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Motivation, Emotion, and Goal Direction in Neural Networks

Author: Daniel S. Levine

Publisher: Psychology Press

Published: 2014-01-14

Total Pages: 468

ISBN-13: 1317784553

The articles gathered in this volume represent examples of a unique approach to the study of mental phenomena: a blend of theory and experiment, informed not just by easily measurable laboratory data but also by human introspection. Subjects such as approach and avoidance, desire and fear, and novelty and habit are studied as natural events that may not exactly correspond to, but at least correlate with, some (known or unknown) electrical and chemical events in the brain.

Fundamentals of Neural Network Modeling

Author: Randolph W. Parks

Publisher: MIT Press

Published: 1998

Total Pages: 450

ISBN-13: 9780262161756

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Provides an introduction to the neural network modeling of complex cognitive and neuropsychological processes. Over the past few years, computer modeling has become more prevalent in the clinical sciences as an alternative to traditional symbol-processing models. This book provides an introduction to the neural network modeling of complex cognitive and neuropsychological processes. It is intended to make the neural network approach accessible to practicing neuropsychologists, psychologists, neurologists, and psychiatrists. It will also be a useful resource for computer scientists, mathematicians, and interdisciplinary cognitive neuroscientists. The editors (in their introduction) and contributors explain the basic concepts behind modeling and avoid the use of high-level mathematics. The book is divided into four parts. Part I provides an extensive but basic overview of neural network modeling, including its history, present, and future trends. It also includes chapters on attention, memory, and primate studies. Part II discusses neural network models of behavioral states such as alcohol dependence, learned helplessness, depression, and waking and sleeping. Part III presents neural network models of neuropsychological tests such as the Wisconsin Card Sorting Task, the Tower of Hanoi, and the Stroop Test. Finally, part IV describes the application of neural network models to dementia: models of acetycholine and memory, verbal fluency, Parkinsons disease, and Alzheimer's disease. Contributors J. Wesson Ashford, Rajendra D. Badgaiyan, Jean P. Banquet, Yves Burnod, Nelson Butters, John Cardoso, Agnes S. Chan, Jean-Pierre Changeux, Kerry L. Coburn, Jonathan D. Cohen, Laurent Cohen, Jose L. Contreras-Vidal, Antonio R. Damasio, Hanna Damasio, Stanislas Dehaene, Martha J. Farah, Joaquin M. Fuster, Philippe Gaussier, Angelika Gissler, Dylan G. Harwood, Michael E. Hasselmo, J, Allan Hobson, Sam Leven, Daniel S. Levine, Debra L. Long, Roderick K. Mahurin, Raymond L. Ownby, Randolph W. Parks, Michael I. Posner, David P. Salmon, David Servan-Schreiber, Chantal E. Stern, Jeffrey P. Sutton, Lynette J. Tippett, Daniel Tranel, Bradley Wyble

Optimality in Biological and Artificial Networks?

Author: Daniel S. Levine

Publisher: Psychology Press

Published: 2013-06-17

Total Pages: 525

ISBN-13: 1134786387

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This book is the third in a series based on conferences sponsored by the Metroplex Institute for Neural Dynamics, an interdisciplinary organization of neural network professionals in academia and industry. The topics selected are of broad interest to both those interested in designing machines to perform intelligent functions and those interested in studying how these functions are actually performed by living organisms and generate discussion of basic and controversial issues in the study of mind. The topic of optimality was chosen because it has provoked considerable discussion and controversy in many different academic fields. There are several aspects to the issue of optimality. First, is it true that actual behavior and cognitive functions of living animals, including humans, can be considered as optimal in some sense? Second, what is the utility function for biological organisms, if any, and can it be described mathematically? Rather than organize the chapters on a "biological versus artificial" basis or by what stance they took on optimality, it seemed more natural to organize them either by what level of questions they posed or by what intelligent functions they dealt with. The book begins with some general frameworks for discussing optimality, or the lack of it, in biological or artificial systems. The next set of chapters deals with some general mathematical and computational theories that help to clarify what the notion of optimality might entail in specific classes of networks. The final section deals with optimality in the context of many different high-level issues, including exploring one's environment, understanding mental illness, linguistic communication, and social organization. The diversity of topics covered in this book is designed to stimulate interdisciplinary thinking and speculation about deep problems in intelligent system organization.

Introduction to Neural and Cognitive Modeling

Author: Daniel S. Levine

Publisher: Psychology Press

Published: 2000-02-01

Total Pages: 573

ISBN-13: 1135692246

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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/

Radial Basis Function Networks 1

Author: Robert J.Howlett

Publisher: Springer Science & Business Media

Published: 2001-03-27

Total Pages: 344

ISBN-13: 9783790813678

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The Radial Basis Function (RBF) neural network has gained in popularity over recent years because of its rapid training and its desirable properties in classification and functional approximation applications. RBF network research has focused on enhanced training algorithms and variations on the basic architecture to improve the performance of the network. In addition, the RBF network is proving to be a valuable tool in a diverse range of application areas, for example, robotics, biomedical engineering, and the financial sector. The two volumes provide a comprehensive survey of the latest developments in this area. Volume 1 covers advances in training algorithms, variations on the architecture and function of the basis neurons, and hybrid paradigms, for example RBF learning using genetic algorithms. Both volumes will prove extremely useful to practitioners in the field, engineers, researchers and technically accomplished managers.

Handbook of Psychopathy, Second Edition

Author: Christopher J. Patrick

Publisher: Guilford Publications

Published: 2019-06-14

Total Pages: 849

ISBN-13: 1462541232

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Widely considered the go-to reference--and now extensively revised with over 65% new material--this authoritative handbook surveys the landscape of current knowledge on psychopathy and addresses essential clinical and applied topics. Leading researchers explore major theoretical models; symptomatology and diagnostic subtypes; assessment methods; developmental pathways; and causal influences, from genes and neurobiology to environmental factors. The volume examines manifestations of psychopathy in specific populations as well as connections to antisocial behavior and recidivism. It presents contemporary perspectives on prevention and treatment and discusses special considerations in clinical and forensic practice. New to This Edition *Extensively revised with more than a decade's theoretical, empirical, and clinical advances. *Many new authors and topics. *Expanded coverage of phenotypic facets, with chapters on behavioral disinhibition, callous–unemotional traits, and boldness. *Chapters on DSM-5, clinical interviewing, cognitive and emotional processing, and serial murder. *Significantly updated coverage of etiology, assessment methods, neuroimaging research, and adult and juvenile treatment approaches.

From Synapses to Rules

Author: Bruno Apolloni

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 402

ISBN-13: 1461507057

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One high-level ability of the human brain is to understand what it has learned. This seems to be the crucial advantage in comparison to the brain activity of other primates. At present we are technologically almost ready to artificially reproduce human brain tissue, but we still do not fully understand the information processing and the related biological mechanisms underlying this ability. Thus an electronic clone of the human brain is still far from being realizable. At the same time, around twenty years after the revival of the connectionist paradigm, we are not yet satisfied with the typical subsymbolic attitude of devices like neural networks: we can make them learn to solve even difficult problems, but without a clear explanation of why a solution works. Indeed, to widely use these devices in a reliable and non elementary way we need formal and understandable expressions of the learnt functions. of being tested, manipulated and composed with These must be susceptible other similar expressions to build more structured functions as a solution of complex problems via the usual deductive methods of the Artificial Intelligence. Many effort have been steered in this directions in the last years, constructing artificial hybrid systems where a cooperation between the sub symbolic processing of the neural networks merges in various modes with symbolic algorithms. In parallel, neurobiology research keeps on supplying more and more detailed explanations of the low-level phenomena responsible for mental processes.

Dealing with Complexity

Author: Mirek Karny

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 323

ISBN-13: 1447115236

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In almost all areas of science and engineering, the use of computers and microcomputers has, in recent years, transformed entire subject areas. What was not even considered possible a decade or two ago is now not only possible but is also part of everyday practice. As a result, a new approach usually needs to be taken (in order) to get the best out of a situation. What is required is now a computer's eye view of the world. However, all is not rosy in this new world. Humans tend to think in two or three dimensions at most, whereas computers can, without complaint, work in n dimensions, where n, in practice, gets bigger and bigger each year. As a result of this, more complex problem solutions are being attempted, whether or not the problems themselves are inherently complex. If information is available, it might as well be used, but what can be done with it? Straightforward, traditional computational solutions to this new problem of complexity can, and usually do, produce very unsatisfactory, unreliable and even unworkable results. Recently however, artificial neural networks, which have been found to be very versatile and powerful when dealing with difficulties such as nonlinearities, multivariate systems and high data content, have shown their strengths in general in dealing with complex problems. This volume brings together a collection of top researchers from around the world, in the field of artificial neural networks.

Oscillations in Neural Systems

Author: Daniel S. Levine

Publisher: Psychology Press

Published: 1999-09

Total Pages: 454

ISBN-13: 1135691908

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Written for those interested in designing machines to perform intelligent functions & those interested in studying how these functions are performed by living organisms,this bk dicusses the mathematical structure & functional significance of neural oscil

The Evolutionary Neuroethology of Paul MacLean

Author: Gerald A. Cory Jr.

Publisher: Bloomsbury Publishing USA

Published: 2002-12-30

Total Pages: 469

ISBN-13: 0313013160

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In the mid-20th century, integrative efforts began concerning the brain and its social and humanistic functions. These efforts were led by Paul D. MacLean's integrative research and thought. As the century ended, however, such efforts were lost in the surge of new effort in brain and genome research. Nobel Prizes were awarded on biochemical and cellular findings relevant to psychiatry. Findings on these levels seemed to provide ultimate answers. By contrast, Cory, Gardner, and their contributors provide a more comprehensive view by extending MacLean's findings and integrative theory. Supported by new findings and extended by critical analyses of current work, the collection provides foundations for more integrative efforts that the editors and contributors believe will prevail increasingly in coming decades. Looked at from another vantage point, therapeutic, social, economic, and politial sciences have proceeded wtihout operating theories congruent with, or based on, brain functions. Across-species perspectives have been lacking. This collection redresses this problem and leads the way toward more comprehensive 21st century research on the one hand, and practical applications on the other. Multiple approaches extend from modeling efforts to across-species comparisons, to the basic science of psychiatry to theoretical explanations of political and economic systems. But most important, these essays abolish the Berlin wall that currently separates the brain from its social functions. A major guide for scholars, students, and researchers involved in the neurobehavioral sciences, for psychologists, psychiatrists, and others involved with human clinical sciences, and for social scientists concerned with the impact of the nervous system and its function.