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,
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.