spike_train_injector – Neuron that emits prescribed spike trains.

Description

The spike train injector neuron emits spikes at prescribed spike times which are given as an array. The neuron does not allow incoming connections and is thus not able to process incoming spikes or currents.

Note

spike_train_injector is recommended if the spike trains have a similar rate to regular neurons. For very high rates, use spike generator.

Spike times are given in milliseconds as an array. The spike_times array must be sorted with the earliest spike first. All spike times must be strictly in the future. Trying to set a spike time in the past or at the current time step will cause a NEST error. Setting a spike time of 0.0 will also result in an error.

Multiple occurrences of the same time indicate that more than one event is to be generated at this particular time.

The spike generator supports spike times that do not coincide with a time step, that is, are not falling on the grid defined by the simulation resolution. Spike times that do not coincide with a step are handled with one of three options (see examples below):

Option 1: precise_times default: false

If false, spike times will be rounded to simulation steps, i.e., multiples of the resolution. The rounding is controlled by the two other flags. If true, spike times will not be rounded but represented exactly as a combination of step and offset. This should only be used if all neurons receiving the spike train can handle precise timing information. In this case, the other two options are ignored.

Option 2: allow_offgrid_times default: false

If false, spike times will be rounded to the nearest step if they are less than tic/2 from the step, otherwise NEST reports an error. If true, spike times are rounded to the nearest step if within tic/2 from the step, otherwise they are rounded up to the end of the step. This setting has no effect if precise_times is true.

Option 3: shift_now_spikes default: false

This option is mainly for use by the PyNN-NEST interface. If false, spike times rounded down to the current point in time will be considered in the past and ignored. If true, spike times that are rounded down to the current time step are shifted one time step into the future.

Note that GetStatus will report the spike times that the spike_generator will actually use, i.e., for grid-based simulation the spike times rounded to the appropriate point on the time grid. This means that GetStatus may return different spike_times values at different resolutions.

Example:

nest.Create("spike_train_injector",
            params={"spike_times": [1.0, 2.0, 3.0]})

Instructs the spike train injector neuron to emit events at 1.0, 2.0, and 3.0 milliseconds, relative to the timer origin.

Example:

Assume that NEST works with default resolution (step size) of 0.1 ms and default tic length of 0.001 ms. Then, spikes times not falling onto the grid will be handled as follows for different option settings:

nest.Create("spike_train_injector",
           params={"spike_times": [1.0, 1.9999, 3.0001]})

—> spikes at steps 10 (==1.0 ms), 20 (==2.0 ms) and 30 (==3.0 ms)

nest.Create("spike_train_injector",
           params={"spike_times": [1.0, 1.05, 3.0001]})

—> Error! Spike time 1.05 not within tic/2 of step

nest.Create("spike_train_injector",
           params={"spike_times": [1.0, 1.05, 3.0001],
           "allow_offgrid_times": True})
—> spikes at steps 10, 11 (mid-step time rounded up),

30 (time within tic/2 of step moved to step)

nest.Create("spike_train_injector",
           params={"spike_times": [1.0, 1.05, 3.0001],
           "precise_times": True})
—> spikes at step 10, offset 0.0; step 11, offset -0.05;

step 31, offset -0.0999

Assume we have simulated 10.0 ms and simulation time is thus 10.0 (step 100). Then, any spike times set at this time must be later than step 100.

nest.Create("spike_train_injector",
           params={"spike_times": [10.0001]})
—> spike time is within tic/2 of step 100, rounded down to 100 thus

not in the future; spike will not be emitted

nest.Create("spike_train_injector",
           params={"spike_times": [10.0001],
           "precise_times": True})

—> spike at step 101, offset -0.0999 is in the future

nest.Create("spike_train_injector",
           params={"spike_times": [10.0001, 11.0001],
           "shift_now_spikes": True})
—> spike at step 101, spike shifted into the future, and spike at step

110, not shifted, since it is in the future anyways

Parameters

origin

A positive floating point number (default : 0.0) used as the reference time in ms for start and stop.

start

A positive floating point number (default: 0.0) specifying the activation time in ms, relative to origin.

stop

A floating point number (default: infinity) specifying the deactivation time in ms, relative to origin. The value of stop must be greater than or equal to start.

spike_times

List of spike times in ms.

spike_multiplicities

List of multiplicities of spikes, same length as spike_times; mostly for debugging.

precise_times

See above.

allow_offgrid_times

See above.

shift_now_spikes

See above.

Receives

None

Sends

SpikeEvent

See also

Neuron, Device, Spike, Generator

Examples using this model

None