Artificial Neural Nets: The Head or Tail of the Dog?

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Abstract

Originally published in Contemporary Psychology: APA Review of Books, 1994, Vol 39(2), 127–129. Reviews the book, The Computational Brain by Patricia S. Churchland and Terrence J. Sejnowski (1992). The authors are doing nothing less than making a case for how neuroscience should proceed in the future. Sejnowski and Churchland believe that the nascent field of computational neuroscience should lead the way, ideally with computational models leading to new wet-lab experiments, subsequently leading to new and better computational models Given the overwhelming diversity and quantity of the raw data being produced by neuroscientists on a weekly basis (to say nothing of the quality), their agenda makes a lot of sense. The Computational Brain represents a major effort to bring together the fields of neurophilosophy and neural networks into one comprehensive tome. The seven chapters and Appendix that make up the book are structured in such a way as to lead the reader from an overview of classical neuroscience through the basics of artificial neural networks. From those basics, Churchland and Sejnowski proceed to deal sequentially with perception, memory formation, motor integration, and their summing up in a conclusions chapter. (PsycINFO Database Record (c) 2006 APA, all rights reserved)

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