mat2_psc_exp.h

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/*
 *  mat2_psc_exp.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 MAT2_PSC_EXP_H
#define MAT2_PSC_EXP_H
 
// Includes from nestkernel:
#include "archiving_node.h"
#include "connection.h"
#include "event.h"
#include "nest_types.h"
#include "recordables_map.h"
#include "ring_buffer.h"
#include "universal_data_logger.h"
 
namespace nest
{
 
/* BeginUserDocs: neuron, integrate-and-fire, current-based, adaptation, hard threshold
 
Short description
+++++++++++++++++
 
Non-resetting leaky integrate-and-fire neuron model with exponential PSCs and adaptive threshold
 
Description
+++++++++++
 
``mat2_psc_exp`` is an implementation of a leaky integrate-and-fire model
with exponential shaped postsynaptic currents (PSCs). Thus, postsynaptic
currents have an infinitely short rise time.
 
The threshold is lifted when the neuron is fired and then decreases in a
fixed time scale toward a fixed level :footcite:p:`Kobayashi2009`.
 
The threshold crossing is followed by a total refractory period
during which the neuron is not allowed to fire, even if the membrane
potential exceeds the threshold. The membrane potential is NOT reset,
but continuously integrated.
 
The linear subthreshold dynamics is integrated by the Exact
Integration scheme :footcite:p:`Rotter1999`. 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:`Rotter1999`. A flow chart can be found in :footcite:p:`Diesmann2001`.
 
The current implementation requires tau_m != tau_syn_{ex,in} to avoid
a degenerate case of the ODE describing the model :footcite:p:`Rotter1999`. For very
similar values, numerics will be unstable.
 
The following state variables can be read out with the multimeter device:
 
====== ====  =================================
 V_m   mV    Non-resetting membrane potential
 V_th  mV    Two-timescale adaptive threshold
====== ====  =================================
 
Parameters
++++++++++
 
The following parameters can be set in the status dictionary:
 
============ =======  ========================================================
 C_m          pF      Capacity of the membrane
 E_L          mV      Resting potential
 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        ms      Duration of absolute refractory period (no spiking)
 V_m          mV      Membrane potential
 I_e          pA      Constant input current
 t_spike      ms      Point in time of last spike
 tau_1        ms      Short time constant of adaptive threshold
 tau_2        ms      Long time constant of adaptive threshold
 alpha_1      mV      Amplitude of short time threshold adaption :footcite:p:`Kobayashi2009`
 alpha_2      mV      Amplitude of long time threshold adaption :footcite:p:`Kobayashi2009`
 omega        mV      Resting spike threshold (absolute value, not
                      relative to E_L as in :footcite:p:`Kobayashi2009`)
============ =======  ========================================================
 
The following state variables can be read out with the multimeter device:
 
====== ====  =================================
 V_m   mV    Non-resetting membrane potential
 V_th  mV    Two-timescale adaptive threshold
====== ====  =================================
 
Remarks:
 
tau_m != tau_syn_{ex,in} is required by the current implementation to avoid a
degenerate case of the ODE describing the model :footcite:p:`Rotter1999`. For very similar values,
numerics will be unstable.
 
References
++++++++++
 
.. footbibliography::
 
Sends
+++++
 
SpikeEvent
 
Receives
++++++++
 
SpikeEvent, CurrentEvent, DataLoggingRequest
 
Examples using this model
+++++++++++++++++++++++++
 
.. listexamples:: mat2_psc_exp
 
EndUserDocs */
 
void register_mat2_psc_exp( const std::string& name );
 
class mat2_psc_exp : public ArchivingNode
{
 
public:
  mat2_psc_exp();
  mat2_psc_exp( const mat2_psc_exp& );
 
  using Node::handle;
  using Node::handles_test_event;
 
  size_t send_test_event( Node&, size_t, synindex, bool ) 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 handle( SpikeEvent& ) override;
  void handle( CurrentEvent& ) override;
  void handle( DataLoggingRequest& ) 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 private members
  friend class RecordablesMap< mat2_psc_exp >;
  friend class UniversalDataLogger< mat2_psc_exp >;
 
  // ----------------------------------------------------------------
 
  struct Parameters_
  {
    double Tau_;
 
    double C_;
 
    double tau_ref_;
 
    double E_L_;
 
    double I_e_;
 
    double tau_ex_;
 
    double tau_in_;
 
    double tau_1_;
    double tau_2_;
 
    double alpha_1_;
    double alpha_2_;
 
    double omega_;
 
    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_;       
    double V_th_1_;
    double V_th_2_;
 
    int r_;  
 
    State_();  
 
    void get( Dictionary&, const Parameters_& ) const;
 
    void set( const Dictionary&, const Parameters_&, double, Node* );
  };
 
  // ----------------------------------------------------------------
 
  struct Buffers_
  {
    Buffers_( mat2_psc_exp& );                   
    Buffers_( const Buffers_&, mat2_psc_exp& );  
 
    RingBuffer spikes_ex_;
    RingBuffer spikes_in_;
    RingBuffer currents_;
 
    UniversalDataLogger< mat2_psc_exp > logger_;
  };
 
  // ----------------------------------------------------------------
 
  struct Variables_
  {
 
    //    double PSCInitialValue_;
 
    // time evolution operator of membrane potential
    double P20_;  // constant currents
    double P11ex_;
    double P11in_;
    double P21ex_;
    double P21in_;
    double P22_expm1_;
 
    // time evolution operator of dynamic threshold
    // P = ( exp(-h/tau_1)   0               )
    //    ( 0                 exp(-h/tau_2) )
    double P11th_;
    double P22th_;
 
    int RefractoryCountsTot_;
  };
  // ----------------------------------------------------------------
 
  double
  get_V_m_() const
  {
    return S_.V_m_ + P_.E_L_;
  }
  double
  get_V_th_() const
  {
    return P_.E_L_ + P_.omega_ + S_.V_th_1_ + S_.V_th_2_;
  }
 
  // ----------------------------------------------------------------
 
  Parameters_ P_;
  State_ S_;
  Variables_ V_;
  Buffers_ B_;
  static RecordablesMap< mat2_psc_exp > recordablesMap_;
};
 
 
inline size_t
mat2_psc_exp::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
mat2_psc_exp::handles_test_event( SpikeEvent&, size_t receptor_type )
{
  if ( receptor_type != 0 )
  {
    throw UnknownReceptorType( receptor_type, get_name() );
  }
  return 0;
}
 
inline size_t
mat2_psc_exp::handles_test_event( CurrentEvent&, size_t receptor_type )
{
  if ( receptor_type != 0 )
  {
    throw UnknownReceptorType( receptor_type, get_name() );
  }
  return 0;
}
 
inline size_t
mat2_psc_exp::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
mat2_psc_exp::get_status( Dictionary& d ) const
{
  P_.get( d );
  S_.get( d, P_ );
  ArchivingNode::get_status( d );
 
  d[ names::recordables ] = recordablesMap_.get_list();
}
 
inline void
mat2_psc_exp::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  // MAT2_PSC_EXP_H