Just like human brains, Artificial Neural Networks are made of building blocks known as neurons. The neurons are usually arranged in array-like structures known as the input, hidden and output layers. Each layer consists of at least one neuron. Each neuron is represented by a mathematical function that transforms the incoming signals from the layer below into an outgoing signal. This process is repeated until the neural network output (prediction) is produced. See also STATISTICA Neural Networks.