gamma_sup_generator – Simulate the superimposed spike train of a population of gamma processes¶
The gamma_sup_generator generator simulates the pooled spike train of a population of neurons firing independently with gamma process statistics.
All stimulation devices share the parameters
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 start < t <= stop are emitted. Spikes that have timestamp of t = 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 (start, start+h], i.e., an effect can be recorded at the earliest at time start+h. The last interval during which the current affects the target’s dynamics is (stop-h, stop].
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.
A string (default: “”) specifying an arbitrary textual label for the device. Stimulation backends might use the label to generate device specific identifiers like filenames and such.
A positive floating point number (default : 0.0) used as the reference time in ms for start and stop.
A positive floating point number (default: 0.0) specifying the activation time in ms, relative to origin.
A string (default: “”) 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.
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.
Mean firing rate of the component processes, default: 0 spikes/s
Shape parameter of component gamma processes, default: 1
Number of superimposed independent component processes, default: 1
Set 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:
Deger, Helias, Boucsein, Rotter (2011). Statistical properties of superimposed stationary spike trains. Journal of Computational Neuroscience. DOI: https://doi.org/10.1007/s10827-011-0362-8