Biological Neuron Model - Artificial Neuron Abstraction

Artificial Neuron Abstraction

The most basic model of a neuron consists of an input with some synaptic weight vector and an activation function or transfer function inside the neuron determining output. This is the basic structure used in artificial neurons, which in a neural network often looks like

where y_i is the output of the i th neuron, x_j is the j th input neuron signal, w_ij is the synaptic weight between the neurons i and j, and φ is the activation function. Some of the earliest biological models took this form until kinetic models such as the Hodgkin-Huxley model became dominant.