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Stochastic Methods in Neuroscience

2010 Mathematics
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Release : 2010
Genre : Mathematics
Kind : eBook
Book Rating : 074/5 ( reviews)

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Book Synopsis Stochastic Methods in Neuroscience by : Carlo Laing

Download or read book Stochastic Methods in Neuroscience written by Carlo Laing. This book was released on 2010. Available in PDF, EPUB and Kindle. Book excerpt: Great interest is now being shown in computational and mathematical neuroscience, fuelled in part by the rise in computing power, the ability to record large amounts of neurophysiological data, and advances in stochastic analysis. These techniques are leading to biophysically more realistic models. It has also become clear that both neuroscientists and mathematicians profit from collaborations in this exciting research area.Graduates and researchers in computational neuroscience and stochastic systems, and neuroscientists seeking to learn more about recent advances in the modelling and analysis of noisy neural systems, will benefit from this comprehensive overview. The series of self-contained chapters, each written by experts in their field, covers key topics such as: Markov chain models for ion channel release; stochastically forced single neurons and populations of neurons; statistical methods for parameterestimation; and the numerical approximation of these stochastic models.Each chapter gives an overview of a particular topic, including its history, important results in the area, and future challenges, and the text comes complete with a jargon-busting index of acronyms to allow readers to familiarize themselves with the language used.

Stochastic Processes in the Neurosciences

1989-01-01 Technology & Engineering
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Release : 1989-01-01
Genre : Technology & Engineering
Kind : eBook
Book Rating : 159/5 ( reviews)

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Book Synopsis Stochastic Processes in the Neurosciences by : Henry C. Tuckwell

Download or read book Stochastic Processes in the Neurosciences written by Henry C. Tuckwell. This book was released on 1989-01-01. Available in PDF, EPUB and Kindle. Book excerpt: This monograph is centered on quantitative analysis of nerve-cell behavior. The work is foundational, with many higher order problems still remaining, especially in connection with neural networks. Thoroughly addressed topics include stochastic problems in neurobiology, and the treatment of the theory of related Markov processes.

Stochastic Neuron Models

2016-02-02 Mathematics
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Release : 2016-02-02
Genre : Mathematics
Kind : eBook
Book Rating : 119/5 ( reviews)

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Book Synopsis Stochastic Neuron Models by : Priscilla E. Greenwood

Download or read book Stochastic Neuron Models written by Priscilla E. Greenwood. This book was released on 2016-02-02. Available in PDF, EPUB and Kindle. Book excerpt: This book describes a large number of open problems in the theory of stochastic neural systems, with the aim of enticing probabilists to work on them. This includes problems arising from stochastic models of individual neurons as well as those arising from stochastic models of the activities of small and large networks of interconnected neurons. The necessary neuroscience background to these problems is outlined within the text, so readers can grasp the context in which they arise. This book will be useful for graduate students and instructors providing material and references for applying probability to stochastic neuron modeling. Methods and results are presented, but the emphasis is on questions where additional stochastic analysis may contribute neuroscience insight. An extensive bibliography is included. Dr. Priscilla E. Greenwood is a Professor Emerita in the Department of Mathematics at the University of British Columbia. Dr. Lawrence M. Ward is a Professor in the Department of Psychology and the Brain Research Centre at the University of British Columbia.

Stochastic Biomathematical Models

2012-10-19 Mathematics
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Release : 2012-10-19
Genre : Mathematics
Kind : eBook
Book Rating : 577/5 ( reviews)

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Book Synopsis Stochastic Biomathematical Models by : Mostafa Bachar

Download or read book Stochastic Biomathematical Models written by Mostafa Bachar. This book was released on 2012-10-19. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic biomathematical models are becoming increasingly important as new light is shed on the role of noise in living systems. In certain biological systems, stochastic effects may even enhance a signal, thus providing a biological motivation for the noise observed in living systems. Recent advances in stochastic analysis and increasing computing power facilitate the analysis of more biophysically realistic models, and this book provides researchers in computational neuroscience and stochastic systems with an overview of recent developments. Key concepts are developed in chapters written by experts in their respective fields. Topics include: one-dimensional homogeneous diffusions and their boundary behavior, large deviation theory and its application in stochastic neurobiological models, a review of mathematical methods for stochastic neuronal integrate-and-fire models, stochastic partial differential equation models in neurobiology, and stochastic modeling of spreading cortical depression.

Phase Resetting in Medicine and Biology

1999-05-21 Science
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Release : 1999-05-21
Genre : Science
Kind : eBook
Book Rating : 975/5 ( reviews)

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Book Synopsis Phase Resetting in Medicine and Biology by : Peter A. Tass

Download or read book Phase Resetting in Medicine and Biology written by Peter A. Tass. This book was released on 1999-05-21. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a new theoretical approach to phase resetting and stimulation-induced synchronization and desynchronization in a population of oscillators. The author uses stochastic methods from statistical mechanics and applies his theory to models of practical importance in physiology and neuroscience. The book is accessible to readers not familiar with the mathematical formalism. The author also proposes improvements to stimulation techniques as used by neurologists and neurosurgeons in the context of Parkinson's disease and MEG/EEG data analysis.

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