diff --git a/synfire/self_synfire.py b/synfire/self_synfire.py
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+++ b/synfire/self_synfire.py
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+# Copyright (c) 2016 The University of Manchester
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+
+"""
+Synfire chain example
+"""
+import matplotlib.pyplot as plt
+import pyNN.spiNNaker as sim
+import pyNN.utility.plotting as plot
+
+# number of neurons in each population
+n_neurons = 1000
+simtime = 600
+pops = 50
+
+sim.setup(timestep=1.0, min_delay=1.0)
+
+spikeArray = {'spike_times': [[0]]}
+stimulus = sim.Population(1, sim.SpikeSourceArray, spikeArray,
+                          label='stimulus')
+injectionConnection = [(0, 0)]
+chainConnection = [(n_neurons-1, 0)]
+for i in range(n_neurons-1):
+    chainConnection.append((i, i+1))
+
+for i in range(pops):
+    pop = sim.Population(n_neurons, sim.IF_curr_exp, {}, label=f'chain{i}')
+    pop.record("spikes")
+    #pop.record(["spikes", "v"])
+    sim.Projection(stimulus, pop,
+                   sim.FromListConnector(injectionConnection),
+                   sim.StaticSynapse(weight=5, delay=1))
+    sim.Projection(pop, pop,
+                   sim.FromListConnector(chainConnection),
+                   sim.StaticSynapse(weight=5, delay=1))
+
+sim.run(simtime)
+neo = pop.get_data(variables=["spikes"])
+#neo = pop.get_data(variables=["spikes", "v"])
+spikes = neo.segments[0].spiketrains
+# print(spikes)
+# v = neo.segments[0].filter(name='v')[0]
+# print(v)
+sim.end()
+
+plot.Figure(
+    # plot voltage for first ([0]) neuron
+    # plot.Panel(v, ylabel="Membrane potential (mV)",
+    #           data_labels=[pop.label], yticks=True, xlim=(0, simtime)),
+    # plot spikes
+    plot.Panel(spikes, yticks=True, markersize=5, xlim=(0, simtime)),
+    title="Self Synfire Example",
+    annotations="Simulated with {}".format(sim.name())
+)
+plt.show()
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