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 double - Transmission probability, must be between 0 and 1
Transmits:
SpikeEvent, RateEvent, CurrentEvent, ConductanceEvent,
DoubleDataEvent, DataLoggingRequest
References:
[1] Sandrine Lefort, Christian Tomm, J.-C. Floyd Sarria, Carl C.H. Petersen,
The Excitatory Neuronal Network of the C2 Barrel Column in Mouse Primary
Somatosensory Cortex, Neuron, Volume 61, Issue 2, 29 January 2009, Pages
301-316, DOI: 10.1016/j.neuron.2008.12.020.
[2] Jun-nosuke Teramae, Yasuhiro Tsubo & Tomoki Fukai, Optimal spike-based
communication in excitable networks with strong-sparse and weak-dense links,
Scientific Reports 2, Article number: 485 (2012), DOI: 10.1038/srep00485
[3] Yoshiyuki Omura, Milena M. Carvalho, Kaoru Inokuchi, Tomoki Fukai, A
Lognormal Recurrent Network Model for Burst Generation during Hippocampal
Sharp Waves, Journal of Neuroscience 28 October 2015, 35 (43) 14585-14601,
DOI: 10.1523/JNEUROSCI.4944-14.2015
Author:
Susanne Kunkel, Maximilian Schmidt, Milena Menezes Carvalho
FirstVersion:
June 2017
SeeAlso:
Source:/builddir/build/BUILD/nest-simulator-2.16.0/nest-simulator-2.16.0/models/bernoulli_connection.h