Name:parrot_neuron - Neuron that repeats incoming spikes.
Description:
The parrot neuron simply emits one spike for every incoming spike.
An important application is to provide identical poisson spike
trains to a group of neurons. The poisson_generator sends a different
spike train to each of its target neurons. By connecting one
poisson_generator to a parrot_neuron and then that parrot_neuron to
a group of neurons, all target neurons will receive the same poisson
spike train.
Parameters:
No parameters to be set in the status dictionary.
Receives:
SpikeEvent
Sends:
SpikeEvent
Remarks:
- Weights on connection to the parrot_neuron are ignored.
- Weights on connections from the parrot_neuron are handled as usual.
- Delays are honored on incoming and outgoing connections.
Only spikes arriving on connections to port 0 will be repeated.
Connections onto port 1 will be accepted, but spikes incoming
through port 1 will be ignored. This allows setting exact pre-
and post-synaptic spike times for STDP protocols by connecting
two parrot neurons spiking at desired times by, e.g., a
stdp_synapse onto port 1 on the post-synaptic parrot neuron.
Author:
David Reichert, Abigail Morrison, Alexander Seeholzer, Hans Ekkehard
Plesser
FirstVersion:
May 2006
Source:/opt/conda/conda-bld/nest_1512397208563/work/nest-2.14.0/models/parrot_neuron.h