One neuron with noise

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This script simulates a neuron with input from the poisson_generator, and records the neuron’s membrane potential.

First, we import all necessary modules needed to simulate, analyze and plot our example. Additionally, we set the verbosity to only show warnings and reset the kernel. Resetting the kernel removes any nodes we may have created previously and resets the internal clock to zero. This allows us to execute the script several times in a Python shell without interference from previous NEST simulations.

import matplotlib.pyplot as plt
import nest
import nest.voltage_trace

nest.set_verbosity("M_WARNING")
nest.ResetKernel()

Second, the nodes (the neuron, poisson generator (two of them), and the voltmeter) are created using the Create function. We store the returned handles in variables for later reference.

neuron = nest.Create("iaf_psc_alpha")
noise = nest.Create("poisson_generator", 2)
voltmeter = nest.Create("voltmeter")

Third, the Poisson generator is configured using SetStatus, which expects a list of node handles and a list of parameter dictionaries. We set the Poisson generators to 80,000 Hz and 15,000 Hz, respectively. Note that we do not need to set parameters for the neuron and the voltmeter, since they have satisfactory defaults.

noise[0].rate = 80000.0
noise[1].rate = 15000.0

Fourth, the neuron is connected to the poisson_generator and to the voltmeter. We also specify the synaptic weight and delay in this step.

nest.Connect(noise, neuron, syn_spec={"weight": [[1.2, -1.0]], "delay": 1.0})
nest.Connect(voltmeter, neuron)

Now we simulate the network using Simulate, which takes the desired simulation time in milliseconds.

nest.Simulate(1000.0)

Finally, we plot the neuron’s membrane potential as a function of time.

nest.voltage_trace.from_device(voltmeter)
plt.show()