bernoulli_synapse – Static synapse with stochastic transmission¶
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 .
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.
Transmission probability, must be between 0 and 1
SpikeEvent, RateEvent, CurrentEvent, ConductanceEvent, DoubleDataEvent, DataLoggingRequest
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.
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
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