3.1.7: Modeling Brain-Behaviour

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Another major method, which is used in cognitive neuroscience, is the use of neural networks (computer modelling techniques) in order to simulate the action of the brain and its processes. These models help researchers to test theories of neuropsychological functioning and to derive principles viewing brain-behaviour relationships.

A basic neural network.

In order to simulate mental functions in humans, a variety of computational models can be used. The basic component of most such models is a “unit”, which one can imagine as showing neuron-like behaviour. These units receive input from other units, which are summed to produce a net input. The net input to a unit is then transformed into that unit’s output, mostly utilizing a sigmoid function. These units are connected together forming layers. Most models consist of an input layer, an output layer and a “hidden” layer as you can see on the right side. The input layer simulates the taking up of information from the outside world, the output layer simulates the response of the system and the “hidden” layer is responsible for the transformations, which are necessary to perform the computation under investigation. The units of different layers are connected via connection weights, which show the degree of influence that a unit in one level has on the unit in another one.

The most interesting and important about these models is that they are able to "learn" without being provided specific rules. This ability to “learn” can be compared to the human ability e.g. to learn the native language, because there is nobody who tells one “the rules” in order to be able to learn this one. The computational models learn by extracting the regularity of relationships with repeated exposure. This exposure occurs then via “training” in which input patterns are provided over and over again. The adjustment of “the connection weights between units” as already mentioned above is responsible for learning within the system. Learning occurs because of changes in the interrelationships between units, which occurrence is thought to be similar in the nervous system.