/***************************************************************************
* ExpState.h *
* ------------------- *
* copyright : (C) 2011 by Jesus Garrido *
* email : jgarrido@atc.ugr.es *
***************************************************************************/
/***************************************************************************
* *
* This program 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 3 of the License, or *
* (at your option) any later version. *
* *
***************************************************************************/
#ifndef EXPSTATE_H_
#define EXPSTATE_H_
#include "ConnectionState.h"
/*!
* \file ExpState.h
*
* \author Jesus Garrido
* \date October 2011
*
* This file declares a class which abstracts the current state of a synaptic connection
* with exponential learning rule.
*/
/*!
* \class ExpState
*
* \brief Synaptic connection current state.
*
* This class abstracts the state of a synaptic connection including Sinusoidal learning rule and defines the state variables of
* that connection. The kernel function is f(t) = (t/tau)*exp(-t/tau), where t represents the time since
* the last presynaptic spike reached the cell.
*
* \author Jesus Garrido
* \date October 2011
*/
class ExpState : public ConnectionState{
private:
/*!
* Tau constant of the learning rule.
*/
float tau;
float inv_tau;
public:
/*!
* \brief Default constructor with parameters.
*
* It generates a new state of a connection.
*
* \param NewTau The temporal constant of the learning rule.
*/
ExpState(unsigned int NumSynapses, float NewTau);
/*!
* \brief Class destructor.
*
* It destroys an object of this class.
*/
virtual ~ExpState();
/*!
* \brief It gets the value of the accumulated presynaptic activity.
*
* It gets the value of the accumulated presynaptic activity.
*
* \param index The synapse's index inside the learning rule.
* \return The accumulated presynaptic activity.
*/
virtual float GetPresynapticActivity(unsigned int index);
/*!
* \brief It gets the value of the accumulated postsynaptic activity.
*
* It gets the value of the accumulated postsynaptic activity.
*
* \param index The synapse's index inside the learning rule.
* \return The accumulated postsynaptic activity.
*/
virtual float GetPostsynapticActivity(unsigned int index);
/*!
* \brief It gets the number of variables that you can print in this state.
*
* It gets the number of variables that you can print in this state.
*
* \return The number of variables that you can print in this state.
*/
virtual unsigned int GetNumberOfPrintableValues();
/*!
* \brief It gets a value to be printed from this state.
*
* It gets a value to be printed from this state.
*
* \return The value at position-th position in this state.
*/
virtual double GetPrintableValuesAt(unsigned int position);
/*!
* \brief set new time to spikes.
*
* It set new time to spikes.
*
* \param index The synapse's index inside the learning rule.
* \param NewTime new time.
* \param pre_post In some learning rules (i.e. STDPLS) this variable indicate wether the update affects the pre- or post- variables.
*/
virtual void SetNewUpdateTime(unsigned int index, double NewTime, bool pre_post);
/*!
* \brief It implements the behaviour when it transmits a spike.
*
* It implements the behaviour when it transmits a spike. It must be implemented
* by any inherited class.
*
* \param index The synapse's index inside the learning rule.
*/
virtual void ApplyPresynapticSpike(unsigned int index);
/*!
* \brief It implements the behaviour when the target cell fires a spike.
*
* It implements the behaviour when it the target cell fires a spike. It must be implemented
* by any inherited class.
*
* \param index The synapse's index inside the learning rule.
*/
virtual void ApplyPostsynapticSpike(unsigned int index);
};
#endif /* NEURONSTATE_H_ */