spynnaker.pyNN.models.neuron.threshold_types package

Module contents

class spynnaker.pyNN.models.neuron.threshold_types.AbstractThresholdType(structs: List[Struct], units: Dict[str, str])

Bases: AbstractStandardNeuronComponent

Represents types of threshold for a neuron (e.g., stochastic).

Parameters:

  • structs (list(Struct)) – The structures of the component

  • units (dict) – The units to use for each parameter

class spynnaker.pyNN.models.neuron.threshold_types.ThresholdTypeFixedProb(v_thresh: float | Iterable[float] | RandomDistribution | ndarray[Any, dtype[floating]], p_thresh: float | Iterable[float] | RandomDistribution | ndarray[Any, dtype[floating]], seed: int)

Bases: AbstractThresholdType

A threshold that spikes with a fixed probability when over a static value.

Parameters:

  • v_thresh (float or iterable(float) or RandomDistribution or (mapping) function) – \(V_{thresh}\)

  • p_thresh (float or iterable(float) or RandomDistribution or (mapping) function) – \(P_{thresh}\)

  • seed – Random number generator seed

add_parameters(parameters: RangeDictionary[float])[source]

Add the initial values of the parameters to the parameter holder.

Parameters:

parameters (RangeDictionary) – A holder of the parameters

add_state_variables(state_variables: RangeDictionary[float])[source]

Add the initial values of the state variables to the state variables holder.

Parameters:

state_variables (RangeDictionary) – A holder of the state variables

property p_thresh: float | Iterable[float] | RandomDistribution | ndarray[Any, dtype[floating]]

\(P_{thresh}\)

property v_thresh: float | Iterable[float] | RandomDistribution | ndarray[Any, dtype[floating]]

\(V_{thresh}\)

class spynnaker.pyNN.models.neuron.threshold_types.ThresholdTypeMaassStochastic(du_th: float | Iterable[float] | RandomDistribution | ndarray[Any, dtype[floating]], tau_th: float | Iterable[float] | RandomDistribution | ndarray[Any, dtype[floating]], v_thresh: float | Iterable[float] | RandomDistribution | ndarray[Any, dtype[floating]])

Bases: AbstractThresholdType

A stochastic threshold.

Habenschuss S, Jonke Z, Maass W. Stochastic computations in cortical microcircuit models. PLoS Computational Biology. 2013;9(11):e1003311. doi:10.1371/journal.pcbi.1003311

Parameters:

  • du_th (float or iterable(float) or RandomDistribution or (mapping) function) – \(du_{thresh}\)

  • tau_th (float or iterable(float) or RandomDistribution or (mapping) function) – \(\tau_{thresh}\)

  • v_thresh (float or iterable(float) or RandomDistribution or (mapping) function) – \(V_{thresh}\)

add_parameters(parameters: RangeDictionary[float])[source]

Add the initial values of the parameters to the parameter holder.

Parameters:

parameters (RangeDictionary) – A holder of the parameters

add_state_variables(state_variables: RangeDictionary[float])[source]

Add the initial values of the state variables to the state variables holder.

Parameters:

state_variables (RangeDictionary) – A holder of the state variables

property du_th: float | Iterable[float] | RandomDistribution | ndarray[Any, dtype[floating]]

\(du_{thresh}\)

property tau_th: float | Iterable[float] | RandomDistribution | ndarray[Any, dtype[floating]]

\(\tau_{thresh}\)

property v_thresh: float | Iterable[float] | RandomDistribution | ndarray[Any, dtype[floating]]

\(V_{thresh}\)

class spynnaker.pyNN.models.neuron.threshold_types.ThresholdTypeStatic(v_thresh: float | Iterable[float] | RandomDistribution | ndarray[Any, dtype[floating]])

Bases: AbstractThresholdType

A threshold that is a static value.

Parameters:

v_thresh (float or iterable(float) or RandomDistribution or (mapping) function) – \(V_{thresh}\)

add_parameters(parameters: RangeDictionary[float])[source]

Add the initial values of the parameters to the parameter holder.

Parameters:

parameters (RangeDictionary) – A holder of the parameters

add_state_variables(state_variables: RangeDictionary[float])[source]

Add the initial values of the state variables to the state variables holder.

Parameters:

state_variables (RangeDictionary) – A holder of the state variables

property v_thresh: float | Iterable[float] | RandomDistribution | ndarray[Any, dtype[floating]]

\(V_{thresh}\)