# 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, axon_spike=None, reset=None, axon_reset=None, refractory=None, functions=None, name='', description='', extra_values={})[source]

Base class to define a neuron.

Parameters: 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). axon_spike – condition to emit an axonal spike (only for spiking neurons and optional). The axonal spike can appear additional to the spike and is independent from refractoriness of a neuron. reset – changes to the variables after a spike (only for spiking neurons). axon_reset – changes to the variables after an axonal 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).