Connectionist Models of Memory and Language Book

	Preface
	Acknowledgements
	Contributors
Sect. I	Memory	1
1	Competitive queuing and the articulatory loop	5
2	Temporal chunking and synchronization using a modular recurrent network architecture	31
3	Learning to learn in a connectionist network: the development of associative learning	41
4	Interference and discrimination in neural net memory	57
5	Transfer of learning in back-propagation and in related neural network models	73
6	Interactions between short- and long-term weights: applications for cognitive modelling	95
Sect. II	Reading	113
7	Self-learning and connectionist approaches to text-phoneme conversion	117
8	Reading exception words and pseudowords: are two routes really necessary?	145
9	Neural network models of reading: solving the alignment problem without Wickelfeatures	161
Sect. III	Computation and Statistics	179
10	Cortical neurocomputation, language and cognition	181
11	Neural networks: the new statistical models of mind	207
12	Acquiring syntactic information from distributional statistics	229
Sect. IV	Speech and Audition	243
13	Onset/offset filters for the segmentation of sound	247
14	Time-warping tasks and recurrent neural networks	269
15	Bottom-up connectionist modelling of speech	289
16	Interactive models of lexicalization: some constraints from speech error, picture naming and neuropsychological data	311
	Index	333