Warning
This is A PREVIEW for NEST 3.0 and NOT an OFFICIAL RELEASE! Some functionality may not be available and information may be incomplete!
weight_recorder – Recording weights from synapses¶
Description¶
The change in synaptic weights over time is a key observable property in
studies of plasticity in neuronal network models. To access this information, the
weight_recorder
can be used. In contrast to other recording
devices, which are connected to a specific set of neurons, the weight
recorder is instead set as a parameter in the synapse model.
After assigning an instance of a weight recorder to the synapse model
by setting its weight_recorder
property, the weight
recorder collects the global IDs of source and target neurons together
with the weight for each spike event that travels through the observed
synapses.
To only record from a subset of connected synapses, the
weight recorder accepts NodeCollections in the parameters senders
and
targets
. If set, they restrict the recording of data to only
synapses that fulfill the given criteria.
>>> wr = nest.Create('weight_recorder')
>>> nest.CopyModel("stdp_synapse", "stdp_synapse_rec", {"weight_recorder": wr})
>>> pre = nest.Create("iaf_psc_alpha", 10)
>>> post = nest.Create("iaf_psc_alpha", 10)
>>> nest.Connect(pre, post, syn_spec="stdp_synapse_rec")