Author
Donald O. Hebb
1 reading card from 1 book · 1949.
1 card
The Organization of Behavior · 1949
Neurons that fire together wire together: learning is local, not commanded from above.
Hebb argued that learning lives in the connections between neurons, not in a central command post. His mechanism is local: when one neuron repeatedly helps fire another, the link between them becomes more effective. No supervisor is needed to tell each cell what to do. This rule, now called the Hebbian rule, became the foundation of learning in neural networks. Neuromorphic chips take it one letter further by putting it into silicon. Carver Mead and Misha Mahowald built analog circuits in which each transistor imitates a neuron, and the connections between them carry a weight that changes exactly like a synapse. In their chips, for instance the silicon retina, pixels talk through pulses, just like biological neurons. Spiking networks run on the same principle: artificial neurons send brief events instead of continuous numbers, and they learn from the coincidence of pulses. The engineering target is clear: the brain runs on roughly 20 watts, so neuromorphic chips chase that same ratio of computation to energy, not raw speed.
“When an axon of cell A is near enough to excite a cell B and repeatedly or persistently takes part in firing it, some growth process or metabolic change takes place in one or both cells such that A's efficiency, as one of the cells firing B, is increased.”