iaf_psc_exp_htum.h

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/*
 *  iaf_psc_exp_htum.h
 *
 *  This file is part of NEST.
 *
 *  Copyright (C) 2004 The NEST Initiative
 *
 *  NEST is free software: you can redistribute it and/or modify
 *  it under the terms of the GNU General Public License as published by
 *  the Free Software Foundation, either version 2 of the License, or
 *  (at your option) any later version.
 *
 *  NEST is distributed in the hope that it will be useful,
 *  but WITHOUT ANY WARRANTY; without even the implied warranty of
 *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *  GNU General Public License for more details.
 *
 *  You should have received a copy of the GNU General Public License
 *  along with NEST.  If not, see <http://www.gnu.org/licenses/>.
 *
 */
 
 
#ifndef iaf_psc_exp_htum_H
#define iaf_psc_exp_htum_H
 
// Includes from nestkernel:
#include "archiving_node.h"
#include "connection.h"
#include "event.h"
#include "nest_types.h"
#include "ring_buffer.h"
#include "universal_data_logger.h"
 
namespace nest
{
 
/* BeginUserDocs: neuron, integrate-and-fire, hard threshold
 
Short description
+++++++++++++++++
 
Leaky integrate-and-fire model with separate relative and absolute refractory period
 
Description
+++++++++++
 
``iaf_psc_exp_htum`` is an implementation of a leaky integrate-and-fire model
with exponential shaped postsynaptic currents (PSCs) according to :footcite:p:`Tsodyks2000`.
The postsynaptic currents have an infinitely short rise time.
In particular, this model allows setting an absolute and relative
refractory time separately, as required by :footcite:p:`Tsodyks2000`.
 
The threshold crossing is followed by an absolute refractory period
(``t_ref_abs``) during which the membrane potential is clamped to the resting
potential. During the total refractory period (``t_ref_tot``), the membrane
potential evolves, but the neuron will not emit a spike, even if the
membrane potential reaches threshold. The total refractory time must be
larger or equal to the absolute refractory time. If equal, the
refractoriness of the model if equivalent to the other models of NEST.
 
The linear subthreshold dynamics is integrated by the Exact
Integration scheme :footcite:p:`Hill1936`. 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
:footcite:p:`Hill1936`. A flow chart can be found in :footcite:p:`Rotter1999`.
 
.. note::
 
   The present implementation uses individual variables for the
   components of the state vector and the non-zero matrix elements of
   the propagator. Because the propagator is a lower triangular matrix,
   no full matrix multiplication needs to be carried out and the
   computation can be done "in place", i.e. no temporary state vector
   object is required.
 
   The template support of recent C++ compilers enables a more succinct
   formulation without loss of runtime performance already at minimal
   optimization levels. A future version of iaf_psc_exp_htum will probably
   address the problem of efficient usage of appropriate vector and
   matrix objects.
 
.. note::
 
   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 implementation details see the
    `IAF Integration Singularity notebook <../model_details/IAF_Integration_Singularity.ipynb>`_.
 
 
See also :footcite:p:`Diesmann2001`.
 
Parameters
++++++++++
 
The following parameters can be set in the status dictionary.
 
===========  ====== ========================================================
 E_L          mV     Resting membrane potenial
 C_m          pF     Capacity of the membrane
 tau_m        ms     Membrane time constant
 tau_syn_ex   ms     Time constant of postsynaptic excitatory currents
 tau_syn_in   ms     Time constant of postsynaptic inhibitory currents
 t_ref_abs    ms     Duration of absolute refractory period (V_m = V_reset)
 t_ref_tot    ms     Duration of total refractory period (no spiking)
 V_m          mV     Membrane potential
 V_th         mV     Spike threshold
 V_reset      mV     Reset membrane potential after a spike
 I_e          pA     Constant input current
 t_spike      ms     Point in time of last spike
===========  ====== ========================================================
 
References
++++++++++
 
.. footbibliography::
 
Sends
+++++
 
SpikeEvent
 
Receives
++++++++
 
SpikeEvent, CurrentEvent, DataLoggingRequest
 
Examples using this model
+++++++++++++++++++++++++
 
.. listexamples:: iaf_psc_exp_htum
 
EndUserDocs */
 
void register_iaf_psc_exp_htum( const std::string& name );
 
class iaf_psc_exp_htum : public ArchivingNode
{
 
public:
  iaf_psc_exp_htum();
  iaf_psc_exp_htum( const iaf_psc_exp_htum& );
 
  using Node::handle;
  using Node::handles_test_event;
 
  size_t send_test_event( Node&, size_t, synindex, bool ) override;
 
  void handle( SpikeEvent& ) override;
  void handle( CurrentEvent& ) override;
  void handle( DataLoggingRequest& ) override;
 
  size_t handles_test_event( SpikeEvent&, size_t ) override;
  size_t handles_test_event( CurrentEvent&, size_t ) override;
  size_t handles_test_event( DataLoggingRequest&, size_t ) override;
 
  void get_status( Dictionary& ) const override;
  void set_status( const Dictionary& ) override;
 
private:
  void init_buffers_() override;
  void pre_run_hook() override;
 
  void update( Time const&, const long, const long ) override;
 
  // The next two classes need to be friends to access the State_ class/member
  friend class RecordablesMap< iaf_psc_exp_htum >;
  friend class UniversalDataLogger< iaf_psc_exp_htum >;
 
  // ----------------------------------------------------------------
 
  struct Parameters_
  {
    double Tau_;
 
    double C_;
 
    double tau_ref_tot_;
    double tau_ref_abs_;
 
    double E_L_;
 
    double I_e_;
 
    double Theta_;
 
    double V_reset_;
 
    double tau_ex_;
 
    double tau_in_;
 
    Parameters_();  
 
    void get( Dictionary& ) const;  
 
    double set( const Dictionary&, Node* node );
  };
 
  // ----------------------------------------------------------------
 
  struct State_
  {
    // state variables
    double i_0_;       
    double i_syn_ex_;  
    double i_syn_in_;  
    double V_m_;       
 
    int r_abs_;
    int r_tot_;  
 
    State_();  
 
    void get( Dictionary&, const Parameters_& ) const;
 
    void set( const Dictionary&, const Parameters_&, double delta_EL, Node* );
  };
 
  // ----------------------------------------------------------------
 
  struct Buffers_
  {
    Buffers_( iaf_psc_exp_htum& );
    Buffers_( const Buffers_&, iaf_psc_exp_htum& );
 
    RingBuffer spikes_ex_;
    RingBuffer spikes_in_;
    RingBuffer currents_;
 
    UniversalDataLogger< iaf_psc_exp_htum > logger_;
  };
 
  // ----------------------------------------------------------------
 
  struct Variables_
  {
    //    double PSCInitialValue_;
 
    // time evolution operator
    double P20_;
    double P11ex_;
    double P11in_;
    double P21ex_;
    double P21in_;
    double P22_;
 
    int RefractoryCountsAbs_;
    int RefractoryCountsTot_;
  };
 
  // Access functions for UniversalDataLogger -------------------------------
 
  double
  get_V_m_() const
  {
    return S_.V_m_;
  }
  double
  get_I_syn_ex_() const
  {
    return S_.i_syn_ex_;
  }
  double
  get_I_syn_in_() const
  {
    return S_.i_syn_in_;
  }
 
  // ----------------------------------------------------------------
 
  Parameters_ P_;
  State_ S_;
  Variables_ V_;
  Buffers_ B_;
  static RecordablesMap< iaf_psc_exp_htum > recordablesMap_;
};
 
 
inline size_t
iaf_psc_exp_htum::send_test_event( Node& target, size_t receptor_type, synindex, bool )
{
  SpikeEvent e;
  e.set_sender( *this );
  return target.handles_test_event( e, receptor_type );
}
 
inline size_t
iaf_psc_exp_htum::handles_test_event( SpikeEvent&, size_t receptor_type )
{
  if ( receptor_type != 0 )
  {
    throw UnknownReceptorType( receptor_type, get_name() );
  }
  return 0;
}
 
inline size_t
iaf_psc_exp_htum::handles_test_event( CurrentEvent&, size_t receptor_type )
{
  if ( receptor_type != 0 )
  {
    throw UnknownReceptorType( receptor_type, get_name() );
  }
  return 0;
}
 
inline size_t
iaf_psc_exp_htum::handles_test_event( DataLoggingRequest& dlr, size_t receptor_type )
{
  if ( receptor_type != 0 )
  {
    throw UnknownReceptorType( receptor_type, get_name() );
  }
  return B_.logger_.connect_logging_device( dlr, recordablesMap_ );
}
 
 
inline void
iaf_psc_exp_htum::get_status( Dictionary& d ) const
{
  P_.get( d );
  S_.get( d, P_ );
  ArchivingNode::get_status( d );
  d[ names::recordables ] = recordablesMap_.get_list();
}
 
inline void
iaf_psc_exp_htum::set_status( const Dictionary& d )
{
  Parameters_ ptmp = P_;                        // temporary copy in case of errors
  const double delta_EL = ptmp.set( d, this );  // throws if BadProperty
  State_ stmp = S_;                             // temporary copy in case of errors
  stmp.set( d, ptmp, delta_EL, this );          // throws if BadProperty
 
  // We now know that (ptmp, stmp) are consistent. We do not
  // write them back to (P_, S_) before we are also sure that
  // the properties to be set in the parent class are internally
  // consistent.
  ArchivingNode::set_status( d );
 
  // if we get here, temporaries contain consistent set of properties
  P_ = ptmp;
  S_ = stmp;
}
 
}  // namespace
 
#endif  // iaf_psc_exp_htum_H