diff --git a/examples/one_neuron_example.py b/examples/one_neuron_example.py
new file mode 100644
index 00000000..23362dbb
--- /dev/null
+++ b/examples/one_neuron_example.py
@@ -0,0 +1,87 @@
+# encoding: utf-8
+"""
+A conversion to PyNN of the "One neuron example" from the NEST examples gallery.
+
+See: https://nest-simulator.readthedocs.io/en/stable/auto_examples/one_neuron.html
+
+
+Usage: one_neuron_example.py [-h] [--plot-figure] [--debug DEBUG] simulator
+
+positional arguments:
+  simulator      neuron, nest, brian or another backend simulator
+
+optional arguments:
+  -h, --help     show this help message and exit
+  --plot-figure  plot the simulation results to a file
+  --debug DEBUG  print debugging information
+"""
+
+from pyNN.utility import get_simulator, init_logging, normalized_filename
+from pyNN.utility.plotting import Figure, Panel
+
+sim, options = get_simulator(("--plot-figure", "Plot the simulation results to a file.", {"action": "store_true"}),
+                             ("--debug", "Print debugging information."))
+
+
+if options.debug:
+    init_logging(None, debug=True)
+
+# === Define parameters ========================================================
+
+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": 0.376,  # (nA)
+}
+
+# === Build the network ========================================================
+
+sim.setup(timestep=0.1)  # (ms)
+
+cell_type = sim.IF_curr_alpha(**cell_params)
+neuron = sim.Population(1, cell_type, initial_values={"v": -70.0}, label="Simulation result")
+neuron.record("v")
+
+
+# === Run simulation ===========================================================
+
+sim.run(1000.0)
+
+data_v = neuron.get_data().segments[0].filter(name="v")[0]
+
+if options.plot_figure:
+    from neo import AsciiSignalIO
+    from quantities import kHz
+
+    reference_data = AsciiSignalIO(
+        "one_neuron_example_reference_data.txt", sampling_rate=1 * kHz
+    ).read_block()
+
+    figure_filename = normalized_filename(
+        "Results", "one_neuron_example", "png", options.simulator, sim.num_processes()
+    )
+    Figure(
+        Panel(
+            reference_data.segments[0].analogsignals[0],
+            data_v[:, 0],
+            xticks=True,
+            yticks=True,
+            xlabel="Time (in ms)",
+            ylabel="Membrane Potential (mV)",
+            line_properties=[{"lw": 3}, {"lw": 1}],
+            data_labels=["Reference data", "Simulation result"]
+        ),
+        title="One Neuron",
+        annotations=f"One Neuron Example using PyNN (simulator: {options.simulator})",
+    ).save(figure_filename)
+    print(figure_filename)
+
+# === Clean up and quit ========================================================
+
+sim.end()
diff --git a/examples/one_neuron_example_reference_data.txt b/examples/one_neuron_example_reference_data.txt
new file mode 100644
index 00000000..93ebf239
--- /dev/null
+++ b/examples/one_neuron_example_reference_data.txt
@@ -0,0 +1,1000 @@
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diff --git a/examples/one_neuron_noise_example.py b/examples/one_neuron_noise_example.py
new file mode 100644
index 00000000..8c694fcf
--- /dev/null
+++ b/examples/one_neuron_noise_example.py
@@ -0,0 +1,98 @@
+# encoding: utf-8
+"""
+A conversion to PyNN of the "One neuron with noise" example from the NEST examples gallery.
+
+See: https://nest-simulator.readthedocs.io/en/stable/auto_examples/one_neuron_with_noise.html
+
+
+Usage: one_neuron_noise_example.py [-h] [--plot-figure] [--debug DEBUG] simulator
+
+positional arguments:
+  simulator      neuron, nest, brian or another backend simulator
+
+optional arguments:
+  -h, --help     show this help message and exit
+  --plot-figure  plot the simulation results to a file
+  --debug DEBUG  print debugging information
+"""
+
+from pyNN.utility import get_simulator, init_logging, normalized_filename
+from pyNN.utility.plotting import Figure, Panel
+
+sim, options = get_simulator(("--plot-figure", "Plot the simulation results to a file.", {"action": "store_true"}),
+                             ("--debug", "Print debugging information."))
+
+
+if options.debug:
+    init_logging(None, debug=True)
+
+# === Define parameters ========================================================
+
+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)
+}
+
+# === Build the network ========================================================
+
+sim.setup(timestep=0.01)  # (ms)
+
+cell_type = sim.IF_curr_alpha(**cell_params)
+
+neuron = sim.Population(1, cell_type, initial_values={"v": -70}, label="Neuron")
+neuron.record(["v", "spikes"])
+
+poisson_noise_generators = sim.Population(2, sim.SpikeSourcePoisson(rate=[80000, 15000]))
+poisson_noise_generators.record("spikes")
+
+prjs = [
+    sim.Projection(
+        poisson_noise_generators[0:1],
+        neuron,
+        sim.AllToAllConnector(),
+        sim.StaticSynapse(weight=0.0012, delay=1),
+        receptor_type="excitatory",
+    ),
+    sim.Projection(
+        poisson_noise_generators[1:2],
+        neuron,
+        sim.AllToAllConnector(),
+        sim.StaticSynapse(weight=-0.001, delay=1),
+        receptor_type="inhibitory",
+    ),
+]
+
+# === Run simulation ===========================================================
+
+sim.run(1000)
+
+data_v = neuron.get_data().segments[0].filter(name="v")[0]
+data_spikes = neuron.get_data().segments[0].spiketrains
+
+if options.plot_figure:
+    figure_filename = normalized_filename(
+        "Results", "one_neuron_noise_example", "png", options.simulator
+    )
+    Figure(
+        Panel(
+            data_v[:, 0],
+            xlabel="Time (in ms)",
+            ylabel="Membrane Potential",
+            xticks=True,
+            yticks=True,
+        ),
+        title="One neuron with noise",
+        annotations=f"One neuron with noise example using PyNN (simulator: {options.simulator})",
+    ).save(figure_filename)
+    print(figure_filename)
+
+# === Clean up and quit ========================================================
+
+sim.end()
diff --git a/examples/two_neuron_example.py b/examples/two_neuron_example.py
new file mode 100644
index 00000000..fe5296f4
--- /dev/null
+++ b/examples/two_neuron_example.py
@@ -0,0 +1,79 @@
+"""
+A conversion to PyNN of the "Two neuron example" from the NEST examples gallery.
+
+See: https://nest-simulator.readthedocs.io/en/stable/auto_examples/twoneurons.html
+
+Usage: two_neuron_example.py [-h] [--plot-figure] [--debug DEBUG] simulator
+
+positional arguments:
+  simulator      neuron, nest, brian or another backend simulator
+
+optional arguments:
+  -h, --help     show this help message and exit
+  --plot-figure  plot the simulation results to a file
+  --debug DEBUG  print debugging information
+
+"""
+
+from pyNN.utility import get_simulator, init_logging, normalized_filename
+from pyNN.utility.plotting import Figure, Panel
+
+sim, options = get_simulator(("--plot-figure", "Plot the simulation results to a file.", {"action": "store_true"}),
+                             ("--debug", "Print debugging information."))
+
+if options.debug:
+    init_logging(None, debug=True)
+
+# === Define parameters ========================================================
+
+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)
+}
+
+# === Build the network ========================================================
+
+sim.setup(timestep=0.1)  # (ms)
+
+cell_type = sim.IF_curr_alpha(**cell_params)
+neurons = sim.Population(2, cell_type, initial_values={"v": -70}, label="Neurons")
+neurons[0:1].set(i_offset=0.376)
+neurons.record("v")
+
+syn = sim.StaticSynapse(weight=0.02, delay=1.0)
+projection1 = sim.Projection(neurons[0:1], neurons[1:2], sim.AllToAllConnector(), syn)
+
+# === Run simulation ===========================================================
+
+sim.run(1000)
+
+data = neurons.get_data().segments[0].filter(name="v")[0]
+
+if options.plot_figure:
+    figure_filename = normalized_filename(
+        "Results", "two_neuron_example", "png", options.simulator
+    )
+
+    Figure(
+        Panel(
+            data,
+            xticks=True,
+            yticks=True,
+            xlabel="Time (in ms)",
+            ylabel="Membrane Potential (in mV)",
+        ),
+        title="Two neurons",
+        annotations=f"Two neuron example using PyNN (simulator: {options.simulator})",
+    ).save(figure_filename)
+    print(figure_filename)
+
+# === Clean up and quit ========================================================
+
+sim.end()