diff --git a/examples/one_neuron_noise_example.py b/examples/one_neuron_noise_example.py
new file mode 100644
index 00000000..388487dd
--- /dev/null
+++ b/examples/one_neuron_noise_example.py
@@ -0,0 +1,43 @@
+import pyNN.nest as sim
+from pyNN.utility.plotting import Figure, Panel
+import matplotlib.pyplot as plt
+
+sim.setup(timestep=0.1) # (ms)
+
+
+cell_params = {
+    "v_rest": -70.0, # (mV)
+    "v_reset": -70.0, # (mV)
+    "cm": 0.250, # (nF)
+    "tau_m": 10, # (ms)
+    "tau_refrac": 2, # (ms)
+    "tau_syn_E": 2, # (ms)
+    "tau_syn_I": 2, # (ms)
+    "v_thresh": -55.0, # (mV)
+    "i_offset": 0, # (nA)
+}
+
+
+cell_type = sim.IF_curr_alpha(**cell_params)
+
+neuron = sim.Population(1, cell_type, label="Neuron")
+neuron.record(["v", "spikes"])
+
+poisson_noise_generators = sim.Population(2, sim.SpikeSourcePoisson(rate=[80000, 15000]))
+poisson_noise_generators.record("spikes")
+
+syn = sim.StaticSynapse(weight=0.0012, delay=1)
+
+prj = sim.Projection(poisson_noise_generators, neuron, sim.AllToAllConnector() , syn)
+prj.setWeights([0.0012, 0.001])
+prj.setDelays([1, 1])
+
+sim.run(1000)
+
+data_v = neuron.get_data().segments[0].filter(name="v")[0]
+data_spikes = neuron.get_data().segments[0].spiketrains
+
+Figure(
+    Panel(data_v[:,0], xlabel="Time (in ms)", ylabel="Membrane Potential", xticks=True, yticks=True)
+).show()
+