DESCRIPTION:
Connectionism is a way of modelling how the brain uses streams of sensory inputs to understand the world and produce behaviour, based on cognitive processes which actually occur. This book describes the principles, and their application to explaining how the brain produces speech, forms memories and recognises faces, how intellect develops, and how it deteriorates after brain damage. Part I explores the basic concepts, the architecture and properties of the most common connectionist models, and how connectionist learning rules work. Part II describes and evaluates connectionist models of a variety of cognitive processes, including the learning and production of speech, the formation of episodic memories and visual representations, the development of cognitive processes in infancy, and their breakdown in brain-damaged patients. The models range from some well-known classics to others at the frontiers of current research.
Each chapter ends with a list of recommended further reading. Also included is a disk with the software for running tlearn, a user-friendly simulator for connectionist modelling of cognitive processes, which will run on either PCs or Macs. The software includes exercises to introduce the simulator, and working copies to explore some of the models described in the text. A reference handbook for tlearn is included to enable readers to build their own models. The authors, as well as being leading researchers in their field, have extensive experience of teaching connectionism to undergraduates. They have written the first comprehensive, up-to-date textbook on connectionist modelling, designed specifically for advanced undergraduates, and accessible to those with only limited knowledge of mathematics. This will be an essential introductory text for all students in psychology or cognitive science taking a course on connectionism.
CONTENTS:
1: The basics of connectionist information processing
2: The appeal of parallel distributed processing for modelling cognition
3: Pattern association
4: Auto association
5: Training a multi-layer network with an error signal: hidden units and backpropagation
6: Competitive networks
7: Recurrent networks
8: Reading aloud
9: Language acquisition
10: Connectionism and cognitive development
11: Connectionist neuropsychology - lesioning neural networks
12: Mental representation: Rules, symbols, and connectionist networks
13: Network models of brain function
14: Evolutionary connectionism
15: A selective history of connectionism before 1986
Author Information:
Peter McLeod, Kim Plunkett, and Edmund T. Rolls, all at Department of Experimental Psychology, Oxford University
