Author: Leslie S. Smith
Publisher: Springer Science & Business Media
ISBN: 1447135792
Category : Computers
Languages : en
Pages : 232
Book Description
The papers that appear in this volume are refereed versions of presenta tions made at the third Neural Computation and Psychology Workshop, held at Stirling University, Scotland, from 31 August to 2 September 1994. The aim of this series of conferences has been to explore the interface between Neural Computing and Psychology: this has been a fruitful area for many researchers for a number of reasons. The development ofNeural Computation has supplied tools to researchers in Cognitive Neuroscience, allowing them to look at possible mechanisms for implementing theories which would otherwise remain 'black box' techniques. These theories may be high-level theories, concerned with interaction between a number of brain areas, or low-level, describing the way in which smaller local groups of neurons behave. Neural Computation techniques have allowed computer scientists to implement systems which are based on how real brains appear to function, providing effective pattern recognition systems. We can thus mount a two-pronged attack on perception. The papers here come from both the Cognitive Psychology viewpoint and from the Computer Science viewpoint: it is a mark of the growing maturity of the interface between the two subjects that they can under stand each other's papers, and the level of discussion at the workshop itself showed how important each camp considers the other to be. The papers here are divided into four sections, reflecting the primary areas of the material.
Neural Computation and Psychology
Author: Leslie S. Smith
Publisher: Springer Science & Business Media
ISBN: 1447135792
Category : Computers
Languages : en
Pages : 232
Book Description
The papers that appear in this volume are refereed versions of presenta tions made at the third Neural Computation and Psychology Workshop, held at Stirling University, Scotland, from 31 August to 2 September 1994. The aim of this series of conferences has been to explore the interface between Neural Computing and Psychology: this has been a fruitful area for many researchers for a number of reasons. The development ofNeural Computation has supplied tools to researchers in Cognitive Neuroscience, allowing them to look at possible mechanisms for implementing theories which would otherwise remain 'black box' techniques. These theories may be high-level theories, concerned with interaction between a number of brain areas, or low-level, describing the way in which smaller local groups of neurons behave. Neural Computation techniques have allowed computer scientists to implement systems which are based on how real brains appear to function, providing effective pattern recognition systems. We can thus mount a two-pronged attack on perception. The papers here come from both the Cognitive Psychology viewpoint and from the Computer Science viewpoint: it is a mark of the growing maturity of the interface between the two subjects that they can under stand each other's papers, and the level of discussion at the workshop itself showed how important each camp considers the other to be. The papers here are divided into four sections, reflecting the primary areas of the material.
Publisher: Springer Science & Business Media
ISBN: 1447135792
Category : Computers
Languages : en
Pages : 232
Book Description
The papers that appear in this volume are refereed versions of presenta tions made at the third Neural Computation and Psychology Workshop, held at Stirling University, Scotland, from 31 August to 2 September 1994. The aim of this series of conferences has been to explore the interface between Neural Computing and Psychology: this has been a fruitful area for many researchers for a number of reasons. The development ofNeural Computation has supplied tools to researchers in Cognitive Neuroscience, allowing them to look at possible mechanisms for implementing theories which would otherwise remain 'black box' techniques. These theories may be high-level theories, concerned with interaction between a number of brain areas, or low-level, describing the way in which smaller local groups of neurons behave. Neural Computation techniques have allowed computer scientists to implement systems which are based on how real brains appear to function, providing effective pattern recognition systems. We can thus mount a two-pronged attack on perception. The papers here come from both the Cognitive Psychology viewpoint and from the Computer Science viewpoint: it is a mark of the growing maturity of the interface between the two subjects that they can under stand each other's papers, and the level of discussion at the workshop itself showed how important each camp considers the other to be. The papers here are divided into four sections, reflecting the primary areas of the material.
Computational Explorations in Cognitive Neuroscience
Author: Randall C. O'Reilly
Publisher: MIT Press
ISBN: 9780262650540
Category : Medical
Languages : en
Pages : 540
Book Description
This text, based on a course taught by Randall O'Reilly and Yuko Munakata over the past several years, provides an in-depth introduction to the main ideas in the computational cognitive neuroscience. The goal of computational cognitive neuroscience is to understand how the brain embodies the mind by using biologically based computational models comprising networks of neuronlike units. This text, based on a course taught by Randall O'Reilly and Yuko Munakata over the past several years, provides an in-depth introduction to the main ideas in the field. The neural units in the simulations use equations based directly on the ion channels that govern the behavior of real neurons, and the neural networks incorporate anatomical and physiological properties of the neocortex. Thus the text provides the student with knowledge of the basic biology of the brain as well as the computational skills needed to simulate large-scale cognitive phenomena. The text consists of two parts. The first part covers basic neural computation mechanisms: individual neurons, neural networks, and learning mechanisms. The second part covers large-scale brain area organization and cognitive phenomena: perception and attention, memory, language, and higher-level cognition. The second part is relatively self-contained and can be used separately for mechanistically oriented cognitive neuroscience courses. Integrated throughout the text are more than forty different simulation models, many of them full-scale research-grade models, with friendly interfaces and accompanying exercises. The simulation software (PDP++, available for all major platforms) and simulations can be downloaded free of charge from the Web. Exercise solutions are available, and the text includes full information on the software.
Publisher: MIT Press
ISBN: 9780262650540
Category : Medical
Languages : en
Pages : 540
Book Description
This text, based on a course taught by Randall O'Reilly and Yuko Munakata over the past several years, provides an in-depth introduction to the main ideas in the computational cognitive neuroscience. The goal of computational cognitive neuroscience is to understand how the brain embodies the mind by using biologically based computational models comprising networks of neuronlike units. This text, based on a course taught by Randall O'Reilly and Yuko Munakata over the past several years, provides an in-depth introduction to the main ideas in the field. The neural units in the simulations use equations based directly on the ion channels that govern the behavior of real neurons, and the neural networks incorporate anatomical and physiological properties of the neocortex. Thus the text provides the student with knowledge of the basic biology of the brain as well as the computational skills needed to simulate large-scale cognitive phenomena. The text consists of two parts. The first part covers basic neural computation mechanisms: individual neurons, neural networks, and learning mechanisms. The second part covers large-scale brain area organization and cognitive phenomena: perception and attention, memory, language, and higher-level cognition. The second part is relatively self-contained and can be used separately for mechanistically oriented cognitive neuroscience courses. Integrated throughout the text are more than forty different simulation models, many of them full-scale research-grade models, with friendly interfaces and accompanying exercises. The simulation software (PDP++, available for all major platforms) and simulations can be downloaded free of charge from the Web. Exercise solutions are available, and the text includes full information on the software.
Fundamentals of Neural Network Modeling
Author: Randolph W. Parks
Publisher: MIT Press
ISBN: 9780262161756
Category : Computers
Languages : en
Pages : 450
Book Description
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
Publisher: MIT Press
ISBN: 9780262161756
Category : Computers
Languages : en
Pages : 450
Book Description
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
Computational Neuroscience and Cognitive Modelling
Author: Britt Anderson
Publisher: SAGE
ISBN: 1446297373
Category : Psychology
Languages : en
Pages : 241
Book Description
"For the neuroscientist or psychologist who cringes at the sight of mathematical formulae and whose eyes glaze over at terms like differential equations, linear algebra, vectors, matrices, Bayes’ rule, and Boolean logic, this book just might be the therapy needed." - Anjan Chatterjee, Professor of Neurology, University of Pennsylvania "Anderson provides a gentle introduction to computational aspects of psychological science, managing to respect the reader’s intelligence while also being completely unintimidating. Using carefully-selected computational demonstrations, he guides students through a wide array of important approaches and tools, with little in the way of prerequisites...I recommend it with enthusiasm." - Asohan Amarasingham, The City University of New York This unique, self-contained and accessible textbook provides an introduction to computational modelling neuroscience accessible to readers with little or no background in computing or mathematics. Organized into thematic sections, the book spans from modelling integrate and firing neurons to playing the game Rock, Paper, Scissors in ACT-R. This non-technical guide shows how basic knowledge and modern computers can be combined for interesting simulations, progressing from early exercises utilizing spreadsheets, to simple programs in Python. Key Features include: Interleaved chapters that show how traditional computing constructs are simply disguised versions of the spread sheet methods. Mathematical facts and notation needed to understand the modelling methods are presented at their most basic and are interleaved with biographical and historical notes for contex. Numerous worked examples to demonstrate the themes and procedures of cognitive modelling. An excellent text for postgraduate students taking courses in research methods, computational neuroscience, computational modelling, cognitive science and neuroscience. It will be especially valuable to psychology students.
Publisher: SAGE
ISBN: 1446297373
Category : Psychology
Languages : en
Pages : 241
Book Description
"For the neuroscientist or psychologist who cringes at the sight of mathematical formulae and whose eyes glaze over at terms like differential equations, linear algebra, vectors, matrices, Bayes’ rule, and Boolean logic, this book just might be the therapy needed." - Anjan Chatterjee, Professor of Neurology, University of Pennsylvania "Anderson provides a gentle introduction to computational aspects of psychological science, managing to respect the reader’s intelligence while also being completely unintimidating. Using carefully-selected computational demonstrations, he guides students through a wide array of important approaches and tools, with little in the way of prerequisites...I recommend it with enthusiasm." - Asohan Amarasingham, The City University of New York This unique, self-contained and accessible textbook provides an introduction to computational modelling neuroscience accessible to readers with little or no background in computing or mathematics. Organized into thematic sections, the book spans from modelling integrate and firing neurons to playing the game Rock, Paper, Scissors in ACT-R. This non-technical guide shows how basic knowledge and modern computers can be combined for interesting simulations, progressing from early exercises utilizing spreadsheets, to simple programs in Python. Key Features include: Interleaved chapters that show how traditional computing constructs are simply disguised versions of the spread sheet methods. Mathematical facts and notation needed to understand the modelling methods are presented at their most basic and are interleaved with biographical and historical notes for contex. Numerous worked examples to demonstrate the themes and procedures of cognitive modelling. An excellent text for postgraduate students taking courses in research methods, computational neuroscience, computational modelling, cognitive science and neuroscience. It will be especially valuable to psychology students.
An Introductory Course in Computational Neuroscience
Author: Paul Miller
Publisher: MIT Press
ISBN: 0262347563
Category : Science
Languages : en
Pages : 405
Book Description
A textbook for students with limited background in mathematics and computer coding, emphasizing computer tutorials that guide readers in producing models of neural behavior. This introductory text teaches students to understand, simulate, and analyze the complex behaviors of individual neurons and brain circuits. It is built around computer tutorials that guide students in producing models of neural behavior, with the associated Matlab code freely available online. From these models students learn how individual neurons function and how, when connected, neurons cooperate in a circuit. The book demonstrates through simulated models how oscillations, multistability, post-stimulus rebounds, and chaos can arise within either single neurons or circuits, and it explores their roles in the brain. The book first presents essential background in neuroscience, physics, mathematics, and Matlab, with explanations illustrated by many example problems. Subsequent chapters cover the neuron and spike production; single spike trains and the underlying cognitive processes; conductance-based models; the simulation of synaptic connections; firing-rate models of large-scale circuit operation; dynamical systems and their components; synaptic plasticity; and techniques for analysis of neuron population datasets, including principal components analysis, hidden Markov modeling, and Bayesian decoding. Accessible to undergraduates in life sciences with limited background in mathematics and computer coding, the book can be used in a “flipped” or “inverted” teaching approach, with class time devoted to hands-on work on the computer tutorials. It can also be a resource for graduate students in the life sciences who wish to gain computing skills and a deeper knowledge of neural function and neural circuits.
Publisher: MIT Press
ISBN: 0262347563
Category : Science
Languages : en
Pages : 405
Book Description
A textbook for students with limited background in mathematics and computer coding, emphasizing computer tutorials that guide readers in producing models of neural behavior. This introductory text teaches students to understand, simulate, and analyze the complex behaviors of individual neurons and brain circuits. It is built around computer tutorials that guide students in producing models of neural behavior, with the associated Matlab code freely available online. From these models students learn how individual neurons function and how, when connected, neurons cooperate in a circuit. The book demonstrates through simulated models how oscillations, multistability, post-stimulus rebounds, and chaos can arise within either single neurons or circuits, and it explores their roles in the brain. The book first presents essential background in neuroscience, physics, mathematics, and Matlab, with explanations illustrated by many example problems. Subsequent chapters cover the neuron and spike production; single spike trains and the underlying cognitive processes; conductance-based models; the simulation of synaptic connections; firing-rate models of large-scale circuit operation; dynamical systems and their components; synaptic plasticity; and techniques for analysis of neuron population datasets, including principal components analysis, hidden Markov modeling, and Bayesian decoding. Accessible to undergraduates in life sciences with limited background in mathematics and computer coding, the book can be used in a “flipped” or “inverted” teaching approach, with class time devoted to hands-on work on the computer tutorials. It can also be a resource for graduate students in the life sciences who wish to gain computing skills and a deeper knowledge of neural function and neural circuits.
Computational Neuroscience for Advancing Artificial Intelligence: Models, Methods and Applications
Author: Alonso, Eduardo
Publisher: IGI Global
ISBN: 1609600231
Category : Computers
Languages : en
Pages : 394
Book Description
"This book argues that computational models in behavioral neuroscience must be taken with caution, and advocates for the study of mathematical models of existing theories as complementary to neuro-psychological models and computational models"--
Publisher: IGI Global
ISBN: 1609600231
Category : Computers
Languages : en
Pages : 394
Book Description
"This book argues that computational models in behavioral neuroscience must be taken with caution, and advocates for the study of mathematical models of existing theories as complementary to neuro-psychological models and computational models"--
Neurocognitive Mechanisms
Author: Gualtiero Piccinini
Publisher: Oxford University Press, USA
ISBN: 0198866283
Category : Philosophy
Languages : en
Pages : 413
Book Description
Gualtiero Piccinini presents a systematic and rigorous philosophical defence of the computational theory of cognition. His view posits that cognition involves neural computation within multilevel neurocognitive mechanisms, and includes novel ideas about ontology, functions, neural representation, neural computation, and consciousness.
Publisher: Oxford University Press, USA
ISBN: 0198866283
Category : Philosophy
Languages : en
Pages : 413
Book Description
Gualtiero Piccinini presents a systematic and rigorous philosophical defence of the computational theory of cognition. His view posits that cognition involves neural computation within multilevel neurocognitive mechanisms, and includes novel ideas about ontology, functions, neural representation, neural computation, and consciousness.
Faith Physics
Author: Andrej Bicanski
Publisher:
ISBN: 9781999941109
Category :
Languages : en
Pages : 160
Book Description
Faith Physics is a satirical novella and contemporary critique of religion. Humanity can build machines to converse with the afterlife. What could possibly go wrong? It turns out, the departed are not very forthcoming about their "living conditions". Nevertheless, the accumulating body of knowledge about the afterlife changes religion, science, and personal hygiene forever.
Publisher:
ISBN: 9781999941109
Category :
Languages : en
Pages : 160
Book Description
Faith Physics is a satirical novella and contemporary critique of religion. Humanity can build machines to converse with the afterlife. What could possibly go wrong? It turns out, the departed are not very forthcoming about their "living conditions". Nevertheless, the accumulating body of knowledge about the afterlife changes religion, science, and personal hygiene forever.
Computational Psychiatry
Author: Peggy Series
Publisher: MIT Press
ISBN: 0262360713
Category : Psychology
Languages : en
Pages : 344
Book Description
The first introductory textbook in the emerging, fast-developing field of computational psychiatry. Computational psychiatry applies computational modeling and theoretical approaches to psychiatric questions, focusing on building mathematical models of neural or cognitive phenomena relevant to psychiatric diseases. It is a young and rapidly growing field, drawing on concepts from psychiatry, psychology, computer science, neuroscience, electrical and chemical engineering, mathematics, and physics. This book, accessible to nonspecialists, offers the first introductory textbook in computational psychiatry.
Publisher: MIT Press
ISBN: 0262360713
Category : Psychology
Languages : en
Pages : 344
Book Description
The first introductory textbook in the emerging, fast-developing field of computational psychiatry. Computational psychiatry applies computational modeling and theoretical approaches to psychiatric questions, focusing on building mathematical models of neural or cognitive phenomena relevant to psychiatric diseases. It is a young and rapidly growing field, drawing on concepts from psychiatry, psychology, computer science, neuroscience, electrical and chemical engineering, mathematics, and physics. This book, accessible to nonspecialists, offers the first introductory textbook in computational psychiatry.
Neural Codes and Distributed Representations
Author: L. F. Abbott
Publisher: MIT Press
ISBN: 9780262511001
Category : Computers
Languages : en
Pages : 378
Book Description
Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computation collects, by topic, the most significant papers that have appeared in the journal over the past nine years. The present volume focuses on neural codes and representations, topics of broad interest to neuroscientists and modelers. The topics addressed are: how neurons encode information through action potential firing patterns, how populations of neurons represent information, and how individual neurons use dendritic processing and biophysical properties of synapses to decode spike trains. The papers encompass a wide range of levels of investigation, from dendrites and neurons to networks and systems.
Publisher: MIT Press
ISBN: 9780262511001
Category : Computers
Languages : en
Pages : 378
Book Description
Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computation collects, by topic, the most significant papers that have appeared in the journal over the past nine years. The present volume focuses on neural codes and representations, topics of broad interest to neuroscientists and modelers. The topics addressed are: how neurons encode information through action potential firing patterns, how populations of neurons represent information, and how individual neurons use dendritic processing and biophysical properties of synapses to decode spike trains. The papers encompass a wide range of levels of investigation, from dendrites and neurons to networks and systems.