The Brain and the Computer

Paper Summary:

The paper explains that when dealing with models of mental representation, or knowledge processing, there are many differences between computer modules used for artificial intelligence and research, and models inspired by the human brain. The paper examines the implications of these differences that make the two models suitable for different purposes. The paper concludes that both brain and computer models are complex and require vast understanding of the way in which information is represented.

From the Paper:

"Models of information processing in relation to knowledge representation based on the human brain rely on the basic principle that knowledge is stored in a highly organized fashion. The brain can retrieve information in fractions of a second. The human brain models of information processing presuppose that mental representations of information assume three forms of representation. The first is the prepositional representation. This is related to natural language. The form of representation is non-analog, non-iconic, discrete, and arbitrary to reference. The second form is that of mental models. These models are structural analogies to the real world. Finally, the third form is that of mental imagery, which is a perceptual correlation to a model from a single point of view. This representation is analog, iconic, continuous, and referentially isomorphic (Johnson-Laird and Byrne, 1991)."

Sample of Sources Used:

• Bechtel, W. (1991). Connectionism and the philosophy of mind: An overview. In T. Horgan and J. Tienson, Eds., Connectionism and the Philosophy of Mind. Dordrecht: Kluwer, pp. 30-59.
• Johnson-Laird, P.N & Byrne, R.M. (1991). Deduction. Hillsdale, N.J.: Lawrence Erlbaum.
• Preece, J., Rogers, H., Sharp, D., Benyon, S., & Carey, T. (1994). Human Computer Interaction. Boston, M.A.: Addison Wesley.
• Sternberg, R.J. (2006). Cognitive Psychology, 4th Ed. Boston, M.A.: Thompson Learning.

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