navis.interfaces.neuron.comp.CompartmentModel.add_synaptic_input

CompartmentModel.add_synaptic_input(where, start=5, spike_no=1, spike_int=10, spike_noise=0, syn_tau1=0.1, syn_tau2=10, syn_rev_pot=0, cn_thresh=10, cn_delay=1, cn_weight=0.05)

Add synaptic input to model.

This uses the Exp2Syn synapse. All targets in where are triggered by the same NetStim - i.e. they will all receive their spike(s) at the same time.

Parameters:

• where (int | list of int) – Node IDs at which to simulate synaptic input.

• spikes (Properties for presynaptic) –

• start (int) – Onset [ms] of first spike from beginning of simulation.

• spike_no (int) – Number of presynaptic spikes to produce.

• spike_int (int) – Interval [ms] between consecutive spikes.

• spike_noise (float [0-1]) – Fractional randomness in spike timing.

• properties (Connection) –

• syn_tau1 (int) – Rise time constant [ms].

• syn_tau2 (int) – Decay time constant [ms].

• syn_rev_pot (int) – Reversal potential (e) [mV].

• properties –

• cn_thresh (int) – Presynaptic membrane potential [mV] at which synaptic event is triggered.

• cn_delay (int) – Delay [ms] between presynaptic trigger and postsynaptic event.

• cn_weight (float) – Weight variable. This bundles a couple of synaptic properties such as e.g. how much transmitter is released or binding affinity at postsynaptic receptors.