Dear Benedikt
1) Are there any implementations for tonic neuron
input, that means an
additional Neuron input channel that mulitplies with all synaptic inputs?
We don't have an implementation that does this, but I don't see any
reason why you can't make your own. The most effective way to do this is
using NESTML, then you don't have to worry about C++ or numerics. A
brief description of NESTML with links to publications and Github is here:
https://www.fz-juelich.de/ias/jsc/EN/Expertise/SimLab/slns/research/nestml/…
we are happy to support you in using this.
2) Can synaptic weights be normalized, in particular keeping the sum of
all inputs of a single neuron equal to 1?
This is tricky. We did implement something close to this for a paper:
https://www.frontiersin.org/articles/10.3389/fncom.2010.00160/full
but we did not merge the infrastructure changes with master, because we
felt it wasn't general enough. Making a general version would be a
large, complicated job. As a workaround, you could consider running your
simulation in small time segments, and after each segment you can
read-out, sum and normalise the incoming weights for each neuron
'manually' from your simulation script. For a small network this will
work fine, but it won't scale.
All the best,
Abigail
--
Prof. Dr. Abigail Morrison
IAS-6 / INM-6 / SimLab Neuroscience
Jülich Research Center
&
Institute of Cognitive Neuroscience
Ruhr-University Bochum
http://www.fz-juelich.de/inm/inm-6
http://www.fz-juelich.de/ias/jsc/slns
http://www.ikn.psy.ruhr-uni-bochum.de
Office: +49 2461 61-9805
Fax # : +49 2461 61-9460
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