to tau_syn_ex or tau_syn_in, the model
      will numerically behave as if tau_m is equal to tau_syn_ex or
      tau_syn_in, respectively, to avoid numerical instabilities.
      For details, please see IAF_Neruons_Singularity.ipynb in the
      NEST source code (docs/model_details).

References:

      [1] Morrison A, Straube S, Plesser HE & Diesmann M (2007) Exact subthreshold
      integration with continuous spike times in discrete time neural network
      simulations. Neural Comput 19, 47-79
      [2] Hanuschkin A, Kunkel S, Helias M, Morrison A and Diesmann M (2010) A
      general and efficient method for incorporating precise spike times in
      globally timedriven simulations. Front Neuroinform 4:113
      [3] Rotter S & Diesmann M (1999) Exact simulation of time-invariant linear
      systems with applications to neuronal modeling. Biol Cybern 81:381-402

Author:

    Kunkel

SeeAlso:

- iaf_psc_exp
- iaf_psc_alpha_canon

Source:

    /opt/conda/conda-bld/nest_1510212701067/work/nest-2.14.0/precise/iaf_psc_exp_ps.h

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