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...	...	@@ -334,28 +334,22 @@
334	334	population2.set(i_offset=0)
335	335	population1.record("v")
336	336	population2.record("v")(%%)
337		-(% style="color:#000000" %)connection_algorithm = sim.FixedProbabilityConnector(p=0.5)
	337	+(% style="color:#e74c3c" %)connection_algorithm = sim.FixedProbabilityConnector(p=0.5)
338	338	synapse_type = sim.StaticSynapse(weight=0.5, delay=0.5)
339	339	connections = sim.Projection(population1, population2, connection_algorithm, synapse_type)(%%)
340	340	(% style="color:#000000" %)sim.run(100.0)(%%)
341		-(% style="color:#e74c3c" %)data1_v(% style="color:#000000" %) = population1.get_data().segments[0].filter(name='v')[0](%%)
342		-(% style="color:#e74c3c" %)data2_v = population2.get_data().segments[0].filter(name='v')[0](%%)
343		-(% style="color:#000000" %)Figure(
	341	+(% style="color:#000000" %)data_v = population1.get_data().segments[0].filter(name='v')[0]
	342	+Figure(
344	344	Panel(
345		- (% style="color:#e74c3c" %)data1_v(% style="color:#000000" %)[:, 0:5],
346		- xticks=True, (% style="color:#e74c3c" %)--xlabel="Time (ms)",--(%%)
347		-(% style="color:#000000" %) yticks=True, ylabel="Membrane potential (mV)"
348		- ),
349		- (% style="color:#e74c3c" %)Panel(
350		- data2_v[:, 0:5],
	344	+ data_v[:, 0:5],
351	351	xticks=True, xlabel="Time (ms)",
352		- yticks=True"
353		- ),(%%)
354		-(% style="color:#000000" %) title="Response of (% style="color:#e74c3c" %)simple network(% style="color:#000000" %)",
	346	+ yticks=True, ylabel="Membrane potential (mV)"
	347	+ ),
	348	+ title="Response of first five neurons with heterogeneous parameters",
355	355	annotations="Simulated with NEST"
356	356	).show()
357	357
358		-**Run script in terminal, show figure**
	352	+Run script in terminal, show figure
359	359	)))
360	360
361	361	(% class="wikigeneratedid" id="HSummary28Inthistutorial2CyouhavelearnedtodoX202629" %)