Computational Models For Neuroscience

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Computational Models Of Brain And Behavior

Author : Ahmed A. Moustafa
ISBN : 9781119159063
Genre : Psychology
File Size : 31.55 MB
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A comprehensive Introduction to the world of brain and behavior computational models This book provides a broad collection of articles covering different aspects of computational modeling efforts in psychology and neuroscience. Specifically, it discusses models that span different brain regions (hippocampus, amygdala, basal ganglia, visual cortex), different species (humans, rats, fruit flies), and different modeling methods (neural network, Bayesian, reinforcement learning, data fitting, and Hodgkin-Huxley models, among others). Computational Models of Brain and Behavior is divided into four sections: (a) Models of brain disorders; (b) Neural models of behavioral processes; (c) Models of neural processes, brain regions and neurotransmitters, and (d) Neural modeling approaches. It provides in-depth coverage of models of psychiatric disorders, including depression, posttraumatic stress disorder (PTSD), schizophrenia, and dyslexia; models of neurological disorders, including Alzheimer’s disease, Parkinson’s disease, and epilepsy; early sensory and perceptual processes; models of olfaction; higher/systems level models and low-level models; Pavlovian and instrumental conditioning; linking information theory to neurobiology; and more. Covers computational approximations to intellectual disability in down syndrome Discusses computational models of pharmacological and immunological treatment in Alzheimer's disease Examines neural circuit models of serotonergic system (from microcircuits to cognition) Educates on information theory, memory, prediction, and timing in associative learning Computational Models of Brain and Behavior is written for advanced undergraduate, Master's and PhD-level students—as well as researchers involved in computational neuroscience modeling research.
Category: Psychology

Computational Neuroscience Models Of The Basal Ganglia

Author : V. Srinivasa Chakravarthy
ISBN : 9789811084942
Genre : Technology & Engineering
File Size : 31.11 MB
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The book is a compendium of the aforementioned subclass of models of Basal Ganglia, which presents some the key existent theories of Basal Ganglia function. The book presents computational models of basal ganglia-related disorders, including Parkinson’s disease, schizophrenia, and addiction. Importantly, it highlights the applications of understanding the role of the basal ganglia to treat neurological and psychiatric disorders. The purpose of the present book is to amend and expand on James Houk’s book (MIT press; ASIN: B010BF4U9K) by providing a comprehensive overview on computational models of the basal ganglia. This book caters to researchers and academics from the area of computational cognitive neuroscience.
Category: Technology & Engineering

Computational Neuroscience For Advancing Artificial Intelligence Models Methods And Applications

Author : Alonso, Eduardo
ISBN : 9781609600235
Genre : Computers
File Size : 55.5 MB
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"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"--
Category: Computers

Computational Models For Neuroscience

Author : Robert Hecht-Nielsen
ISBN : 9781447100850
Genre : Medical
File Size : 52.32 MB
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Formal study of neuroscience (broadly defined) has been underway for millennia. For example, writing 2,350 years ago, Aristotle! asserted that association - of which he defined three specific varieties - lies at the center of human cognition. Over the past two centuries, the simultaneous rapid advancements of technology and (conse quently) per capita economic output have fueled an exponentially increasing effort in neuroscience research. Today, thanks to the accumulated efforts of hundreds of thousands of scientists, we possess an enormous body of knowledge about the mind and brain. Unfortunately, much of this knowledge is in the form of isolated factoids. In terms of "big picture" understanding, surprisingly little progress has been made since Aristotle. In some arenas we have probably suffered negative progress because certain neuroscience and neurophilosophy precepts have clouded our self-knowledge; causing us to become largely oblivious to some of the most profound and fundamental aspects of our nature (such as the highly distinctive propensity of all higher mammals to automatically seg ment all aspects of the world into distinct holistic objects and the massive reorganiza tion of large portions of our brains that ensues when we encounter completely new environments and life situations). At this epoch, neuroscience is like a huge collection of small, jagged, jigsaw puz zle pieces piled in a mound in a large warehouse (with neuroscientists going in and tossing more pieces onto the mound every month).
Category: Medical

Principles Of Computational Modelling In Neuroscience

Author : David Sterratt
ISBN : 9781139500791
Genre : Medical
File Size : 83.81 MB
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The nervous system is made up of a large number of interacting elements. To understand how such a complex system functions requires the construction and analysis of computational models at many different levels. This book provides a step-by-step account of how to model the neuron and neural circuitry to understand the nervous system at all levels, from ion channels to networks. Starting with a simple model of the neuron as an electrical circuit, gradually more details are added to include the effects of neuronal morphology, synapses, ion channels and intracellular signalling. The principle of abstraction is explained through chapters on simplifying models, and how simplified models can be used in networks. This theme is continued in a final chapter on modelling the development of the nervous system. Requiring an elementary background in neuroscience and some high school mathematics, this textbook is an ideal basis for a course on computational neuroscience.
Category: Medical

Computational Psychiatry

Author : Alan Anticevic
ISBN : 9780128098264
Genre : Medical
File Size : 62.28 MB
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Computational Psychiatry: Mathematical Modeling of Mental Illness is the first systematic effort to bring together leading scholars in the fields of psychiatry and computational neuroscience who have conducted the most impactful research and scholarship in this area. It includes an introduction outlining the challenges and opportunities facing the field of psychiatry that is followed by a detailed treatment of computational methods used in the service of understanding neuropsychiatric symptoms, improving diagnosis and guiding treatments. This book provides a vital resource for the clinical neuroscience community with an in-depth treatment of various computational neuroscience approaches geared towards understanding psychiatric phenomena. Its most valuable feature is a comprehensive survey of work from leaders in this field. Offers an in-depth overview of the rapidly evolving field of computational psychiatry Written for academics, researchers, advanced students and clinicians in the fields of computational neuroscience, clinical neuroscience, psychiatry, clinical psychology, neurology and cognitive neuroscience Provides a comprehensive survey of work from leaders in this field and a presentation of a range of computational psychiatry methods and approaches geared towards a broad array of psychiatric problems
Category: Medical

Computational Modeling Of Cognition And Behavior

Author : Simon Farrell
ISBN : 9781107109995
Genre : Psychology
File Size : 27.45 MB
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This book presents an integrated framework for developing and testing computational models in psychology and related disciplines. Researchers and students are given the knowledge and tools to interpret models published in their area, as well as to develop, fit, and test their own models.
Category: Psychology

Computational Neuroscience In Epilepsy

Author : Ivan Soltesz
ISBN : 0080559530
Genre : Science
File Size : 37.54 MB
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Epilepsy is a neurological disorder that affects millions of patients worldwide and arises from the concurrent action of multiple pathophysiological processes. The power of mathematical analysis and computational modeling is increasingly utilized in basic and clinical epilepsy research to better understand the relative importance of the multi-faceted, seizure-related changes taking place in the brain during an epileptic seizure. This groundbreaking book is designed to synthesize the current ideas and future directions of the emerging discipline of computational epilepsy research. Chapters address relevant basic questions (e.g., neuronal gain control) as well as long-standing, critically important clinical challenges (e.g., seizure prediction). Computational Neuroscience in Epilepsy should be of high interest to a wide range of readers, including undergraduate and graduate students, postdoctoral fellows and faculty working in the fields of basic or clinical neuroscience, epilepsy research, computational modeling and bioengineering. Covers a wide range of topics from molecular to seizure predictions and brain implants to control seizures Contributors are top experts at the forefront of computational epilepsy research Chapter contents are highly relevant to both basic and clinical epilepsy researchers
Category: Science

The Computational Brain

Author : Patricia Smith Churchland
ISBN : 0262531208
Genre : Medical
File Size : 89.68 MB
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Churchland and Sejnowski address the foundational ideas of the emerging field of computational neuroscience, examine a diverse range of neural network models, and consider future directions of the field. How do groups of neurons interact to enable the organism to see, decide, and move appropriately? What are the principles whereby networks of neurons represent and compute? These are the central questions probed by The Computational Brain. Churchland and Sejnowski address the foundational ideas of the emerging field of computational neuroscience, examine a diverse range of neural network models, and consider future directions of the field. The Computational Brain is the first unified and broadly accessible book to bring together computational concepts and behavioral data within a neurobiological framework. Computer models constrained by neurobiological data can help reveal how -- networks of neurons subserve perception and behavior -- bow their physical interactions can yield global results in perception and behavior, and how their physical properties are used to code information and compute solutions. The Computational Brain focuses mainly on three domains: visual perception, learning and memory, and sensorimotor integration. Examples of recent computer models in these domains are discussed in detail, highlighting strengths and weaknesses, and extracting principles applicable to other domains. Churchland and Sejnowski show how both abstract models and neurobiologically realistic models can have useful roles in computational neuroscience, and they predict the coevolution of models and experiments at many levels of organization, from the neuron to the system. 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 pr�cis of neurobiological techniques. The Computational Brain is the first unified and broadly accessible book to bring together computational concepts and behavioral data within a neurobiological framework. Churchland and Sejnowski address the foundational ideas of the emerging field of computational neuroscience, examine a diverse range of neural network models, and consider future directions of the field. A Bradford Book Computational Neuroscience series
Category: Medical

Advanced Data Analysis In Neuroscience

Author : Daniel Durstewitz
ISBN : 9783319599762
Genre : Medical
File Size : 40.26 MB
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This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level, and theoretical neuroscientists with a limited background in statistics. It reviews almost all areas of applied statistics, from basic statistical estimation and test theory, linear and nonlinear approaches for regression and classification, to model selection and methods for dimensionality reduction, density estimation and unsupervised clustering. Its focus, however, is linear and nonlinear time series analysis from a dynamical systems perspective, based on which it aims to convey an understanding also of the dynamical mechanisms that could have generated observed time series. Further, it integrates computational modeling of behavioral and neural dynamics with statistical estimation and hypothesis testing. This way computational models in neuroscience are not only explanat ory frameworks, but become powerful, quantitative data-analytical tools in themselves that enable researchers to look beyond the data surface and unravel underlying mechanisms. Interactive examples of most methods are provided through a package of MatLab routines, encouraging a playful approach to the subject, and providing readers with a better feel for the practical aspects of the methods covered. "Computational neuroscience is essential for integrating and providing a basis for understanding the myriads of remarkable laboratory data on nervous system functions. Daniel Durstewitz has excellently covered the breadth of computational neuroscience from statistical interpretations of data to biophysically based modeling of the neurobiological sources of those data. His presentation is clear, pedagogically sound, and readily useable by experts and beginners alike. It is a pleasure to recommend this very well crafted discussion to experimental neuroscientists as well as mathematically well versed Physicists. The book acts as a window to the issues, to the questions, and to the tools for finding the answers to interesting inquiries about brains and how they function." Henry D. I. Abarbanel Physics and Scripps Institution of Oceanography, University of California, San Diego “This book delivers a clear and thorough introduction to sophisticated analysis approaches useful in computational neuroscience. The models described and the examples provided will help readers develop critical intuitions into what the methods reveal about data. The overall approach of the book reflects the extensive experience Prof. Durstewitz has developed as a leading practitioner of computational neuroscience. “ Bruno B. Averbeck
Category: Medical

Computational Neuroscience Modeling And Applications

Author : Scott Carter
ISBN : 1682856178
Genre :
File Size : 38.98 MB
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Computational neuroscience is the branch of neuroscience that uses mathematical models, theoretical analysis and abstractions, to understand the development, structure and information-processing of the nervous system. It also attempts to understand the principles that govern the physiology and cognitive abilities of the nervous system. Computational neuroscience models help in the understanding of biological phenomena at different spatial-temporal scales. It covers all aspects of membrane currents, proteins, network oscillations, learning, memory, etc. Research in computational neuroscience delves into the concepts of consciousness and the processes of cognition, sensory processing, memory and axonal patterning and development. This book discusses the fundamentals as well as modern approaches of computational neuroscience. It covers all the important aspects of modeling and their applications. Different approaches, evaluations, methodologies and advanced studies have been included in this book. With state-of-the-art inputs by acclaimed experts of this field, this book targets students and researchers alike.

Computational Neuroscience

Author : Jianfeng Feng
ISBN : 9780203494462
Genre : Mathematics
File Size : 68.6 MB
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How does the brain work? After a century of research, we still lack a coherent view of how neurons process signals and control our activities. But as the field of computational neuroscience continues to evolve, we find that it provides a theoretical foundation and a set of technological approaches that can significantly enhance our understanding.
Category: Mathematics

Computational Explorations In Cognitive Neuroscience

Author : Randall C. O'Reilly
ISBN : 0262650541
Genre : Computers
File Size : 80.82 MB
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This text introduces the reader to the main ideas in the field of computational cognitive neuroscience. The aim of the discipline is to understand how the brain embodies the mind by using biologically based computational models which simulate neuronal networks.
Category: Computers

Theoretical Neuroscience

Author : Peter Dayan
ISBN : 9780262541855
Genre : Medical
File Size : 37.97 MB
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The construction and analysis of mathematical and computational models of neural systems.
Category: Medical

Computational Modelling In Behavioural Neuroscience

Author : Dietmar Heinke
ISBN : 9781135430030
Genre : Psychology
File Size : 60.67 MB
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Classically, behavioural neuroscience theorizes about experimental evidence in a qualitative way. However, more recently there has been an increasing development of mathematical and computational models of experimental results, and in general these models are more clearly defined and more detailed than their qualitative counter parts. These new computational models can be set up so that they are consistent with both single neuron and whole-system levels of operation, allowing physiological results to be meshed with behavioural data – thus closing the gap between neurophysiology and human behaviour. There is considerable diversity between models with respect to the methodology of designing a model, the degree to which neurophysiological processes are taken into account and the way data (behavioural, electrophysiological, etc) constrains a model. This book presents examples of this diversity and in doing so represents the state-of-art in the field through a unique collection of papers from the world's leading researchers in the area of computational modelling in behavioural neuroscience. Based on talks given at the third Behavioural Brain Sciences Symposium, held at the Behavioural Brain Sciences Centre, University of Birmingham, in May 2007, the book appeals to a broad audience, from postgraduate students beginning to work in the field to experienced experimenters interested in an overview.
Category: Psychology

Fundamentals Of Computational Neuroscience

Author : Thomas Trappenberg
ISBN : 9780199568413
Genre : Mathematics
File Size : 29.7 MB
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The new edition of Fundamentals of Computational Neuroscience build on the success and strengths of the first edition. 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 networkarchitectures 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 begained with such studies.
Category: Mathematics

Computational Neuroscience Of Drug Addiction

Author : Boris Gutkin
ISBN : 1461407516
Genre : Medical
File Size : 82.62 MB
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Drug addiction remains one of the most important public health problems in western societies and is a rising concern for developing nations. Over the past 3 decades, experimental research on the neurobiology and psychology of drug addiction has generated a torrent of exciting data, from the molecular up to the behavioral levels. As a result, a new and pressing challenge for addiction research is to formulate a synthetic theoretical framework that goes well beyond mere scientific eclectism to deepen our understanding of drug addiction and to foster our capacity to prevent and to cure drug addiction. Intrigued by the apparent irrational behavior of drug addicts, researchers from a wide range of scientific disciplines have formulated a plethora of theoretical schemes over the years to understand addiction. However, most of these theories and models are qualitative in nature and are formulated using terms that are often ill-defined. As a result, the empirical validity of these models has been difficult to test rigorously, which has served to generate more controversy than clarity. In this context, as in other scientific fields, mathematical and computational modeling should contribute to the development of more testable and rigorous models of addiction.
Category: Medical

Computational Neuroscience

Author : Eric L. Schwartz
ISBN : 0262691647
Genre : Medical
File Size : 85.43 MB
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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.
Category: Medical

Statistical And Process Models For Cognitive Neuroscience And Aging

Author : Michael J. Wenger
ISBN : 9781135603359
Genre : Psychology
File Size : 53.94 MB
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Statistical and Process Models for Cognitive Neuroscience and Aging addresses methodological techniques for researching cognitive impairment, Alzheimer's disease, the biophysics and structure of the nervous system, the physiology of memory, and the analysis of EEG data. Each chapter, written by the expert in the area, provides a carefully crafted introduction to the subject at hand and the key methodological challenges facing that area of study. Although the chapters describe sophisticated techniques, each is accessible to scientists from a variety of fields. The editors' goal is to expose researchers working on a range of issues associated with cognitive aging to a variety of approaches and technologies, in an effort to cross disciplinary boundaries and further research in cognitive aging. Intended for researchers in cognitive, behavioral, and computational neuroscience, psychometrics, gerontology, cognitive, health, and developmental psychology, radiology, and medical research, this book also serves as a text for graduate level courses in cognitive science and cognitive aging.
Category: Psychology


Author : Jerome R. Busemeyer
ISBN : 9780128073117
Genre : Medical
File Size : 71.79 MB
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This chapter provides a brief overview of all the steps of computational modeling and illustrates their use in cognitive and decision neuroscience. The chapter starts with a simple example model developed for a popular “decision from experience” type of task. Second, the chapter discusses the important issue concerning analysis of group versus individual data. Third, methods for estimating model parameters are presented, which includes least squares, maximum likelihood, Bayesian estimation, and hierarchical Bayesian estimation. Fourth methods for model comparison are discussed such as R-square, chi-square, Akaike information criterion, Bayesian information criterion, generalization criterion, and cross validation. Finally the importance of using these methods are illustrated with an example model based fMRI application.
Category: Medical