Thanks for your advices.
I started from initial parameter’s of the NEST and succeeded to get record from the EI
network with ‘iaf_exp_cond’. After working the network with initial parameter’s and using
the Pynest example parameters for the number of connections I changed the synaptic time
constant and so far everything works fine.
From the Pynest folder, I only chose: p_rate, CI, CE and left all other parameters to
their initial values.
Also thanks for the paper.
On 25 May 2020 AD, at 16:19, Charl Linssen
I am surprised you find the ``pynest/examples/brunel_alpha_nest.py`` example to be not
working; it is working fine for me. I would be happy to troubleshoot this, could you tell
us a bit more about what you observe/don't observe?
It should not be too difficult to modify this example, changing the alpha synaptic
kernels for exponential kernels. You will need to look at how the synaptic time constant
and amplitude, and rate of the external Poisson generators need to be updated for
Finding parameters is, in general, one of the more difficult parts of computational
neuroscience. It very much helps if you can find a publication that contains a set of
parameter values known to work (in your case, based on cond-exp synapses). Then, you can
modify the NEST script with these parameters. I am not an expert on evolutionary
algorithms for parameter optimisation; this is a whole field of research in and of itself,
and in the early stages of neural network development, I would recommend to use your own
skill and knowledge to get the parameters in a reasonable operating regime. Again, having
a publication that lists a set of known-good parameters is invaluable as a starting point.
Perhaps the following paper contains some useful leads:
Please let us know if you run into any issues with NEST Simulator during your further
With kind regards,
On Wed, May 13, 2020, at 12:13, nosratullah mohammadi wrote:
> Dear Nest Users,
> I hope all of you be in health during these times.
> I want to create a balanced network as it’s the first step of my master
> thesis. The model I want to use is “iaf_cond_exp” which is a must for
> later purposes. There’s an example in Pynest folder of a balanced
> network, unless it’s using “iaf_psc_alpha” and it doesn’t fit my goals.
> When I try to change the model, and run the program, the network
> doesn’t get active and there’s nothing to record.
> I divided my question into two part:
> - Does anyone have a balanced network with “iaf_cond_exp” neurons and
> all of its necessary parameters to run?
> - In general, how do people find or calculate their network parameters
> to fit the neuron model they use and don’t get lost in the massive
> number of parameters.
> Note: I also tried to use the example of
> “brunel_alpha_evolution_strategies.py” example which is a genetic
> algorithm to find the best parameter, although it finds the parameters
> after 50 generation, I use those parameters afterwards. It just doesn’t
> Kind regards,
> Nosratullah Mohammadi
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