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Computational Techniques In Neuroscience
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Book Synopsis Handbook of Research on Futuristic Design and Intelligent Computational Techniques in Neuroscience and Neuroengineering by : Vikas Khullar
Download or read book Handbook of Research on Futuristic Design and Intelligent Computational Techniques in Neuroscience and Neuroengineering written by Vikas Khullar and published by . This book was released on 2021 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research book include quality chapters on computational models, designs and multidisciplinary approaches for neurological diagnosis and treatment, offering a resource of neurological databases, computational intelligence, brain health informatics, effective analysis of neural functions and technological interventions.
Book Synopsis Principles of Computational Modelling in Neuroscience by : David Sterratt
Download or read book Principles of Computational Modelling in Neuroscience written by David Sterratt and published by Cambridge University Press. This book was released on 2023-10-05 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to use computational modelling techniques to understand the nervous system at all levels, from ion channels to networks.
Book Synopsis Computational Techniques in Neuroscience by : Kamal Malik
Download or read book Computational Techniques in Neuroscience written by Kamal Malik and published by CRC Press. This book was released on 2023-11-14 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: The text discusses the techniques of deep learning and machine learning in the field of neuroscience, engineering approaches to study the brain structure and dynamics, convolutional networks for fast, energy-efficient neuromorphic computing, and reinforcement learning in feedback control. It showcases case studies in neural data analysis. Features: Focuses on neuron modeling, development, and direction of neural circuits to explain perception, behavior, and biologically inspired intelligent agents for decision making Showcases important aspects such as human behavior prediction using smart technologies and understanding the modeling of nervous systems Discusses nature-inspired algorithms such as swarm intelligence, ant colony optimization, and multi-agent systems Presents information-theoretic, control-theoretic, and decision-theoretic approaches in neuroscience. Includes case studies in functional magnetic resonance imaging (fMRI) and neural data analysis This reference text addresses different applications of computational neuro-sciences using artificial intelligence, deep learning, and other machine learning techniques to fine-tune the models, thereby solving the real-life problems prominently. It will further discuss important topics such as neural rehabili-tation, brain-computer interfacing, neural control, neural system analysis, and neurobiologically inspired self-monitoring systems. It will serve as an ideal reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, information technology, and biomedical engineering.
Book Synopsis Computational Neuroscience by : Hanspeter A Mallot
Download or read book Computational Neuroscience written by Hanspeter A Mallot and published by Springer Science & Business Media. This book was released on 2013-05-23 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Neuroscience - A First Course provides an essential introduction to computational neuroscience and equips readers with a fundamental understanding of modeling the nervous system at the membrane, cellular, and network level. The book, which grew out of a lecture series held regularly for more than ten years to graduate students in neuroscience with backgrounds in biology, psychology and medicine, takes its readers on a journey through three fundamental domains of computational neuroscience: membrane biophysics, systems theory and artificial neural networks. The required mathematical concepts are kept as intuitive and simple as possible throughout the book, making it fully accessible to readers who are less familiar with mathematics. Overall, Computational Neuroscience - A First Course represents an essential reference guide for all neuroscientists who use computational methods in their daily work, as well as for any theoretical scientist approaching the field of computational neuroscience.
Book Synopsis Computational Neuroscience and Cognitive Modelling by : Britt Anderson
Download or read book Computational Neuroscience and Cognitive Modelling written by Britt Anderson and published by SAGE. This book was released on 2014-01-08 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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.
Book Synopsis Computational Neuroscience by : Erik De Schutter
Download or read book Computational Neuroscience written by Erik De Schutter and published by CRC Press. This book was released on 2000-11-22 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designed primarily as an introduction to realistic modeling methods, Computational Neuroscience: Realistic Modeling for Experimentalists focuses on methodological approaches, selecting appropriate methods, and identifying potential pitfalls. The author addresses varying levels of complexity, from molecular interactions within single neurons to the
Book Synopsis Encyclopedia of Computational Neuroscience by : Dieter Jaeger
Download or read book Encyclopedia of Computational Neuroscience written by Dieter Jaeger and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Methods in Neuronal Modeling by : Christof Koch
Download or read book Methods in Neuronal Modeling written by Christof Koch and published by MIT Press. This book was released on 1998 with total page 700 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kinetic Models of Synaptic Transmission / Alain Destexhe, Zachary F. Mainen, Terrence J. Sejnowski / - Cable Theory for Dendritic Neurons / Wilfrid Rall, Hagai Agmon-Snir / - Compartmental Models of Complex Neurons / Idan Segev, Robert E. Burke / - Multiple Channels and Calcium Dynamics / Walter M. Yamada, Christof Koch, Paul R. Adams / - Modeling Active Dendritic Processes in Pyramidal Neurons / Zachary F. Mainen, Terrence J. Sejnowski / - Calcium Dynamics in Large Neuronal Models / Erik De Schutter, Paul Smolen / - Analysis of Neural Excitability and Oscillations / John Rinzel, Bard Ermentrout / - Design and Fabrication of Analog VLSI Neurons / Rodney Douglas, Misha Mahowald / - Principles of Spike Train Analysis / Fabrizio Gabbiani, Christof Koch / - Modeling Small Networks / Larry Abbott, Eve Marder / - Spatial and Temporal Processing in Central Auditory Networks / Shihab Shamma / - Simulating Large Networks of Neurons / Alexander D. Protopapas, Michael Vanier, James M. Bower / ...
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.
Book Synopsis Computational Modeling Methods for Neuroscientists by : Erik De Schutter
Download or read book Computational Modeling Methods for Neuroscientists written by Erik De Schutter and published by National Geographic Books. This book was released on 2009-09-04 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to computational modeling methods in neuroscience, covering a range of modeling scales from molecular reactions to large neural networks. This book offers an introduction to current methods in computational modeling in neuroscience. The book describes realistic modeling methods at levels of complexity ranging from molecular interactions to large neural networks. A “how to” book rather than an analytical account, it focuses on the presentation of methodological approaches, including the selection of the appropriate method and its potential pitfalls. It is intended for experimental neuroscientists and graduate students who have little formal training in mathematical methods, but it will also be useful for scientists with theoretical backgrounds who want to start using data-driven modeling methods. The mathematics needed are kept to an introductory level; the first chapter explains the mathematical methods the reader needs to master to understand the rest of the book. The chapters are written by scientists who have successfully integrated data-driven modeling with experimental work, so all of the material is accessible to experimentalists. The chapters offer comprehensive coverage with little overlap and extensive cross-references, moving from basic building blocks to more complex applications. Contributors Pablo Achard, Haroon Anwar, Upinder S. Bhalla, Michiel Berends, Nicolas Brunel, Ronald L. Calabrese, Brenda Claiborne, Hugo Cornelis, Erik De Schutter, Alain Destexhe, Bard Ermentrout, Kristen Harris, Sean Hill, John R. Huguenard, William R. Holmes, Gwen Jacobs, Gwendal LeMasson, Henry Markram, Reinoud Maex, Astrid A. Prinz, Imad Riachi, John Rinzel, Arnd Roth, Felix Schürmann, Werner Van Geit, Mark C. W. van Rossum, Stefan Wils
Book Synopsis Computational Techniques in Neuroscience by : Kamal Malik
Download or read book Computational Techniques in Neuroscience written by Kamal Malik and published by CRC Press. This book was released on 2023-11-14 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: The text discusses the techniques of deep learning and machine learning in the field of neuroscience, engineering approaches to study the brain structure and dynamics, convolutional networks for fast, energy-efficient neuromorphic computing, and reinforcement learning in feedback control. It showcases case studies in neural data analysis. Features: Focuses on neuron modeling, development, and direction of neural circuits to explain perception, behavior, and biologically inspired intelligent agents for decision making Showcases important aspects such as human behavior prediction using smart technologies and understanding the modeling of nervous systems Discusses nature-inspired algorithms such as swarm intelligence, ant colony optimization, and multi-agent systems Presents information-theoretic, control-theoretic, and decision-theoretic approaches in neuroscience. Includes case studies in functional magnetic resonance imaging (fMRI) and neural data analysis This reference text addresses different applications of computational neuro-sciences using artificial intelligence, deep learning, and other machine learning techniques to fine-tune the models, thereby solving the real-life problems prominently. It will further discuss important topics such as neural rehabili-tation, brain-computer interfacing, neural control, neural system analysis, and neurobiologically inspired self-monitoring systems. It will serve as an ideal reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, information technology, and biomedical engineering.
Book Synopsis 20 Years of Computational Neuroscience by : James M Bower
Download or read book 20 Years of Computational Neuroscience written by James M Bower and published by Springer Science & Business Media. This book was released on 2013-07-11 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: When funding agencies and policy organizations consider the role of modeling and simulation in modern biology, the question is often posed, what has been accomplished ? This book will be organized around a symposium on the 20 year history of the CNS meetings, to be held as part of CNS 2010 in San Antonio Texas in July 2010. The book, like the symposium is intended to summarize progress made in Computational Neuroscience over the last 20 years while also considering current challenges in the field. As described in the table of contents, the chapter’s authors have been selected to provide wide coverage of the applications of computational techniques to a broad range of questions and model systems in neuroscience. The proposed book will include several features that establish the history of the field. For each article, its author will select an article originally appearing in a CNS conference proceedings from 15 – 20 years ago. These short (less than 6 page) articles will provide illustrations of the state of the field 20 years ago. The new articles will describe what has been learned about the subject in the following 20 years, and pose specific challenges for the next 20 years. The second historical mechanism will be the reproduction of the first 12 years of posters from the CNS meeting. These posters in and of themselves have become famous in the field (they hang in the halls of the NIH in Bethesda Maryland) and were constructed as allegories for the state and development of computational neuroscience. The posters were designed by the book’s editor, who will, for the first time, provide a written description of each poster.
Book Synopsis Nonlinear Dynamics in Computational Neuroscience by : Fernando Corinto
Download or read book Nonlinear Dynamics in Computational Neuroscience written by Fernando Corinto and published by Springer. This book was released on 2018-06-19 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an essential overview of computational neuroscience. It addresses a broad range of aspects, from physiology to nonlinear dynamical approaches to understanding neural computation, and from the simulation of brain circuits to the development of engineering devices and platforms for neuromorphic computation. Written by leading experts in such diverse fields as neuroscience, physics, psychology, neural engineering, cognitive science and applied mathematics, the book reflects the remarkable advances that have been made in the field of computational neuroscience, an emerging discipline devoted to the study of brain functions in terms of the information-processing properties of the structures forming the nervous system. The contents build on the workshop “Nonlinear Dynamics in Computational Neuroscience: from Physics and Biology to ICT,” which was held in Torino, Italy in September 2015.
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.
Book Synopsis Futuristic Design and Intelligent Computational Techniques in Neuroscience and Neuroengineering by : Singh, Harjit Pal
Download or read book Futuristic Design and Intelligent Computational Techniques in Neuroscience and Neuroengineering written by Singh, Harjit Pal and published by IGI Global. This book was released on 2022-01-07 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: Each day, novel neuroscientific findings show that researchers are focusing on developing advanced smart hardware designs and intelligent computational models to imitate the human brain’s computational abilities. The advancements in smart materials provide a significant role in inventing intelligent bioelectronic device designs with smart features such as accuracy, low power consumption, and more. These advanced and intelligent computing models through machine and smart deep learning algorithms help to understand the information processing capabilities of the human brain with optimum accuracy. Futuristic Design and Intelligent Computational Techniques in Neuroscience and Neuroengineering highlights advanced computational models and hardware designs in neurology and integration of mathematical physical, biological, chemical, and engineering models to mimic brain functions; discovers new technological diagnosis techniques; and achieves high accuracy in learning models to better understand the functioning of the human brain. Providing rich information on brain-computer interfacing, gamification in children, and vestibular rehabilitation, this text acts as an essential resource for experts in electrophysiological studies, neurologists, neuro-physiotherapists, neuro-radiologists, intelligent system developers, bio-software and hardware developers, neuro database collectors, electro-physiologists, professors associated with neurology, psychiatrists, engineers, scientists, and students from academia and industry involved in interdisciplinary approaches to neurology.
Book Synopsis New Techniques in Systems Neuroscience by : Adam D. Douglass
Download or read book New Techniques in Systems Neuroscience written by Adam D. Douglass and published by Springer. This book was released on 2015-04-13 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is essential reading for anyone wishing to understand the recent explosion of experimental tools in neuroscience that now make it possible to manipulate, record, and understand neuronal activity within the intact brain, and which are helping us learn how the many neurons that comprise a network act together to control behavior. Leaders in the field discuss the latest developments in optogenetics, functional imaging, circuit mapping, and the application of these tools to complex biological problems.
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.
