The Computational Brain 25th Anniversary Edition

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The Computational Brain, 25th Anniversary Edition

Author : Patricia S. Churchland
Publisher : MIT Press
ISBN 13 : 0262339668
Total Pages : 569 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis The Computational Brain, 25th Anniversary Edition by : Patricia S. Churchland

Download or read book The Computational Brain, 25th Anniversary Edition written by Patricia S. Churchland and published by MIT Press. This book was released on 2016-10-28 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: An anniversary edition of the classic work that influenced a generation of neuroscientists and cognitive neuroscientists. Before The Computational Brain was published in 1992, conceptual frameworks for brain function were based on the behavior of single neurons, applied globally. In The Computational Brain, Patricia Churchland and Terrence Sejnowski developed a different conceptual framework, based on large populations of neurons. They did this by showing that patterns of activities among the units in trained artificial neural network models had properties that resembled those recorded from populations of neurons recorded one at a time. It is one of the first books to bring together computational concepts and behavioral data within a neurobiological framework. Aimed at a broad audience of neuroscientists, computer scientists, cognitive scientists, and philosophers, The Computational Brain is written for both expert and novice. This anniversary edition offers a new preface by the authors that puts the book in the context of current research. This approach influenced a generation of researchers. Even today, when neuroscientists can routinely record from hundreds of neurons using optics rather than electricity, and the 2013 White House BRAIN initiative heralded a new era in innovative neurotechnologies, the main message of The Computational Brain is still relevant.

The Computational Brain

Author : Patricia Smith Churchland
Publisher : MIT Press
ISBN 13 : 9780262531207
Total Pages : 564 pages
Book Rating : 4.5/5 (312 download)

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Book Synopsis The Computational Brain by : Patricia Smith Churchland

Download or read book The Computational Brain written by Patricia Smith Churchland and published by MIT Press. This book was released on 1992 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The Computational Brain addresses a broad audience: neuroscientists, computer scientists, cognitive scientists, and philosophers. It is written for both the expert and novice. A basic overview of neuroscience and computational theory is provided, followed by a study of some of the most recent and sophisticated modeling work in the context of relevant neurobiological research. Technical terms are clearly explained in the text, and definitions are provided in an extensive glossary. The appendix contains a précis of neurobiological techniques."--Jacket.

The Computational Brain, 25th Anniversary Edition

Author : Patricia S. Churchland
Publisher : MIT Press
ISBN 13 : 0262533391
Total Pages : 569 pages
Book Rating : 4.2/5 (625 download)

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Book Synopsis The Computational Brain, 25th Anniversary Edition by : Patricia S. Churchland

Download or read book The Computational Brain, 25th Anniversary Edition written by Patricia S. Churchland and published by MIT Press. This book was released on 2016-11-04 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: An anniversary edition of the classic work that influenced a generation of neuroscientists and cognitive neuroscientists. Before The Computational Brain was published in 1992, conceptual frameworks for brain function were based on the behavior of single neurons, applied globally. In The Computational Brain, Patricia Churchland and Terrence Sejnowski developed a different conceptual framework, based on large populations of neurons. They did this by showing that patterns of activities among the units in trained artificial neural network models had properties that resembled those recorded from populations of neurons recorded one at a time. It is one of the first books to bring together computational concepts and behavioral data within a neurobiological framework. Aimed at a broad audience of neuroscientists, computer scientists, cognitive scientists, and philosophers, The Computational Brain is written for both expert and novice. This anniversary edition offers a new preface by the authors that puts the book in the context of current research. This approach influenced a generation of researchers. Even today, when neuroscientists can routinely record from hundreds of neurons using optics rather than electricity, and the 2013 White House BRAIN initiative heralded a new era in innovative neurotechnologies, the main message of The Computational Brain is still relevant.

Unsupervised Learning

Author : Geoffrey Hinton
Publisher : MIT Press
ISBN 13 : 9780262581684
Total Pages : 420 pages
Book Rating : 4.5/5 (816 download)

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Book Synopsis Unsupervised Learning by : Geoffrey Hinton

Download or read book Unsupervised Learning written by Geoffrey Hinton and published by MIT Press. This book was released on 1999-05-24 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. This volume of Foundations of Neural Computation, on unsupervised learning algorithms, focuses on neural network learning algorithms that do not require an explicit teacher. The goal of unsupervised learning is to extract an efficient internal representation of the statistical structure implicit in the inputs. These algorithms provide insights into the development of the cerebral cortex and implicit learning in humans. They are also of interest to engineers working in areas such as computer vision and speech recognition who seek efficient representations of raw input data.

Memory and the Computational Brain

Author : C. R. Gallistel
Publisher : John Wiley & Sons
ISBN 13 : 1444359762
Total Pages : 300 pages
Book Rating : 4.4/5 (443 download)

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Book Synopsis Memory and the Computational Brain by : C. R. Gallistel

Download or read book Memory and the Computational Brain written by C. R. Gallistel and published by John Wiley & Sons. This book was released on 2011-09-09 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Memory and the Computational Brain offers a provocative argument that goes to the heart of neuroscience, proposing that the field can and should benefit from the recent advances of cognitive science and the development of information theory over the course of the last several decades. A provocative argument that impacts across the fields of linguistics, cognitive science, and neuroscience, suggesting new perspectives on learning mechanisms in the brain Proposes that the field of neuroscience can and should benefit from the recent advances of cognitive science and the development of information theory Suggests that the architecture of the brain is structured precisely for learning and for memory, and integrates the concept of an addressable read/write memory mechanism into the foundations of neuroscience Based on lectures in the prestigious Blackwell-Maryland Lectures in Language and Cognition, and now significantly reworked and expanded to make it ideal for students and faculty

Self-organizing Map Formation

Author : Klaus Obermayer
Publisher : MIT Press
ISBN 13 : 9780262650601
Total Pages : 472 pages
Book Rating : 4.6/5 (56 download)

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Book Synopsis Self-organizing Map Formation by : Klaus Obermayer

Download or read book Self-organizing Map Formation written by Klaus Obermayer and published by MIT Press. This book was released on 2001 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of self-organizing map formation, including recent developments. Self-organizing maps form a branch of unsupervised learning, which is the study of what can be determined about the statistical properties of input data without explicit feedback from a teacher. The articles are drawn from the journal Neural Computation.The book consists of five sections. The first section looks at attempts to model the organization of cortical maps and at the theory and applications of the related artificial neural network algorithms. The second section analyzes topographic maps and their formation via objective functions. The third section discusses cortical maps of stimulus features. The fourth section discusses self-organizing maps for unsupervised data analysis. The fifth section discusses extensions of self-organizing maps, including two surprising applications of mapping algorithms to standard computer science problems: combinatorial optimization and sorting. Contributors J. J. Atick, H. G. Barrow, H. U. Bauer, C. M. Bishop, H. J. Bray, J. Bruske, J. M. L. Budd, M. Budinich, V. Cherkassky, J. Cowan, R. Durbin, E. Erwin, G. J. Goodhill, T. Graepel, D. Grier, S. Kaski, T. Kohonen, H. Lappalainen, Z. Li, J. Lin, R. Linsker, S. P. Luttrell, D. J. C. MacKay, K. D. Miller, G. Mitchison, F. Mulier, K. Obermayer, C. Piepenbrock, H. Ritter, K. Schulten, T. J. Sejnowski, S. Smirnakis, G. Sommer, M. Svensen, R. Szeliski, A. Utsugi, C. K. I. Williams, L. Wiskott, L. Xu, A. Yuille, J. Zhang

Graphical Models

Author : Michael Irwin Jordan
Publisher : MIT Press
ISBN 13 : 9780262600422
Total Pages : 450 pages
Book Rating : 4.6/5 (4 download)

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Book Synopsis Graphical Models by : Michael Irwin Jordan

Download or read book Graphical Models written by Michael Irwin Jordan and published by MIT Press. This book was released on 2001 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book exemplifies the interplay between the general formal framework of graphical models and the exploration of new algorithm and architectures. The selections range from foundational papers of historical importance to results at the cutting edge of research. Graphical models use graphs to represent and manipulate joint probability distributions. They have their roots in artificial intelligence, statistics, and neural networks. The clean mathematical formalism of the graphical models framework makes it possible to understand a wide variety of network-based approaches to computation, and in particular to understand many neural network algorithms and architectures as instances of a broader probabilistic methodology. It also makes it possible to identify novel features of neural network algorithms and architectures and to extend them to more general graphical models.This book exemplifies the interplay between the general formal framework of graphical models and the exploration of new algorithms and architectures. The selections range from foundational papers of historical importance to results at the cutting edge of research. Contributors H. Attias, C. M. Bishop, B. J. Frey, Z. Ghahramani, D. Heckerman, G. E. Hinton, R. Hofmann, R. A. Jacobs, Michael I. Jordan, H. J. Kappen, A. Krogh, R. Neal, S. K. Riis, F. B. Rodríguez, L. K. Saul, Terrence J. Sejnowski, P. Smyth, M. E. Tipping, V. Tresp, Y. Weiss

Modeling Neural Circuits Made Simple with Python

Author : Robert Rosenbaum
Publisher : MIT Press
ISBN 13 : 0262548089
Total Pages : 169 pages
Book Rating : 4.2/5 (625 download)

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Book Synopsis Modeling Neural Circuits Made Simple with Python by : Robert Rosenbaum

Download or read book Modeling Neural Circuits Made Simple with Python written by Robert Rosenbaum and published by MIT Press. This book was released on 2024-03-19 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible undergraduate textbook in computational neuroscience that provides an introduction to the mathematical and computational modeling of neurons and networks of neurons. Understanding the brain is a major frontier of modern science. Given the complexity of neural circuits, advancing that understanding requires mathematical and computational approaches. This accessible undergraduate textbook in computational neuroscience provides an introduction to the mathematical and computational modeling of neurons and networks of neurons. Starting with the biophysics of single neurons, Robert Rosenbaum incrementally builds to explanations of neural coding, learning, and the relationship between biological and artificial neural networks. Examples with real neural data demonstrate how computational models can be used to understand phenomena observed in neural recordings. Based on years of classroom experience, the material has been carefully streamlined to provide all the content needed to build a foundation for modeling neural circuits in a one-semester course. Proven in the classroom Example-rich, student-friendly approach Includes Python code and a mathematical appendix reviewing the requisite background in calculus, linear algebra, and probability Ideal for engineering, science, and mathematics majors and for self-study

An Introductory Course in Computational Neuroscience

Author : Paul Miller
Publisher : MIT Press
ISBN 13 : 0262038250
Total Pages : 405 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis An Introductory Course in Computational Neuroscience by : Paul Miller

Download or read book An Introductory Course in Computational Neuroscience written by Paul Miller and published by MIT Press. This book was released on 2018-10-02 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Fundamentals of Computational Neuroscience

Author : Thomas Trappenberg
Publisher : Oxford University Press
ISBN 13 : 0192696122
Total Pages : 411 pages
Book Rating : 4.1/5 (926 download)

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Book Synopsis Fundamentals of Computational Neuroscience by : Thomas Trappenberg

Download or read book Fundamentals of Computational Neuroscience written by Thomas Trappenberg and published by Oxford University Press. This book was released on 2022-12-08 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational neuroscience is the theoretical study of the brain to uncover the principles and mechanisms that guide the development, organization, information processing, and mental functions of the nervous system. Although not a new area, it is only recently that enough knowledge has been gathered to establish computational neuroscience as a scientific discipline in its own right. Given the complexity of the field, and its increasing importance in progressing our understanding of how the brain works, there has long been a need for an introductory text on what is often assumed to be an impenetrable topic. The new edition of Fundamentals of Computational Neuroscience build on the success and strengths of the previous editions. It introduces the theoretical foundations of neuroscience with a focus on the nature of information processing in the brain. The book covers the introduction and motivation of simplified models of neurons that are suitable for exploring information processing in large brain-like networks. Additionally, it introduces several fundamental network architectures and discusses their relevance for information processing in the brain, giving some examples of models of higher-order cognitive functions to demonstrate the advanced insight that can be gained with such studies. Each chapter starts by introducing its topic with experimental facts and conceptual questions related to the study of brain function. An additional feature is the inclusion of simple Matlab programs that can be used to explore many of the mechanisms explained in the book. An accompanying webpage includes programs for download. The book will be the essential text for anyone in the brain sciences who wants to get to grips with this topic.

The Deep Learning Revolution

Author : Terrence J. Sejnowski
Publisher : MIT Press
ISBN 13 : 026203803X
Total Pages : 354 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis The Deep Learning Revolution by : Terrence J. Sejnowski

Download or read book The Deep Learning Revolution written by Terrence J. Sejnowski and published by MIT Press. This book was released on 2018-10-23 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy. Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.

Computational Neuroscience

Author : Eric L. Schwartz
Publisher : MIT Press
ISBN 13 : 9780262691642
Total Pages : 468 pages
Book Rating : 4.6/5 (916 download)

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Book Synopsis Computational Neuroscience by : Eric L. Schwartz

Download or read book Computational Neuroscience written by Eric L. Schwartz and published by MIT Press. This book was released on 1993-08-26 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: The thirty original contributions in this book provide a working definition of"computational neuroscience" as the area in which problems lie simultaneously within computerscience and neuroscience. They review this emerging field in historical and philosophical overviewsand in stimulating summaries of recent results. Leading researchers address the structure of thebrain and the computational problems associated with describing and understanding this structure atthe synaptic, neural, map, and system levels.The overview chapters discuss the early days of thefield, provide a philosophical analysis of the problems associated with confusion between brainmetaphor and brain theory, and take up the scope and structure of computationalneuroscience.Synaptic-level structure is addressed in chapters that relate the properties ofdendritic branches, spines, and synapses to the biophysics of computation and provide a connectionbetween real neuron architectures and neural network simulations.The network-level chapters take upthe preattentive perception of 3-D forms, oscillation in neural networks, the neurobiologicalsignificance of new learning models, and the analysis of neural assemblies and local learningrides.Map-level structure is explored in chapters on the bat echolocation system, cat orientationmaps, primate stereo vision cortical cognitive maps, dynamic remapping in primate visual cortex, andcomputer-aided reconstruction of topographic and columnar maps in primates.The system-level chaptersfocus on the oculomotor system VLSI models of early vision, schemas for high-level vision,goal-directed movements, modular learning, effects of applied electric current fields on corticalneural activity neuropsychological studies of brain and mind, and an information-theoretic view ofanalog representation in striate cortex.Eric L. Schwartz is Professor of Brain Research and ResearchProfessor of Computer Science, Courant Institute of Mathematical Sciences, New York UniversityMedical Center. Computational Neuroscience is included in the System Development FoundationBenchmark Series.

From Computer to Brain

Author : William W. Lytton
Publisher : Springer Science & Business Media
ISBN 13 : 0387227334
Total Pages : 364 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis From Computer to Brain by : William W. Lytton

Download or read book From Computer to Brain written by William W. Lytton and published by Springer Science & Business Media. This book was released on 2007-05-08 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biology undergraduates, medical students and life-science graduate students often have limited mathematical skills. Similarly, physics, math and engineering students have little patience for the detailed facts that make up much of biological knowledge. Teaching computational neuroscience as an integrated discipline requires that both groups be brought forward onto common ground. This book does this by making ancillary material available in an appendix and providing basic explanations without becoming bogged down in unnecessary details. The book will be suitable for undergraduates and beginning graduate students taking a computational neuroscience course and also to anyone with an interest in the uses of the computer in modeling the nervous system.

Self and Identity

Author : Matthew Tieu
Publisher : Taylor & Francis
ISBN 13 : 1000773051
Total Pages : 188 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Self and Identity by : Matthew Tieu

Download or read book Self and Identity written by Matthew Tieu and published by Taylor & Francis. This book was released on 2022-10-21 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is a self? What does it mean to have selfhood? What is the relationship between selfhood and identity? These are puzzling questions that philosophers, psychologists, social scientists, and many other researchers often grapple with. Self and Identity is a book that explores and brings together relevant ideas on selfhood and identity, while also helping to clarify some important and long standing scientific and philosophical debates. It will enable readers to understand the difference between selves in humans and other animals, and the different selves that we come to possess from when we are born to when we become old. It also explains how and why the self might break down due to mental illness, thereby providing insight into how we might treat illnesses such as dementia and depression, both of which are conditions that fundamentally affect our selfhood. Taking an important step towards clarifying our understanding of human selfhood and applying it to mental illness, this book will be of great interest to researchers and postgraduate students exploring philosophical questions of selfhood, as well as those examining the connection to clinical disorders.

Epiphanies, Individuation, and Human Flourishing

Author : Frances Gray
Publisher : Taylor & Francis
ISBN 13 : 0429663137
Total Pages : 174 pages
Book Rating : 4.4/5 (296 download)

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Book Synopsis Epiphanies, Individuation, and Human Flourishing by : Frances Gray

Download or read book Epiphanies, Individuation, and Human Flourishing written by Frances Gray and published by Taylor & Francis. This book was released on 2023-05-05 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Within this book, Gray argues that moments of profound existential importance are given to us in the presence of Art, and that such moments are important motivators in our personal, civic, and moral lives. Using the work of Jung, Freud, Berger, and Nussbaum, this book looks to Art in its theory and practice as a driver of psychic epiphany. Examining music, environment, architecture, poetry, and painting, it traces the relationship between the ordinary and the extraordinary, showing how we can and do locate ourselves beyond our own psyches in a world of artistic endeavour. Gray concludes that Art plays a critical role in psychological practice and human flourishing on an individual and collective level. Epiphanies, Individuation, and Human Flourishing will appeal to artists, art theorists, therapists, and analysts as a teaching tool that demonstrates the possible connections that can be made among the arts, sciences and psycho-therapeutic communities, and Nature.

Lectures in Supercomputational Neuroscience

Author : Peter Graben
Publisher : Springer
ISBN 13 : 3540731598
Total Pages : 377 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Lectures in Supercomputational Neuroscience by : Peter Graben

Download or read book Lectures in Supercomputational Neuroscience written by Peter Graben and published by Springer. This book was released on 2007-10-19 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written from the physicist’s perspective, this book introduces computational neuroscience with in-depth contributions by system neuroscientists. The authors set forth a conceptual model for complex networks of neurons that incorporates important features of the brain. The computational implementation on supercomputers, discussed in detail, enables you to adapt the algorithm for your own research. Worked-out examples of applications are provided.

The Ecological Brain

Author : Luis H. H. Favela
Publisher : Taylor & Francis
ISBN 13 : 1003830404
Total Pages : 262 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis The Ecological Brain by : Luis H. H. Favela

Download or read book The Ecological Brain written by Luis H. H. Favela and published by Taylor & Francis. This book was released on 2023-12-22 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Ecological Brain is the first book of its kind, using complexity science to integrate the seemingly disparate fields of ecological psychology and neuroscience. The book develops a unique framework for unifying investigations and explanations of mind that span brain, body, and environment: the NeuroEcological Nexus Theory (NExT). Beginning with an introduction to the history of the fields, the author provides an assessment of why ecological psychology and neuroscience are commonly viewed as irreconcilable methods for investigating and explaining cognition, intelligent behavior, and the systems that realize them. The book then progresses to its central aim: presenting a unified investigative and explanatory framework offering concepts, methods, and theories applicable across neural and ecological scales of investigation. By combining the core principles of ecological psychology, neural population dynamics, and synergetics under a unified complexity science approach, NExT offers a compressive investigative framework to explain and understand neural, bodily, and environmental contributions to perception-action and other forms of intelligent behavior and thought. The book progresses the conversation around the role of brains in ecological psychology, as well as bodies and environments in neuroscience. It is essential reading for all students of ecological psychology, perception, cognitive sciences, and neuroscience, as well as anyone interested in the history and philosophy of the brain/mind sciences and their state-of-the-art methods and theories.