+ def simulate(self):
+ with nengo.Network() as net:
+ # Nodes
+ time_node = nengo.Node(output=time_function)
+ noise_wm_node = nengo.Node(output=noise_bias_function)
+ noise_decision_node = nengo.Node(
+ output=noise_decision_function)
+
+ # Ensembles
+ wm = nengo.Ensemble(neurons_wm, 2)
+ decision = nengo.Ensemble(neurons_decide, 2)
+ inputs = nengo.Ensemble(neurons_inputs, 2)
+ output = nengo.Ensemble(neurons_decide, 1)
+
+ # Connections
+ nengo.Connection(time_node, inputs[1], synapse=None)
+ nengo.Connection(inputs, wm, synapse=tau_wm,
+ function=inputs_function)
+ wm_recurrent = nengo.Connection(wm, wm, synapse=tau_wm,
+ function=wm_recurrent_function)
+ nengo.Connection(noise_wm_node, wm.neurons, synapse=tau_wm,
+ transform=np.ones((neurons_wm, 1)) * tau_wm)
+ wm_to_decision = nengo.Connection(
+ wm[0], decision[0], synapse=tau)
+ nengo.Connection(noise_decision_node,
+ decision[1], synapse=None)
+ nengo.Connection(decision, output, function=decision_function)
+
+ # Probes
+ #probes_wm = nengo.Probe(
+ # wm[0], synapse=0.01, sample_every=dt_sample)
+ #probes_spikes = nengo.Probe(wm.neurons, 'spikes',
+ # sample_every=dt_sample)
+ #probe_output = nengo.Probe(output, synapse=None,
+ # same_every=dt_sample)
+
+ # Run simulation
+ with nengo.Simulator(net, dt=dt) as sim:
+ sim.run(t_cue + t_delay)
+
+