[NEST Users] NESTML: neuron/synapse model with differential dynamics for computing post synaptic currents

Dear all, I am a new NEST user. I have a question concerning the range of neuron/synapses model possibilities of NEST. I would like to implement my own neuron/synapse model with NESTML, but I am unsure that it would be possible. Indeed, in my model, synaptic currents are not only relying on pre-synaptic spikes. To compute synaptic currents, the opening probability of pre-synaptic channel receptors are required. Those pre-synaptic channel receptors opening probabilities are evolving according to differential equations involving second order dynamics, with specific decays and taking into account the pre-synaptic spikes arrivals times at this specific synapse. Those differential equations for the opening probabilities are relying on different parameters, according to the neurotransmitter type (GABA A,GABA B, NMDA, AMPA ). Furthermore, additionally to the input spikes and the pre-synaptic channel receptors opening probabilities, the current membrane potential of the post-synaptic neuron is also required to compute the synaptic currents. Do you know if one of the NEST models implement similar dynamics? Is it possible to compute such synaptic dynamics with NESTML by creating a synapse or (and) a neuron model? Or is it not, due to specific limitations? Thank you, Best regards, JB