Donald Hebb
In plain wordsA Canadian psychologist who proposed in 1949 that connections between brain cells strengthen when the cells are active together, an idea behind many learning rules for neural networks.
Canadian psychologist at McGill University whose book 'The Organization of Behavior' (1949) proposed the learning rule now called Hebbian learningHebbian learning, n.: The idea that a connection between two brain cells grows stronger when they are active at the same time — the principle behind the slogan 'cells that fire together wire together'.: when one neuron repeatedly takes part in firing another, the connection between them is strengthened. He argued that such changes bind neurons into cell assemblies that represent percepts and concepts, and that sequences of assemblies underlie thought, bridging psychology and neurophysiology when behaviorism dominated the field. The postulate, later supported by the discovery of long-term potentiation at synapses in the 1970s, became a foundation of connectionismconnectionism, n.: The view that minds and intelligent machines are best built from huge networks of simple, neuron-like units whose connection strengths are learned, rather than from explicit rules and symbols.: it underlies associative memories such as the Hopfield networkHopfield network, n.: A network of on–off units, all connected to one another, that stores patterns as stable states. Given a partial or noisy pattern, it settles into the closest stored one, like recalling a memory from a hint. and many unsupervised learning rules for neural networksneural network, n.: A kind of computer program that learns a task from examples by tuning thousands to billions of connections between simple number-crunching units, an arrangement loosely inspired by nerve cells in the brain.. Before joining McGill he studied with Karl Lashley at Harvard and worked with the neurosurgeon Wilder Penfield in Montreal; he later served as McGill's chancellor and as president of the American Psychological Association (1960).
Related
- Hebbian learningHebbian learning, n.: The idea that a connection between two brain cells grows stronger when they are active at the same time — the principle behind the slogan 'cells that fire together wire together'.
- connectionismconnectionism, n.: The view that minds and intelligent machines are best built from huge networks of simple, neuron-like units whose connection strengths are learned, rather than from explicit rules and symbols.
- Hopfield networkHopfield network, n.: A network of on–off units, all connected to one another, that stores patterns as stable states. Given a partial or noisy pattern, it settles into the closest stored one, like recalling a memory from a hint.
- artificial neuronartificial neuron, n.: The basic building block of a neural network: a tiny calculator that multiplies each incoming number by a weight, adds them up, and passes the total through a simple function to decide its output.
- unsupervised learningunsupervised learning, n.: Machine learning without answer keys: the computer looks at unlabeled data and finds structure on its own, such as groups of similar customers or the main ways in which data vary.
Sources
- Hebb, D. O. (1949). The Organization of Behavior: A Neuropsychological Theory. Wiley.