NeuronGroup class

(Shortest import: from brian2 import NeuronGroup)

class brian2.groups.neurongroup.NeuronGroup(N, model, method=('linear', 'euler', 'heun'), threshold=None, reset=None, refractory=False, events=None, namespace=None, dtype=None, dt=None, clock=None, order=0, name='neurongroup*', codeobj_class=None)[source]

Bases: brian2.groups.group.Group, brian2.core.spikesource.SpikeSource

A group of neurons.

Parameters:

N : int

Number of neurons in the group.

model : (str, Equations)

The differential equations defining the group

method : (str, function), optional

The numerical integration method. Either a string with the name of a registered method (e.g. “euler”) or a function that receives an Equations object and returns the corresponding abstract code. If no method is specified, a suitable method will be chosen automatically.

threshold : str, optional

The condition which produces spikes. Should be a single line boolean expression.

reset : str, optional

The (possibly multi-line) string with the code to execute on reset.

refractory : {str, Quantity}, optional

Either the length of the refractory period (e.g. 2*ms), a string expression that evaluates to the length of the refractory period after each spike (e.g. '(1 + rand())*ms'), or a string expression evaluating to a boolean value, given the condition under which the neuron stays refractory after a spike (e.g. 'v > -20*mV')

events : dict, optional

User-defined events in addition to the “spike” event defined by the threshold. Has to be a mapping of strings (the event name) to strings (the condition) that will be checked.

namespace: dict, optional :

A dictionary mapping variable/function names to the respective objects. If no namespace is given, the “implicit” namespace, consisting of the local and global namespace surrounding the creation of the class, is used.

dtype : (dtype, dict), optional

The numpy.dtype that will be used to store the values, or a dictionary specifying the type for variable names. If a value is not provided for a variable (or no value is provided at all), the preference setting core.default_float_dtype is used.

codeobj_class : class, optional

The CodeObject class to run code with.

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.

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

A unique name for the group, otherwise use neurongroup_0, etc.

Notes

NeuronGroup contains a StateUpdater, Thresholder and Resetter, and these are run at the ‘groups’, ‘thresholds’ and ‘resets’ slots (i.e. the values of their when attribute take these values). The order attribute will be passed down to the contained objects but can be set individually by setting the order attribute of the state_updater, thresholder and resetter attributes, respectively.

Attributes

_refractory The refractory condition or timespan
event_codes Code that is triggered on events (e.g.
events Events supported by this group
method_choice The state update method selected by the user
namespace The group-specific namespace
resetter Reset neurons which have spiked (or perform arbitrary actions for
spikes The spikes returned by the most recent thresholding operation.
state_updater Performs numerical integration step
subexpression_updater Update the “constant over a time step” subexpressions
thresholder Checks the spike threshold (or abitrary user-defined events)
user_equations The original equations as specified by the user (i.e.

Methods

before_run([run_namespace])
run_on_event(event, code[, when, order]) Run code triggered by a custom-defined event (see NeuronGroup documentation for the specification of events).The created Resetter object will be automatically added to the group, it therefore does not need to be added to the network manually.
set_event_schedule(event[, when, order]) Change the scheduling slot for checking the condition of an event.
state(name[, use_units, level])

Details

_refractory

The refractory condition or timespan

event_codes

Code that is triggered on events (e.g. reset)

events

Events supported by this group

method_choice

The state update method selected by the user

namespace

The group-specific namespace

resetter

Reset neurons which have spiked (or perform arbitrary actions for user-defined events)

spikes

The spikes returned by the most recent thresholding operation.

state_updater

Performs numerical integration step

subexpression_updater

Update the “constant over a time step” subexpressions

thresholder

Checks the spike threshold (or abitrary user-defined events)

user_equations

The original equations as specified by the user (i.e. without the multiplied int(not_refractory) term for equations marked as (unless refractory))

before_run(run_namespace=None)[source]
run_on_event(event, code, when='after_resets', order=None)[source]

Run code triggered by a custom-defined event (see NeuronGroup documentation for the specification of events).The created Resetter object will be automatically added to the group, it therefore does not need to be added to the network manually. However, a reference to the object will be returned, which can be used to later remove it from the group or to set it to inactive.

Parameters:

event : str

The name of the event that should trigger the code

code : str

The code that should be executed

when : str, optional

The scheduling slot that should be used to execute the code. Defaults to 'after_resets'.

order : int, optional

The order for operations in the same scheduling slot. Defaults to the order of the NeuronGroup.
Returns:

obj : Resetter

A reference to the object that will be run.
set_event_schedule(event, when='after_thresholds', order=None)[source]

Change the scheduling slot for checking the condition of an event.

Parameters:

event : str

The name of the event for which the scheduling should be changed

when : str, optional

The scheduling slot that should be used to check the condition. Defaults to 'after_thresholds'.

order : int, optional

The order for operations in the same scheduling slot. Defaults to the order of the NeuronGroup.
state(name, use_units=True, level=0)[source]