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There are two different kinds of variables in neural networks. One class of variables represents the activity of the nerve cells, or neurons. The other class of variables describes the synapses, or connections, between the nerve cells. A complete model of an adaptive neural system requires two sets of dynamical equations, one for each class of variables, to specify the evolution and behavior of the neural system.