Introduction to Neural and Cognitive Modeling
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/

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.

Neuronal Dynamics
Neuronal Dynamics

Author: Wulfram Gerstner

Publisher: Cambridge University Press

Published: 2014-07-24

Total Pages: 591

ISBN-13: 1107060834

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This solid introduction uses the principles of physics and the tools of mathematics to approach fundamental questions of neuroscience.

Animal Learning and Cognition
Animal Learning and Cognition

Author: Nestor A. Schmajuk

Publisher: Cambridge University Press

Published: 1997-04-28

Total Pages: 356

ISBN-13: 9780521456968

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In this advanced text, the author, starting with the simple assumption that psychological associations are represented by the strength of synaptic connections, details several mechanistic descriptions of complex cognitive behaviors. Part I presents neural network theories of classical conditioning; Part II describes neural networks of operant conditioning, and animal communication; Part III discusses spatial and cognitive mapping, and finally, Part IV shows how neural network models permit one to simultaneously develop psychological theories and models of the brain. The book includes computer software that allows the computer simulation of classical conditioning and the effect of different brain lesions on many classical paradigms. All those people interested in neural networks, from psychologists, through neuroscientists to computer scientists working on artificial intelligence and robotics, will find this book an excellent advanced guide to the subject.

Neural Network Models of Cognition
Neural Network Models of Cognition

Author: J.W. Donahoe

Publisher: Elsevier

Published: 1997-09-26

Total Pages: 601

ISBN-13: 0080537367

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This internationally authored volume presents major findings, concepts, and methods of behavioral neuroscience coordinated with their simulation via neural networks. A central theme is that biobehaviorally constrained simulations provide a rigorous means to explore the implications of relatively simple processes for the understanding of cognition (complex behavior). Neural networks are held to serve the same function for behavioral neuroscience as population genetics for evolutionary science. The volume is divided into six sections, each of which includes both experimental and simulation research: (1) neurodevelopment and genetic algorithms, (2) synaptic plasticity (LTP), (3) sensory/hippocampal systems, (4) motor systems, (5) plasticity in large neural systems (reinforcement learning), and (6) neural imaging and language. The volume also includes an integrated reference section and a comprehensive index.

Neural Networks
Neural Networks

Author: G David Garson

Publisher: SAGE

Published: 1998-09-24

Total Pages: 201

ISBN-13: 0857026275

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This book provides the first accessible introduction to neural network analysis as a methodological strategy for social scientists. The author details numerous studies and examples which illustrate the advantages of neural network analysis over other quantitative and modelling methods in widespread use. Methods are presented in an accessible style for readers who do not have a background in computer science. The book provides a history of neural network methods, a substantial review of the literature, detailed applications, coverage of the most common alternative models and examples of two leading software packages for neural network analysis.

Neural-Symbolic Cognitive Reasoning
Neural-Symbolic Cognitive Reasoning

Author: Artur S. D'Avila Garcez

Publisher: Springer Science & Business Media

Published: 2009

Total Pages: 200

ISBN-13: 3540732454

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This book explores why, regarding practical reasoning, humans are sometimes still faster than artificial intelligence systems. It is the first to offer a self-contained presentation of neural network models for many computer science logics.

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.

The Construction of Cognitive Maps
The Construction of Cognitive Maps

Author: Juval Portugali

Publisher: Springer Science & Business Media

Published: 2007-08-23

Total Pages: 365

ISBN-13: 0585334854

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and processes which are exclusive to humans in their encoding, storing, decoding and retrieving spatial knowledge for various tasks. The authors present and discuss connectionist models of cognitive maps which are based on local representation, versus models which are based on distributed representation, as well as connectionist models concerning language and spatial relations. As is well known, Gibson's (1979) ecological approach suggests a view on cognition which is diametrically different from the classical main stream view: perception (and thus cognition) is direct, immediate and needs no internal information processing, and is thus essentially an external process of interaction between an organism and its external environment. The chapter by Harry Heft introduces J. J. Gibson's ecological approach and its implication to the construction of cognitive maps in general and to the issue of wayfinding in particular. According to Heft, main stream cognitive sciences are essentially Cartesian in nature and have not as yet internalized the implications of Darwin's theory of evolution. Gibson, in his ecological approach, has tried to do exactly this. The author introduces the basic terminology of the ecological approach and relates its various notions, in particular optic flow, nested hierarchy and affordances, to navigation and the way routes and places in the environment are learned.