Dear Hartmut,

This should be quite straightforward if you are using NESTML to write your neuron model. Check out the documentation here for making multiple input ports:

Your code would look something like this:

  spikes_curr pA <- spike  # spike input port for current-based synapse
  spikes_cond nS <- spike  # spike input port for conductance-based synapse

  shape syn_kernel = exp(-t / tau_syn)
  function I_syn_curr pA = convolve(syn_kernel, spikes_curr)
  function I_syn_cond pA = convolve(syn_kernel, spikes_cond) * (V_abs - E_L - E_syn)
  V_abs' = -V_abs/tau_m + (I_syn_curr + I_syn_cond) / C_m

Please let me know if this works for you.

With kind regards,
Charl Linssen

On Wed, Jun 10, 2020, at 15:43, Hartmut Schmidt wrote:
> Dear all,

> I am trying to implement a network consisting of LIF neurons with mixed 
> current based and conductance based synaptic connections.
> Eg. one LIF neuron which gets two inputs from which one is treated as 
> current input and the other as conductance input.
> That means, how to treat the input should be encoded in the synapse and 
> not in the type of the postsynaptic neuron.
> Is such a neuron model already implemented or is there a way to 
> implement this?

> Thanks for your help.

> Best,
> Hartmut
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