3.2. Neuron

Neurons are container objects for all information corresponding to a special neuron type. This encapsulation allows a higher readability of the code. Through derivation of ANNarchy.Neuron, the user can define the neuron types he needs in his model.

The type of the neuron (rate-coded or spiking) depends on the presence of the 'spike' argument.

3.2.1. Class Neuron

class ANNarchy.Neuron(parameters='', equations='', spike=None, reset=None, refractory=None, functions=None, name='', description='', extra_values={})[source]

Base class to define a neuron.


  • parameters: parameters of the neuron and their initial value.
  • equations: equations defining the temporal evolution of variables.
  • functions: additional functions used in the variables’ equations.
  • spike: condition to emit a spike (only for spiking neurons).
  • reset: changes to the variables after a spike (only for spiking neurons).
  • refractory: refractory period of a neuron after a spike (only for spiking neurons).
  • name: name of the neuron type (used for reporting only).
  • description: short description of the neuron type (used for reporting).