Directions for research

Part 1 Network architecture: "De memoria et reminiscentia", Aristotle "Cybernetics", Norbert Wiener "Outline of a theory of thought-processes and thinking machines", E.R. Caianiello "Adaptive systems using learning matrices", K. Steinbuch and E. Schmitt "A memory storage model utilizing spatial correlation functions", James A. Anderson "Associatron - a model of associative memory", Kaoru Nakano "The holographic hypothesis of memory structure in brain function and perception", Karl H. Pribram et al "How patterned neural connections can be set up by self-organization", D.J. Willshaw and C. von der Malsburg "Topographic organization of nerve fields", Shun-ichi Amari "ART 2 - self-organization of stable category recognition codes for analog input patterns", Gail A. Carpenter and Stephen Grossberg "Bidirectional associative memories", Bart Kosko "Sparse distributed memory", Pentti Kanerva. Part 2 Computation and neurobiology: "What the frog's eye tells the frog's brain", J.Y. Lettvin et al "Single units and sensation - a neuron doctrine for perceptual psychology?", H.B. Barlow "Large receptive fields and spatial transformations in the visual system", J.T. McIlwain "The extent to which biosonar information is represented in the bat auditory context", Nobuo Suga "Learning by selection", J.-P. Changeux et al "Neuronal group selection in the cerebral cortex", Gerald M. Edelman and Leif H. Finkel "Plasticity in the organization of adult cerebral cortical maps - a computer simulation based on neuronal group selection", John C. Pearson et al "Tensor network theory of the metaorganization of functional geometries in the central nervous system", A. Pellionisz and R. Llinas "How brains make chaos in order to make sense of the world", Christine A. Skarda and Walter J. Freeman "Computational maps in the brain", Eric I. Knudsen et al "A back-propagation programmed network that simulates response properties of a subset of posterior parietal neurons", David Zipser and Richard A. Andersen "Long-term synaptic potentiation", Thomas H. Brown et al. Part 3 Statistics and pattern classification: "Learning machines", Nils Nilsson "Nearest neighbor pattern classification", T.M. Cover and P.E. Hart "Practical techniques for pattern recognition", Bruce G. Batchelor "A neural model for category learning", Douglas L. Reilly et al "A relaxation model for memory with high storage density", Charles M. Bachmann et al "Statistical pattern recognition with neural networks - benchmarking studies", Teuvo Kohonen et al "Self-organization in a perceptual network", Ralph Linsker "Image compression by back propagation - an example of extensional programming", Garrison W. Cottrell et al "Neural networks and principal component analysis - learning from examples without local minima", Pierre Baldi and Kurt Hornik. Part 4 Current applications and future problems: "Perceptrons", Marvin L. Minsky and Seymour A. Papert. (Part contents).