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The neural computational approach to cognitive and psychological processes is relatively new. However, Neural Computation and Psychology Workshops (NCPW), first held 16 years ago, lie at the heart of this fast-moving discipline, thanks to its interdisciplinary nature ? bringing together researchers from different disciplines such as artificial intelligence, cognitive science, computer science, neurobiology, philosophy and psychology to discuss their work on models of cognitive processes.Once again, the Eleventh Neural Computation and Psychology Workshop (NCPW11), held in 2008 at the University of Oxford (England), reflects the interdisciplinary nature and wide range of backgrounds of this field. This volume is a collection of peer-reviewed contributions of most of the papers presented at NCPW11 by researchers from four continents and 15 countries.
The neural computational approach to cognitive and psychological processes is relatively new. However, Neural Computation and Psychology Workshops (NCPW), first held 16 years ago, lie at the heart of this fast-moving discipline, thanks to its interdisciplinary nature — bringing together researchers from different disciplines such as artificial intelligence, cognitive science, computer science, neurobiology, philosophy and psychology to discuss their work on models of cognitive processes.Once again, the Eleventh Neural Computation and Psychology Workshop (NCPW11), held in 2008 at the University of Oxford (England), reflects the interdisciplinary nature and wide range of backgrounds of this field. This volume is a collection of peer-reviewed contributions of most of the papers presented at NCPW11 by researchers from four continents and 15 countries.
A cutting-edge reference source for the interdisciplinary field of computational cognitive modeling.
Connectionist Models in Cognitive Psychology is a state-of-the-art review of neural network modelling in core areas of cognitive psychology including: memory and learning, language (written and spoken), cognitive development, cognitive control, attention and action. The chapters discuss neural network models in a clear and accessible style, with an emphasis on the relationship between the models and relevant experimental data drawn from experimental psychology, neuropsychology and cognitive neuroscience. These lucid high-level contributions will serve as introductory articles for postgraduates and researchers whilst being of great use to undergraduates with an interest in the area of connectionist modelling.
Connectionist modelling and neural network applications had become a major sub-field of cognitive science by the mid-1990s. In this ground-breaking book, originally published in 1995, leading connectionists shed light on current approaches to memory and language modelling at the time. The book is divided into four sections: Memory; Reading; Computation and statistics; Speech and audition. Each section is introduced and set in context by the editors, allowing a wide range of language and memory issues to be addressed in one volume. This authoritative advanced level book will still be of interest for all engaged in connectionist research and the related areas of cognitive science concerned with language and memory.
Computational Models of Cognitive Processes collects refereed versions of papers presented at the 13th Neural Computation and Psychology Workshop (NCPW13) that took place July 2012, in San Sebastian (Spain). This workshop series is a well-established and unique forum that brings together researchers from such diverse disciplines as artificial intelligence, cognitive science, computer science, neurobiology, philosophy and psychology to discuss their latest work on models of cognitive processes.
This volume presents peer-reviewed versions of papers presented at the 14th Neural Computation and Psychology Workshop (NCPW14), which took place in July 2014 at Lancaster University, UK. The workshop draws international attendees from the cutting edge of interdisciplinary research in psychology, computational modeling, artificial intelligence and psychology, and aims to drive forward our understanding of the mechanisms underlying a range of cognitive processes.
This textbook provides an introduction and review of connectionist models applied to psychological topics. Chapters include basic reviews of connectionist models, their properties and their attributes. The application of these models to the domains of perception, memory, attention, word processing, higher language processing, and cognitive neuropsychology is then reviewed.
Philosophers and cognitive scientists reassess systematicity in the post-connectionist era, offering perspectives from ecological psychology, embodied and distributed cognition, enactivism, and other methodologies. In 1988, Jerry Fodor and Zenon Pylyshyn challenged connectionist theorists to explain the systematicity of cognition. In a highly influential critical analysis of connectionism, they argued that connectionist explanations, at best, can only inform us about details of the neural substrate; explanations at the cognitive level must be classical insofar as adult human cognition is essentially systematic. More than twenty-five years later, however, conflicting explanations of cognition do not divide along classicist-connectionist lines, but oppose cognitivism (both classicist and connectionist) with a range of other methodologies, including distributed and embodied cognition, ecological psychology, enactivism, adaptive behavior, and biologically based neural network theory. This volume reassesses Fodor and Pylyshyn's “systematicity challenge” for a post-connectionist era. The contributors consider such questions as how post-connectionist approaches meet Fodor and Pylyshyn's conceptual challenges; whether there is empirical evidence for or against the systematicity of thought; and how the systematicity of human thought relates to behavior. The chapters offer a representative sample and an overview of the most important recent developments in the systematicity debate. Contributors Ken Aizawa, William Bechtel, Gideon Borensztajn, Paco Calvo, Anthony Chemero, Jonathan D. Cohen, Alicia Coram, Jeffrey L. Elman, Stefan L. Frank, Antoni Gomila, Seth A. Herd, Trent Kriete, Christian J. Lebiere, Lorena Lobo, Edouard Machery, Gary Marcus, Emma Martín, Fernando Martínez-Manrique, Brian P. McLaughlin, Randall C. O'Reilly, Alex A. Petrov, Steven Phillips, William Ramsey, Michael Silberstein, John Symons, David Travieso, William H. Wilson, Willem Zuidema
At the fascinating frontiers of neurobiology, mathematics and psychophysics, this book addresses the problem of human and computer vision on the basis of cognitive modeling. After recalling the physics of light and its transformation through media and optics, Hérault presents the principles of the primate's visual system in terms of anatomy and functionality. Then, the neuronal circuitry of the retina is analyzed in terms of spatio-temporal filtering. This basic model is extended to the concept of neuromorphic circuits for motion processing and to the processing of color in the retina. For more in-depth studies, the adaptive non-linear properties of the photoreceptors and of ganglion cells are addressed, exhibiting all the power of the retinal pre-processing of images as a system of information cleaning suitable for further cortical processing. As a target of retinal information, the primary visual area is presented as a bank of filters able to extract valuable descriptors of images, suitable for categorization and recognition and also for local information extraction such as saliency and perspective. All along the book, many comparisons between the models and human perception are discussed as well as detailed applications to computer vision./a