Motivation, Emotion, and Goal Direction in Neural Networks

Motivation, Emotion, and Goal Direction in Neural Networks
Author: Daniel S. Levine
Publisher: Psychology Press
Total Pages: 468
Release: 2014-01-14
Genre: Psychology
ISBN: 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.

Brain and Values

Brain and Values
Author: Karl H. Pribram
Publisher: Psychology Press
Total Pages: 576
Release: 2018-01-17
Genre: Psychology
ISBN: 113499785X

This 5th volume of the Appalachian Conference discusses how the brain processes information, the role of memory and value, and models of creativity. It pursues aspects of cognitive neuroscience and behavioral neurodynamics, such as the topic of values and quantum-distributed processing in the brain.

Neural Networks for Knowledge Representation and Inference

Neural Networks for Knowledge Representation and Inference
Author: Daniel S. Levine
Publisher: Psychology Press
Total Pages: 523
Release: 2013-04-15
Genre: Psychology
ISBN: 1134771541

The second published collection based on a conference sponsored by the Metroplex Institute for Neural Dynamics -- the first is Motivation, Emotion, and Goal Direction in Neural Networks (LEA, 1992) -- this book addresses the controversy between symbolicist artificial intelligence and neural network theory. A particular issue is how well neural networks -- well established for statistical pattern matching -- can perform the higher cognitive functions that are more often associated with symbolic approaches. This controversy has a long history, but recently erupted with arguments against the abilities of renewed neural network developments. More broadly than other attempts, the diverse contributions presented here not only address the theory and implementation of artificial neural networks for higher cognitive functions, but also critique the history of assumed epistemologies -- both neural networks and AI -- and include several neurobiological studies of human cognition as a real system to guide the further development of artificial ones. Organized into four major sections, this volume: * outlines the history of the AI/neural network controversy, the strengths and weaknesses of both approaches, and shows the various capabilities such as generalization and discreetness as being along a broad but common continuum; * introduces several explicit, theoretical structures demonstrating the functional equivalences of neurocomputing with the staple objects of computer science and AI, such as sets and graphs; * shows variants on these types of networks that are applied in a variety of spheres, including reasoning from a geographic database, legal decision making, story comprehension, and performing arithmetic operations; * discusses knowledge representation process in living organisms, including evidence from experimental psychology, behavioral neurobiology, and electroencephalographic responses to sensory stimuli.

Cognitive Science Perspectives on Personality and Emotion

Cognitive Science Perspectives on Personality and Emotion
Author: G. Matthews
Publisher: Elsevier
Total Pages: 575
Release: 1997-12-11
Genre: Psychology
ISBN: 0080529305

This book aims to highlight the vigour, diversity and insight of the various cognitive science perspectives on personality and emotion. It aims also to emphasise the rigorous scientific basis for research to be found in the integration of experimental psychology with neuroscience, connectionism and the new evolutionary psychology. The contributors to this book provide a wide-ranging survey of leading-edge research topics. It is divided into three parts, on general frameworks for cognitive science, on perspectives from emotion research, and on perspectives from studies of personality traits.

Introduction to Neural and Cognitive Modeling

Introduction to Neural and Cognitive Modeling
Author: Daniel S. Levine
Publisher: Routledge
Total Pages: 480
Release: 2018-10-26
Genre: Psychology
ISBN: 0429828802

This textbook provides a general introduction to the field of neural networks. Thoroughly revised and updated from the previous editions of 1991 and 2000, the current edition concentrates on networks for modeling brain processes involved in cognitive and behavioral functions. Part one explores the philosophy of modeling and the field’s history starting from the mid-1940s, and then discusses past models of associative learning and of short-term memory that provide building blocks for more complex recent models. Part two of the book reviews recent experimental findings in cognitive neuroscience and discusses models of conditioning, categorization, category learning, vision, visual attention, sequence learning, behavioral control, decision making, reasoning, and creativity. The book presents these models both as abstract ideas and through examples and concrete data for specific brain regions. The book includes two appendices to help ground the reader: one reviewing the mathematics used in network modeling, and a second reviewing basic neuroscience at both the neuron and brain region level. The book also includes equations, practice exercises, and thought experiments.

Fundamentals of Neural Network Modeling

Fundamentals of Neural Network Modeling
Author: Randolph W. Parks
Publisher: MIT Press
Total Pages: 450
Release: 1998
Genre: Computers
ISBN: 9780262161756

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

Encyclopedia of Computer Science and Technology

Encyclopedia of Computer Science and Technology
Author: Allen Kent
Publisher: CRC Press
Total Pages: 386
Release: 1999-08-19
Genre: Computers
ISBN: 9780824722944

This 41st volume covers Application of Bayesan Belief Networks to Highway Construction to Virtual Reality Software and Technology.

The Mind Within the Net

The Mind Within the Net
Author: Manfred Spitzer
Publisher: MIT Press
Total Pages: 382
Release: 1999
Genre: Education
ISBN: 9780262692366

"Computer models can help us understand what appear to be the most private of all human experiences ... a mathematical theory can fundamentally change the way in which we think about learning, creativity, thinking, and acting." (x).

Optimality in Biological and Artificial Networks?

Optimality in Biological and Artificial Networks?
Author: Daniel S. Levine
Publisher: Psychology Press
Total Pages: 525
Release: 2013-06-17
Genre: Psychology
ISBN: 1134786387

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.