Ignore-and-spike mechanism example

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This script demonstrates the ignore-and-spike mechanism, which causes a neuron to spike at defined intervals with a specified initial offset, ignoring spikes from its internal dynamics.

Two neurons are simulated: one with the ignore-and-spike mechanism enabled and one without. Both receive the same external current, and their spike times are recorded and compared.

First, we import all necessary modules for simulation, analysis and plotting. Additionally, we set the verbosity to suppress info messages and reset the kernel.

import matplotlib.pyplot as plt
import nest

nest.verbosity = nest.VerbosityLevel.WARNING
nest.ResetKernel()

Second, we set the simulation resolution.

nest.set(resolution=0.1)

Third, we create two neurons and a spike recorder. The first neuron uses the ignore-and-spike mechanism to fire at regular intervals (every 10 ms, starting at 5 ms). The second neuron behaves normally, responding to its internal dynamics.

nrn_regular = nest.Create("iaf_psc_delta")
nrn_ignore_spike = nest.Create(
    "iaf_psc_delta",
    params=dict(
        ignore_and_spike=True,
        ignore_and_spike_offset=5.0,
        ignore_and_spike_interval=10.0,
    ),
)

spike_recorder = nest.Create("spike_recorder")

Fourth, we set the same external current for both neurons. Without the ignore-and-spike mechanism, this would cause irregular spiking based on the neuron’s membrane dynamics.

nrn_regular.I_e = 400.0
nrn_ignore_spike.I_e = 400.0

Fifth, we connect both neurons to the spike recorder.

nest.Connect(nrn_regular, spike_recorder)
nest.Connect(nrn_ignore_spike, spike_recorder)

Now we simulate the network for 100 ms.

nest.Simulate(100.0)

Finally, we retrieve the spike times and plot them as a raster plot. The neuron with ignore-and-spike enabled should show perfectly regular spikes at 5, 15, 25, 35, … ms, regardless of the external input.

events = spike_recorder.get("events")
senders = events["senders"]
times = events["times"]

fig, ax = plt.subplots(figsize=(6, 2))
fig.subplots_adjust(left=0.3, right=0.95)

ax.scatter(times, senders, marker="|", color="#3455B4", s=300)
ax.set_xlabel("Time (ms)")
ax.set_yticks([nrn_regular.global_id, nrn_ignore_spike.global_id])
ax.set_yticklabels(["Regular neuron", "Ignore-and-spike\nneuron"], ha="center")
ax.tick_params(axis="y", pad=50)
ax.set_xticks(range(0, 105, 5))
ax.set_xlim(0, 100)
ax.set_ylim(0.5, 2.5)
ax.spines[["top", "right"]].set_visible(False)
ax.grid(True, alpha=0.3)

fig.tight_layout()

plt.show()