What is being proposed appears to be Hebbian learning rule and the paper does not even mention that or the Hebb network, why? By the way, Hebbian learning rule was proposed in 1949 and is one of the pioneering work that demonstrated neuron-based models are worth investigation.
Is this really just Hebbian learning? That's often stated as "cells that fire together wire together", and I can see how that can line up with FF increasing the 'goodness' of actual data. But decreasing the 'goodness' of negative data seems like a qualitatively different mechanism.
What you are saying is half truth. If a cell excites (or inhibits) another cell repeatedly enough that its ability to excite (or inhibit) that neighboring cell improves over time.
"fire together" originally meant fire in same direction, but Hebb's rule was extended quite early to mean that if some cells inhibit some others too often, wiring in that direction will get stronger.
