This is a simple STDP rule including a time delay for the finite transmission speed of the synapse. More...

#include <newWeightUpdateModels.h>

Inheritance diagram for WeightUpdateModels::PiecewiseSTDP:

Public Member Functions
	DECLARE_WEIGHT_UPDATE_MODEL (PiecewiseSTDP, 10, 2, 0, 0)

virtual StringVec	getParamNames () const override
	Gets names of of (independent) model parameters. More...

virtual StringPairVec	getVars () const override
	Gets names and types (as strings) of model variables. More...

virtual std::string	getSimCode () const override
	Gets simulation code run when 'true' spikes are received. More...

virtual std::string	getLearnPostCode () const override
	Gets code to include in the learnSynapsesPost kernel/function. More...

virtual DerivedParamVec	getDerivedParams () const override

virtual bool	isPreSpikeTimeRequired () const override
	Whether presynaptic spike times are needed or not. More...

virtual bool	isPostSpikeTimeRequired () const override
	Whether postsynaptic spike times are needed or not. More...

Public Member Functions inherited from WeightUpdateModels::Base
virtual std::string	getEventCode () const
	Gets code run when events (all the instances where event threshold condition is met) are received. More...

virtual std::string	getSynapseDynamicsCode () const
	Gets code for synapse dynamics which are independent of spike detection. More...

virtual std::string	getEventThresholdConditionCode () const
	Gets codes to test for events. More...

virtual std::string	getSimSupportCode () const
	Gets support code to be made available within the synapse kernel/function. More...

virtual std::string	getLearnPostSupportCode () const
	Gets support code to be made available within learnSynapsesPost kernel/function. More...

virtual std::string	getSynapseDynamicsSuppportCode () const
	Gets support code to be made available within the synapse dynamics kernel/function. More...

virtual std::string	getPreSpikeCode () const

virtual std::string	getPostSpikeCode () const

virtual StringPairVec	getPreVars () const

virtual StringPairVec	getPostVars () const

virtual StringPairVec	getExtraGlobalParams () const

size_t	getPreVarIndex (const std::string &varName) const
	Find the index of a named presynaptic variable. More...

size_t	getPostVarIndex (const std::string &varName) const
	Find the index of a named postsynaptic variable. More...

Public Member Functions inherited from NewModels::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 ()

Additional Inherited Members
Public Types inherited from Snippet::Base
typedef std::function< double(const std::vector< double > &, double)>	DerivedParamFunc

typedef std::vector< std::string >	StringVec

typedef std::vector< std::pair< std::string, std::string > >	StringPairVec

typedef std::vector< std::pair< std::string, std::pair< std::string, double > > >	NameTypeValVec

typedef std::vector< std::pair< std::string, DerivedParamFunc > >	DerivedParamVec

Static Protected Member Functions inherited from NewModels::Base
static size_t	getVarIndex (const std::string &varName, const StringPairVec &vars)

Detailed Description

This is a simple STDP rule including a time delay for the finite transmission speed of the synapse.

The STDP window is defined as a piecewise function:

The STDP curve is applied to the raw synaptic conductance gRaw, which is then filtered through the sugmoidal filter displayed above to obtain the value of g.

Note: The STDP curve implies that unpaired pre- and post-synaptic spikes incur a negative increment in gRaw (and hence in g).; The time of the last spike in each neuron, "sTXX", where XX is the name of a neuron population is (somewhat arbitrarily) initialised to -10.0 ms. If neurons never spike, these spike times are used.; It is the raw synaptic conductance gRaw that is subject to the STDP rule. The resulting synaptic conductance is a sigmoid filter of gRaw. This implies that g is initialised but not gRaw, the synapse will revert to the value that corresponds to gRaw.

An example how to use this synapse correctly is given in map_classol.cc (MBody1 userproject):

for (int i= 0; i < model.neuronN[1]*model.neuronN[3]; i++) {
        if (gKCDN[i] < 2.0*SCALAR_MIN){
            cnt++;
            fprintf(stdout, "Too low conductance value %e detected and set to 2*SCALAR_MIN= %e, at index %d \n", gKCDN[i], 2*SCALAR_MIN, i);
            gKCDN[i] = 2.0*SCALAR_MIN; //to avoid log(0)/0 below
        }
        scalar tmp = gKCDN[i] / myKCDN_p[5]*2.0 ;
        gRawKCDN[i]=  0.5 * log( tmp / (2.0 - tmp)) /myKCDN_p[7] + myKCDN_p[6];
}
cerr << "Total number of low value corrections: " << cnt << endl;

Note: One cannot set values of g fully to 0, as this leads to gRaw= -infinity and this is not support. I.e., 'g' needs to be some nominal value > 0 (but can be extremely small so that it acts like it's 0).

The model has 2 variables:

g: conductance of scalar type
gRaw: raw conductance of scalar type

Parameters are (compare to the figure above):

tLrn: Time scale of learning changes
tChng: Width of learning window
tDecay: Time scale of synaptic strength decay
tPunish10: Time window of suppression in response to 1/0
tPunish01: Time window of suppression in response to 0/1
gMax: Maximal conductance achievable
gMid: Midpoint of sigmoid g filter curve
gSlope: Slope of sigmoid g filter curve
tauShift: Shift of learning curve
gSyn0: Value of syn conductance g decays to

Member Function Documentation

◆ DECLARE_WEIGHT_UPDATE_MODEL()

WeightUpdateModels::PiecewiseSTDP::DECLARE_WEIGHT_UPDATE_MODEL	(	PiecewiseSTDP	,
		10	,
		2	,
		0	,
		0
	)

◆ getDerivedParams()

virtual DerivedParamVec WeightUpdateModels::PiecewiseSTDP::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.

◆ getLearnPostCode()

virtual std::string WeightUpdateModels::PiecewiseSTDP::getLearnPostCode ( ) const

inlineoverridevirtual

Gets code to include in the learnSynapsesPost kernel/function.

For examples when modelling STDP, this is where the effect of postsynaptic spikes which occur after presynaptic spikes are applied.

Reimplemented from WeightUpdateModels::Base.

◆ getParamNames()

virtual StringVec WeightUpdateModels::PiecewiseSTDP::getParamNames ( ) const

inlineoverridevirtual

Gets names of of (independent) model parameters.

Reimplemented from Snippet::Base.

◆ getSimCode()

virtual std::string WeightUpdateModels::PiecewiseSTDP::getSimCode ( ) const

inlineoverridevirtual

Gets simulation code run when 'true' spikes are received.

Reimplemented from WeightUpdateModels::Base.

◆ getVars()

virtual StringPairVec WeightUpdateModels::PiecewiseSTDP::getVars ( ) const

inlineoverridevirtual

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

Reimplemented from NewModels::Base.

◆ isPostSpikeTimeRequired()

virtual bool WeightUpdateModels::PiecewiseSTDP::isPostSpikeTimeRequired ( ) const

inlineoverridevirtual

Whether postsynaptic spike times are needed or not.

Reimplemented from WeightUpdateModels::Base.

◆ isPreSpikeTimeRequired()

virtual bool WeightUpdateModels::PiecewiseSTDP::isPreSpikeTimeRequired ( ) const

inlineoverridevirtual

Whether presynaptic spike times are needed or not.

Reimplemented from WeightUpdateModels::Base.

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

newWeightUpdateModels.h

Public Member Functions

Additional Inherited Members

Detailed Description

Member Function Documentation

◆ DECLARE_WEIGHT_UPDATE_MODEL()

◆ getDerivedParams()

◆ getLearnPostCode()

◆ getParamNames()

◆ getSimCode()

◆ getVars()

◆ isPostSpikeTimeRequired()

◆ isPreSpikeTimeRequired()