Principles Of Computational Modelling In Neuroscience
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Principles Of Computational Modelling In Neuroscience
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Author : David Sterratt
language : en
Publisher: Cambridge University Press
Release Date : 2023-10-05
Principles Of Computational Modelling In Neuroscience written by David Sterratt and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-05 with Science categories.
Learn to use computational modelling techniques to understand the nervous system at all levels, from ion channels to networks.
Principles Of Computational Modelling In Neuroscience
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Author : David Sterratt
language : en
Publisher: Cambridge University Press
Release Date : 2011-06-30
Principles Of Computational Modelling In Neuroscience written by David Sterratt and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-30 with Medical categories.
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.
Principles Of Computational Modelling In Neuroscience
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Author :
language : en
Publisher:
Release Date : 2011
Principles Of Computational Modelling In Neuroscience written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Computational neuroscience categories.
"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"--
Principles Of Computational Modelling In Neuroscience
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Author : David Sterratt
language : en
Publisher: Cambridge University Press
Release Date : 2011-06-30
Principles Of Computational Modelling In Neuroscience written by David Sterratt and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-30 with Medical categories.
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 signaling. 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 modeling 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.
Principles Of Computational Modelling In Neuroscience
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Author : David Sterratt
language : en
Publisher:
Release Date : 2014-05-14
Principles Of Computational Modelling In Neuroscience written by David Sterratt and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-14 with Computational neuroscience categories.
How to use techniques of computational modelling to understand the nervous system at all levels from ion channels to networks.
Cognitive And Computational Neuroscience
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Author : Seyyed Abed Hosseini
language : en
Publisher: BoD – Books on Demand
Release Date : 2018-05-30
Cognitive And Computational Neuroscience written by Seyyed Abed Hosseini and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-30 with Medical categories.
The book "Cognitive and Computational Neuroscience - Principles, Algorithms and Applications" will answer the following question and statements: System-level neural modeling: what and why? We know a lot about the brain! Need to integrate data: molecular/cellular/system levels. Complexity: need to abstract away higher-order principles. Models are tools to develop explicit theories, constrained by multiple levels (neural and behavioral). Key: models (should) make novel testable predictions on both neural and behavioral levels. Models are useful tools for guiding experiments. The hope is that the information provided in this book will trigger new researches that will help to connect basic neuroscience to clinical medicine.
Theoretical Neuroscience Computational And Mathematical Modeling Of Neural Systems
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Author : Lucio Johnston
language : en
Publisher: American Medical Publishers
Release Date : 2023-09-19
Theoretical Neuroscience Computational And Mathematical Modeling Of Neural Systems written by Lucio Johnston and has been published by American Medical Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-19 with Computers categories.
Theoretical neuroscience refers to a subfield of neuroscience which makes use of brain abstractions, mathematical models and theoretical analysis. It provides a quantitative foundation to explain what nervous systems do, determines how they work and discovers the underlying general principles of their operation. Computational modelling and theoretical analysis are useful tools for describing what nervous systems do, figuring out how they work and understanding why they do so in a specific manner. Neuroscience includes a wide range of methods from molecular and cellular research as well as human, psychophysics and psychology. Theoretical neuroscience promotes cross-disciplinary collaboration through creating compact representations of what has been learned, bridging the gap among different levels of description and recognizing unifying concepts and principles. The basic function of computational modeling neuroscience is to understand the principles governing the development, structure, physiology and cognitive abilities of the nervous system. The goal of models in theoretical neuroscience is to capture the key characteristics of the biological system at multiple spatial-temporal scales. This book is a valuable compilation of topics, ranging from the basic to the most complex advancements in the field of theoretical neuroscience. It aims to shed light on the computational and mathematical modeling of neural systems. The book is appropriate for those seeking detailed information in this area.
Computational Models Of Brain And Behavior
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Author : Ahmed A. Moustafa
language : en
Publisher: John Wiley & Sons
Release Date : 2017-11-13
Computational Models Of Brain And Behavior written by Ahmed A. Moustafa and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-13 with Psychology categories.
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.
Analysis And Modeling Of Coordinated Multi Neuronal Activity
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Author : Masami Tatsuno
language : en
Publisher: Springer
Release Date : 2014-11-13
Analysis And Modeling Of Coordinated Multi Neuronal Activity written by Masami Tatsuno and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-13 with Medical categories.
Since information in the brain is processed by the exchange of spikes among neurons, a study of such group dynamics is extremely important in understanding hippocampus dependent memory. These spike patterns and local field potentials (LFPs) have been analyzed by various statistical methods. These studies have led to important findings of memory information processing. For example, memory-trace replay, a reactivation of behaviorally induced neural patterns during subsequent sleep, has been suggested to play an important role in memory consolidation. It has also been suggested that a ripple/sharp wave event (one of the characteristics of LFPs in the hippocampus) and spiking activity in the cortex have a specific relationship that may facilitate the consolidation of hippocampal dependent memory from the hippocampus to the cortex. The book will provide a state-of-the-art finding of memory information processing through the analysis of multi-neuronal data. The first half of the book is devoted to this analysis aspect. Understanding memory information representation and its consolidation, however, cannot be achieved only by analyzing the data. It is extremely important to construct a computational model to seek an underlying mathematical principle. In other words, an entire picture of hippocampus dependent memory system would be elucidated through close collaboration among experiments, data analysis, and computational modeling. Not only does computational modeling benefit the data analysis of multi-electrode recordings, but it also provides useful insight for future experiments and analyses. The second half of the book will be devoted to the computational modeling of hippocampus-dependent memory.
Computational Modeling Methods For Neuroscientists
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Author : Erik De Schutter
language : en
Publisher: National Geographic Books
Release Date : 2009-09-04
Computational Modeling Methods For Neuroscientists written by Erik De Schutter and has been published by National Geographic Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-04 with Medical categories.
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