PoissonGroup class

(Shortest import: from brian2 import PoissonGroup)

class brian2.input.poissongroup.PoissonGroup(*args, **kw)

Bases: Group, SpikeSource

Poisson spike source

Parameters

N : int

Number of neurons

rates : Quantity, str

Single rate, array of rates of length N, or a string expression evaluating to a rate. This string expression will be evaluated at every time step, it can therefore be time-dependent (e.g. refer to a TimedArray).

dt : Quantity, optional

The time step to be used for the simulation. Cannot be combined with the clock argument.

clock : Clock, optional

The update clock to be used. If neither a clock, nor the dt argument is specified, the defaultclock will be used.

when : str, optional

When to run within a time step, defaults to the 'thresholds' slot. See Scheduling for possible values.

order : int, optional

The priority of of this group for operations occurring at the same time step and in the same scheduling slot. Defaults to 0.

name : str, optional

Unique name, or use poissongroup, poissongroup_1, etc.

Attributes

spikes

The spikes returned by the most recent thresholding operation.

Methods

before_run([run_namespace])

Optional method to prepare the object before a run.

Details

spikes

The spikes returned by the most recent thresholding operation.

before_run(run_namespace=None)

Optional method to prepare the object before a run.

Called by Network.after_run before the main simulation loop starts.

Tutorials and examples using this

• Tutorial 3-intro-to-brian-simulations

• Example adaptive_threshold

• Example advanced/custom_events

• Example frompapers/Stimberg_et_al_2018/example_4_rsmean

• Example frompapers/Stimberg_et_al_2018/example_4_synrel

• Example standalone/STDP_standalone

• Example standalone/standalone_multiplerun

• Example synapses/STDP

• Example synapses/spike_based_homeostasis