GeNN  4.9.0
GPU enhanced Neuronal Networks (GeNN)
NeuronModels::RulkovMap Class Reference

Rulkov Map neuron. More...

#include <neuronModels.h>

Inheritance diagram for NeuronModels::RulkovMap:
NeuronModels::Base Models::Base Snippet::Base

Public Types

typedef Snippet::ValueBase< 4 > ParamValues
 
typedef Models::VarInitContainerBase< 2 > VarValues
 
typedef Models::VarInitContainerBase< 0 > PreVarValues
 
typedef Models::VarInitContainerBase< 0 > PostVarValues
 
- Public Types inherited from Models::Base
typedef std::vector< VarVarVec
 
typedef std::vector< VarRefVarRefVec
 
typedef std::vector< EGPRefEGPRefVec
 
- Public Types inherited from Snippet::Base
typedef std::vector< std::string > StringVec
 
typedef std::vector< EGPEGPVec
 
typedef std::vector< ParamValParamValVec
 
typedef std::vector< DerivedParamDerivedParamVec
 

Public Member Functions

virtual std::string getSimCode () const override
 Gets the code that defines the execution of one timestep of integration of the neuron model. More...
 
virtual std::string getThresholdConditionCode () const override
 Gets code which defines the condition for a true spike in the described neuron model. More...
 
virtual StringVec getParamNames () const override
 Gets names of of (independent) model parameters. More...
 
virtual VarVec getVars () const override
 Gets names and types (as strings) of model variables. More...
 
virtual DerivedParamVec getDerivedParams () const override
 
- Public Member Functions inherited from NeuronModels::Base
virtual std::string getResetCode () const
 Gets code that defines the reset action taken after a spike occurred. This can be empty. More...
 
virtual std::string getSupportCode () const
 Gets support code to be made available within the neuron kernel/funcion. More...
 
virtual Models::Base::ParamValVec getAdditionalInputVars () const
 
virtual bool isAutoRefractoryRequired () const
 Does this model require auto-refractory logic? More...
 
boost::uuids::detail::sha1::digest_type getHashDigest () const
 Update hash from model. More...
 
void validate () const
 Validate names of parameters etc. More...
 
- Public Member Functions inherited from Models::Base
size_t getVarIndex (const std::string &varName) const
 Find the index of a named variable. More...
 
- Public Member Functions inherited from Snippet::Base
virtual ~Base ()
 
virtual EGPVec getExtraGlobalParams () const
 
size_t getExtraGlobalParamIndex (const std::string &paramName) const
 Find the index of a named extra global parameter. More...
 

Static Public Member Functions

static const NeuronModels::RulkovMapgetInstance ()
 

Additional Inherited Members

- Protected Member Functions inherited from Models::Base
void updateHash (boost::uuids::detail::sha1 &hash) const
 
void validate () const
 Validate names of parameters etc. More...
 
- Protected Member Functions inherited from Snippet::Base
void updateHash (boost::uuids::detail::sha1 &hash) const
 
void validate () const
 Validate names of parameters etc. More...
 
- Static Protected Member Functions inherited from Snippet::Base
template<typename T >
static size_t getNamedVecIndex (const std::string &name, const std::vector< T > &vec)
 

Detailed Description

Rulkov Map neuron.

The RulkovMap type is a map based neuron model based on [7] but in the 1-dimensional map form used in [5] :

\begin{eqnarray*} V(t+\Delta t) &=& \left\{ \begin{array}{ll} V_{\rm spike} \Big(\frac{\alpha V_{\rm spike}}{V_{\rm spike}-V(t) \beta I_{\rm syn}} + y \Big) & V(t) \leq 0 \\ V_{\rm spike} \big(\alpha+y\big) & V(t) \leq V_{\rm spike} \big(\alpha + y\big) \; \& \; V(t-\Delta t) \leq 0 \\ -V_{\rm spike} & {\rm otherwise} \end{array} \right. \end{eqnarray*}

Note
The RulkovMap type only works as intended for the single time step size of DT= 0.5.

The RulkovMap type has 2 variables:

  • V - the membrane potential
  • preV - the membrane potential at the previous time step

and it has 4 parameters:

  • Vspike - determines the amplitude of spikes, typically -60mV
  • alpha - determines the shape of the iteration function, typically $\alpha $= 3
  • y - "shift / excitation" parameter, also determines the iteration function,originally, y= -2.468
  • beta - roughly speaking equivalent to the input resistance, i.e. it regulates the scale of the input into the neuron, typically $\beta$= 2.64 ${\rm M}\Omega$.
Note
The initial values array for the RulkovMap type needs two entries for V and preV and the parameter array needs four entries for Vspike, alpha, y and beta, in that order.

Member Typedef Documentation

◆ ParamValues

◆ PostVarValues

◆ PreVarValues

◆ VarValues

Member Function Documentation

◆ getDerivedParams()

virtual DerivedParamVec NeuronModels::RulkovMap::getDerivedParams ( ) const
inlineoverridevirtual

Gets names of derived model parameters and the function objects to call to Calculate their value from a vector of model parameter values

Reimplemented from Snippet::Base.

◆ getInstance()

static const NeuronModels::RulkovMap* NeuronModels::RulkovMap::getInstance ( )
inlinestatic

◆ getParamNames()

virtual StringVec NeuronModels::RulkovMap::getParamNames ( ) const
inlineoverridevirtual

Gets names of of (independent) model parameters.

Reimplemented from Snippet::Base.

◆ getSimCode()

virtual std::string NeuronModels::RulkovMap::getSimCode ( ) const
inlineoverridevirtual

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.

Reimplemented from NeuronModels::Base.

◆ getThresholdConditionCode()

virtual std::string NeuronModels::RulkovMap::getThresholdConditionCode ( ) const
inlineoverridevirtual

Gets code which defines the condition for a true spike in the described neuron model.

This evaluates to a bool (e.g. "V > 20").

Reimplemented from NeuronModels::Base.

◆ getVars()

virtual VarVec NeuronModels::RulkovMap::getVars ( ) const
inlineoverridevirtual

Gets names and types (as strings) of model variables.

Reimplemented from Models::Base.


The documentation for this class was generated from the following file: