Artificial neural networks were inspired by the behavior of biological neurons. In 1958, Frank Rosenblatt created the Perceptron, a mathematical neuron model that basically multiplies weights (w1, w2, w3...) by input signals (x1, x2, x3...), adds them all up and the result is the activation or not of the output neuron.
This is a companion discussion topic for the original entry at https://community.robotshop.com/index.php/blog/show/deep-learning-vs-neuromorphic-computing-in-robotic-systems