NLP Glossary: Hebbian Theory

As extracted from WikipediaDendritesMerge
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In 1929, Hans Berger discovered that the mind exhibits continuous electrical activity and cast doubt on the Pavlovian model of perception and response because, now, there appeared to be something going on in the brain even without much stimulus.

At the same time, there were many mysteries. For example, if there was a method for the brain to recognize a circle, how does it recognize circles of various sizes or imperfect roundness? To accommodate every single possible circle that could exist, the brain would need a far greater capacity than it has.

Another theory, the Gestalt theory, stated that signals to the brain established a sort of field. The form of this field depended only on the pattern of the inputs, but it still could not explain how this field was understood by the mind.

The behaviorist theories at the time did well at explaining how the processing of patterns happened. However, they could not account for how these patterns made it into the mind.

Hebb combined up-to-date data about behavior and the mind into a single theory. And, while the understanding of the anatomy of the brain did not advance much since the development of the older theories on the operation of the brain, he was still able to piece together a theory that got a lot of the important functions of the brain right.

His theory became known as Hebbian theory and the models which follow this theory are said to exhibit Hebbian learning. This method of learning is best expressed by this quote from the book:

When an axon of cell A is near enough to excite 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

This is often paraphrased as “Neurons that fire together wire together.” It is commonly referred to as Hebb’s Law.

The combination of neurons which could be grouped together as one processing unit, Hebb referred to as “cell-assemblies”. And their combination of connections made up the ever-changing algorithm which dictated the brain’s response to stimuli.

Not only did Hebb’s model for the working of the mind influence how psychologists understood the processing of stimuli within the mind but also it opened up the way for the creation of computational machines that mimicked the biological processes of a living nervous system. And while the dominant form of synaptic transmission in the nervous system was later found to be chemical, modern artificial neural networks are still based on the transmission of signals via electrical impulses that Hebbian theory was first designed around.

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