[SOLVED] Monitoring spikes with direct nest


Dear All,

I am using the NRP with direct nest.
Almost everything works quite well. I got
my own neuron model implemented and am
building the network right now.

One thing I don’t know how to solve is the
spike monitoring. If I use a NeuronMonitor
similar to the husky robot experiment the
spikes are monitored with their global ids.
That means that I can’t see the spikes of
all populations in the Brain Visualizer because
the ids are too high.
I read that the Device Parameter use_ids
can be set to False for the spike_recorder.
How do I have to modify the NeuronMonitor
function to implement that feature?

Here my up to date NeuronMonitor:

#Imported Python Transfer Function

#import hbp_nrp_cle.tf_framework as nrp
#This specifies that the neurons of the motor population
#should be monitored. You can see them in the spike train widget
@nrp.NeuronMonitor(nrp.brain.semd_lr, nrp.spike_recorder)
def all_neurons_spike_monitor(t):
# Uncomment to log into the ‘log-console’ visible in the simulation
#clientLogger.info("Time: ", t)
return True

Thank you and best regards,
Thorben Schoepe

Research Assistant and PhD student at
Neuromorphic Behaving Systems group,
Technical Faculty, Bielefeld University


Created an enhancement request in


Hi Thorben,

Is that still an issue? If so could you provide us with some example code on how to reproduce this? It would help us in identifying what exactly we need to change from our side.



This issue has been fixed with https://hbpneurorobotics.atlassian.net/browse/NUIT-187.