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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

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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.


Current Directions in Motivation and Emotion

Current Directions in Motivation and Emotion
Author: Kennon Marshall Sheldon
Publisher: Prentice Hall
Total Pages: 0
Release: 2010
Genre: Emotions
ISBN: 9780205680115

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This updated and exciting reader includes 25 articles that have been carefully selected for the undergraduate audience, and taken from the very accessible Current Directions in Psychological Science journal. These timely, cutting-edge articles allow instructors to bring their students real-world perspective-–from a reliable source–-about today’s most current and pressing issues in abnormal psychology.


Motivation, Effort, and the Neural Network Model

Motivation, Effort, and the Neural Network Model
Author: Theodore Wasserman
Publisher: Springer
Total Pages: 164
Release: 2020-10-28
Genre: Psychology
ISBN: 9783030587239

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Our understanding of how the human brain operates and completes its essential tasks continues is fundamentally altered from what it was ten years ago. We have moved from an understanding based on the modularity of key structural components and their specialized functions to an almost diametrically opposed, highly integrated neural network model, based on a vertically organized brain dependent on small world hub principles. This new understanding completely changes how we understand essential psychological constructs such as motivation. Network modeling posits that motivation is a construct that describes a modified aspect of the operation of the human learning system that is specifically designed to cause a person to pursue a goal. Anthropologically and developmentally, these goals were initially basic, including things like food, shelter and reproduction. Over the course of time and development they develop into a complex web of extrinsic and then intrinsic goals, objectives and values. The core for all of this development is the inborn flight or fight reaction has been modified over time by a combination of inborn human temperamental characteristics and life experiences. This process of modification is, in part, based on the operation of a network based error-prediction network working in concert with the reward network to produce a system of ever evolving valuations of goals and objectives. These valuations are never truly fixed. They are constantly evolving, being modified and shaped by experience. The error prediction network and learning related networks work in concert with the limbic system to allow affect laden experiences to inform the process of valuation. These networks, operating in concert, produce a cognitive process we call motivation. Like most networks, the motivation system of networks is recruited when the task demands of the situation require them. Understanding motivation from this perspective has profound implications for many scientific disciplines in general and psychology in specific. Psychologically, this new understanding will alter how we understand client behavior in therapy and when being evaluated. This new understanding will provide direction for new therapeutic intervention for a variety of disorders of mental health. It will also inform testing practices concerning the evaluation of effort and malingering. This book is not a project in reductionism. It is the polar opposite. A neural network understanding of the operation of the human brain allows for the integration of what has come before into a comprehensive and integrated model. It will likely provide the basis for future research for years to come.


Integrative Views of Motivation, Cognition, and Emotion

Integrative Views of Motivation, Cognition, and Emotion
Author: William Delbert Spaulding
Publisher: U of Nebraska Press
Total Pages: 288
Release: 1994
Genre: Psychology
ISBN: 9780803242333

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Psychological theory has traditionally attempted to explain events in terms of motivation, emotion, or cognition. Over the past decade, psychology has come to be viewed as a paradigmatic science; the new paradigm being the understanding of behavior in terms of cognitive representations. This cognitive revolution has fostered a view of the passing of information back and forth between perceptual, memory, and motor components of an integrated system, known as the ?computational metaphor.? With cognition as the new paradigm, can we expect that the explanatory scope of psychology will be clarified? Will a cognitive perspective be extended to phenomena that have traditionally fallen under the rubric of motivation and emotion? The psychologists involved in this volume of the Nebraska Symposium address these questions specifically. Their contributions stimulate a hypothesis that the cognitive paradigm has begun to move psychology toward a ?unified field theory? of behavior and experience. Herbert A. Simon tests the limits of a pure information processing paradigm. A basic tenet of this theoretical approach is that information exists independent of the medium by which it is represented. By analyzing the information processing capabilities of nonbiological systems, or ?artificial intelligence,? we may determine which aspects of motivation and emotion require the biological substrate of cognition. Muriel D. Lezak raises a similar question by focusing on the biological substrate itself and by analyzing the constraints and determinations that it imposes. Howard Gardner considers the medium and the information it processes; thus he lays a conceptual foundation for making the facts of biological brain science congruent with the richness of human behavior and experience.


Understanding Motivation and Emotion

Understanding Motivation and Emotion
Author: Johnmarshall Reeve
Publisher:
Total Pages: 592
Release: 2005
Genre: Psychology
ISBN:

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This work focuses on human needs and illustrates how to apply motivational principles. A strong humanistic orientation with balanced coverage of behavioral, cognitive and physiological approaches is presented in the text.


Goal-directed Neural System

Goal-directed Neural System
Author: Daniel S. Levine
Publisher:
Total Pages: 141
Release: 2009
Genre:
ISBN:

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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

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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.


Fundamentals of Neural Network Modeling

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