Connectionist models of memory and language
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Part 1 Memory: competitive queuing and the articulatory loop, David W. Glasspool temporal chunking and synchronization using a modular recurrent network architecture, Dimitrios Bairaktaris learning to learn in a connectionist network - thedevelopment of associative learning, Gordon D. A. Brown, Tim Preece, and Charles Hulme interference and discrimination in neural net memory, Noel E. Sharkey and Amanda J.C. Sharkey transfer of learning in backpropagation and in related neural networkmodels, Jacob M.J. Murre interactions between short and long- term weights - applications for cognitive modelling, Joseph P. Levy and Dimitrios Bairaktaris. Part 2 Reading: self-learnning and connectionist approaches to text-phoneme conversion, R.I.Damper reading exception words and pseudowords - are two routes really necessary , D.C. Plaut, J.L.McClelland, and M.S. Seidenberg neural network models of reading - solving the alignment problem without wickelfeatures, J.A. Bullinaria. Part 3Computation and statistics: cortical neural computation, language and cognition, Robert W. Kentridge neural networks - the new statistical models of mind, Nick Chater acquiring syntactic information from distributional statistics, Steve Finch, NickChater and Martin Redington. Part 4 Speech and audition: onset/offset filters for the segmentation of sound, Leslie s. Smith time-warping tasks and recurrent neural networks, Mukhlis Abu-Baker and Nick Chater bottom up connectionist modelling of speech,Paul Cairns, Richard Shillcock, Nick Chater, and Joseph P. Levy interactive models of lexicalization - some constrants from speech error, picture naming and neuropsychological data, Trevor A. Harley, and Siobhan B.G. MacAndrew.