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Dear Spikey users and developers,

the Spikey-PyNN interface LIF neuron model provides a limited number
of neuron parameters compared to the canonical IF_cond_exp model --
which is perfectly fine for my application.

However, in order to have some coarse prediction of how the neurons
behave, I need some values for the missing parameters in the
IF_cond_exp model. The non-user definable parameters are:

cm --> set to 0.2 nF
tau_m --> implicitly given as cm / g_leak
e_rev_E --> set to 0 mV
tau_syn_E --> ?
tau_syn_I --> ?

As I don't use inhibitory synapses, I basically only need the value
for tau_syn_E. I could of course capture the membrane potential over
time and fit it to the IF_cond_exp model, but is there a easier
method for getting these values?

Eric mentioned last week that these could probably be read from the
calibration tools, but I couldn't quite find something like that in
the source code tree.

Thank you for your support!

Cheers,
Andreas

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