sinusoidal_poisson_generator – Generate sinusoidally modulated Poisson spike trains

Description

sinusoidal_poisson_generator generates sinusoidally modulated Poisson spike trains. By default, each target of the generator will receive a different spike train.

The instantaneous rate of the process is given by

\[f(t) = \mathrm{max} \left(0, \mathrm{rate} + \mathrm{amplitude} \cdot \sin \left( 2 \pi \cdot \mathrm{frequency} \cdot t + \mathrm{phase} \cdot \frac{\pi}{180} \right) \right) >= 0\]

Note

  • If \(\mathrm{amplitude} > \mathrm{rate}\), firing rate is cut off at zero. In this case, the mean firing rate will be less than rate.

  • The state of the generator is reset on calibration.

  • The generator does not support precise spike timing.

  • You can use the multimeter to sample the rate of the generator.

  • The generator will create different trains if run at different temporal resolutions.

By default, the generator sends a different spike train to each of its targets. If individual_spike_trains is set to False using either SetDefaults() or CopyModel() before a generator node is created, the generator will send the same spike train to all of its targets.

All stimulation devices share the parameters start and stop, which control the stimulation period. The property origin is a global offset that shifts the stimulation period. All three values are set as times in ms.

  • For spike-emitting devices, only spikes with times t that fulfill \(\mathrm{start} < t \leq \mathrm{stop}\) are emitted. Spikes that have timestamp of \(t = \mathrm{start}\) are not emitted.

  • For current-emitting devices, the current is activated and deactivated such that the current first affects the target dynamics during the update step \((\mathrm{start}, \mathrm{start}+h]\), that is, an effect can be recorded at the earliest at time \(\mathrm{start}+h\). The last interval during which the current affects the target’s dynamics is \((\textrm{stop}-h, \textrm{stop}]\).

The property stimulus_source defaults to an empty string. It can be set to the name of a stimulation backend, in which case it will take its parameters from the configured backend instead of from the internally stored values. More details on available backends and their properties can be found in the guide to stimulating the network.

Parameters

label

A string specifying an arbitrary textual label for the device. Stimulation backends might use the label to generate device specific identifiers like filenames and such. Default: "".

origin

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

start

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

stimulus_source

A string specifying the name of the stimulation backend from which to get the data for updating the stimulus parameters of the device. By default, the device uses its internally stored parameters for updating the stimulus. Default: "".

stop

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

rate

Mean firing rate in spikes/second. Default: 0.0.

amplitude

Firing rate modulation amplitude in spikes/second. Default: 0.0.

frequency

Modulation frequency in Hz. Default: 0.0.

phase

Modulation phase in degree [0-360]. Default: 0.0.

individual_spike_trains

See note above. Default: True.

Setting parameters from a stimulation backend

The parameters in this stimulation device can be updated with input coming from a stimulation backend. The data structure used for the update holds one value for each of the parameters mentioned above. The indexing is as follows:

  1. rate

  2. frequency

  3. phase

  4. amplitude

  5. individual_spike_trains

Receives

DataLoggingRequest

Sends

SpikeEvent

See also

poisson_generator, sinusoidal_gamma_generator

Examples using this model