CARLsim User Interface This class provides a user interface to the public sections of CARLsimCore source code. Example networks that use this methodology can be found in the examples/ directory. Documentation is available on our website. More...

#include <carlsim.h>

Classes
class	Impl

Public Member Functions
	CARLsim (const std::string &netName="SNN", SimMode preferredSimMode=CPU_MODE, LoggerMode loggerMode=USER, int ithGPUs=0, int randSeed=-1)
	CARLsim constructor. Creates a new instance of class CARLsim. All input arguments are optional, but if specified will be constant throughout the lifetime of the CARLsim object. More...

	~CARLsim ()

void	biasWeights (short int connId, float bias, bool updateWeightRange=false)
	Adds a constant bias to the weight of every synapse in the connection. More...

short int	connect (int grpId1, int grpId2, const std::string &connType, const RangeWeight &wt, float connProb, const RangeDelay &delay=RangeDelay(1), const RadiusRF &radRF=RadiusRF(-1.0), bool synWtType=SYN_FIXED, float mulSynFast=1.0f, float mulSynSlow=1.0f)
	Connects a presynaptic to a postsynaptic group using fixed/plastic weights and a range of delay values. More...

short int	connect (int grpId1, int grpId2, ConnectionGenerator *conn, bool synWtType=SYN_FIXED)
	Shortcut to make connections with custom connectivity profile but omit scaling factors for synaptic conductances (default is 1.0 for both) More...

short int	connect (int grpId1, int grpId2, ConnectionGenerator *conn, float mulSynFast, float mulSynSlow, bool synWtType=SYN_FIXED)
	make connections with custom connectivity profile More...

short int	connectCompartments (int grpIdLower, int grpIdUpper)
	make a compartmental connection between two compartmentally enabled groups Note: all compartmentally connected groups must be located on the same partition. More...

int	createGroup (const std::string &grpName, int nNeur, int neurType, int preferredPartition=ANY, ComputingBackend preferredBackend=CPU_CORES)
	creates a group of Izhikevich spiking neurons More...

int	createGroup (const std::string &grpName, const Grid3D &grid, int neurType, int preferredPartition=ANY, ComputingBackend preferredBackend=CPU_CORES)
	Create a group of Izhikevich spiking neurons on a 3D grid (a primitive cubic Bravais lattice with cubic side length 1) More...

int	createGroupLIF (const std::string &grpName, int nNeur, int neurType, int preferredPartition=ANY, ComputingBackend preferredBackend=CPU_CORES)
	creates a group of Leaky-Integrate-and-Fire (LIF) spiking neurons More...

int	createGroupLIF (const std::string &grpName, const Grid3D &grid, int neurType, int preferredPartition=ANY, ComputingBackend preferredBackend=CPU_CORES)
	Create a group of LIF spiking neurons on a 3D grid (a primitive cubic Bravais lattice with cubic side length 1) More...

int	createSpikeGeneratorGroup (const std::string &grpName, int nNeur, int neurType, int preferredPartition=ANY, ComputingBackend preferredBackend=CPU_CORES)
	creates a spike generator group More...

int	createSpikeGeneratorGroup (const std::string &grpName, const Grid3D &grid, int neurType, int preferredPartition=ANY, ComputingBackend preferredBackend=CPU_CORES)
	create a group of spike generators on a 3D grid More...

void	findWavefrontPath (std::vector< int > &path, std::vector< float > &eligibility, int netId, int grpId, int startNId, int goalNId)
	Extracts the path from a spiking wave front and returns the eligibility trace. More...

CARLsimState	getCARLsimState ()
	Writes population weights from gIDpre to gIDpost to file fname in binary. More...

std::vector< float >	getConductanceAMPA (int grpId)
	gets AMPA vector of a group More...

bool	getConductanceConfig (int grpId, float &dAMPA, float &rNMDA, float &dNMDA, float &dGABAa, float &rGABAb, float &dGABAb)

bool	getConductanceConfig (int grpId, int &tdAMPA, int &trNMDA, int &tdNMDA, int &tdGABAa, int &trGABAb, int &tdGABAb)

std::vector< float >	getConductanceGABAa (int grpId)
	gets GABAa vector of a group More...

std::vector< float >	getConductanceGABAb (int grpId)
	gets GABAb vector of a group More...

std::vector< float >	getConductanceNMDA (int grpId)
	gets NMDA vector of a group More...

ConnSTDPInfo	getConnSTDPInfo (int grpId)
	returns the stdp information of a group specified by grpId More...

RangeDelay	getDelayRange (short int connId)
	returns the RangeDelay struct for a specific connection ID More...

uint8_t *	getDelays (int gIDpre, int gIDpost, int &Npre, int &Npost)
	gets delays More...

int	getGroupEndNeuronId (int grpId)
	returns the last neuron id of a groupd specified by grpId More...

Grid3D	getGroupGrid3D (int grpId)
	returns the 3D grid struct of a group More...

int	getGroupId (std::string grpName)
	finds the ID of the group with name grpName More...

std::string	getGroupName (int grpId)
	gets group name More...

GroupNeuromodulatorInfo	getGroupNeuromodulatorInfo (int grpId)
	returns the neuromodulator information of a group specified by grpId More...

int	getGroupNumNeurons (int grpId)
	returns the number of neurons of a group specified by grpId More...

int	getGroupStartNeuronId (int grpId)
	returns the first neuron id of a groupd specified by grpId More...

IcalcType	getIcalcType (int grpId)
	Returns the iCalc of a group. More...

const FILE *	getLogFpDeb ()
	returns file pointer to debug log More...

const FILE *	getLogFpErr ()
	returns file pointer to error log More...

const FILE *	getLogFpInf ()
	returns file pointer to info log More...

const FILE *	getLogFpLog ()
	returns file pointer to log file More...

int	getMaxNumCompConnections ()
	Returns the maximum number of allowed compartmental connections per group. More...

int	getNeuronId (int grpId, Point3D location)
	returns the neuron ID for a 3D location More...

Point3D	getNeuronLocation3D (int neurId)
	returns the 3D location a neuron codes for More...

Point3D	getNeuronLocation3D (int grpId, int relNeurId)
	returns the 3D location a neuron codes for More...

int	getNumConnections ()
	Returns the number of connections (pairs of pre-post groups) in the network. More...

int	getNumGroups ()
	returns the number of groups in the network More...

int	getNumNeurons ()
	returns the total number of allocated neurons in the network More...

int	getNumNeuronsGen ()
	returns the total number of spike generator neurons More...

int	getNumNeuronsGenExc ()
	returns the total number of excitatory spike generator neurons More...

int	getNumNeuronsGenInh ()
	returns the total number of inhibitory spike generator neurons More...

int	getNumNeuronsReg ()
	returns the total number of regular (Izhikevich) neurons More...

int	getNumNeuronsRegExc ()
	returns the total number of regular (Izhikevich) excitatory neurons More...

int	getNumNeuronsRegInh ()
	returns the total number of regular (Izhikevich) inhibitory neurons More...

int	getNumSynapses ()
	returns the total number of allocated synaptic connections in the network More...

int	getNumSynapticConnections (short int connectionId)
	returns the number of connections associated with a connection ID More...

int	getSimTime ()
	returns More...

int	getSimTimeMsec ()
	returns More...

int	getSimTimeSec ()
	returns More...

SpikeMonitor *	getSpikeMonitor (int grpId)
	Returns the number of spikes per neuron for a certain group. More...

RangeWeight	getWeightRange (short int connId)
	returns the RangeWeight struct for a specific connection ID More...

bool	isConnectionPlastic (short int connId)
	Returns whether a connection is fixed or plastic. More...

bool	isExcitatoryGroup (int grpId)
	returns More...

bool	isGroupWith (int grpId, IcalcType icalcType)

bool	isGroupWithCOBA (int grpId)

bool	isGroupWithCUBA (int grpId)

bool	isGroupWithHomeostasis (int grpId)
	Returns whether a group has homeostasis enabled. More...

bool	isInhibitoryGroup (int grpId)
	returns More...

bool	isPoissonGroup (int grpId)
	returns More...

bool	isSimulationWithCOBA ()
	Returns true is the network is COBA enabled. More...

bool	isSimulationWithCUBA ()
	Returns true is the network exclusivle operate on current basis. More...

void	loadSimulation (FILE *fid)
	Loads a simulation (and network state) from file. The file pointer fid must point to a valid CARLsim network save file (created with CARLsim::saveSimulation). More...

void	printEntrails (char *buffer, unsigned length, int gGrpIdPre, int gGrpIdPost)
	print entrails of SNN to string buffer More...

int	runNetwork (int nSec, int nMsec=0, bool printRunSummary=true)
	run the simulation for time=(nSecseconds + nMsecmilliseconds) More...

void	saveSimulation (const std::string &fileName, bool saveSynapseInfo=true)
	Saves important simulation and network infos to file. More...

void	scaleWeights (short int connId, float scale, bool updateWeightRange=false)
	reset Spike Counter to zero More...

void	setACNE12 (int grpId)
	Sets IcalcType to ACNE12 for a specific neuron group. More...

void	setCompartmentParameters (int grpId, float couplingUp, float couplingDown)
	Sets coupling constants G_u and G_d for the compartment. More...

void	setConductances (bool isSet)
	Sets default values for conduction decay and rise times or disables COBA alltogether. More...

void	setConductances (bool isSet, int tdAMPA, int tdNMDA, int tdGABAa, int tdGABAb)
	Sets custom values for conduction decay times (instantaneous rise time) or disables COBA alltogether. More...

void	setConductances (bool isSet, int tdAMPA, int trNMDA, int tdNMDA, int tdGABAa, int trGABAb, int tdGABAb)
	Sets custom values for conduction rise and decay times or disables COBA alltogether. More...

void	setConductances (int grpId, bool isSet)
	Sets default values for conduction decay and rise times or disables COBA for a specific neuron group. More...

void	setConductances (int grpId, bool isSet, int tdAMPA, int tdNMDA, int tdGABAa, int tdGABAb)
	Sets IcalcType to COBA and configure custom values for conduction decay times (instantaneous rise time) for a specific neuron group. More...

void	setConductances (int grpId, bool isSet, int tdAMPA, int trNMDA, int tdNMDA, int tdGABAa, int trGABAb, int tdGABAb)
	Sets IcalcType to COBA and configure for conduction rise and decay times for a specific neuron group. More...

void	setConnectionModulation (int preGrpId, int postGrpId, IcalcType icalcType)

ConnectionMonitor *	setConnectionMonitor (int grpIdPre, int grpIdPost, const std::string &fname)
	Sets a connection monitor for a group, custom ConnectionMonitor class. More...

void	setDefaultConductanceTimeConstants (int tdAMPA, int trNMDA, int tdNMDA, int tdGABAa, int trGABAb, int tdGABAb)
	Sets default values for conductance time constants. More...

void	setDefaultESTDPparams (float alphaPlus, float tauPlus, float alphaMinus, float tauMinus, STDPType stdpType)
	sets default values for E-STDP params More...

void	setDefaultHomeostasisParams (float homeoScale, float avgTimeScale)
	Sets default homeostasis params. More...

void	setDefaultISTDPparams (float betaLTP, float betaLTD, float lambda, float delta, STDPType stdpType)
	sets default values for I-STDP params More...

void	setDefaultSaveOptions (std::string fileName, bool saveSynapseInfo)
	Sets default options for save file. More...

void	setDefaultSTDPparams (float alphaPlus, float tauPlus, float alphaMinus, float tauMinus, STDPType stdpType)
	sets default STDP params More...

void	setDefaultSTPparams (int neurType, float STP_U, float STP_tau_u, float STP_tau_x)
	Sets default values for STP params U, tau_u, and tau_x of a neuron group (pre-synaptically) More...

void	setESTDP (int preGrpId, int postGrpId, bool isSet)
	Sets default E-STDP mode and parameters. More...

void	setESTDP (int preGrpId, int postGrpId, bool isSet, STDPType type, ExpCurve curve)
	Sets E-STDP with the exponential curve. More...

void	setESTDP (int preGrpId, int postGrpId, bool isSet, STDPType type, ExpCurve curve, PkaPlcModulation modulation)
	Sets neuromodulator controlled LTP and LTD by PKA and PCL pathways. More...

void	setESTDP (int preGrpId, int postGrpId, bool isSet, STDPType type, TimingBasedCurve curve)
	Sets E-STDP with the timing-based curve. More...

void	setExternalCurrent (int grpId, const std::vector< float > &current)
	Sets the amount of current (mA) to inject into a group. More...

void	setExternalCurrent (int grpId, float current)
	Sets the amount of current (mA) to inject to each neuron in a group. More...

GroupMonitor *	setGroupMonitor (int grpId, const std::string &fname, int mode=0)
	Sets a group monitor for a group, custom GroupMonitor class. More...

void	setHomeoBaseFiringRate (int grpId, float baseFiring, float baseFiringSD=0.0f)
	Sets the homeostatic target firing rate (enforced through homeostatic synaptic scaling) More...

void	setHomeostasis (int grpId, bool isSet, float homeoScale, float avgTimeScale)
	Sets custom values for implementation of homeostatic synaptic scaling. More...

void	setHomeostasis (int grpId, bool isSet)
	Sets default values for implementation of homeostatic synaptic scaling. More...

void	setIntegrationMethod (integrationMethod_t method, int numStepsPerMs)

void	setISTDP (int preGrpId, int postGrpId, bool isSet)
	Sets default I-STDP mode and parameters. More...

void	setISTDP (int preGrpId, int postGrpId, bool isSet, STDPType type, ExpCurve curve)
	Sets I-STDP with the exponential curve. More...

void	setISTDP (int preGrpId, int postGrpId, bool isSet, STDPType type, PulseCurve curve)
	Sets I-STDP with the pulse curve. More...

void	setLogFile (const std::string &fileName)
	Sets the name of the log file. More...

void	setLogsFpCustom (FILE fpInf=NULL, FILE fpErr=NULL, FILE fpDeb=NULL, FILE fpLog=NULL)
	Sets the file pointers for all log files in CUSTOM mode. More...

void	setNeuromodulator (int grpId, float baseDP, float tauDP, float base5HT, float tau5HT, float baseACh, float tauACh, float baseNE, float tauNE)
	Sets baseline concentration and decay time constant of neuromodulators (DP, 5HT, ACh, NE) for a neuron group. More...

void	setNeuromodulator (int grpId, float baseDP, float tauDP, float releaseDP, bool activeDP, float base5HT, float tau5HT, float release5HT, bool active5HT, float baseACh, float tauACh, float releaseAch, bool activeACh, float baseNE, float tauNE, float releaseNE, bool activeNE)

void	setNeuromodulator (int grpId, float tauDP=100.0f, float tau5HT=100.0f, float tauACh=100.0f, float tauNE=100.0f)
	Sets default neuromodulators. More...

NeuronMonitor *	setNeuronMonitor (int grpId, const std::string &fileName)
	Sets a Neuron Monitor for a groups, print voltage, recovery, and total current values to binary file. More...

void	setNeuronParameters (int grpId, float izh_a, float izh_a_sd, float izh_b, float izh_b_sd, float izh_c, float izh_c_sd, float izh_d, float izh_d_sd)
	Sets Izhikevich params a, b, c, and d with as mean +- standard deviation. More...

void	setNeuronParameters (int grpId, float izh_a, float izh_b, float izh_c, float izh_d)
	Sets Izhikevich params a, b, c, and d of a neuron group. More...

void	setNeuronParameters (int grpId, float izh_C, float izh_k, float izh_vr, float izh_vt, float izh_a, float izh_b, float izh_vpeak, float izh_c, float izh_d)
	Sets Izhikevich params C, k, vr, vt, a, b, vpeak, c, and d of a neuron group C must be positive. There are no limits imposed on other parameters This is a nine parameter Izhikevich simple spiking model. More...

void	setNeuronParameters (int grpId, float izh_C, float izh_C_sd, float izh_k, float izh_k_sd, float izh_vr, float izh_vr_sd, float izh_vt, float izh_vt_sd, float izh_a, float izh_a_sd, float izh_b, float izh_b_sd, float izh_vpeak, float izh_vpeak_sd, float izh_c, float izh_c_sd, float izh_d, float izh_d_sd)
	Sets Izhikevich params C, k, vr, vt, a, b, vpeak, c, and d with as mean +- standard deviation C must be positive. There are no limits imposed on other parameters This is a nine parameter Izhikevich simple spiking model. More...

void	setNeuronParametersLIF (int grpId, int tau_m, int tau_ref=0, float vTh=1.0f, float vReset=0.0f, const RangeRmem &rMem=RangeRmem(1.0f))
	Sets neuron parameters for a group of LIF spiking neurons. More...

void	setNM4STP (int grpId, float wSTP_U[], float wSTP_tau_u[], float wSTP_tau_x[])
	Sets neuromodulator targeting STP params U, tau_u, and tau_x of a neuron group (pre-synaptically) More...

void	setNM4weighted (int grpId, IcalcType type, float wDA=1.f, float w5HT=1.f, float wACh=1.f, float wNE=1.f, float wNorm=4.f, float wBase=1.0f)
	Sets IcalcType to NM4weighted for a specific neuron group. More...

void	setSpikeGenerator (int grpId, SpikeGenerator *spikeGenFunc)
	A SpikeCounter keeps track of the number of spikes per neuron in a group. More...

SpikeMonitor *	setSpikeMonitor (int grpId, const std::string &fileName)
	Sets a Spike Monitor for a groups, prints spikes to binary file. More...

void	setSpikeRate (int grpId, PoissonRate *spikeRate, int refPeriod=1)
	Sets a spike rate. More...

void	setSTDP (int preGrpId, int postGrpId, bool isSet)
	Sets default STDP mode and params. More...

void	setSTDP (int preGrpId, int postGrpId, bool isSet, STDPType type, float alphaPlus, float tauPlus, float alphaMinus, float tauMinus)
	Sets STDP params for a group, custom. More...

void	setSTP (int grpId, bool isSet, float STP_U, float STP_tau_u, float STP_tau_x)
	Sets STP params U, tau_u, and tau_x of a neuron group (pre-synaptically) More...

void	setSTP (int grpId, bool isSet)
	Sets STP params U, tau_u, and tau_x of a neuron group (pre-synaptically) using default values. More...

void	setupNetwork ()
	build the network More...

void	setupNetworkMT ()
	featFastSetup LN 20201108 More...

void	setWeight (short int connId, int neurIdPre, int neurIdPost, float weight, bool updateWeightRange=false)
	Sets the weight value of a specific synapse. More...

void	setWeightAndWeightChangeUpdate (UpdateInterval wtANDwtChangeUpdateInterval, bool enableWtChangeDecay, float wtChangeDecay=0.9f)
	Sets the weight and weight change update parameters. More...

void	startTesting (bool updateWeights=true)
	Enters a testing phase in which all weight changes are disabled. More...

void	stopTesting ()
	Exits a testing phase, making weight changes possible again. More...

bool	updateDelays (int gGrpIdPre, int gGrpIdPost, std::vector< std::tuple< int, int, uint8_t >> connDelays)
	Updates the delays directly the backend memory. More...

Static Public Member Functions
static int	cudaDeviceCount ()
	LN extension 20201017. More...

static void	cudaDeviceDescription (unsigned ithGPU, const char **desc)
	LN extension 20201017. More...

Detailed Description

This class provides a user interface to the public sections of CARLsimCore source code. Example networks that use this methodology can be found in the examples/ directory. Documentation is available on our website. This file is organized into different sections in the following way:

*  ├── Public section
*  │     ├── Public methods
*  │     │     ├── Constructor / destructor
*  │     │     ├── Setting up a simulation
*  │     │     ├── Running a simulation
*  │     │     ├── Plotting / logging
*  │     │     ├── Interacting with a simulation
*  │     │     ├── Getters / setters
*  │     │     └── Set defaults
*  │     └── Public properties
*  └── Private section
*        ├── Private methods
*        └── Private properties
*

Within these sections, methods and properties are ordered alphabetically.

Definition at line 142 of file carlsim.h.

Constructor & Destructor Documentation

◆ CARLsim()

CARLsim	(	const std::string &	netName = `"SNN"`,
		SimMode	preferredSimMode = `CPU_MODE`,
		LoggerMode	loggerMode = `USER`,
		int	ithGPUs = `0`,
		int	randSeed = `-1`
	)

CARLsim allows execution on both generic x86 CPUs and standard off-the-shelf GPUs by specifying the simulation mode (CPU_MODE and GPU_MODE, respectively). When using the latter in a multi-GPU system, the user can also specify which CUDA device to use (param numGPUs, 0-indexed).

The logger mode defines where to print all status, error, and debug messages. Logger mode can either be USER (for experiment-oriented simulations), DEVELOPER (for developing and debugging code), SHOWTIME (where only warnings and errors are printed to console), SILENT (e.g., for benchmarking, where no output is generated at all), or CUSTOM (where the user can specify the file pointers of all log files). In summary, messages are printed to the following locations, depending on the logger mode:

*                 |    USER    | DEVELOPER  |  SHOWTIME  |   SILENT   |  CUSTOM
* ----------------|------------|------------|------------|------------|---------
* Status msgs     |   stdout   |   stdout   | /dev/null  | /dev/null  |    ?
* Errors/warnings |   stderr   |   stderr   |   stderr   | /dev/null  |    ?
* Debug msgs      | /dev/null  |   stdout   | /dev/null  | /dev/null  |    ?
* All msgs        | debug.log  | debug.log  |  debug.log | debug.log  |    ?
*

Location of the CARLsim log file can be set in any mode using setLogFile. In mode CUSTOM, the other file pointers can be set using setLogsFpCustom.

Parameters

[in]	netName	network name
[in]	preferredSimMode	CPU_MODE, GPU_MODE, or HYBRID_MODE
[in]	loggerMode	USER, DEVELOPER, SILENT, or CUSTOM
[in]	ithGPUs	on which GPU to establish a context (deprecated parameter)
[in]	randSeed	random number generator seed

See also: setLogFile; setLogsFpCustom

Definition at line 2057 of file carlsim.cpp.

◆ ~CARLsim()

~CARLsim ( )

Definition at line 2059 of file carlsim.cpp.

Member Function Documentation

◆ biasWeights()

void biasWeights	(	short int	connId,
		float	bias,
		bool	updateWeightRange = `false`
	)

This method adds a constant bias to the weight of every synapse in the connection specified by connId. The bias can be positive or negative. If a bias is specified that makes any weight+bias lie outside the range [minWt,maxWt] of this connection, the range will be updated accordingly if the flag updateWeightRange is set to true. If the flag is set to false, then the specified weight value will be corrected to lie on the boundary (either minWt or maxWt).

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Parameters

[in]	connId	the connection ID to manipulate
[in]	bias	the bias value to add to every synapse
[in]	updateWeightRange	a flag specifying what to do when the specified weight+bias lies outside the range [minWt,maxWt]. Set to true to update the range accordingly. Set to false to adjust the weight to be either minWt or maxWt. Default: false.

Note: A weight cannot drop below zero, no matter what.

See also: setWeight; scaleWeights

Since: v3.0

Definition at line 2335 of file carlsim.cpp.

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◆ connect() [1/3]

short int connect	(	int	grpId1,
		int	grpId2,
		const std::string &	connType,
		const RangeWeight &	wt,
		float	connProb,
		const RangeDelay &	delay = `RangeDelay(1)`,
		const RadiusRF &	radRF = `RadiusRF(-1.0)`,
		bool	synWtType = `SYN_FIXED`,
		float	mulSynFast = `1.0f`,
		float	mulSynSlow = `1.0f`
	)

This function is a shortcut to create synaptic connections from a pre-synaptic group grpId1 to a post-synaptic group grpId2 using a pre-defined primitive type (such as "full", "one-to-one", or "random"). Synapse weights will stay the same throughout the simulation (SYN_FIXED, no plasticity). All synapses will have the same delay. For more flexibility, see the other connect() calls.

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in]	grpId1	ID of the pre-synaptic group
[in]	grpId2	ID of the post-synaptic group
[in]	connType	connection type. "random": random connectivity. "one-to-one": connect the i-th neuron in pre to the i-th neuron in post. "full": connect all neurons in pre to all neurons in post. "full-no-direct": same as "full", but i-th neuron of grpId1 will not be connected to the i-th neuron of grpId2. "gaussian": distance-dependent weights depending on the RadiusRF struct, where neurons coding for the same location have weight initWt, and neurons lying on the border of the RF have weight 0.1*initWt.
[in]	wt	a struct specifying the range of weight magnitudes (initial value and max value). Weights range from 0 to maxWt, and are initialized with initWt. All weight values should be non-negative (equivalent to weight magnitudes), even for inhibitory connections. Examples: RangeWeight(0.1) => all weights will be 0.1 (wt.min=0.1, wt.max=0.1, wt.init=0.1) RangeWeight(0.0,0.2) => If pre is excitatory: all weights will be in range [0.0,0.2], and wt.init=0.0. If pre is inhibitory: all weights will be in range [-0.2,0.0], and wt.init=0.0. RangeWeight(0.0,0.1,0.2) => If pre is excitatory: all weights will be in range [0.0,0.2], and wt.init=0.1. If pre is inhibitory: all weights will be in range [-0.2,0.0], and wt.init=0.0.
[in]	connProb	connection probability
[in]	delay	A struct specifying the range of delay values (ms). Synaptic delays must be greater than or equal to 1 ms. Examples: RangeDelay(2) => all delays will be 2 (delay.min=2, delay.max=2) RangeDelay(1,10) => delays will be in range [1,10]
[in]	radRF	A struct specifying the radius of the receptive field (RF). A radius can be specified in 3 dimensions x, y, and z (following the topographic organization of neurons as specified by Grid3D). Receptive fields will be circular with radius as specified. The 3 dimensions follow the ones defined by Grid3D. If the radius in one dimension is 0, no connections will be made in this dimension. If the radius in one dimension is -1, then all possible connections will be made in this dimension (effectively making RF of infinite size). Otherwise, if the radius is a positive real number, the RF radius will be exactly this number. Call RadiusRF with only one argument to make that radius apply to all 3 dimensions. Examples: Create a 2D Gaussian RF of radius 10 in z-plane: RadiusRF(10, 10, 0) Neuron pre will be connected to neuron post iff (pre.x-post.x)^2+(pre.y-post.y)^2<=100 and pre.z==post.z. Create a 2D heterogeneous Gaussian RF (an ellipse) with semi-axes 10 and 5: RadiusRF(10, 5, 0) Neuron pre will be connected to neuron post iff (pre.x-post.x)/100 + (pre.y-post.y)^2/25 <= 1 and pre.z==post.z. Connect all, no matter the RF (default): RadiusRF(-1, -1, -1) Connect one-to-one: RadiusRF(0, 0, 0) Neuron pre will be connected to neuron post iff pre.x==post.x, pre.y==post.y, pre.z==post.z. Note: Use CARLsim::connect with type "one-to-one" instead.
[in]	synWtType	specifies whether the synapse should be of fixed value (SYN_FIXED) or plastic (SYN_PLASTIC)
[in]	mulSynFast	a multiplication factor to be applied to the fast synaptic current (AMPA in the case of excitatory, and GABAa in the case of inhibitory connections). Default: 1.0
[in]	mulSynSlow	a multiplication factor to be applied to the slow synaptic current (NMDA in the case of excitatory, and GABAb in the case of inhibitory connections). Default: 1.0

Returns: a unique ID associated with the newly created connection

See also: ch4s1_primitive_types

Definition at line 2062 of file carlsim.cpp.

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◆ connect() [2/3]

short int connect	(	int	grpId1,
		int	grpId2,
		ConnectionGenerator *	conn,
		bool	synWtType = `SYN_FIXED`
	)

TODO:: finish docu

Allowed CARLsim states:: CONFIG_STATE

See also: ch4s3_user_defined

Definition at line 2069 of file carlsim.cpp.

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◆ connect() [3/3]

short int connect	(	int	grpId1,
		int	grpId2,
		ConnectionGenerator *	conn,
		float	mulSynFast,
		float	mulSynSlow,
		bool	synWtType = `SYN_FIXED`
	)

TODO:: finish docu

Allowed CARLsim states:: CONFIG_STATE

See also: ch4s3_user_defined

Definition at line 2072 of file carlsim.cpp.

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◆ connectCompartments()

short int connectCompartments	(	int	grpIdLower,
		int	grpIdUpper
	)

first group is in the lower layer; second group is in the upper layer

TODO:: finish docu

Allowed CARLsim states:: CONFIG

Definition at line 2078 of file carlsim.cpp.

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◆ createGroup() [1/2]

int createGroup	(	const std::string &	grpName,
		int	nNeur,
		int	neurType,
		int	preferredPartition = `ANY`,
		ComputingBackend	preferredBackend = `CPU_CORES`
	)

TODO:: finish doc

Allowed CARLsim states:: CONFIG_STATE

Definition at line 2086 of file carlsim.cpp.

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◆ createGroup() [2/2]

int createGroup	(	const std::string &	grpName,
		const Grid3D &	grid,
		int	neurType,
		int	preferredPartition = `ANY`,
		ComputingBackend	preferredBackend = `CPU_CORES`
	)

Neurons of a group can be arranged topographically, so that they virtually lie on a 3D grid. Connections can then be specified depending on the relative placement of neurons via CARLsim::connect. This allows for the creation of networks with complex spatial structure.

Each neuron in the group gets assigned a (x,y,z) location on a 3D grid centered around the origin, so that calling Grid3D(Nx,Ny,Nz) creates coordinates that fall in the range [-(Nx-1)/2, (Nx-1)/2], [-(Ny-1)/2, (Ny-1)/2], and [-(Nz-1)/2, (Nz-1)/2]. The resulting grid is a primitive cubic Bravais lattice with cubic side length 1 (arbitrary units). The primitive (or simple) cubic crystal system consists of one lattice point (neuron) on each corner of the cube. Each neuron at a lattice point is then shared equally between eight adjacent cubes.

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in]	grpName	the group name
[in]	grid	a Grid3D struct specifying the dimensions of the 3D lattice
[in]	neurType	either EXCITATORY_NEURON, INHIBITORY_NEURON or DOPAMINERGIC_NEURON

Since: v3.0

Definition at line 2083 of file carlsim.cpp.

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◆ createGroupLIF() [1/2]

int createGroupLIF	(	const std::string &	grpName,
		int	nNeur,
		int	neurType,
		int	preferredPartition = `ANY`,
		ComputingBackend	preferredBackend = `CPU_CORES`
	)

TODO:: finish doc

Allowed CARLsim states:: CONFIG_STATE

Definition at line 2094 of file carlsim.cpp.

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◆ createGroupLIF() [2/2]

int createGroupLIF	(	const std::string &	grpName,
		const Grid3D &	grid,
		int	neurType,
		int	preferredPartition = `ANY`,
		ComputingBackend	preferredBackend = `CPU_CORES`
	)

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in]	grpName	the group name
[in]	grid	a Grid3D struct specifying the dimensions of the 3D lattice
[in]	neurType	either EXCITATORY_NEURON, INHIBITORY_NEURON or DOPAMINERGIC_NEURON

Since: v4.0

Definition at line 2091 of file carlsim.cpp.

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◆ createSpikeGeneratorGroup() [1/2]

int createSpikeGeneratorGroup	(	const std::string &	grpName,
		int	nNeur,
		int	neurType,
		int	preferredPartition = `ANY`,
		ComputingBackend	preferredBackend = `CPU_CORES`
	)

TODO:: finish docu

Allowed CARLsim states:: CONFIG_STATE

Definition at line 2102 of file carlsim.cpp.

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◆ createSpikeGeneratorGroup() [2/2]

int createSpikeGeneratorGroup	(	const std::string &	grpName,
		const Grid3D &	grid,
		int	neurType,
		int	preferredPartition = `ANY`,
		ComputingBackend	preferredBackend = `CPU_CORES`
	)

Neurons of a group can be arranged topographically, so that they virtually lie on a 3D grid. This simplifies the creation of topographic connections in the network. Each neuron thus gets assigned a (x,y,z) location on a 3D grid (integer coordinates). Neuron numbers will be assigned to location in order; where the first dimension specifies the width, the second dimension is height, and the third dimension is depth. Grid3D(2,2,2) would thus assign neurId 0 to location (0,0,0), neurId 1 to (1,0,0), neurId 3 to (0,1,0), neurId 6 to (2,2,1), and so on. The third dimension can be thought of as a depth (z-coordinate in 3D), a cortical column (each of which consists of a 2D arrangement of neurons on a plane), or a channel (such as RGB channels, each of which consists of a 2D arrangements of neurons coding for (x,y) coordinates of an image). For the user's convenience, the struct thus provides members Grid3D::depth, Grid3D::column, and Grid3D::channels, which differ only semantically.

Allowed CARLsim states:: CONFIG_STATE

TODO:: finish doc

Definition at line 2099 of file carlsim.cpp.

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◆ cudaDeviceCount()

static int cudaDeviceCount ( )

static

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◆ cudaDeviceDescription()

static void cudaDeviceDescription	(	unsigned	ithGPU,
		const char **	desc
	)

static

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◆ findWavefrontPath()

void findWavefrontPath	(	std::vector< int > &	path,
		std::vector< float > &	eligibility,
		int	netId,
		int	grpId,
		int	startNId,
		int	goalNId
	)

The the start and goal neurons are identified by local ids.

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Definition at line 2301 of file carlsim.cpp.

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◆ getCARLsimState()

CARLsimState getCARLsimState ( )

TODO:: finish docu

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Returns the current CARLsim state

A CARLsim simulation goes through the following states:

CONFIG_STATE configuration state, where the neural network is configured
SETUP_STATE setup state, where the neural network is prepared for execution
RUN_STATE execution state, where the simulation is executed

Certain methods can only be called in certain states. Check their documentation to see which method can be called in which state.

Certain methods perform state transitions. setupNetwork will change the state from CONFIG_STATE to SETUP_STATE. The first call to runNetwork will change the state from SETUP_STATE to RUN_STATE.

Returns: current CARLsim state

Definition at line 2397 of file carlsim.cpp.

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◆ getConductanceAMPA()

std::vector< float > getConductanceAMPA ( int grpId )

TODO:: finish docu

Allowed CARLsim states:: RUN_STATE

Deprecated:: This function is deprecated. It will be replaced by NeuronMonitor.

Definition at line 2411 of file carlsim.cpp.

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◆ getConductanceConfig() [1/2]

bool getConductanceConfig	(	int	grpId,
		float &	dAMPA,
		float &	rNMDA,
		float &	dNMDA,
		float &	dGABAa,
		float &	rGABAb,
		float &	dGABAb
	)

Definition at line 2536 of file carlsim.cpp.

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◆ getConductanceConfig() [2/2]

bool getConductanceConfig	(	int	grpId,
		int &	tdAMPA,
		int &	trNMDA,
		int &	tdNMDA,
		int &	tdGABAa,
		int &	trGABAb,
		int &	tdGABAb
	)

Definition at line 2543 of file carlsim.cpp.

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◆ getConductanceGABAa()

std::vector< float > getConductanceGABAa ( int grpId )

TODO:: finish docu

Allowed CARLsim states:: RUN_STATE

Deprecated:: This function is deprecated. It will be replaced by NeuronMonitor.

Definition at line 2417 of file carlsim.cpp.

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◆ getConductanceGABAb()

std::vector< float > getConductanceGABAb ( int grpId )

TODO:: finish docu

Allowed CARLsim states:: RUN_STATE

Deprecated:: This function is deprecated. It will be replaced by NeuronMonitor.

Definition at line 2420 of file carlsim.cpp.

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◆ getConductanceNMDA()

std::vector< float > getConductanceNMDA ( int grpId )

TODO:: finish docu

Allowed CARLsim states:: RUN_STATE

Deprecated:: This function is deprecated. It will be replaced by NeuronMonitor.

Definition at line 2414 of file carlsim.cpp.

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◆ getConnSTDPInfo()

ConnSTDPInfo getConnSTDPInfo ( int grpId )

This function returns the current STDP setting of a group.

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

See also: GroupSTDPInfo

Definition at line 2493 of file carlsim.cpp.

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◆ getDelayRange()

RangeDelay getDelayRange ( short int connId )

This function returns the RangeDelay struct for a specific connection ID. The RangeDelay struct contains fields for the minimum and maximum synaptic delay in the connection.

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE, RUN_STATE

Parameters

[in] connId connection ID

Returns: RangeDelay struct

Since: v3.0

Definition at line 2423 of file carlsim.cpp.

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◆ getDelays()

uint8_t * getDelays	(	int	gIDpre,
		int	gIDpost,
		int &	Npre,
		int &	Npost
	)

TODO:: finish docu

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Definition at line 2426 of file carlsim.cpp.

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◆ getGroupEndNeuronId()

int getGroupEndNeuronId ( int grpId )

TODO:: finish docu

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Definition at line 2487 of file carlsim.cpp.

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◆ getGroupGrid3D()

Grid3D getGroupGrid3D ( int grpId )

TODO:: : This function is called in SNN::connect() at CONFIG_STATE, which violate the restriction

This function returns the Grid3D struct of a particular neuron group. Neurons of a group can be arranged topographically, so that they virtually lie on a 3D grid. This simplifies the creation of topographic connections in the network. The dimensions of the grid can thus be retrieved by calling Grid3D.width, Grid3D.height, and Grid3D.depth. The total number of neurons is given by Grid3D.N. See createGroup and Grid3D for more information.

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Parameters

[in] grpId the group ID for which to get the Grid3D struct

Returns: the 3D grid struct of a group

Definition at line 2431 of file carlsim.cpp.

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◆ getGroupId()

int getGroupId ( std::string grpName )

TODO:: finish docu

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Definition at line 2433 of file carlsim.cpp.

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◆ getGroupName()

std::string getGroupName ( int grpId )

TODO:: finish docu

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Definition at line 2436 of file carlsim.cpp.

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◆ getGroupNeuromodulatorInfo()

GroupNeuromodulatorInfo getGroupNeuromodulatorInfo ( int grpId )

This function returns the current setting for neuromodulators.

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

See also: GroupNeuromodulatorInfo

Definition at line 2496 of file carlsim.cpp.

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◆ getGroupNumNeurons()

int getGroupNumNeurons ( int grpId )

TODO:: finish docu

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE, RUN_STATE

Definition at line 2490 of file carlsim.cpp.

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◆ getGroupStartNeuronId()

int getGroupStartNeuronId ( int grpId )

TODO:: finish docu

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Definition at line 2484 of file carlsim.cpp.

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◆ getIcalcType()

IcalcType getIcalcType ( int grpId )

This functions returns IcalcType of a neuron group

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE, RUN_STATE

Parameters

[in] grpId group ID

Since: v6.0

Definition at line 2533 of file carlsim.cpp.

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◆ getLogFpDeb()

const FILE * getLogFpDeb ( )

Definition at line 2317 of file carlsim.cpp.

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◆ getLogFpErr()

const FILE * getLogFpErr ( )

Definition at line 2316 of file carlsim.cpp.

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◆ getLogFpInf()

const FILE * getLogFpInf ( )

Definition at line 2315 of file carlsim.cpp.

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◆ getLogFpLog()

const FILE * getLogFpLog ( )

Definition at line 2318 of file carlsim.cpp.

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◆ getMaxNumCompConnections()

int getMaxNumCompConnections ( )

A compartmentally enabled neuron group cannot have more than this number of compartmental connections. This value is controlled by MAX_NUM_COMP_CONN in carlsim_definitions.h.

Definition at line 2451 of file carlsim.cpp.

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◆ getNeuronId()

int getNeuronId	(	int	grpId,
		Point3D	location
	)

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE, ::EXE_STATE

Parameters

[in]	grpId	the group ID
[in]	location	the 3D location a neuron codes for as a Point3D struct

Returns: relNeurId the neuron ID (relative to the group) of the 3D location

Definition at line 2445 of file carlsim.cpp.

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◆ getNeuronLocation3D() [1/2]

Point3D getNeuronLocation3D ( int neurId )

This function returns the (x,y,z) location that a neuron with ID neurID (global) codes for. Note that neurID is global; that is, the first neuron in the group does not necessarily have ID 0.

The location is determined by the actual neuron ID (the first neuron in the group coding for the origin (0,0,0), and by the dimensions of the 3D grid the group is allocated on (integer coordinates). Neuron numbers are assigned to location in order; where the first dimension specifies the width, the second dimension is height, and the third dimension is depth.

For more information see createGroup and the Grid3D struct. See also getNeuronLocation3D(int grpId, int relNeurId).

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE, ::EXE_STATE

Parameters

[in] neurId the neuron ID for which the 3D location should be returned

Returns: the 3D location a neuron codes for as a Point3D struct

Definition at line 2439 of file carlsim.cpp.

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◆ getNeuronLocation3D() [2/2]

Point3D getNeuronLocation3D	(	int	grpId,
		int	relNeurId
	)

This function returns the (x,y,z) location that a neuron with ID relNeurId (relative to the group) codes for. Note that neurID is relative to the ID of the first neuron in the group; that is, the first neuron in the group has relNeurId 0, the second one has relNeurId 1, etc. In other words: relNeurId = neurId - sim.getGroupStartNeuronId();

The location is determined by the actual neuron ID (the first neuron in the group coding for the origin (0,0,0), and by the dimensions of the 3D grid the group is allocated on (integer coordinates). Neuron numbers are assigned to location in order; where the first dimension specifies the width, the second dimension is height, and the third dimension is depth.

For more information see createGroup and the Grid3D struct. See also getNeuronLocation3D(int neurId).

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE, ::EXE_STATE

Parameters

[in]	grpId	the group ID
[in]	relNeurId	the neuron ID (relative to the group) for which the 3D location should be returned

Returns: the 3D location a neuron codes for as a Point3D struct

Definition at line 2442 of file carlsim.cpp.

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◆ getNumConnections()

int getNumConnections ( )

This function returns the number of connections (pairs of pre-post groups) in the network. Each pre-post pair of neuronal groups has its own connection ID, which is returned by a call to connect.

Note: This number might change throughout CARLsim state CONFIG_STATE, up to calling setupNetwork).

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE, RUN_STATE

Returns: the number of connections (pairs of pre-post groups) in the network

Definition at line 2449 of file carlsim.cpp.

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◆ getNumGroups()

int getNumGroups ( )

Note: This number might change throughout CARLsim state CONFIG_STATE, up to calling setupNetwork).

TODO:: finish docu

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE, RUN_STATE

Definition at line 2457 of file carlsim.cpp.

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◆ getNumNeurons()

int getNumNeurons ( )

Note: This number might change throughout CARLsim state CONFIG_STATE, up to calling setupNetwork).

TODO:: finish docu

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE, RUN_STATE

Definition at line 2460 of file carlsim.cpp.

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◆ getNumNeuronsGen()

int getNumNeuronsGen ( )

Note: This number might change throughout CARLsim state CONFIG_STATE, up to calling setupNetwork).

TODO:: finish docu

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE, RUN_STATE

Definition at line 2472 of file carlsim.cpp.

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◆ getNumNeuronsGenExc()

int getNumNeuronsGenExc ( )

Note: This number might change throughout CARLsim state CONFIG_STATE, up to calling setupNetwork).

TODO:: finish docu

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE, RUN_STATE

Definition at line 2475 of file carlsim.cpp.

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◆ getNumNeuronsGenInh()

int getNumNeuronsGenInh ( )

Note: This number might change throughout CARLsim state CONFIG_STATE, up to calling setupNetwork).

TODO:: finish docu

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE, RUN_STATE

Definition at line 2478 of file carlsim.cpp.

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◆ getNumNeuronsReg()

int getNumNeuronsReg ( )

Note: This number might change throughout CARLsim state CONFIG_STATE, up to calling setupNetwork).

TODO:: finish docu

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE, RUN_STATE

Definition at line 2463 of file carlsim.cpp.

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◆ getNumNeuronsRegExc()

int getNumNeuronsRegExc ( )

Note: This number might change throughout CARLsim state CONFIG_STATE, up to calling setupNetwork).

TODO:: finish docu

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE, RUN_STATE

Definition at line 2466 of file carlsim.cpp.

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◆ getNumNeuronsRegInh()

int getNumNeuronsRegInh ( )

Note: This number might change throughout CARLsim state CONFIG_STATE, up to calling setupNetwork).

TODO:: finish docu

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE, RUN_STATE

Definition at line 2469 of file carlsim.cpp.

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◆ getNumSynapses()

int getNumSynapses ( )

TODO:: finish docu

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE, RUN_STATE

Definition at line 2481 of file carlsim.cpp.

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◆ getNumSynapticConnections()

int getNumSynapticConnections ( short int connectionId )

TODO:: finish docu

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Definition at line 2454 of file carlsim.cpp.

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◆ getSimTime()

int getSimTime ( )

TODO:: finish docu

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Definition at line 2500 of file carlsim.cpp.

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◆ getSimTimeMsec()

int getSimTimeMsec ( )

TODO:: finish docu

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Definition at line 2504 of file carlsim.cpp.

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◆ getSimTimeSec()

int getSimTimeSec ( )

TODO:: finish docu

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Definition at line 2502 of file carlsim.cpp.

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◆ getSpikeMonitor()

SpikeMonitor * getSpikeMonitor ( int grpId )

A SpikeCounter keeps track of all spikes per neuron binned into a certain time period (recordDur). This function allows to query the spike array at any point in time. It will return a pointer to an int array if the group has a valid SpikeCounter, or NULL otherwise. The number of elements in the int array is the number of neurons in the group.

Before this function can be used, a SpikeCounter must be set up for the group via CARLsim::setSpikeCounter.

Usage example:

// During CONFIG state, create a neuron group with 10 neurons.
int g0 = sim.createGroup("group0", 10, EXCITATORY_NEURON);
// Set up a SpikeCounter on group g0 that counts the number
// of spikes in bins of 50 ms
sim.setSpikeCounter(g0, 50);
// move to setup state
sim.setupNetwork();
// run the network for a bit, say 32 ms
sim.runNetwork(0,32);
// get the number of spikes in these 32 ms
int* spkArr = sim.getSpikeCounter(g0);
// print number of spikes for each neuron in the group
for (int i=0; i<10; i++)
   printf("Neuron %d has %d spikes\n",i,spkArr[i]);

Allowed CARLsim states:: RUN_STATE

Parameters

[in] grpId the group for which you want the spikes (cannot be ALL)

Returns: pointer to array of ints if SpikeCounter exists, else NULL. Number of elements in array is the number of neurons in group. Each entry is the number of spikes for this neuron (int) since the last reset.

See also: CARLsim::setSpikeCounter; CARLsim::resetSpikeCounter

returns pointer to previously allocated SpikeMonitor object, NULL else

This function returns a pointer to a SpikeMonitor object that has previously been created using the method setSpikeMonitor. If the group does not have a SpikeMonitor, NULL is returned.

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Parameters

[in] grpId the group ID

Returns: pointer to SpikeMonitor object if exists, NULL else

Since: v3.0

Definition at line 2507 of file carlsim.cpp.

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◆ getWeightRange()

RangeWeight getWeightRange ( short int connId )

This function returns the RangeWeight struct for a specific connection ID. The RangeWeight struct contains fields for the minimum, initial, and maximum weight in the connection.

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE, RUN_STATE

Parameters

[in] connId connection ID

Returns: RangeWeight struct

Since: v3.0

Definition at line 2510 of file carlsim.cpp.

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◆ isConnectionPlastic()

bool isConnectionPlastic ( short int connId )

This function returns whether the synapses in a certain connection ID are fixed (false) or plastic (true).

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE, RUN_STATE

Parameters

[in] connId connection ID

Since: v3.1

Definition at line 2513 of file carlsim.cpp.

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◆ isExcitatoryGroup()

bool isExcitatoryGroup ( int grpId )

TODO:: finish docu

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Definition at line 2552 of file carlsim.cpp.

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◆ isGroupWith()

bool isGroupWith	(	int	grpId,
		IcalcType	icalcType
	)

Definition at line 2527 of file carlsim.cpp.

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◆ isGroupWithCOBA()

bool isGroupWithCOBA ( int grpId )

Definition at line 2529 of file carlsim.cpp.

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◆ isGroupWithCUBA()

bool isGroupWithCUBA ( int grpId )

Definition at line 2531 of file carlsim.cpp.

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◆ isGroupWithHomeostasis()

bool isGroupWithHomeostasis ( int grpId )

This functions returns whether a group has homeostasis enabled (true) or not (false).

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE, RUN_STATE

Parameters

[in] grpId group ID

Since: v3.1

Definition at line 2516 of file carlsim.cpp.

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◆ isInhibitoryGroup()

bool isInhibitoryGroup ( int grpId )

TODO:: finish docu

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Definition at line 2554 of file carlsim.cpp.

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◆ isPoissonGroup()

bool isPoissonGroup ( int grpId )

TODO:: finish docu

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Definition at line 2556 of file carlsim.cpp.

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◆ isSimulationWithCOBA()

bool isSimulationWithCOBA ( )

This returns true if the neurons in the networks can hold a conductances.

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE, RUN_STATE

Parameters

[in] grpId group ID

Since: v6.0

Definition at line 2520 of file carlsim.cpp.

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◆ isSimulationWithCUBA()

bool isSimulationWithCUBA ( )

None of the neurons is enabled to hold the conductance state. This saves memory.

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE, RUN_STATE

Parameters

[in] grpId group ID

Since: v6.0

Definition at line 2522 of file carlsim.cpp.

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◆ loadSimulation()

void loadSimulation ( FILE * fid )

Past CARLsim networks can be loaded from file by setting up the same number of groups, connections, and neurons as was used to store the network via CARLsim::saveSimulation, and then calling CARLsim::loadSimulation to overwrite all corresponding synaptic weight and delay values from file.

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in] fid file pointer to a save file created with CARLsim::saveSimulation

Note: In order for CARLsim::loadSimulation to work, the configured network must have the identical number of groups, connections, and neurons as the one stored with CARLsim::saveSimulation.; In addition, CARLsim::saveSimulation must have been called with flag saveSynapseInfo set to true.

Attention: Wait with calling fclose on the file pointer until SETUP_STATE!

See also: CARLsim::saveSimulation

Since: v2.0

Definition at line 2340 of file carlsim.cpp.

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◆ printEntrails()

void printEntrails	(	char *	buffer,
		unsigned	length,
		int	gGrpIdPre,
		int	gGrpIdPost
	)

Pretty printing of interal structures to support unit testing.

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Parameters

[in]	buffer	the string buffer that holds the pretty printing content
[in]	length	the size of the string buffer
[in]	gGrpIdPre	the global ID of the pre-synaptic group
[in]	gGrpIdPost	the global ID of the post-synaptic group

Definition at line 2309 of file carlsim.cpp.

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◆ runNetwork()

int runNetwork	(	int	nSec,
		int	nMsec = `0`,
		bool	printRunSummary = `true`
	)

Allowed CARLsim states:: SETUP_STATE, RUN_STATE. First call to runNetwork will make CARLsim state switch from SETUP_STATE to RUN_STATE.

Parameters

[in]	nSec	number of seconds to run the network
[in]	nMsec	number of milliseconds to run the network
[in]	printRunSummary	enable the printing of a summary at the end of this run

Definition at line 2288 of file carlsim.cpp.

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◆ saveSimulation()

void saveSimulation	(	const std::string &	fileName,
		bool	saveSynapseInfo = `true`
	)

The network state consists of all the synaptic connections, weights, delays, and whether the connections are plastic or fixed. As an option, the user can choose whether or not to save the synaptic weight information (which could be a large amount of data) with the saveSynapseInfo argument. The value of this argument is true by default which causes the synaptic weight values to be output by default along with the rest of the network information.

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Parameters

[in]	fileName	string of filename of saved simulation data.
[in]	saveSynapseInfo	boolean value that determines if the weight values are written to the data file or not. The weight values are written if the boolean value is true.

See also: CARLsim::loadSimulation

Since: v2.0

Definition at line 2321 of file carlsim.cpp.

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◆ scaleWeights()

void scaleWeights	(	short int	connId,
		float	scale,
		bool	updateWeightRange = `false`
	)

Manually resets the spike buffers of a Spike Counter to zero (for a specific group). Buffers get reset to zero automatically after recordDur (see CARLsim::setSpikeCounter). However, the buffer can be manually reset at any point in time (during SETUP_STATE and RUN_STATE).

At any point in time (during SETUP_STATE or RUN_STATE), all SpikeCounters can be reset via:

sim.resetSpikeCounters(-1); // reset for all groups, -1==ALL

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Parameters

grpId the group for which to reset the spike counts. Set to ALL if you want to reset all SpikeCounters.

See also: CARLsim::setSpikeCounter; CARLsim::getSpikeCounter

Multiplies the weight of every synapse in the connection with a scaling factor

This method scales the weight of every synapse in the connection specified by connId with a scaling factor. The scaling factor cannot be negative. If a scaling factor is specified that makes any weight*scale lie outside the range [minWt,maxWt] of this connection, the range will be updated accordingly if the flag updateWeightRange is set to true. If the flag is set to false, then the specified weight value will be corrected to lie on the boundary (either minWt or maxWt).

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Parameters

[in]	connId	the connection ID to manipulate
[in]	scale	the scaling factor to apply to every synapse (cannot be negative)
[in]	updateWeightRange	a flag specifying what to do when the specified weight*scale lies outside the range [minWt,maxWt]. Set to true to update the range accordingly. Set to false to adjust the weight to be either minWt or maxWt. Default: false.

Note: A weight cannot drop below zero, no matter what.

See also: setWeight; biasWeights

Since: v3.0

Definition at line 2343 of file carlsim.cpp.

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◆ setACNE12()

void setACNE12 ( int grpId )

ACNE12 is the Icalc type that is derived from Krichmar (2012)

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in] grpId the group ID of group to which ACNE12 is applied

Definition at line 2136 of file carlsim.cpp.

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◆ setCompartmentParameters()

void setCompartmentParameters	(	int	grpId,
		float	couplingUp,
		float	couplingDown
	)

TODO:: finish docu

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in]	couplingUp	Coupling constant for "up" compartmental connection
[in]	couplingDown	Coupling constant for "down" compartmental connection

Definition at line 2106 of file carlsim.cpp.

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◆ setConductances() [1/6]

void setConductances ( bool isSet )

This function sets the time constants for the decay of AMPA, NMDA, GABA, and GABAb, and the rise times for NMDA and GABAb. These constants will be applied to all connections in the network. Set isSet to false to run your simulation in CUBA mode. Use setDefaultConductanceTimeConstants to set default values for all time constants. If you call this function without setting your own defaults, then the following defaults will be used: tdAMPA=5ms, trNMDA=0, tdNMDA=150ms, tdGABAa=6ms, trGABAb=0, tdGABAb=150ms (instantaneous rise time).

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in] isSet a flag to inform whether to run simulation in COBA mode (true) or CUBA mode (false)

Definition at line 2112 of file carlsim.cpp.

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◆ setConductances() [2/6]

void setConductances	(	bool	isSet,
		int	tdAMPA,
		int	tdNMDA,
		int	tdGABAa,
		int	tdGABAb
	)

This function sets the time constants for the decay of AMPA, NMDA, GABAa, and GABAb. The decay constants will be applied to all connections in the network. Set isSet to false to run your simulation in CUBA mode. The NMDA current is voltage dependent (see Izhikevich et al., 2004). Use setConductances(true) to use default decay values. Use the other setConductances to enable non-zero rise times for NMDA and GABAb.

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in]	isSet	a flag to inform whether to run simulation in COBA mode (true) or CUBA mode (false)
[in]	tdAMPA	time constant for AMPA decay (ms)
[in]	tdNMDA	time constant for NMDA decay (ms)
[in]	tdGABAa	time constant for GABAa decay (ms)
[in]	tdGABAb	time constant for GABAb decay (ms)

Definition at line 2115 of file carlsim.cpp.

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◆ setConductances() [3/6]

void setConductances	(	bool	isSet,
		int	tdAMPA,
		int	trNMDA,
		int	tdNMDA,
		int	tdGABAa,
		int	trGABAb,
		int	tdGABAb
	)

This function sets the time constants for the rise and decay time of AMPA, NMDA, GABAa, and GABAb. AMPA and GABAa will always have instantaneous rise time. The rise times of NMDA and GABAb can be set manually. They need to be strictly smaller than the decay time. Set isSet to false to run your simulation in CUBA mode. We do not provide non-zero rise times for AMPA and GABAa, because these rise times are typically on the order of 1 ms, which is equal to the simulation time step. The NMDA current is voltage dependent (see Izhikevich et al., 2004). Use setConductances(true) to use default decay values.

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in]	isSet	a flag to inform whether to run simulation in COBA mode (true) or CUBA mode (false)
[in]	tdAMPA	time constant for AMPA decay (ms)
[in]	trNMDA	time constant for NMDA rise (ms), must be smaller than tdNMDA
[in]	tdNMDA	time constant for NMDA decay (ms)
[in]	tdGABAa	time constant for GABAa decay (ms)
[in]	trGABAb	time constant for GABAb rise (ms), must be smaller than tdGABAb
[in]	tdGABAb	time constant for GABAb decay (ms)

Definition at line 2118 of file carlsim.cpp.

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◆ setConductances() [4/6]

void setConductances	(	int	grpId,
		bool	isSet
	)

This is the corresponding COBA setting at neuron group level,

See also: network level, without the group id Hint: By setting one group to COBA, the whole network property withConductance is enabled

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in]	grpId	the group ID of group to which Icalc is applied
[in]	isSet	a flag to inform whether calc I in COBA mode (true) or CUBA mode (false)

Definition at line 2124 of file carlsim.cpp.

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◆ setConductances() [5/6]

void setConductances	(	int	grpId,
		bool	isSet,
		int	tdAMPA,
		int	tdNMDA,
		int	tdGABAa,
		int	tdGABAb
	)

This is the corresponding COBA setting at neuron group level,

See also: network level, without the group id

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in]	grpId	the group ID of group to which Icalc is applied
[in]	tdAMPA	time constant for AMPA decay (ms)
[in]	tdNMDA	time constant for NMDA decay (ms)
[in]	tdGABAa	time constant for GABAa decay (ms)
[in]	tdGABAb	time constant for GABAb decay (ms)

Definition at line 2128 of file carlsim.cpp.

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◆ setConductances() [6/6]

void setConductances	(	int	grpId,
		bool	isSet,
		int	tdAMPA,
		int	trNMDA,
		int	tdNMDA,
		int	tdGABAa,
		int	trGABAb,
		int	tdGABAb
	)

This is the corresponding COBA setting at neuron group level,

See also: network level, without the group id

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in]	grpId	the group ID of group to which Icalc is applied
[in]	tdAMPA	time constant for AMPA decay (ms)
[in]	trNMDA	time constant for NMDA rise (ms), must be smaller than tdNMDA
[in]	tdNMDA	time constant for NMDA decay (ms)
[in]	tdGABAa	time constant for GABAa decay (ms)
[in]	trGABAb	time constant for GABAb rise (ms), must be smaller than tdGABAb
[in]	tdGABAb	time constant for GABAb decay (ms)

Definition at line 2132 of file carlsim.cpp.

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◆ setConnectionModulation()

void setConnectionModulation	(	int	preGrpId,
		int	postGrpId,
		IcalcType	icalcType
	)

Definition at line 2240 of file carlsim.cpp.

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◆ setConnectionMonitor()

ConnectionMonitor * setConnectionMonitor	(	int	grpIdPre,
		int	grpIdPost,
		const std::string &	fname
	)

To retrieve connection status, a connection-monitoring callback mechanism is used. This mechanism allows the user to monitor connection status between groups. Connection monitors are registered for two groups (i.e., pre- and post- synaptic groups) and are called automatically by the simulator every second.

CARLsim supports two different recording mechanisms: Recording to a weight file (binary) and recording to a ConnectionMonitor object. The former is useful for off-line analysis of synaptic weights (e.g., using Chapter 9: MATLAB Offline Analysis Toolbox (OAT)). The latter is useful to calculate different weight metrics and statistics on-line, such as the percentage of weight values that fall in a certain weight range, or the number of weights that have been changed since the last snapshot.

A file name can be specified via variable fileName (make sure the specified directory exists). The easiest way is to set fileName to string "DEFAULT", in which case a default file name will be created in the results directory: "results/conn_{preGrpName}_{postGrpName}.dat", where preGrpName is the name assigned to the pre-synaptic group at initialization, and postGrpName is the name assigned to the post-synaptic group at initialization. If no binary file shall be created, set fileName equal to the string "NULL".

The function returns a pointer to a ConnectionMonitor object, which can be used to calculate weight changes and other connection stats. See 7.2 Connection Monitor of the User Guide for more information on how to use ConnectionMonitor.

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE

Parameters

[in]	grpIdPre	the pre-synaptic group ID
[in]	grpIdPost	the post-synaptic group ID
[in]	fname	file name of the binary to be created

See also: ch7s2_connection_monitor; ch9s1_matlab_oat

Definition at line 2348 of file carlsim.cpp.

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◆ setDefaultConductanceTimeConstants()

void setDefaultConductanceTimeConstants	(	int	tdAMPA,
		int	trNMDA,
		int	tdNMDA,
		int	tdGABAa,
		int	trGABAb,
		int	tdGABAb
	)

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in]	tdAMPA	time constant for AMPA decay (ms)
[in]	trNMDA	time constant for NMDA rise (ms)
[in]	tdNMDA	time constant for NMDA decay (ms)
[in]	tdGABAa	time constant for GABAa decay (ms)
[in]	trGABAb	time constant for GABAb rise (ms)
[in]	tdGABAb	time constant for GABAb decay (ms)

Definition at line 2558 of file carlsim.cpp.

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◆ setDefaultESTDPparams()

void setDefaultESTDPparams	(	float	alphaPlus,
		float	tauPlus,
		float	alphaMinus,
		float	tauMinus,
		STDPType	stdpType
	)

Sets default E-STDP parameters. Do not use this function, it is deprecated.

Allowed CARLsim states:: CONFIG_STATE

Deprecated:: For clearness, setting STDP parameters using setESTDP and setISTDP is strongly recommended.

Definition at line 2580 of file carlsim.cpp.

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◆ setDefaultHomeostasisParams()

void setDefaultHomeostasisParams	(	float	homeoScale,
		float	avgTimeScale
	)

TODO:: finish docu

Allowed CARLsim states:: CONFIG_STATE

Definition at line 2565 of file carlsim.cpp.

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◆ setDefaultISTDPparams()

void setDefaultISTDPparams	(	float	betaLTP,
		float	betaLTD,
		float	lambda,
		float	delta,
		STDPType	stdpType
	)

Sets default I-STDP parameters. Do not use this function, it is deprecated.

Allowed CARLsim states:: CONFIG_STATE

Deprecated:: For clearness, setting STDP parameters using setESTDP and setISTDP is strongly recommended.

Definition at line 2585 of file carlsim.cpp.

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◆ setDefaultSaveOptions()

void setDefaultSaveOptions	(	std::string	fileName,
		bool	saveSynapseInfo
	)

TODO:: finish docu

Allowed CARLsim states:: CONFIG_STATE

Definition at line 2570 of file carlsim.cpp.

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◆ setDefaultSTDPparams()

void setDefaultSTDPparams	(	float	alphaPlus,
		float	tauPlus,
		float	alphaMinus,
		float	tauMinus,
		STDPType	stdpType
	)

Sets default STDP parameters. Do not use this function, it is deprecated.

Allowed CARLsim states:: CONFIG_STATE

Deprecated:: For clearness, setting STDP parameters using setESTDP and setISTDP is strongly recommended.

Definition at line 2575 of file carlsim.cpp.

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◆ setDefaultSTPparams()

void setDefaultSTPparams	(	int	neurType,
		float	STP_U,
		float	STP_tau_u,
		float	STP_tau_x
	)

This function sets the default values for STP parameters U tau_u, and tau_x. These values will then apply to all subsequent calls to setSTP(int, bool).

CARLsim will automatically assign the following values, which can be changed at any time during CONFIG_STATE: The default parameters for an excitatory neuron are U=0.45, tau_u=50.0, tau_f=750.0 (depressive). The default parameters for an inhibitory neuron are U=0.15, tau_u=750.0, tau_f=50.0 (facilitative).

Source: Misha Tsodyks and Si Wu (2013) Short-term synaptic plasticity. Scholarpedia, 8(10):3153., rev #136920

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in]	neurType	either EXCITATORY_NEURON or INHIBITORY_NEURON
[in]	STP_U	default value for increment of u induced by a spike
[in]	STP_tau_u	default value for decay constant of u
[in]	STP_tau_x	default value for decay constant of x

See also: setSTP(int, bool); setSTP(int, bool, float, float, float)

Since: v3.0

Definition at line 2590 of file carlsim.cpp.

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◆ setESTDP() [1/4]

void setESTDP	(	int	preGrpId,
		int	postGrpId,
		bool	isSet
	)

Set E-STDP parameters using default settings. Do not use this function, it is deprecated.

Allowed CARLsim states:: CONFIG_STATE

Deprecated:: For clearness, please do not use default STDP settings.

Since: v3.0

Definition at line 2227 of file carlsim.cpp.

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◆ setESTDP() [2/4]

void setESTDP	(	int	preGrpId,
		int	postGrpId,
		bool	isSet,
		STDPType	type,
		ExpCurve	curve
	)

Parameters

[in]	grpId	the group ID of group for which these settings are applied
[in]	isSet	the flag indicating if E-STDP is enabled
[in]	type	the flag indicating if E-STDP is modulated by dopamine (i.e., DA-STDP)
[in]	curve	the struct defining the exponential curve

Allowed CARLsim states:: CONFIG_STATE

See also: STDPType; ExpCurve

Since: v3.0

Definition at line 2230 of file carlsim.cpp.

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◆ setESTDP() [3/4]

void setESTDP	(	int	preGrpId,
		int	postGrpId,
		bool	isSet,
		STDPType	type,
		ExpCurve	curve,
		PkaPlcModulation	modulation
	)

Parameters

[in]	preGrpId	identitying the presynaptic group
[in]	postGrpId	identifying the postsynaptic group
[in]	type	a STDPType utilizing PKA/PLC for modulating LTP/LTD
[in]	curve	the struct defining the exponential curve
[in]	modulation	the parameters for PKA(protein kinase) and PLC(phospholipase)

Definition at line 2236 of file carlsim.cpp.

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◆ setESTDP() [4/4]

void setESTDP	(	int	preGrpId,
		int	postGrpId,
		bool	isSet,
		STDPType	type,
		TimingBasedCurve	curve
	)

Parameters

[in]	grpId	the group ID of group for which these settings are applied
[in]	isSet	the flag indicating if E-STDP is enabled
[in]	type	the flag indicating if E-STDP is modulated by dopamine (i.e., DA-STDP)
[in]	curve	the struct defining the timing-based curve

Allowed CARLsim states:: CONFIG_STATE

See also: STDPType; TimingBasedCurve

Since: v3.0

Definition at line 2246 of file carlsim.cpp.

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◆ setExternalCurrent() [1/2]

void setExternalCurrent	(	int	grpId,
		const std::vector< float > &	current
	)

This method injects current, specified on a per-neuron basis, into the soma of each neuron in the group, at each timestep of the simulation. current is a float vector of current amounts (mA), one element per neuron in the group.

To input different currents into a neuron over time, the idea is to run short periods of runNetwork and subsequently calling setExternalCurrent again with updated current values.

For example: Inject 5mA for 50 ms, then 0mA for 10 sec

// 5mA for 50 ms, 10 neurons in the group
std::vector<float> current(10, 5.0f);
snn.setExternalCurrent(g0, current);
snn.runNetwork(0,50);
// 0mA for 10 sec, use convenience function for reset
snn.setExternalCurrent(g0, 0.0f);
snn.runNetwork(10,0);

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Parameters

[in]	grpId	the group ID
[in]	current	a float vector of current amounts (mA), one value per neuron in the group

Note: This method cannot be applied to SpikeGenerator groups.; If all neurons in the group should receive the same amount of current, you can use the convenience function setExternalCurrent(int grpId, float current).

Attention: Make sure to reset current after use (i.e., for the next call to runNetwork), otherwise the current will keep getting applied to the group.

See also: setExternalCurrent(int grpId, float current); setSpikeRate; setSpikeGenerator; 6.2 Generating Current

Definition at line 2353 of file carlsim.cpp.

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◆ setExternalCurrent() [2/2]

void setExternalCurrent	(	int	grpId,
		float	current
	)

This methods injects a specific amount of current into the soma of every neuron in the group. current is a float value in mA. The same current is applied to every neuron in the group.

For example: inject 4.5 mA into every neuron in the group, for 500 ms

// 4.5 mA for 500 ms
snn.setExternalCurrent(g0, 4.5f);
snn.runNetwork(0,500);
// don't forget to reset current afterwards if necessary
snn.setExternalCurrent(g0, 0.0f);
snn.runNetwork(10,0); // zero external current

Note: This method cannot be applied to SpikeGenerator groups.; If each neuron in the group should receive a different amount of current, you can use the method setExternalCurrent(int grpId, const std::vector<float>& current) instead.

Attention: Make sure to reset current after use (i.e., for the next call to runNetwork), otherwise the current will keep getting applied to the group.

See also: setExternalCurrent(int grpId, const std::vector<float>& current); setSpikeRate; setSpikeGenerator; 6.2 Generating Current

Definition at line 2358 of file carlsim.cpp.

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◆ setGroupMonitor()

GroupMonitor * setGroupMonitor	(	int	grpId,
		const std::string &	fname,
		int	mode = `0`
	)

TODO:: finish docu

Allowed CARLsim states:: SETUP_STATE

LN2020: mode = DA_MODE -> dopamine, compatibility, ALL_MODE -> all neuro transmitter

Definition at line 2361 of file carlsim.cpp.

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◆ setHomeoBaseFiringRate()

void setHomeoBaseFiringRate	(	int	grpId,
		float	baseFiring,
		float	baseFiringSD = `0.0f`
	)

This function allows the user to set the homeostatic target firing with or without a standard deviation. All neurons in the group will use homeostatic synaptic scaling to attain the target firing rate. You can have a standard deviation to the base firing rate or you can leave this argument blank, which will set the standard deviation to 0. It should be noted that the baseFiringSD only sets the base firing rate to a single value within that standard deviation. It does not vary the value of the base firing rate from this value or within a particular range. For more information on this implementation please see: Carlson, et al. (2013). Proc. of IJCNN 2013.

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in]	grpId	the group ID of group for which these settings are applied
[in]	baseFiring	target firing rate of every neuron in this group
[in]	baseFiringSD	standard deviation of target firing rate of every neuron in this group

Definition at line 2152 of file carlsim.cpp.

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◆ setHomeostasis() [1/2]

void setHomeostasis	(	int	grpId,
		bool	isSet,
		float	homeoScale,
		float	avgTimeScale
	)

This function allows the user to set homeostasis for a particular neuron group. All the neurons in this group scale their weights in an attempt to attain a target base firing rate set with the setHomeoBaseFiringRate function. Each neuron keeps track of their own average firing rate. The time over which this average is computed should be on the scale of seconds to minutes to hours as opposed to ms if one is to claim it is biologically realistic. The homeoScale sets the scaling factor applied to the weight change of the synapse due to homeostasis. If you want to make homeostasis stronger than STDP, you increase this value. Scaling of the synaptic weights is multiplicative. For more information on this implementation please see: Carlson, et al. (2013). Proc. of IJCNN 2013.

Reasonable values to start homeostasis with are: homeoScale = 0.1-1.0 avgTimeScale = 5-10 seconds

Default values are: homeoScale = 0.1 avgTimeScale = 10 seconds

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in]	grpId	the group ID of group to which homeostasis is applied
[in]	isSet	a boolean, setting it to true/false enables/disables homeostasis
[in]	homeoScale	scaling factor multiplied to weight change due to homeostasis
[in]	avgTimeScale	time in seconds over which average firing rate for neurons in this group is averaged

Definition at line 2146 of file carlsim.cpp.

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◆ setHomeostasis() [2/2]

void setHomeostasis	(	int	grpId,
		bool	isSet
	)

This function allows the user to set homeostasis with default values for a particular neuron group. For more information, read the setHomeostasis function description above.

Default values are: homeoScale = 0.1 avgTimeScale = 10 seconds

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in]	grpId	the group ID of group to which homeostasis is applied
[in]	isSet	a boolean, setting it to true/false enables/disables homeostasis

Definition at line 2149 of file carlsim.cpp.

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◆ setIntegrationMethod()

void setIntegrationMethod	(	integrationMethod_t	method,
		int	numStepsPerMs
	)

Definition at line 2156 of file carlsim.cpp.

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◆ setISTDP() [1/3]

void setISTDP	(	int	preGrpId,
		int	postGrpId,
		bool	isSet
	)

Set I-STDP parameters using default settings. Do not use this function, it is deprecated.

Allowed CARLsim states:: CONFIG_STATE

Deprecated:: For clearness, please do not use default STDP settings.

Since: v3.0

Definition at line 2251 of file carlsim.cpp.

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◆ setISTDP() [2/3]

void setISTDP	(	int	preGrpId,
		int	postGrpId,
		bool	isSet,
		STDPType	type,
		ExpCurve	curve
	)

Parameters

[in]	grpId	the group ID of group for which these settings are applied
[in]	isSet	the flag indicating if I-STDP is enabled
[in]	type	the flag indicating if I-STDP is modulated by dopamine (i.e., DA-STDP)
[in]	curve	the struct defining the exponential curve

Allowed CARLsim states:: CONFIG_STATE

See also: STDPType; ExpCurve

Since: v3.0

Definition at line 2254 of file carlsim.cpp.

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◆ setISTDP() [3/3]

void setISTDP	(	int	preGrpId,
		int	postGrpId,
		bool	isSet,
		STDPType	type,
		PulseCurve	curve
	)

Parameters

[in]	grpId	the group ID of group for which these settings are applied
[in]	isSet	the flag indicating if I-STDP is enabled
[in]	type	the flag indicating if I-STDP is modulated by dopamine (i.e., DA-STDP)
[in]	curve	the struct defining the pulse curve

Allowed CARLsim states:: CONFIG_STATE

See also: STDPType; PulseCurve

Since: v3.0

Definition at line 2259 of file carlsim.cpp.

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◆ setLogFile()

void setLogFile ( const std::string & fileName )

This function sets a new path/name for the CARLsim log file. By default, the log file name is given depending on the LoggerMode specified in CARLsim. However, it can be manually overridden using this function. In order to disable the log file, pass string "NULL".

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE, RUN_STATE

Parameters

fileName the name of the log file

Note: This function cannot be called in LoggerMode CUSTOM. In this case, use setLogsFpCustom instead

Attention: Make sure the directory exists!

See also: setLogsFpCustom

Definition at line 2326 of file carlsim.cpp.

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◆ setLogsFpCustom()

void setLogsFpCustom	(	FILE *	fpInf = `NULL`,
		FILE *	fpErr = `NULL`,
		FILE *	fpDeb = `NULL`,
		FILE *	fpLog = `NULL`
	)

In LoggerMode CUSTOM, custom file pointers can be used for the info, error, and debug log streams. In this case, CARLsim does not take ownership of the file pointers; that is, the user should fclose them. Setting a file pointer to NULL will not change the currently assigned file pointer (default value points to the bit bucket).

Allowed CARLsim states:: CONFIG_STATE, SETUP_STATE, RUN_STATE

Parameters

[in]	fpInf	file pointer for status info
[in]	fpErr	file pointer for errors/warnings
[in]	fpDeb	file pointer for debug info
[in]	fpLog	file pointer for debug log file that contains all the above info

Note: This function can be called only in LoggerMode CUSTOM.; Use NULL in order not to change current file pointers.

Attention: Make sure to fclose the file pointers. But, do not fclose stdout or stderr, or they will remain closed for the remainder of the process.

Definition at line 2329 of file carlsim.cpp.

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◆ setNeuromodulator() [1/3]

void setNeuromodulator	(	int	grpId,
		float	baseDP,
		float	tauDP,
		float	base5HT,
		float	tau5HT,
		float	baseACh,
		float	tauACh,
		float	baseNE,
		float	tauNE
	)

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in]	grpId	the symbolic name of a group
[in]	baseDP	the baseline concentration of Dopamine
[in]	tauDP	the decay time constant of Dopamine
[in]	base5HT	the baseline concentration of Serotonin
[in]	tau5HT	the decay time constant of Serotonin
[in]	baseACh	the baseline concentration of Acetylcholine
[in]	tauACh	the decay time constant of Acetylcholine
[in]	baseNE	the baseline concentration of Noradrenaline
[in]	tauNE	the decay time constant of Noradrenaline

Definition at line 2205 of file carlsim.cpp.

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◆ setNeuromodulator() [2/3]

void setNeuromodulator	(	int	grpId,
		float	baseDP,
		float	tauDP,
		float	releaseDP,
		bool	activeDP,
		float	base5HT,
		float	tau5HT,
		float	release5HT,
		bool	active5HT,
		float	baseACh,
		float	tauACh,
		float	releaseAch,
		bool	activeACh,
		float	baseNE,
		float	tauNE,
		float	releaseNE,
		bool	activeNE
	)

Definition at line 2192 of file carlsim.cpp.

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◆ setNeuromodulator() [3/3]

void setNeuromodulator	(	int	grpId,
		float	tauDP = `100.0f`,
		float	tau5HT = `100.0f`,
		float	tauACh = `100.0f`,
		float	tauNE = `100.0f`
	)

TODO:: : this should be implemented via default arguments as members of the class, so that the user can call setDefaultNeuromodulators()

Allowed CARLsim states:: CONFIG_STATE

Definition at line 2212 of file carlsim.cpp.

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◆ setNeuronMonitor()

NeuronMonitor * setNeuronMonitor	(	int	grpId,
		const std::string &	fileName
	)

To retrieve outputs, a neuron-monitoring callback mechanism is used. This mechanism allows the user to calculate basic statistics, store voltage/recovery/current values, or perform more complicated output monitoring. Neuron monitors are registered for a group and are called automatically by the simulator every second. Similar to an address event representation (AER), the neuron monitor indicates neuron's state by using the neuron ID within a group (0-indexed). Only one neuron monitor is allowed per group.

CARLsim supports two different recording mechanisms: Recording to a neuron state (voltage, recovery, and current) file (binary) and recording to a NeuronMonitor object. The former is useful for off-line analysis of activity (e.g., using Chapter 9: MATLAB Offline Analysis Toolbox (OAT)). The latter is useful to calculate different neuron state metrics and statistics on-line.

A file name can be specified via variable fileName (make sure the specified directory exists). The easiest way is to set fileName to string "DEFAULT", in which case a default file name will be created in the results directory: "results/nrnstate_{group name}.dat", where group name is the name assigned to the group at initialization (can be retrieved via getGroupName). If no binary file shall be created, set fileName equal to the string "NULL".

The function returns a pointer to a NeuronMonitor object, which can be used to calculate neuron statistics or retrieve all neuron state values from a particular time window. See ??? of the User Guide for more information on how to use NeuronMonitor.

If you call setNeuronMonitor twice on the same group, the same NeuronMonitor pointer will be returned, and the name of the neuron state file will be updated. This is the same as calling NeuronMonitor::setLogFile directly, and allows you to redirect the spike file stream mid-simulation (see 7.1.3 Redirecting File Streams).

Allowed CARLsim states:: SETUP_STATE

Parameters

[in]	grpId	the group ID
[in]	fileName	name of the binary file to be created. Leave empty for default name "results/nrnstate_{grpName}.dat". Set to string "NULL" to suppress file creation. Default: ""

Returns: NeuronMonitor* pointer to a NeuronMonitor object, which can be used to calculate neuron state statistics or retrieve all spikes in AER format

Note: Only one NeuronMonitor is allowed per group. NeuronMonitor cannot be placed on groups with >100 (LARGE_NEURON_MON_GRP_SIZE) neurons

Attention: Using NeuronMonitor::startRecording and NeuronMonitor::stopRecording might significantly slow down the simulation. It is unwise to use this mechanism to record a large number of neuron state values (voltage, recovery, and total current values) over a long period of time.

See also: ???; ch9s1_matlab_oat

Definition at line 2376 of file carlsim.cpp.

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◆ setNeuronParameters() [1/4]

void setNeuronParameters	(	int	grpId,
		float	izh_a,
		float	izh_a_sd,
		float	izh_b,
		float	izh_b_sd,
		float	izh_c,
		float	izh_c_sd,
		float	izh_d,
		float	izh_d_sd
	)

TODO:: finish docu

Allowed CARLsim states:: CONFIG_STATE

Definition at line 2162 of file carlsim.cpp.

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◆ setNeuronParameters() [2/4]

void setNeuronParameters	(	int	grpId,
		float	izh_a,
		float	izh_b,
		float	izh_c,
		float	izh_d
	)

TODO:: finish docu

Allowed CARLsim states:: CONFIG_STATE

Definition at line 2167 of file carlsim.cpp.

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◆ setNeuronParameters() [3/4]

void setNeuronParameters	(	int	grpId,
		float	izh_C,
		float	izh_k,
		float	izh_vr,
		float	izh_vt,
		float	izh_a,
		float	izh_b,
		float	izh_vpeak,
		float	izh_c,
		float	izh_d
	)

Allowed CARLsim states:: CONFIG

Parameters

[in]	grpId	the group ID of a group for which these settings are applied
[in]	izh_C	Membrane capacitance parameter
[in]	izh_k	Coefficient present in equation for voltage
[in]	izh_vr	Resting membrane potential parameter
[in]	izh_vt	Instantaneous threshold potential parameter
[in]	izh_a	Recovery time constant
[in]	izh_b	Coefficient present in equation for voltage
[in]	izh_vpeak	The spike cutoff value parameter
[in]	izh_c	The voltage reset value parameter
[in]	izh_d	Parameter describing the total amount of outward minus inward currents activated during the spike and affecting the after spike behavior

Since: v3.1

Definition at line 2171 of file carlsim.cpp.

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◆ setNeuronParameters() [4/4]

void setNeuronParameters	(	int	grpId,
		float	izh_C,
		float	izh_C_sd,
		float	izh_k,
		float	izh_k_sd,
		float	izh_vr,
		float	izh_vr_sd,
		float	izh_vt,
		float	izh_vt_sd,
		float	izh_a,
		float	izh_a_sd,
		float	izh_b,
		float	izh_b_sd,
		float	izh_vpeak,
		float	izh_vpeak_sd,
		float	izh_c,
		float	izh_c_sd,
		float	izh_d,
		float	izh_d_sd
	)

Allowed CARLsim states:: CONFIG

Parameters

[in]	grpId	the group ID of a group for which these settings are applied
[in]	izh_C	Membrane capacitance parameter
[in]	izh_C_sd	Standard deviation for membrane capacitance parameter
[in]	izh_k	Coefficient present in equation for voltage
[in]	izh_k_sd	Standard deviation for coefficient present in equation for voltage
[in]	izh_vr	Resting membrane potential parameter
[in]	izh_vr_sd	Standard deviation for resting membrane potential parameter
[in]	izh_vt	Instantaneous threshold potential parameter
[in]	izh_vt_sd	Standard deviation for instantaneous threshold potential parameter
[in]	izh_a	Recovery time constant
[in]	izh_a_sd	Standard deviation for recovery time constant
[in]	izh_b	Coefficient present in equation for voltage
[in]	izh_b_sd	Standard deviation for coefficient present in equation for voltage
[in]	izh_vpeak	The spike cutoff value parameter
[in]	izh_vpeak_sd	Standard deviation for the spike cutoff value parameter
[in]	izh_c	The voltage reset value parameter
[in]	izh_c_sd	Standard deviation for the voltage reset value parameter
[in]	izh_d	Parameter describing the total amount of outward minus inward currents activated during the spike and affecting the after spike behavior
[in]	izh_d_sd	Standard deviation for the parameter describing the total amount of outward minus inward currents activated during the spike and affecting the after spike behavior

Since: v3.1

Definition at line 2177 of file carlsim.cpp.

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◆ setNeuronParametersLIF()

void setNeuronParametersLIF	(	int	grpId,
		int	tau_m,
		int	tau_ref = `0`,
		float	vTh = `1.0f`,
		float	vReset = `0.0f`,
		const RangeRmem &	rMem = `RangeRmem(1.0f)`
	)

Parameters

[in]	grpId	group ID
[in]	tau_m	Membrane time constant in ms (controls decay/leak)
[in]	tau_ref	absolute refractory period in ms
[in]	vTh	Threshold voltage for firing (must be > vReset)
[in]	vReset	Membrane potential resets to this value immediately after spike
[in]	rMem	Range of total membrane resistance of the neuron group, uniformly distributed or fixed for the whole group

Allowed CARLsim states:: CONFIG_STATE

Definition at line 2187 of file carlsim.cpp.

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◆ setNM4STP()

void setNM4STP	(	int	grpId,
		float	wSTP_U[],
		float	wSTP_tau_u[],
		float	wSTP_tau_x[]
	)

Uses Normalizing Weight Vectors Hint: Normalizing refers to 6 element array w1-4 for NMs (DA,..,NE), norm + boost, where boost is the Hill coefficient, default 2 -> 80% CARLsim6 implements the short-term plasticity model targeted STDP by the 4 neuro modulators for CARLsim6

WP: requires the STP was set to true utilizing the former interface

U' = U * w / (1 + w)

w = 0 => U' = U w -> oo => U' -> U = (U + w*U) / (1 + w)

Hill-.. -> use the boost param as Hill-Koefficient

U'_k = U * w^k / (1 + w^k) => for k->00 : U' ~ w U, for k = 0 = U' = U

Workaournd: use boost factor, to retail valid ranges, NM -> [a,b] => U' = U + w*[b-a] : U' 0..1 over all goal: if nm is -> then it shall behave as former, whenn nm is at max, then nm shall determinate it

U'(nm) = U, nm = 0 U'(nm) –> wU, nm = nm_max

U' = U * (w/1+w)^k, k = nm_max / ...

e^0 = 1

U' = U e^w, w = 0 U' = U w = U w e^w / e^w

Adopted from Source: Farzan Nadim / Dirk Bucher (2014)

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in]	grpId	pre-synaptic group ID
[in]	STP_U[]	normalizing weight vector for increment of u induced by a spike
[in]	STP_tau_u[]	normalizing weight vector for decay constant of u (tau_F)
[in]	STP_tau_x[]	normalizing weight vector for decay constant of x (tau_D)

Definition at line 2273 of file carlsim.cpp.

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◆ setNM4weighted()

void setNM4weighted	(	int	grpId,
		IcalcType	type,
		float	wDA = `1.f`,
		float	w5HT = `1.f`,
		float	wACh = `1.f`,
		float	wNE = `1.f`,
		float	wNorm = `4.f`,
		float	wBase = `1.0f`
	)

This generalizes the concepts given in Krichmar 2012,2013 and Av 2015 and B 2019 by .. considering all possible NM level in a target neuron group and .. with factor e.g. for Krichmar 2021 type=ACNE12, wACh and wNE is .5f, wNorm=1.f, and .0f otherwise.

Definition at line 2140 of file carlsim.cpp.

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◆ setSpikeGenerator()

void setSpikeGenerator	(	int	grpId,
		SpikeGenerator *	spikeGenFunc
	)

A SpikeCounter keeps track of all spikes per neuron for a certain time period (recordDur). After that, the spike buffers get reset to zero number of spikes.

This function works for Izhikevich neurons as well as Spike Generators.

The recording time can be set to any x number of ms, so that after x ms the spike counts will be reset to zero. If x==-1, then the spike counts will never be reset (should only overflow after 97 days of sim). Also, spike counts can be manually reset at any time by calling CARLsim::resetSpikeCounter(grpId);

At any point in time (during RUN_STATE), CARLsim::getSpikeCounter can be called to get an integer array that contains the number of spikes for each neuron in the group.

There can be only SpikeCounter per group. However, a group can have both a SpikeMonitor and a SpikeCounter.

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in]	grpId	the group for which you want to enable a SpikeCounter
[in]	recordDur	number of ms for which to record spike numbers. Spike numbers will be reset to zero after this. Set frameDur to -1 to never reset spike counts. Default: -1.

See also: CARLsim::getSpikeCounter; CARLsim::resetSpikeCounter

Associates a SpikeGenerator object with a group

A custom SpikeGenerator object can be used to allow for more fine-grained control overs spike generation by specifying individual spike times for each neuron in a group.

In order to specify spike times, a new class must be defined first that derives from the SpikeGenerator class and implements the virtual method SpikeGenerator::nextSpikeTime. Then, in order for a custom SpikeGenerator to be associated with a SpikeGenerator group, CARLsim::setSpikeGenerator must be called on the group in CONFIG_STATE:.

A number of interesting Spike Generators is provided in the tools/spike_generators directory, such as PeriodicSpikeGenerator, SpikeGeneratorFromVector, and SpikeGeneratorFromFile.

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in]	grpId	the group with which to associate a SpikeGenerator object
[in]	spikeGenFunc	pointer to a custom SpikeGenerator object

See also: 6.1 Generating Spikes

Definition at line 2366 of file carlsim.cpp.

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◆ setSpikeMonitor()

SpikeMonitor * setSpikeMonitor	(	int	grpId,
		const std::string &	fileName
	)

To retrieve outputs, a spike-monitoring callback mechanism is used. This mechanism allows the user to calculate basic statistics, store spike trains, or perform more complicated output monitoring. Spike monitors are registered for a group and are called automatically by the simulator every second. Similar to an address event representation (AER), the spike monitor indicates which neurons spiked by using the neuron ID within a group (0-indexed) and the time of the spike. Only one spike monitor is allowed per group.

CARLsim supports two different recording mechanisms: Recording to a spike file (binary) and recording to a SpikeMonitor object. The former is useful for off-line analysis of activity (e.g., using Chapter 9: MATLAB Offline Analysis Toolbox (OAT)). The latter is useful to calculate different spike metrics and statistics on-line, such as mean firing rate and standard deviation, or the number of neurons whose firing rate lies in a certain interval.

A file name can be specified via variable fileName (make sure the specified directory exists). The easiest way is to set fileName to string "DEFAULT", in which case a default file name will be created in the results directory: "results/spk_{group name}.dat", where group name is the name assigned to the group at initialization (can be retrieved via getGroupName). If no binary file shall be created, set fileName equal to the string "NULL".

The function returns a pointer to a SpikeMonitor object, which can be used to calculate spike statistics (such group firing rate, number of silent neurons, etc.) or retrieve all spikes from a particular time window. See 7.1 Spike Monitor of the User Guide for more information on how to use SpikeMonitor.

If you call setSpikeMonitor twice on the same group, the same SpikeMonitor pointer will be returned, and the name of the spike file will be updated. This is the same as calling SpikeMonitor::setLogFile directly, and allows you to redirect the spike file stream mid-simulation (see 7.1.3 Redirecting File Streams).

Allowed CARLsim states:: SETUP_STATE

Parameters

[in]	grpId	the group ID
[in]	fileName	name of the binary file to be created. Leave empty for default name "results/spk_{grpName}.dat". Set to string "NULL" to suppress file creation. Default: ""

Returns: SpikeMonitor* pointer to a SpikeMonitor object, which can be used to calculate spike statistics (such as group firing rate, number of silent neurons, etc.) or retrieve all spikes in AER format

Note: Only one SpikeMonitor is allowed per group.

Attention: Using SpikeMonitor::startRecording and SpikeMonitor::stopRecording might significantly slow down the simulation. It is unwise to use this mechanism to record a large number of spikes over a long period of time.

See also: ch7s1_spike_monitor; ch9s1_matlab_oat

Definition at line 2371 of file carlsim.cpp.

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◆ setSpikeRate()

void setSpikeRate	(	int	grpId,
		PoissonRate *	spikeRate,
		int	refPeriod = `1`
	)

TODO:: finish docu

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Parameters

[in]	grpId	group ID
[in]	spikeRate	pointer to PoissonRate object
[in]	refPeriod	refactory period (ms). Default: 1ms.

Note: This method can only be applied to SpikeGenerator groups.; setSpikeRate will not take over ownership of PoissonRate. In other words, if you allocate the PoissonRate object on the heap, you are responsible for correctly deallocating it.

Attention: Make sure to reset spike rate after use (i.e., for the next call to runNetwork), otherwise the rate will keep getting applied to the group.

See also: setExternalCurrent; setSpikeGenerator

Definition at line 2381 of file carlsim.cpp.

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◆ setSTDP() [1/2]

void setSTDP	(	int	preGrpId,
		int	postGrpId,
		bool	isSet
	)

Set STDP parameters. Do not use this function, it is deprecated.

See also: setESTDP

Deprecated:: For clearness, do not use default STDP settings.

Since: v2.1

Definition at line 2217 of file carlsim.cpp.

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◆ setSTDP() [2/2]

void setSTDP	(	int	preGrpId,
		int	postGrpId,
		bool	isSet,
		STDPType	type,
		float	alphaPlus,
		float	tauPlus,
		float	alphaMinus,
		float	tauMinus
	)

Set STDP parameters. Do not use this function, it is deprecated.

See also: setESTDP

Deprecated:: For clearness, please use CARLsim::setESTDP() with E-STDP curve struct.

Since: v2.1

Definition at line 2220 of file carlsim.cpp.

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◆ setSTP() [1/2]

void setSTP	(	int	grpId,
		bool	isSet,
		float	STP_U,
		float	STP_tau_u,
		float	STP_tau_x
	)

CARLsim implements the short-term plasticity model of (Tsodyks & Markram, 1998; Mongillo, Barak, & Tsodyks, 2008)

$\begin{eqnarray} \frac{du}{dt} & = & \frac{-u}{STP\_tau\_u} + STP\_U (1-u^-) \delta(t-t_{spk}) \\ \frac{dx}{dt} & = & \frac{1-x}{STP\_tau\_x} - u^+ x^- \delta(t-t_{spk}) \\ \frac{dI}{dt} & = & \frac{-I}{\tau_S} + A u^+ x- \delta(t-t_{spk}) \end{eqnarray}$

where u- means value of variable u right before spike update, and x+ means value of variable x right after the spike update, and A is the synaptic weight. The STD effect is modeled by a normalized variable (0<=x<=1), denoting the fraction of resources that remain available after neurotransmitter depletion. The STF effect is modeled by a utilization parameter u, representing the fraction of available resources ready for use (release probability). Following a spike, (i) u increases due to spike-induced calcium influx to the presynaptic terminal, after which (ii) a fraction u of available resources is consumed to produce the post-synaptic current. Between spikes, u decays back to zero with time constant STP_tau_u (tau_F), and x recovers to value one with time constant STP_tau_x (tau_D).

Source: Misha Tsodyks and Si Wu (2013) Short-term synaptic plasticity. Scholarpedia, 8(10):3153., rev #136920

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in]	grpId	pre-synaptic group ID
[in]	isSet	a flag whether to enable/disable STP
[in]	STP_U	increment of u induced by a spike
[in]	STP_tau_u	decay constant of u (tau_F)
[in]	STP_tau_x	decay constant of x (tau_D)

Note: STP will be applied to all outgoing synapses of all neurons in this group.; All outgoing synapses of a certain (pre-synaptic) neuron share the resources of that same neuron.

Definition at line 2264 of file carlsim.cpp.

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◆ setSTP() [2/2]

void setSTP	(	int	grpId,
		bool	isSet
	)

This function enables/disables STP on a specific pre-synaptic group and assign default values to all STP parameters. The default parameters for an excitatory neuron are U=0.45, tau_u=50.0, tau_f=750.0 (depressive). The default parameters for an inhibitory neuron are U=0.15, tau_u=750.0, tau_f=50.0 (facilitative).

Source: Misha Tsodyks and Si Wu (2013) Short-term synaptic plasticity. Scholarpedia, 8(10):3153., rev #136920

These default values can be overridden using setDefaultSTPparams.

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in]	grpId	pre-synaptic group ID
[in]	isSet	a flag whether to enable/disable STP

Note: STP will be applied to all outgoing synapses of all neurons in this group.; All outgoing synapses of a certain (pre-synaptic) neuron share the resources of that same neuron.

See also: setDefaultSTPparams; setSTP(int, bool, float, float, float)

Since: v3.0

Definition at line 2269 of file carlsim.cpp.

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◆ setupNetwork()

void setupNetwork ( )

Allowed CARLsim states:: CONFIG_STATE. Will make CARLsim state switch from CONFIG_STATE to SETUP_STATE.

Definition at line 2293 of file carlsim.cpp.

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◆ setupNetworkMT()

void setupNetworkMT ( )

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◆ setWeight()

void setWeight	(	short int	connId,
		int	neurIdPre,
		int	neurIdPost,
		float	weight,
		bool	updateWeightRange = `false`
	)

This method sets the weight value of the synapse that belongs to connection connId and connects pre-synaptic neuron neurIdPre to post-synaptic neuron neurIdPost. Neuron IDs should be zero-indexed, so that the first neuron in the group has ID 0.

If a weight value is specified that lies outside the range [minWt,maxWt] of this connection, the range will be updated accordingly if the flag updateWeightRange is set to true. If the flag is set to false, then the specified weight value will be corrected to lie on the boundary (either minWt or maxWt).

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Parameters

[in]	connId	the connection ID to manipulate
[in]	neurIdPre	pre-synaptic neuron ID (zero-indexed)
[in]	neurIdPost	post-synaptic neuron ID (zero-indexed)
[in]	weight	the weight value to set for this synapse
[in]	updateWeightRange	a flag specifying what to do when the specified weight lies outside the range [minWt,maxWt]. Set to true to update the range accordingly. Set to false to adjust the weight to be either minWt or maxWt. Default: false.

Note: Neuron IDs should be zero-indexed (first neuron in the group should have ID 0).; A weight cannot drop below zero, no matter what.

Attention: Make sure this function is called on a synapse that actually exists!

See also: biasWeights; scaleWeights

Since: v3.0

Definition at line 2386 of file carlsim.cpp.

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◆ setWeightAndWeightChangeUpdate()

void setWeightAndWeightChangeUpdate	(	UpdateInterval	wtANDwtChangeUpdateInterval,
		bool	enableWtChangeDecay,
		float	wtChangeDecay = `0.9f`
	)

Allowed CARLsim states:: CONFIG_STATE

Parameters

[in]	wtANDwtChangeUpdateInterval	the interval between two wt (weight) and wtChange (weight change) update.
[in]	enableWtChangeDecay	enable weight change decay
[in]	wtChangeDecay	the decay ratio of weight change (wtChange)

Definition at line 2280 of file carlsim.cpp.

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◆ startTesting()

void startTesting ( bool updateWeights = true )

This function can be used to temporarily disable all weight updates (such as from STDP or homeostasis) in the network. This can be useful in an experimental setting that consists of 1) a training phase, where STDP or other plasticity mechanisms learn some input stimulus set, and 2) a testing phase, where the learned synaptic weights are evaluated (without making any further weight modifications) by presenting some test stimuli.

An optional parameter specifies whether the accumulated weight updates so far should be applied to the weights before entering the testing phase. Recall that although weight changes are accumulated every millisecond, they are only applied to the weights every so often (see CARLsim::setWeightAndWeightChangeUpdate). If updateWeights is set to true, then the accumulated weight changes will be applied to the weights, even if CARLsim::startTesting is called off the weight update grid.

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Parameters

[in] updateWeights whether to apply the accumulated weight changes before entering the testing phase

Note: Calling this function on a simulation with no plastic synapses will have no effect.

See also: CARLsim::stopTesting

Since: v3.1

Definition at line 2391 of file carlsim.cpp.

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◆ stopTesting()

void stopTesting ( )

This function can be used to exit a testing phase (in which all weight changes were disabled), after which weight modifications are possible again. This can be useful in an experimental setting with multiple training phases followed by testing phases.

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Note: Calling this function on a simulation with no plastic synapses will have no effect.

See also: CARLsim::startTesting

Since: v3.1

Definition at line 2394 of file carlsim.cpp.

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◆ updateDelays()

bool updateDelays	(	int	gGrpIdPre,
		int	gGrpIdPost,
		std::vector< std::tuple< int, int, uint8_t >>	connDelays
	)

The connection delays to be updated are passed as a vector of tuples (neuronIdPre, neuronIdPost, delay). The neuron ids reference the pre- and post-synaptic neuron group.

Allowed CARLsim states:: SETUP_STATE, RUN_STATE

Parameters

[in]	gGrpIdPre	the global ID of the pre-synaptic group
[in]	gGrpIdPost	the global ID of the post-synaptic group
[in]	connDelays	the new delays as tuples (neuronIdPre, neuronIdPost, delay)

Definition at line 2305 of file carlsim.cpp.

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

Classes

Public Member Functions

Static Public Member Functions

Detailed Description

Constructor & Destructor Documentation

◆ CARLsim()

◆ ~CARLsim()

Member Function Documentation

◆ biasWeights()

◆ connect() [1/3]

◆ connect() [2/3]

◆ connect() [3/3]

◆ connectCompartments()

◆ createGroup() [1/2]

◆ createGroup() [2/2]

◆ createGroupLIF() [1/2]

◆ createGroupLIF() [2/2]

◆ createSpikeGeneratorGroup() [1/2]

◆ createSpikeGeneratorGroup() [2/2]

◆ cudaDeviceCount()

◆ cudaDeviceDescription()

◆ findWavefrontPath()

◆ getCARLsimState()

◆ getConductanceAMPA()

◆ getConductanceConfig() [1/2]

◆ getConductanceConfig() [2/2]

◆ getConductanceGABAa()

◆ getConductanceGABAb()

◆ getConductanceNMDA()

◆ getConnSTDPInfo()

◆ getDelayRange()

◆ getDelays()

◆ getGroupEndNeuronId()

◆ getGroupGrid3D()

◆ getGroupId()

◆ getGroupName()

◆ getGroupNeuromodulatorInfo()

◆ getGroupNumNeurons()

◆ getGroupStartNeuronId()

◆ getIcalcType()

◆ getLogFpDeb()

◆ getLogFpErr()

◆ getLogFpInf()

◆ getLogFpLog()

◆ getMaxNumCompConnections()

◆ getNeuronId()

◆ getNeuronLocation3D() [1/2]

◆ getNeuronLocation3D() [2/2]

◆ getNumConnections()

◆ getNumGroups()

◆ getNumNeurons()

◆ getNumNeuronsGen()

◆ getNumNeuronsGenExc()

◆ getNumNeuronsGenInh()

◆ getNumNeuronsReg()

◆ getNumNeuronsRegExc()

◆ getNumNeuronsRegInh()

◆ getNumSynapses()

◆ getNumSynapticConnections()

◆ getSimTime()

◆ getSimTimeMsec()

◆ getSimTimeSec()

◆ getSpikeMonitor()

◆ getWeightRange()

◆ isConnectionPlastic()

◆ isExcitatoryGroup()

◆ isGroupWith()

◆ isGroupWithCOBA()

◆ isGroupWithCUBA()

◆ isGroupWithHomeostasis()

◆ isInhibitoryGroup()

◆ isPoissonGroup()

◆ isSimulationWithCOBA()

◆ isSimulationWithCUBA()

◆ loadSimulation()

◆ printEntrails()

◆ runNetwork()

◆ saveSimulation()

◆ scaleWeights()

◆ setACNE12()