Network Science in Cognitive Psychology
Network Science in Cognitive Psychology

Author: Michael S. Vitevitch

Publisher: Routledge

Published: 2019-11-26

Total Pages: 309

ISBN-13: 1000740943

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This volume provides an integrative review of the emerging and increasing use of network science techniques in cognitive psychology, first developed in mathematics, computer science, sociology, and physics. The first resource on network science for cognitive psychologists in a growing international market, Vitevitch and a team of expert contributors provide a comprehensive and accessible overview of this cutting-edge topic. This innovative guide draws on the three traditional pillars of cognitive psychological research–experimental, computational, and neuroscientific–and incorporates the latest findings from neuroimaging. The network perspective is applied to the fundamental domains of cognitive psychology including memory, language, problem-solving, and learning, as well as creativity and human intelligence, highlighting the insights to be gained through applying network science to a wide range of approaches and topics in cognitive psychology Network Science in Cognitive Psychology will be essential reading for all upper-level cognitive psychology students, psychological researchers interested in using network science in their work, and network scientists interested in investigating questions related to cognition. It will also be useful for early career researchers and students in methodology and related courses.

Network Science in Cognitive Psychology
Network Science in Cognitive Psychology

Author: Michael S. Vitevitch

Publisher: Routledge

Published: 2019-11-26

Total Pages: 213

ISBN-13: 1000740684

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This volume provides an integrative review of the emerging and increasing use of network science techniques in cognitive psychology, first developed in mathematics, computer science, sociology, and physics. The first resource on network science for cognitive psychologists in a growing international market, Vitevitch and a team of expert contributors provide a comprehensive and accessible overview of this cutting-edge topic. This innovative guide draws on the three traditional pillars of cognitive psychological research–experimental, computational, and neuroscientific–and incorporates the latest findings from neuroimaging. The network perspective is applied to the fundamental domains of cognitive psychology including memory, language, problem-solving, and learning, as well as creativity and human intelligence, highlighting the insights to be gained through applying network science to a wide range of approaches and topics in cognitive psychology Network Science in Cognitive Psychology will be essential reading for all upper-level cognitive psychology students, psychological researchers interested in using network science in their work, and network scientists interested in investigating questions related to cognition. It will also be useful for early career researchers and students in methodology and related courses.

Fundamentals of Neural Network Modeling
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

Cognitive Science
Cognitive Science

Author: Jay Friedenberg

Publisher: SAGE Publications

Published: 2015-09-23

Total Pages: 829

ISBN-13: 1483347427

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In Cognitive Science 3e Friedenberg and Silverman provide a solid understanding of the major theoretical and empirical contributions of cognitive science. Their text, thoroughly updated for this new third edition, describes the major theories of mind as well as the major experimental results that have emerged within each cognitive science discipline. Throughout history, different fields of inquiry have attempted to understand the great mystery of mind and answer questions like: What is the mind? How do we see, think, and remember? Can we create machines that are conscious and capable of self-awareness? This books examines these questions and many more. Focusing on the approach of a particular cognitive science field in each chapter, the authors describe its methodology, theoretical perspective, and findings and then offer a critical evaluation of the field. Features: Offers a wide-ranging, comprehensive, and multidisciplinary introduction to the field of cognitive science and issues of mind. Interdisciplinary Crossroads” sections at the end of each chapter focus on research topics that have been investigated from multiple perspectives, helping students to understand the link between varying disciplines and cognitive science. End-of-chapter “Summing Up” sections provide a concise summary of the major points addressed in each chapter to facilitate student comprehension and exam preparation “Explore More” sections link students to the Student Study Site where the authors have provided activities to help students more quickly master course content and prepare for examinations Supplements: A password-protected Instructor’s Resource contains PowerPoint lectures, a test bank and other pedagogical material.The book's Study Site features Web links, E-flash cards, and interactive quizzes.

Towards a Theoretical Framework for Analyzing Complex Linguistic Networks
Towards a Theoretical Framework for Analyzing Complex Linguistic Networks

Author: Alexander Mehler

Publisher: Springer

Published: 2015-07-07

Total Pages: 350

ISBN-13: 3662472384

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The aim of this book is to advocate and promote network models of linguistic systems that are both based on thorough mathematical models and substantiated in terms of linguistics. In this way, the book contributes first steps towards establishing a statistical network theory as a theoretical basis of linguistic network analysis the boarder of the natural sciences and the humanities. This book addresses researchers who want to get familiar with theoretical developments, computational models and their empirical evaluation in the field of complex linguistic networks. It is intended to all those who are interested in statistical models of linguistic systems from the point of view of network research. This includes all relevant areas of linguistics ranging from phonological, morphological and lexical networks on the one hand and syntactic, semantic and pragmatic networks on the other. In this sense, the volume concerns readers from many disciplines such as physics, linguistics, computer science and information science. It may also be of interest for the upcoming area of systems biology with which the chapters collected here share the view on systems from the point of view of network analysis.

Analyzing Social Networks
Analyzing Social Networks

Author: Stephen P Borgatti

Publisher: SAGE

Published: 2013-05-14

Total Pages: 368

ISBN-13: 1446290565

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Written by a stellar team of experts, Analyzing Social Networks is a practical book on how to collect, visualize, analyze and interpret social network data with a particular emphasis on the use of the software tools UCINET and Netdraw. The book includes a clear and detailed introduction to the fundamental concepts of network analyses, including centrality, subgroups, equivalence and network structure, as well as cross-cutting chapters that helpfully show how to apply network concepts to different kinds of networks. Written using simple language and notation with few equations, this book masterfully covers the research process, including: · The initial design stage · Data collection and manipulation · Measuring key variables · Exploration of structure · Hypothesis testing · Interpretation This is an essential resource for students, researchers and practitioners across the social sciences who want to use network analysis as part of their research. Available with Perusall—an eBook that makes it easier to prepare for class Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more.

Cognitive Science and Its Applications for Human-computer Interaction
Cognitive Science and Its Applications for Human-computer Interaction

Author: Raymonde Guindon

Publisher: Psychology Press

Published: 1988

Total Pages: 364

ISBN-13: 9780898598841

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The field of human-computer interaction is striving to provide the conceptual foundations for designing computer tools and the environment needed to perform increasingly complex and specialized tasks. To achieve this goal, human-computer interaction relies on the meeting of specialized, expert minds. This book is organized around the theme of multidisciplinary research and the contribution of cognitive science to research projects. Research projects may have overlapping goals, but use widely diverse methodologies, or use similar methodologies to investigate quite different questions. The methodologies and techniques come from diverse fields: scaling and measurement, computer science, experimental psychology, and linguistics. These act in synergy to solve the problems posed by human-computer interaction. Each of the research projects presented in this book investigate some critical question on the path of progress in human-computer interaction.

Gateway to Memory
Gateway to Memory

Author: Mark A. Gluck

Publisher: MIT Press

Published: 2001

Total Pages: 470

ISBN-13: 9780262571524

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This book is for students and researchers who have a specific interest in learning and memory and want to understand how computational models can be integrated into experimental research on the hippocampus and learning. It emphasizes the function of brain structures as they give rise to behavior, rather than the molecular or neuronal details. It also emphasizes the process of modeling, rather than the mathematical details of the models themselves. The book is divided into two parts. The first part provides a tutorial introduction to topics in neuroscience, the psychology of learning and memory, and the theory of neural network models. The second part, the core of the book, reviews computational models of how the hippocampus cooperates with other brain structures -- including the entorhinal cortex, basal forebrain, cerebellum, and primary sensory and motor cortices -- to support learning and memory in both animals and humans. The book assumes no prior knowledge of computational modeling or mathematics. For those who wish to delve more deeply into the formal details of the models, there are optional "mathboxes" and appendices. The book also includes extensive references and suggestions for further readings.

Cognitive Modeling
Cognitive Modeling

Author: Thad A. Polk

Publisher: MIT Press

Published: 2002

Total Pages: 1300

ISBN-13: 9780262661164

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A comprehensive introduction to the computational modeling of human cognition.

An Introduction to Artificial Psychology
An Introduction to Artificial Psychology

Author: Hojjatollah Farahani

Publisher: Springer Nature

Published: 2023-05-18

Total Pages: 262

ISBN-13: 3031311728

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Artificial Psychology (AP) is a highly multidisciplinary field of study in psychology. AP tries to solve problems which occur when psychologists do research and need a robust analysis method. Conventional statistical approaches have deep rooted limitations. These approaches are excellent on paper but often fail to model the real world. Mind researchers have been trying to overcome this by simplifying the models being studied. This stance has not received much practical attention recently. Promoting and improving artificial intelligence helps mind researchers to find a holistic model of mental models. This development achieves this goal by using multiple perspectives and multiple data sets together with interactive, and realistic models. In this book, the methodology of approximate inference in psychological research from a theoretical and practical perspective has been considered. Quantitative variable-oriented methodology and qualitative case-oriented methods are both used to explain the set-oriented methodology and this book combines the precision of quantitative methods with information from qualitative methods. This is a book that many researchers can use to expand and deepen their psychological research and is a book which can be useful to postgraduate students. The reader does not need an in-depth knowledge of mathematics or statistics because statistical and mathematical intuitions are key here and they will be learned through practice. What is important is to understand and use the new application of the methods for finding new, dynamic and realistic interpretations. This book incorporates theoretical fuzzy inference and deep machine learning algorithms in practice. This is the kind of book that we wished we had had when we were students. This book covers at least some of the most important issues in mind research including uncertainty, fuzziness, continuity, complexity and high dimensionality which are inherent to mind data. These are elements of artificial psychology. This book implements models using R software.