D. O. Hebb

For decades, the fundamental processes underlying memory and attention have been understood within an "information processing" framework in which information passes from one processing stage to another, leading eventually to a response. More recently, however, the attempt to build a general theoretical framework for information processing has been largely supplanted in favor of two more recent approaches: parallel/connectionist models of processing and direct investigations of brain function. In Attention and Memory, cognitive psychologist Nelson Cowan reconciles theoretical conflicts in the literature to presents an important, analytical update of the traditional information-processing approach by modifying it to incorporate the last few decades of research on memory, attention, and brain functioning. Throughout, the author cogently considers and ultimately refutes recent challenges to the fundamental assumption of the existence of special short-term memory and selective attention faculties. He also draws a new distinction between memory processes operating inside and outside of the focus of attention. Coherent and balanced, the book offers a clearer understanding of how memory and attention operate together, and how both functions are produced by brain processes. It will be welcomed by students and researchers in cognitive psychology.

This thoroughly, thoughtfully revised edition of a very successful textbook makes the principles and the details of neural network modeling accessible to cognitive scientists of all varieties as well as to others interested in these models. Research since the publication of the first edition has been systematically incorporated into a framework of proven pedagogical value. Features of the second edition include: * A new section on spatiotemporal pattern processing * Coverage of ARTMAP networks (the supervised version of adaptive resonance networks) and recurrent back-propagation networks * A vastly expanded section on models of specific brain areas, such as the cerebellum, hippocampus, basal ganglia, and visual and motor cortex * Up-to-date coverage of applications of neural networks in areas such as combinatorial optimization and knowledge representation As in the first edition, the text includes extensive introductions to neuroscience and to differential and difference equations as appendices for students without the requisite background in these areas. As graphically revealed in the flowchart in the front of the book, the text begins with simpler processes and builds up to more complex multilevel functional systems. For more information visit the author's personal Web site at www.uta.edu/psychology/faculty/levine/

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.