We now turn to the important question of how memory is actually stored. As you can expect, there are a number of theories that attempt to explain this. Early work had suggested that there were brain cells that stored specific information. For example, there may be brain cells that store information about faces or some that store information about paintings and so on. Obviously, there is too much information to be stored in this way. A logical way to store information would be to organize it as a pattern and store that pattern in a network of brain cells.
The advantage of storing information in networks as opposed to discrete chunks is that memory will not be totally lost. It will be accessible through different routes. Typically, when we are trying to remember a name or a date, we try and use associated information—things like ‘I know it rhymes with car’ or, ‘It was a company party when I had met him’ and so on. These associations help us in recalling many facts. The common term used for such a network is ‘Neural Network’. It is interesting to note that this term has entered popular literature due to its use in computer science.
Some years back, modelling human memory and developing programmes to mimic the human model of learning were a rage in computer science research and the term neural network entered the popular lexicon.
I will give a very simple description of how a neural network works in storing information. Consider a network of neurons that are interconnected. At the bottom of the network are the neurons that store one simple fact. Say, each neuron at the bottom knows one car model. The neuron at the next level has connections to all the other neurons. At the lowest level, one of the neurons knows about a Maruti Zen while its neighbour may know about an Indica.
The next step up knows about different medium-sized cars and knows about ‘B-segment or mid-sized’ cars. It has knowledge that does not come from any single input, but emerges from the convergence of information feeding into it. The next level up may know about cars from different countries and may be associated with information about those countries and so on. We take advantage of such linked informa-tion when trying to recall a particular piece of information.
The above is a wildly simplistic explanation of how memory is organized. As you can imagine, there are no specialized neurons that know about cars or other facts for that matter. Neuroscientists think of learning and storing of information as a process that strengthens some part of a neural network.
The obvious question to ask is how does such strengthening take place? Recall from our discussion on neural communication in chapter 10 on depression, that neurons communicate with each other using neurotransmitters. The neurotransmitters with a role in depression that we looked at were serotonin and norepinephrine. The stores of long-term memory use the neurotransmitter glutamate. This is a very excitable transmitter and the neurons that are sensitive to this transmitter have two very important properties:
• The synapses are non-linear in their function. To understand this concept better, let us take the case of two neurons communicating using glutamate. The first neuron has some exciting information (metaphorically speaking) to pass on to the second neuron. It sends out some glutamate. Nothing happens. It sends out some more glutamate and still nothing happens. It is only when the glutamate passes some threshold that the second neuron receives it and gets all excited.
Many of us have had this experience when learning some new or complicated subject. We read about it 20 times and it is all a big mystery. Somewhere around the 21st time, we have that ‘Aha!’ moment and it becomes clear. On a simplistic level, it can be said that the threshold for excitation has been passed.
• After a certain number of excitations, the synapse becomes persistently more excitable. Say, a neuron has been excited repeatedly by the glutamate. At some point, the neuron becomes super sensitive to the glutamate. Now, even a smidgen of the glutamate can get the neuron all excited. This is the stage when we say that the neuron has just ‘learned’ something. The scientific term for this phenomenon is ‘potentiation’. The important thing to note is that this potentiation can last for a very long time.