.. index:: pair: class; NeuronModels::Izhikevich
.. toctree::
:hidden:
:ref:`Izhikevich <doxid-d7/d0a/classNeuronModels_1_1Izhikevich>` neuron with fixed parameters :ref:`izhikevich2003simple <doxid-d0/de3/citelist_1CITEREF_izhikevich2003simple>`. :ref:`More...<details-d7/d0a/classNeuronModels_1_1Izhikevich>`
.. ref-code-block:: cpp
:class: doxyrest-overview-code-block
#include <neuronModels.h>
class Izhikevich: public :ref:`NeuronModels::Base<doxid-d7/dad/classNeuronModels_1_1Base>`
{
public:
// typedefs
typedef :ref:`Snippet::ValueBase<doxid-da/d76/classSnippet_1_1ValueBase>`<4> :target:`ParamValues<doxid-d7/d0a/classNeuronModels_1_1Izhikevich_1ae94c10cb33862aef367793f56cdbddd8>`;
typedef :ref:`Models::VarInitContainerBase<doxid-d6/d24/classModels_1_1VarInitContainerBase>`<2> :target:`VarValues<doxid-d7/d0a/classNeuronModels_1_1Izhikevich_1aed21c7cc4971268506c9114d17e6bf22>`;
typedef :ref:`Models::VarInitContainerBase<doxid-d6/d24/classModels_1_1VarInitContainerBase>`<0> :target:`PreVarValues<doxid-d7/d0a/classNeuronModels_1_1Izhikevich_1a59bb450aa8a6e840d9445d52095c1486>`;
typedef :ref:`Models::VarInitContainerBase<doxid-d6/d24/classModels_1_1VarInitContainerBase>`<0> :target:`PostVarValues<doxid-d7/d0a/classNeuronModels_1_1Izhikevich_1a674301f3dc07282505a2350217791ee0>`;
// methods
static const NeuronModels::Izhikevich* :target:`getInstance<doxid-d7/d0a/classNeuronModels_1_1Izhikevich_1acf0e3e311aab815bc4d7bdf8a048239f>`();
virtual std::string :ref:`getSimCode<doxid-d7/d0a/classNeuronModels_1_1Izhikevich_1a67669e3ef6477d221b6023c19a357960>`() const;
virtual std::string :ref:`getThresholdConditionCode<doxid-d7/d0a/classNeuronModels_1_1Izhikevich_1af85c7d6485949e74cc766fd5860f55bc>`() const;
virtual :ref:`StringVec<doxid-db/d97/classSnippet_1_1Base_1a06cd0f6da1424a20163e12b6fec62519>` :ref:`getParamNames<doxid-d7/d0a/classNeuronModels_1_1Izhikevich_1a3a5d58236a09163fce623add3b1095c0>`() const;
virtual :ref:`VarVec<doxid-d6/d97/classModels_1_1Base_1a5a6bc95969a38ac1ac68ab4a0ba94c75>` :ref:`getVars<doxid-d7/d0a/classNeuronModels_1_1Izhikevich_1a4da70b0f1e24f4634b60d15e2e1c6343>`() const;
};
// direct descendants
class :ref:`IzhikevichVariable<doxid-dc/d87/classNeuronModels_1_1IzhikevichVariable>`;
.. ref-code-block:: cpp
:class: doxyrest-overview-inherited-code-block
public:
// typedefs
typedef std::vector<std::string> :ref:`StringVec<doxid-db/d97/classSnippet_1_1Base_1a06cd0f6da1424a20163e12b6fec62519>`;
typedef std::vector<:ref:`EGP<doxid-dd/d5d/structSnippet_1_1Base_1_1EGP>`> :ref:`EGPVec<doxid-db/d97/classSnippet_1_1Base_1a43ece29884e2c6cabffe9abf985807c6>`;
typedef std::vector<:ref:`ParamVal<doxid-d7/dda/structSnippet_1_1Base_1_1ParamVal>`> :ref:`ParamValVec<doxid-db/d97/classSnippet_1_1Base_1a0156727ddf8f9c9cbcbc0d3d913b6b48>`;
typedef std::vector<:ref:`DerivedParam<doxid-d9/d0c/structSnippet_1_1Base_1_1DerivedParam>`> :ref:`DerivedParamVec<doxid-db/d97/classSnippet_1_1Base_1ad14217cebf11eddffa751a4d5c4792cb>`;
typedef std::vector<:ref:`Var<doxid-d5/d42/structModels_1_1Base_1_1Var>`> :ref:`VarVec<doxid-d6/d97/classModels_1_1Base_1a5a6bc95969a38ac1ac68ab4a0ba94c75>`;
// structs
struct :ref:`DerivedParam<doxid-d9/d0c/structSnippet_1_1Base_1_1DerivedParam>`;
struct :ref:`EGP<doxid-dd/d5d/structSnippet_1_1Base_1_1EGP>`;
struct :ref:`ParamVal<doxid-d7/dda/structSnippet_1_1Base_1_1ParamVal>`;
struct :ref:`Var<doxid-d5/d42/structModels_1_1Base_1_1Var>`;
// methods
virtual :ref:`~Base<doxid-db/d97/classSnippet_1_1Base_1a17a9ca158277401f2c190afb1e791d1f>`();
virtual :ref:`StringVec<doxid-db/d97/classSnippet_1_1Base_1a06cd0f6da1424a20163e12b6fec62519>` :ref:`getParamNames<doxid-db/d97/classSnippet_1_1Base_1a0c8374854fbdc457bf0f75e458748580>`() const;
virtual :ref:`DerivedParamVec<doxid-db/d97/classSnippet_1_1Base_1ad14217cebf11eddffa751a4d5c4792cb>` :ref:`getDerivedParams<doxid-db/d97/classSnippet_1_1Base_1ab01de002618efa59541c927ffdd463f5>`() const;
virtual :ref:`VarVec<doxid-d6/d97/classModels_1_1Base_1a5a6bc95969a38ac1ac68ab4a0ba94c75>` :ref:`getVars<doxid-d6/d97/classModels_1_1Base_1a9df8ba9bf6d971a574ed4745f6cf946c>`() const;
virtual :ref:`EGPVec<doxid-db/d97/classSnippet_1_1Base_1a43ece29884e2c6cabffe9abf985807c6>` :ref:`getExtraGlobalParams<doxid-d6/d97/classModels_1_1Base_1a7fdddb7d19382736b330ade62c441de1>`() const;
size_t :ref:`getVarIndex<doxid-d6/d97/classModels_1_1Base_1afa0e39df5002efc76448e180f82825e4>`(const std::string& varName) const;
size_t :ref:`getExtraGlobalParamIndex<doxid-d6/d97/classModels_1_1Base_1ae046c19ad56dfb2808c5f4d2cc7475fe>`(const std::string& paramName) const;
virtual std::string :ref:`getSimCode<doxid-d7/dad/classNeuronModels_1_1Base_1a3de4c7ff580f63c5b0ec12cb461ebd3a>`() const;
virtual std::string :ref:`getThresholdConditionCode<doxid-d7/dad/classNeuronModels_1_1Base_1a00ffe96ee864dc67936ce75592c6b198>`() const;
virtual std::string :ref:`getResetCode<doxid-d7/dad/classNeuronModels_1_1Base_1a4bdc01f203f92c2da4d3b1b48109975d>`() const;
virtual std::string :ref:`getSupportCode<doxid-d7/dad/classNeuronModels_1_1Base_1ada27dc79296ef8368ac2c7ab20ca8c8e>`() const;
virtual :ref:`Models::Base::ParamValVec<doxid-db/d97/classSnippet_1_1Base_1a0156727ddf8f9c9cbcbc0d3d913b6b48>` :ref:`getAdditionalInputVars<doxid-d7/dad/classNeuronModels_1_1Base_1afef62c84373334fe4656a754dbb661c7>`() const;
virtual bool :ref:`isAutoRefractoryRequired<doxid-d7/dad/classNeuronModels_1_1Base_1a32c9b73420bbdf11a373faa4e0cceb09>`() const;
:ref:`Izhikevich <doxid-d7/d0a/classNeuronModels_1_1Izhikevich>` neuron with fixed parameters :ref:`izhikevich2003simple <doxid-d0/de3/citelist_1CITEREF_izhikevich2003simple>`.
It is usually described as
\begin{eqnarray*} \frac{dV}{dt} &=& 0.04 V^2 + 5 V + 140 - U + I, \\ \frac{dU}{dt} &=& a (bV-U), \end{eqnarray*}
I is an external input current and the voltage V is reset to parameter c and U incremented by parameter d, whenever V >= 30 mV. This is paired with a particular integration procedure of two 0.5 ms Euler time steps for the V equation followed by one 1 ms time step of the U equation. Because of its popularity we provide this model in this form here event though due to the details of the usual implementation it is strictly speaking inconsistent with the displayed equations.
Variables are:
V- Membrane potentialU- Membrane recovery variable
Parameters are:
a- time scale of Ub- sensitivity of Uc- after-spike reset value of Vd- after-spike reset value of U
.. index:: pair: function; getSimCode
.. ref-code-block:: cpp
:class: doxyrest-title-code-block
virtual std::string getSimCode() const
Gets the code that defines the execution of one timestep of integration of the neuron model.
The code will refer to for the value of the variable with name "NN". It needs to refer to the predefined variable "ISYN", i.e. contain , if it is to receive input.
.. index:: pair: function; getThresholdConditionCode
.. ref-code-block:: cpp
:class: doxyrest-title-code-block
virtual std::string getThresholdConditionCode() const
Gets code which defines the condition for a true spike in the described neuron model.
This evaluates to a bool (e.g. "V > 20").
.. index:: pair: function; getParamNames
.. ref-code-block:: cpp
:class: doxyrest-title-code-block
virtual :ref:`StringVec<doxid-db/d97/classSnippet_1_1Base_1a06cd0f6da1424a20163e12b6fec62519>` getParamNames() const
Gets names of of (independent) model parameters.
.. index:: pair: function; getVars
.. ref-code-block:: cpp
:class: doxyrest-title-code-block
virtual :ref:`VarVec<doxid-d6/d97/classModels_1_1Base_1a5a6bc95969a38ac1ac68ab4a0ba94c75>` getVars() const
Gets names and types (as strings) of model variables.