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
Uncomment to log into the ‘log-console’ visible in the simulation
#clientLogger.info("Time: ", t)
Thank you and best regards,
Waiting for feedback for the user to figure out the neuron model that he uses