[NEST Users] Re: Issue In testing of a trained network

I have put N=16 and gmax as 3 nest.ResetKernel() # Simulation parameters dt = 0.01 # Simulation time step in ms nest.SetKernelStatus({"resolution": dt}) N = 16 # Number of neurons gmax = 3 neuron_params = { "tau_m": 140.0, # Membrane time constant in ms "E_L": -70.6, # Resting potential (in mV) "V_th": -40.4, # Threshold potential (in mV) "V_reset": -70.6, # Reset potential (in mV) "V_m":0.0, } nest.CopyModel("stdp_synapse", "stdp_synapse_exc", {"weight":gmax,"alpha":1,"Wmax":gmax, "tau_plus": 20.0,"lambda": -0.0005, "mu_minus": 0, "mu_plus": 0}) nest.CopyModel("stdp_synapse", "stdp_synapse_inh", {"weight":-gmax/(N-1),"alpha":1,"Wmax":-gmax, "tau_plus": 20.0,"lambda": 0.005, "mu_minus": 0, "mu_plus": 0}) G_spike_gen = nest.Create("spike_generator", N) G_input = nest.Create("parrot_neuron", N) G_hidden = nest.Create("iaf_psc_delta", N,params=neuron_params) G_output = nest.Create("iaf_psc_delta", 1,params=neuron_params) S_in = nest.Connect(G_spike_gen, G_input, "one_to_one") # Connect input to hidden layer with excitatory STDP synapses S_exc = nest.Connect(G_input, G_hidden,"one_to_one",syn_spec = "stdp_synapse_exc") # Retrieve the neuron IDs for G_input and G_hidden input_ids = G_input.tolist() hidden_ids = G_hidden.tolist() # Get the existing excitatory connections and extract their source-target ID pairs exc_connections = nest.GetConnections(G_input, G_hidden) exc_connection_pairs = set(zip(exc_connections.get("source"), exc_connections.get("target"))) for i in input_ids: for h in hidden_ids: if (i, h) not in exc_connection_pairs: nc1 = nest.NodeCollection([i]) nc2 = nest.NodeCollection([h]) nest.Connect(nc1, nc2, syn_spec= "stdp_synapse_inh") S_out = nest.Connect(G_hidden, G_output,"all_to_all",syn_spec = {"weight": 40.4/N}) This is the code architecture