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Memory and the brain
How Memory Works
Forgetting and Amnesia

Help Linked Module: The Hebb Legacy Linked Module: Apprentissage automatique : les réseaux de neurons
History Module:  D. O. Hebb (1904-1985),  Father of Cognitive Psychobiology
Original modules
Experiment Module: Specificity and Associativity of LTP Specificity and Associativity of LTP

Conscious learning is not the only thing that can strengthen the connections in a neural network. Our brain is also designed to detect recognizable patterns in the complex environment in which we live, and encode them in its neural networks automatically.

Thus, we learn some things effortlessly–such as what somebody’s face looks like–while others, such as theoretical mathematics, take more work. It all depends on the networks that already exist in our brains. The presence of these networks can be understood in light of their usefulness in the evolution of our species.


Learning depends on the plasticity of the circuits in the brain - the ability of the neurons to make lasting changes in the efficiency of their synaptic transmission.

The brain can thus be said to store information in networks of modified synapses (the arrangement of which constitutes the information) and to retrieve this information by activating these networks.

Our understanding of the rules that govern association and the networking of neurons goes back to the groundbreaking work done by Donald Hebb over 50 years ago. Hebb had an intuition that if two neurons are active at the same time, the synapses between them are strenghtened. This hypothesis inspired many researchers, and the first mechanism supporting it, long-term potentiation (LTP), was discovered in the early 1970s.

The neurons involved in establishing a network must already be connected by synapses in order for these synapses to be strengthened or weakened. Networks are thus fashioned out of pre-existing “wiring”. Some of these pre-wired networks, such as those in the hippocampus, play a key role in the formation of memories.


Even today, Hebb’s rule, as it is often known, remains one of the primary factors for predicting which synapses will be strengthened in a network of neurons. More recent research has uncovered other characteristics of the networking of groups of neurons. We now know, for example, that the LTP that leads to synaptic strengthening is very specific to neurons that are activated simultaneously, and only to such neurons. We also know that in addition to being associative, LTP can be cooperative: the activity of several neurons converging onto a single neuron facilitates the strengthening of these synapses.

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