Static synapse models

template<typename targetidentifierT>
class BernoulliConnection : public Connection<targetidentifierT>

#include <bernoulli_connection.h>

Name: bernoulli_synapse - Static synapse with stochastic transmission.

Description:

Spikes are transmitted by bernoulli_synapse following a Bernoulli trial with success probability p_transmit. This synaptic mechanism was inspired by the results described in [1] of greater transmission probability for stronger excitatory connections and it was previously applied in [2] and [3].

bernoulli_synapse does not support any kind of plasticity. It simply stores the parameters target, weight, transmission probability, delay and receiver port for each connection.

Parameters:

p_transmit

real

Transmission probability, must be between 0 and 1

FirstVersion: June 2017

Author: Susanne Kunkel, Maximilian Schmidt, Milena Menezes Carvalho

Transmits: SpikeEvent, RateEvent, CurrentEvent, ConductanceEvent, DoubleDataEvent, DataLoggingRequest

SeeAlso: synapsedict, static_synapse, static_synapse_hom_w

References:

1

Lefort S, Tomm C, Sarria J-C F, Petersen CCH (2009). The excitatory neuronal network of the C2 barrel column in mouse primary somatosensory cortex. Neuron, 61(2):301-316. DOI: https://doi.org/10.1016/j.neuron.2008.12.020.

2

Teramae J, Tsubo Y, Fukai T (2012). Optimal spike-based communication in excitable networks with strong-sparse and weak-dense links, Scientific Reports 2,485. DOI: https://doi.org/10.1038/srep00485

3

Omura Y, Carvalho MM, Inokuchi K, Fukai T (2015). A lognormal recurrent network model for burst generation during hippocampal sharp waves. Journal of Neuroscience, 35(43):14585-14601. DOI: https://doi.org/10.1523/JNEUROSCI.4944-14.2015

template<typename targetidentifierT>
class StaticConnection : public Connection<targetidentifierT>

#include <static_connection.h>

Name: static_synapse - Synapse type for static connections.

Description:

static_synapse does not support any kind of plasticity. It simply stores the parameters target, weight, delay and receiver port for each connection.

FirstVersion: October 2005

Author: Jochen Martin Eppler, Moritz Helias

Transmits: SpikeEvent, RateEvent, CurrentEvent, ConductanceEvent, DoubleDataEvent, DataLoggingRequest

Remarks: Refactored for new connection system design, March 2007

SeeAlso: synapsedict, tsodyks_synapse, stdp_synapse

template<typename targetidentifierT>
class StaticConnectionHomW : public Connection<targetidentifierT>

#include <static_connection_hom_w.h>

Name: static_synapse_hom_w - Synapse type for static connections with homogeneous weight.

Description:

static_synapse_hom_w does not support any kind of plasticity. It simply stores the parameters delay, target, and receiver port for each connection and uses a common weight for all connections.

Remarks:

The common weight for all connections of this model must be set by SetDefaults on the model. If you create copies of this model using CopyModel, each derived model can have a different weight.

Transmits: SpikeEvent, RateEvent, CurrentEvent, ConductanceEvent, DataLoggingRequest, DoubleDataEvent

FirstVersion: April 2008

Author: Susanne Kunkel, Moritz Helias

SeeAlso: synapsedict, static_synapse