SpikingQifNeuralDynamics.cpp

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// Copyright (c) 2005 - 2014 Marc de Kamps
// All rights reserved.
//
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//
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//    * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation
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//
//      If you use this software in work leading to a scientific publication, you should include a reference there to
//      the 'currently valid reference', which can be found at http://miind.sourceforge.net
#include <cmath>
#include "SpikingQifNeuralDynamics.hpp"

using namespace GeomLib;

SpikingQifNeuralDynamics::SpikingQifNeuralDynamics
(
    const OdeParameter& par_ode,
    const QifParameter& par_qif
):
SpikingNeuralDynamics
(
    par_ode
),
_par_qif(par_qif)
{
}

SpikingQifNeuralDynamics::SpikingQifNeuralDynamics
(
    const SpikingQifNeuralDynamics& dyn
):
SpikingNeuralDynamics(dyn),
_par_qif(dyn._par_qif)
{
}

SpikingQifNeuralDynamics::~SpikingQifNeuralDynamics()
{
}

Potential SpikingQifNeuralDynamics::EvolvePotential(Potential V, Time t) const
{
    // evolve the potential under the assumption that no crossing to infinity
    // takes places within time t
    assert(this->TimeToInf(V) > t);

    double sqr = sqrt(_par_qif.Gammasys());
    Potential V_ret = sqr*tan(sqr*(t/this->_par._par_pop._tau) + atan(V/sqr));
    return V_ret;
}

Time SpikingQifNeuralDynamics::TimeToInf(Potential V) const
{
    double sqr = sqrt(_par_qif.Gammasys());
    double t = (this->_par._par_pop._tau/sqr)*(atan(this->_par._par_pop._theta/sqr) - atan(V/sqr));
    return t;
}

SpikingQifNeuralDynamics* SpikingQifNeuralDynamics::Clone() const
{
    return new SpikingQifNeuralDynamics(*this);
}


Time SpikingQifNeuralDynamics::TPeriod() const
{
    return this->TimeToInf(_par._V_min);
}


Time SpikingQifNeuralDynamics::TStep() const
{
    return this->TPeriod()/_par._nr_bins;
}