Associative learning and Hebb’s rule: Cells that fire together wire together

Have you ever wondered how we learn new things? How do we form associations between different stimuli, events, or ideas? How do we remember what we have learned? The answers to these questions lie in the fascinating field of associative learning, which is the study of how the brain links different pieces of information together.

Associative learning occurs when two or more elements (such as objects, sights, sounds, ideas, or behaviours) become connected in our brains through a process called conditioning. Conditioning is the formation of a new response to a previously neutral or unrelated stimulus. For example, if you hear a bell ring every time you get food, you will soon learn to associate the bell with food and salivate when you hear it. This is an example of classical conditioning, which was discovered by the Russian physiologist Ivan Pavlov in his famous experiments with dogs.

Operant conditioning is another type of associative learning developed by the American psychologist B.F. Skinner. Operant conditioning is learning a new behaviour through the consequences of actions. For example, if you press a lever and get a reward, you will learn to press the lever more often. If you press the lever and get a punishment, you will learn to avoid pressing the lever. This is how animals and humans learn to adapt to their environment and achieve their goals.

But how does associative learning happen in the brain? How do the neurons, the basic units of the nervous system, communicate and change as a result of learning? This is where Hebb’s rule comes in. Hebb’s rule is a principle of neural plasticity that explains how learning and memory formation occur. It states that when two or more neurons are activated together repeatedly, the strength of the connection between them increases. This means that the neurons become more efficient at firing each other, forming a neural network. Hebb’s rule was proposed by the Canadian neuropsychologist Donald Hebb in his book The Organization of Behavior (1949).

Hebb’s rule is often summarized as “Cells that fire together wire together“. This catchy phrase captures the essence of Hebb’s theory, which is that learning is the result of the modification of synaptic connections between neurons. Synapses are the junctions where neurons communicate with each other by releasing chemical signals called neurotransmitters. When a neuron fires, it sends a signal to the next neuron, which may or may not fire depending on the strength of the synapse. Hebb’s rule suggests that the more often two neurons fire together^*, the stronger the synapse becomes, and the more likely they are to fire together in the future. This is how neural networks are formed and reinforced, creating patterns of activity that represent what we have learned.

^*Please note that the cells do not fire together at the exact same time. They fire together in succession. Hebb emphasized that cell A has to trigger cell B to work, and this can only happen if cell A works earlier, not at once, with cell B.

Many experimental studies have supported Hebb’s rule, which has shown that synaptic strength can change due to learning. Timothy Bliss and Terje Lømo discovered long-term potentiation (LTP), a long-lasting increase in synaptic strength after repeated stimulation in the late 60s. LTP is considered to be one of the main mechanisms of memory formation in the brain. Conversely, long-term depression (LTD) is a decrease in synaptic strength after low-frequency stimulation, which may be involved in forgetting or pruning of unused connections.

Hebb’s rule has also been applied to artificial neural networks, which are computer models that mimic the structure and function of biological neural networks. Artificial neural networks can learn from data and perform tasks such as pattern recognition, classification, prediction, and optimization. Hebbian learning is one of the simplest and oldest learning rules in artificial neural networks, which updates the weights of the connections according to the correlation between the inputs and outputs of the neurons.

Key takeaways

• Associative learning is the process of connecting or associating two or more things together in order to understand them better.
• There are two main types of associative learning: classical conditioning and operant conditioning. Classical conditioning is learning a new response to a previously neutral or unrelated stimulus. Operant conditioning is learning a new behaviour through the consequences of actions.
• Hebb’s rule is a principle of neural plasticity that explains how learning and memory formation occur. It states that when two or more neurons are activated together repeatedly, the strength of the connection between them increases. This means that the neurons become more efficient at firing each other, forming a neural network.
• Hebb’s rule is often summarized as “Cells that fire together wire together”. This phrase captures the essence of Hebb’s theory, which is that learning is the result of the modification of synaptic connections between neurons.