Associating neural networks with neurobiology, for instance, automatically associates neurons, synapses, dendrites, and other related terminology to computerized neural networks but, in so doing, it tends to narrow the scientist's field of vision. Other material that could potentially be of use may be ignored because it is not traditionally associated with neurobiology, even though it may greatly enhance the activity or precision of the neural network. Combining experience in AI and studies in cognitive psychology gives us a better understanding of the cognitive processes involved in software development, allowing us the possibility of simulating true intelligence despite the technological structures we must adhere to. A potential combination of these areas can be found in a parallel fuzzy neural network using memory and thought patterns borrowed from cognitive psychology. Fuzzy logic allows us to make mathematical calculations and judgements in situations of uncertainty.
Neural networks allow systems to learn and adapt to new material.
Parallel processing imitates the human thought process by allowing computations to be simultaneously made and distributed throughout a computer system. And cognitive psychology gives us a place to start. More details in these areas will be provided when deviations are taken from traditionally accepted viewpoints, but it would be impossible to provide a firm background in these areas within the length of this paper.