auryn::SymmetricSTDPConnection Class Reference

Implements a symmetric STDP window with an optional presynaptic offset as used for inhibitory plasticity in Vogels et al. 2011. More...

#include <SymmetricSTDPConnection.h>

Inheritance diagram for auryn::SymmetricSTDPConnection:

Collaboration diagram for auryn::SymmetricSTDPConnection:

Public Member Functions
AurynWeight	dw_pre (NeuronID post)
AurynWeight	dw_post (NeuronID pre)
void	propagate_forward ()
void	propagate_backward ()
	SymmetricSTDPConnection (SpikingGroup *source, NeuronGroup *destination, AurynWeight weight, AurynFloat sparseness=0.05, AurynFloat eta=1e-3, AurynFloat kappa=5., AurynFloat tau_stdp=20e-3, AurynWeight maxweight=10., TransmitterType transmitter=GABA, string name="SymmetricSTDPConnection")
	SymmetricSTDPConnection (SpikingGroup *source, NeuronGroup *destination, const char *filename, AurynFloat eta=1e-3, AurynFloat kappa=5., AurynFloat tau_stdp=20e-3, AurynWeight maxweight=10, TransmitterType transmitter=GABA)
virtual	~SymmetricSTDPConnection ()
void	init (AurynFloat eta, AurynFloat kappa, AurynFloat tau_stdp, AurynWeight maxweight)
void	free ()
virtual void	propagate ()
	Internally used propagate method. More...
Public Member Functions inherited from auryn::DuplexConnection
	DuplexConnection (const char *filename)
	DuplexConnection (NeuronID rows, NeuronID cols)
	DuplexConnection (SpikingGroup *source, NeuronGroup *destination, TransmitterType transmitter=GLUT)
	DuplexConnection (SpikingGroup *source, NeuronGroup *destination, const char *filename, TransmitterType transmitter=GLUT)
	DuplexConnection (SpikingGroup *source, NeuronGroup *destination, AurynWeight weight, AurynFloat sparseness=0.05, TransmitterType transmitter=GLUT, std::string name="DuplexConnection")
virtual	~DuplexConnection ()
virtual void	finalize ()
	Finalizes connection after random or manual initialization of the weights. More...
void	prune ()
	Prune weight matrices. More...
Public Member Functions inherited from auryn::SparseConnection
	SparseConnection ()
	Empty constructor which should not be used – TODO should be deprecated at some point. More...
	SparseConnection (const char *filename)
	Load from wmat file constructor which should not be used – TODO should be deprecated at some point. More...
	SparseConnection (NeuronID rows, NeuronID cols)
	Deprecated constructor for manual filling. More...
	SparseConnection (SpikingGroup *source, NeuronGroup *destination, const char *filename, TransmitterType transmitter=GLUT)
	Deprecated constructor for loading from file. More...
	SparseConnection (SpikingGroup *source, NeuronGroup *destination, TransmitterType transmitter=GLUT, string name="SparseConnection")
	Constructor for manual filling. More...
	SparseConnection (SpikingGroup *source, NeuronGroup *destination, AurynWeight weight, AurynDouble sparseness=0.05, TransmitterType transmitter=GLUT, string name="SparseConnection")
	Default constructor which sets up a random sparse matrix with fixed weight between the source and destination group. More...
	SparseConnection (SpikingGroup *source, NeuronGroup *destination, SparseConnection *con, string name="SparseConnection")
	This constructor tries to clone a connection by guessing all parameters except source and destination from another connection instance. More...
	SparseConnection (SpikingGroup *source, NeuronGroup *destination, AurynWeight weight, AurynDouble sparseness, NeuronID lo_row, NeuronID hi_row, NeuronID lo_col, NeuronID hi_col, TransmitterType transmitter=GLUT)
	Sparse block constructor. More...
virtual	~SparseConnection ()
	The default destructor. More...
void	allocate_manually (AurynLong expected_size)
	Is used whenever memory has to be allocated manually. Automatically adjusts for number of ranks and for security margin. More...
AurynLong	estimate_required_nonzero_entires (AurynLong nonzero, double sigma=5.)
	This function estimates the required size of the nonzero entry buffer. More...
void	seed (NeuronID randomseed)
	This function seeds the pseudo random number generator for all random fill operatios. More...
virtual AurynWeight	get (NeuronID i, NeuronID j)
	Returns weight value of a given element if it exists. More...
virtual AurynWeight *	get_ptr (NeuronID i, NeuronID j)
	Returns pointer to given weight element if it exists. Returns NULL if element does not exist. More...
virtual AurynWeight	get_data (NeuronID i)
	Returns weight value of a given element referenced by index in the data array. More...
virtual void	set_data (NeuronID i, AurynWeight value)
	Sets weight value of a given element referenced by its index in the data array. More...
virtual void	set (NeuronID i, NeuronID j, AurynWeight value)
	Sets a single connection to value if it exists. More...
virtual void	set (std::vector< neuron_pair > element_list, AurynWeight value)
	Sets a list of connection to value if they exists. More...
void	random_data (AurynWeight mean, AurynWeight sigma)
	Synonym for random_data. More...
void	random_data_normal (AurynWeight mean, AurynWeight sigma)
	Set weights of all existing connections randomly using a normal distrubtion. More...
void	random_data_lognormal (AurynWeight m, AurynWeight s)
	Set weights of all existing connections randomly using a lognormal distribution. More...
void	init_random_binary (AurynFloat prob=0.5, AurynWeight wlo=0.0, AurynWeight whi=1.0)
	Initialize with random binary at wlo and whi. More...
void	random_col_data (AurynWeight mean, AurynWeight sigma)
	Sets weights in cols to the same value drewn from a Gaussian distribution. More...
void	set_block (NeuronID lo_row, NeuronID hi_row, NeuronID lo_col, NeuronID hi_col, AurynWeight weight)
	Sets all weights of existing connections in a block spanned by the first 4 parameters to the value given. More...
void	scale_block (NeuronID lo_row, NeuronID hi_row, NeuronID lo_col, NeuronID hi_col, AurynWeight alpha)
	Scale all weights of existing connections in a block spanned by the first 4 parameters to the value given. More...
virtual void	set_all (AurynWeight weight)
	Sets all weights of existing connections to the given value. More...
virtual void	scale_all (AurynFloat value)
	Scales all weights in the weight matrix with the given value. More...
virtual void	clip (AurynWeight lo, AurynWeight hi)
	Clip weights. More...
void	set_upper_triangular (AurynWeight weight)
	Sets weights in a upper triangular matrix. More...
virtual void	sparse_set_data (AurynDouble sparseness, AurynWeight value)
	Sets a sparse random subset of connection elements wight the given value. More...
void	connect_random (AurynWeight weight=1.0, AurynDouble sparseness=0.05, bool skip_diag=false)
	Connect src and dst SpikingGroup and NeuronGroup randomly with given sparseness. More...
void	connect_block_random (AurynWeight weight, AurynDouble sparseness, NeuronID lo_row, NeuronID hi_row, NeuronID lo_col, NeuronID hi_col, bool skip_diag=false)
	Underlying sparse fill method. More...
bool	push_back (NeuronID i, NeuronID j, AurynWeight weight)
	Pushes a single element to the ComplexMatrix. More...
AurynLong	get_nonzero ()
	Returns number of nonzero elements in this SparseConnection. More...
void	put_pattern (type_pattern *pattern, AurynWeight strength, bool overwrite)
	Puts cell assembly to existing sparse weights. More...
void	put_pattern (type_pattern *pattern1, type_pattern *pattern2, AurynWeight strength, bool overwrite)
	Puts cell assembly or synfire pattern to existing sparse weights. More...
void	load_patterns (string filename, AurynWeight strength, int nb_max_patterns=10000, bool overwrite=false, bool chainmode=false)
	Reads first n patterns from a .pat file and adds them as Hebbian assemblies onto an existing weight matrix. More...
void	load_pre_post_patterns (std::string pre_file, std::string post_file, AurynWeight strength, int nb_max_patterns=10000, bool overwrite=false)
	Reads patterns from two files and connects them. More...
void	sanity_check ()
	Quick an dirty function that checks if all units on the local rank are connected. More...
virtual AurynDouble	sum ()
	Computes sum of all weight elements in the Connection. More...
virtual void	stats (AurynDouble &mean, AurynDouble &std)
	Computes mean and variance of weights in default weight matrix. More...
virtual void	stats (AurynDouble &mean, AurynDouble &std, NeuronID zid)
	Computes mean and variance of weights for matrix state zid. More...
bool	write_to_file (ForwardMatrix *m, string filename)
	Writes rank specific weight matrix on the same rank to a file. More...
virtual bool	write_to_file (string filename)
	Writes rank specific default weight matrix on the same rank to a file. More...
virtual bool	load_from_complete_file (string filename)
	Loads weight matrix from a single file. More...
virtual bool	load_from_file (string filename)
	Loads weight matrix from Matrix Market (wmat) file. More...
bool	load_from_file (ForwardMatrix *m, string filename, AurynLong data_size=0)
	Loads weight matrix from Matrix Market (wmat) file to specified weight matrix. More...
virtual void	set_min_weight (AurynWeight minimum_weight)
	Sets minimum weight (for plastic connections). More...
AurynWeight	get_min_weight ()
	Gets minimum weight (for plastic connections). More...
virtual void	set_max_weight (AurynWeight maximum_weight)
	Sets maximum weight (for plastic connections). More...
AurynWeight	get_max_weight ()
	Gets maximum weight (for plastic connections). More...
std::vector< neuron_pair >	get_block (NeuronID lo_row, NeuronID hi_row, NeuronID lo_col, NeuronID hi_col)
	Returns a vector of ConnectionsID of a block specified by the arguments. More...
std::vector< neuron_pair >	get_post_partners (NeuronID i)
	Returns a vector of ConnectionsID of postsynaptic parterns of neuron i. More...
std::vector< neuron_pair >	get_pre_partners (NeuronID j)
	Returns a vector of ConnectionsID of presynaptic parterns of neuron i. More...
Public Member Functions inherited from auryn::Connection
	Connection ()
	Connection (NeuronID rows, NeuronID cols)
	Connection (SpikingGroup *source, NeuronGroup *destination, TransmitterType transmitter=GLUT, std::string name="Connection")
virtual	~Connection ()
void	set_size (NeuronID i, NeuronID j)
void	set_name (std::string name)
	Set name of connection. More...
std::string	get_name ()
	Returns name of connection. More...
std::string	get_file_name ()
	Extracts the class name of the connection from the file name. More...
std::string	get_log_name ()
	Returns a string which is the combination of file and connection name for logging. More...
AurynStateVector *	get_target_vector ()
	Returns target state vector if one is defined. More...
NeuronID	get_m_rows ()
	Get number of rows (presynaptic) in connection. More...
NeuronID	get_n_cols ()
	Get number of columns (postsynaptic) in connection. More...
TransmitterType	get_transmitter ()
	Returns transmitter type. More...
void	set_target (AurynWeight *ptr)
	Sets target state of this connection directly via a pointer. More...
void	set_target (AurynStateVector *ptr)
	Sets target state of this connection directly via a StateVector. More...
void	set_receptor (AurynStateVector *ptr)
	Same as set_target. More...
void	set_transmitter (AurynStateVector *ptr)
	Same as set_target. More...
void	set_transmitter (TransmitterType transmitter)
	Sets target state of this connection for a given receptor as one of Auryn's default transmitter types. More...
void	set_receptor (string state_name)
	Sets target state of this connection directly the name of a state vector. More...
void	set_target (string state_name)
	Same as set_receptor. More...
void	set_transmitter (string state_name)
	Same as set_receptor, but DEPRECATED. More...
void	set_source (SpikingGroup *source)
	Sets source SpikingGroup of this connection. More...
SpikingGroup *	get_source ()
	Returns pointer to the presynaptic group. More...
void	set_destination (NeuronGroup *source)
	Sets destination SpikingGroup of this connection. More...
NeuronGroup *	get_destination ()
	Returns pointer to the postsynaptic group. More...
virtual void	evolve ()
	Evolve method to update internal connection state. Called by System run method. More...
void	conditional_propagate ()
	DEPRECATED. (Such connections should not be registered in the first place) Calls propagate only if the postsynaptic NeuronGroup exists on the local rank. More...
Trace *	get_pre_trace (const AurynDouble tau)
	Returns a pointer to a presynaptic trace object. More...
Trace *	get_post_trace (const AurynDouble tau)
	Returns a pointer to a postsynaptic trace object. More...
Trace *	get_post_state_trace (const string state_name, const AurynDouble tau, const AurynDouble jump_size=0.0)
	Returns a pointer to a postsynaptic state trace object. More...
void	transmit (const NeuronID id, const AurynWeight amount)
	Default way to transmit a spike to a postsynaptic partner. More...
void	targeted_transmit (SpikingGroup *target_group, AurynStateVector *target_state, const NeuronID id, const AurynWeight amount)
	Transmits a spike to a given target group and state. More...
void	safe_transmit (NeuronID id, AurynWeight amount)
	Same as transmit but first checks if the target neuron exists and avoids segfaults that way (but it's also slower). More...
SpikeContainer *	get_pre_spikes ()
	Supplies pointer to SpikeContainer of all presynaptic spikes. More...
SpikeContainer *	get_post_spikes ()
	Returns pointer to SpikeContainer for postsynaptic spikes on this node. More...
void	add_number_of_spike_attributes (int x)
	Set up spike delay to accomodate x additional spike attributes. More...
AurynFloat	get_spike_attribute (const NeuronID i, const int attribute_id=0)
	Returns spike attribute belonging to the spike at position i in the get_spikes() SpikeContainer. More...

Public Attributes
AurynFloat	learning_rate
AurynFloat	target
AurynFloat	kappa_fudge
Trace *	tr_pre
Trace *	tr_post
bool	stdp_active
Public Attributes inherited from auryn::DuplexConnection
ForwardMatrix *	fwd
BackwardMatrix *	bkw
Public Attributes inherited from auryn::SparseConnection
bool	patterns_ignore_gamma
	Switch that toggles for the load_patterns function whether or not to use the intensity (gamma) value. Default is false. More...
NeuronID	patterns_every_pre
	The every_pre parameter allows to skip presynaptically over pattern IDs when loading patterns. Default is 1. This can be useful to when loading patterns into the exc->inh connections and there significantly less inhibitory cells than exc ones. More...
NeuronID	patterns_every_post
	The every_post parameter allows to skip postsynaptically over pattern IDs when loading patterns. Default is 1. This can be useful to when loading patterns into the exc->inh connections and there significantly less inhibitory cells than exc ones. More...
bool	wrap_patterns
	Switch that toggles the behavior when loading a pattern to wrap neuron IDs back onto existing cells via the modulo function. More...
ForwardMatrix *	w
	A pointer that points per default to the ComplexMatrix that stores the connectinos. More...
Public Attributes inherited from auryn::Connection
SpikingGroup *	src
	Pointer to the source group of this connection. More...
NeuronGroup *	dst
	Pointer to the destination group of this connection. More...

Additional Inherited Members
Protected Member Functions inherited from auryn::DuplexConnection
void	compute_reverse_matrix (int z=0)
Protected Member Functions inherited from auryn::SparseConnection
void	virtual_serialize (boost::archive::binary_oarchive &ar, const unsigned int version)
void	virtual_serialize (boost::archive::binary_iarchive &ar, const unsigned int version)
void	free ()
void	allocate (AurynLong bufsize)
std::vector< type_pattern >	load_pattern_file (string filename, int nb_max_patterns)
	Reads patterns from a .pat file and returns a vector with the patterns. More...
Protected Member Functions inherited from auryn::Connection
void	init (TransmitterType transmitter=GLUT)
Protected Attributes inherited from auryn::SparseConnection
AurynWeight	wmin
AurynWeight	wmax
bool	skip_diagonal
Protected Attributes inherited from auryn::Connection
TransmitterType	trans
AurynStateVector *	target_state_vector
AurynFloat *	target
	A more direct reference on the first element of the target_state_vector. More...
NeuronID	number_of_spike_attributes
	Number of spike attributes to expect with each spike transmitted through this connection. More...
NeuronID	spike_attribute_offset
	Stores spike attribute offset in attribute array. More...
Static Protected Attributes inherited from auryn::SparseConnection
static boost::mt19937	sparse_connection_gen = boost::mt19937()

Detailed Description

Implements a symmetric STDP window with an optional presynaptic offset as used for inhibitory plasticity in Vogels et al. 2011.

This class implements a plastic connection object implementing the plasticity rule we used in Vogels et al. 2011 for the inhibitory plasticity.

Constructor & Destructor Documentation

SymmetricSTDPConnection() [1/2]

SymmetricSTDPConnection::SymmetricSTDPConnection	(	SpikingGroup *	source,
		NeuronGroup *	destination,
		AurynWeight	weight,
		AurynFloat	sparseness = 0.05,
		AurynFloat	eta = 1e-3,
		AurynFloat	kappa = 5.,
		AurynFloat	tau_stdp = 20e-3,
		AurynWeight	maxweight = 10.,
		TransmitterType	transmitter = GABA,
		std::string	name = "SymmetricSTDPConnection"
	)

Constructor to create a random sparse connection object and set up plasticity.

Parameters

source	the source group from where spikes are coming.
destination	the destination group where spikes are going.
weight	the initial weight of all connections.
sparseness	the connection probability for the sparse random set-up of the connections.
eta	the learning rate parameter.
kappa	the target rate paramter (alpha in the original publication).
tau_stdp	the size of one side of the STDP window.
maxweight	the maxium allowed weight.
transmitter	the transmitter type of the connection - by default GABA for inhibitory connection.
name	a meaningful name of the connection which will appear in debug output.

: DuplexConnection(source, destination, weight, sparseness, transmitter, name)
{
        init(eta , kappa, tau_stdp, maxweight);
}

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SymmetricSTDPConnection() [2/2]

SymmetricSTDPConnection::SymmetricSTDPConnection	(	SpikingGroup *	source,
		NeuronGroup *	destination,
		const char *	filename,
		AurynFloat	eta = 1e-3,
		AurynFloat	kappa = 5.,
		AurynFloat	tau_stdp = 20e-3,
		AurynWeight	maxweight = 10,
		TransmitterType	transmitter = GABA
	)

Constructor that creates the connection directly from a wmat file.

Parameters

source	the source group from where spikes are coming.
destination	the destination group where spikes are going.
filename	the filename of a wmat file to build he connection from
eta	the learning rate parameter.
kappa	the target rate paramter (alpha in the original publication).
tau_stdp	the size of one side of the STDP window.
maxweight	the maxium allowed weight.
transmitter	the transmitter type of the connection - by default GABA for inhibitory connection.
name	a meaningful name of the connection which will appear in debug output.

: DuplexConnection(source, destination, filename, transmitter)
{
        init(eta , kappa, tau_stdp, maxweight);
}

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~SymmetricSTDPConnection()

SymmetricSTDPConnection::~SymmetricSTDPConnection ( )

virtual

{
        free();
}

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Member Function Documentation

dw_post()

AurynWeight SymmetricSTDPConnection::dw_post ( NeuronID  pre )

inline

{
        if (stdp_active) {
                double dw = learning_rate*tr_pre->get(pre);
                return dw;
        }
        else return 0.;
}

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dw_pre()

AurynWeight SymmetricSTDPConnection::dw_pre ( NeuronID  post )

inline

{
        if (stdp_active) {
                double dw = learning_rate*(tr_post->get(post)-kappa_fudge);
                return dw;
        }
        else return 0.;
}

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free()

void SymmetricSTDPConnection::free

(

)

{
}

init()

void SymmetricSTDPConnection::init	(	AurynFloat	eta,
		AurynFloat	kappa,
		AurynFloat	tau_stdp,
		AurynWeight	maxweight
	)

{
        set_max_weight(maxweight);
        learning_rate = eta;
        target = kappa;
        kappa_fudge = 2*target*tau_stdp;

        stdp_active = true;
        if ( learning_rate == 0 )
                stdp_active = false;

        set_name("SymmetricSTDPConnection");

        if ( dst->get_post_size() == 0 ) return;

        tr_pre = src->get_pre_trace(tau_stdp);
        tr_post = dst->get_post_trace(tau_stdp);

}

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propagate()

void SymmetricSTDPConnection::propagate ( )

virtual

Internally used propagate method.

This method propagates spikes in the main simulation loop. Should usually not be called directly by the user.

Reimplemented from auryn::SparseConnection.

{
        // propagate
        propagate_forward();
        propagate_backward();
}

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propagate_backward()

void SymmetricSTDPConnection::propagate_backward ( )

inline

{
        NeuronID * ind = bkw->get_row_begin(0); // first element of index array
        AurynWeight ** data = bkw->get_data_begin();
        SpikeContainer::const_iterator spikes_end = dst->get_spikes_immediate()->end();
        for (SpikeContainer::const_iterator spike = dst->get_spikes_immediate()->begin() ; // spike = post_spike
                        spike != spikes_end ; ++spike ) {
                for (NeuronID * c = bkw->get_row_begin(*spike) ; c != bkw->get_row_end(*spike) ; ++c ) {

                        #if defined(CODE_ACTIVATE_PREFETCHING_INTRINSICS) && defined(CODE_USE_SIMD_INSTRUCTIONS_EXPLICITLY)
                        _mm_prefetch((const char *)data[c-ind+2],  _MM_HINT_NTA);
                        #endif
                        
                        *data[c-ind] += dw_post(*c);
                        if (*data[c-ind] > get_max_weight()) {
                                *data[c-ind] = get_max_weight();
                        }
                }
        }
}

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propagate_forward()

void SymmetricSTDPConnection::propagate_forward ( )

inline

{
        NeuronID * ind = w->get_row_begin(0); // first element of index array
        AurynWeight * data = w->get_data_begin();
        AurynWeight value;
        SpikeContainer::const_iterator spikes_end = src->get_spikes()->end();
        // process spikes
        for (SpikeContainer::const_iterator spike = src->get_spikes()->begin() ; // spike = pre_spike
                        spike != spikes_end ; ++spike ) {
                for (NeuronID * c = w->get_row_begin(*spike) ; c != w->get_row_end(*spike) ; ++c ) {
                        value = data[c-ind]; 
                        // dst->tadd( *c , value , transmitter );
                        transmit( *c, value );
                        NeuronID translated_spike = dst->global2rank(*c);
                          data[c-ind] += dw_pre(translated_spike);
                        if (data[c-ind] < get_min_weight()) {
                                data[c-ind] = get_min_weight();
                        }
                }
        }
}

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Member Data Documentation

kappa_fudge

AurynFloat auryn::SymmetricSTDPConnection::kappa_fudge

learning_rate

AurynFloat auryn::SymmetricSTDPConnection::learning_rate

stdp_active

bool auryn::SymmetricSTDPConnection::stdp_active

target

AurynFloat auryn::SymmetricSTDPConnection::target

tr_post

Trace* auryn::SymmetricSTDPConnection::tr_post

tr_pre

Trace* auryn::SymmetricSTDPConnection::tr_pre

---

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

• /home/zenke/auryn/src/auryn/SymmetricSTDPConnection.h
• /home/zenke/auryn/src/auryn/SymmetricSTDPConnection.cpp