Hebbian Theory

What Does Hebbian Theory Mean?

Hebbian theory is a theoretical type of cell activation model in artificial neural networks that assesses the concept of “synaptic plasticity” or dynamic strengthening or weakening of synapses over time according to input factors.


Hebbian theory is also known as Hebbian learning, Hebb's rule or Hebb's postulate.

Techopedia Explains Hebbian Theory

Hebbian theory is named after Donald Hebb, a neuroscientist from Nova Scotia who wrote “The Organization of Behavior” in 1949, which has been part of the basis for the development of artificial neural networks.

In modern artificial neural networks, algorithms can update weights of neural connections. Professionals sometimes talk about “Hebb’s rule” that describes how these connections work and how they change. Part of the appeal of Hebbian theory is the idea that by changing neural weights and associations, engineers can get different results out of sophisticated artificial neural networks.


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Margaret Rouse

Margaret Rouse is an award-winning technical writer and teacher known for her ability to explain complex technical subjects to a non-technical, business audience. Over the past twenty years her explanations have appeared on TechTarget websites and she's been cited as an authority in articles by the New York Times, Time Magazine, USA Today, ZDNet, PC Magazine and Discovery Magazine.Margaret's idea of a fun day is helping IT and business professionals learn to speak each other’s highly specialized languages. If you have a suggestion for a new definition or how to improve a technical explanation, please email Margaret or contact her…