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Books > Science & Mathematics > Biology, life sciences > Life sciences: general issues > Neurosciences
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Advanced Data Analysis in Neuroscience - Integrating Statistical and Computational Models (Hardcover, 1st ed. 2017)
Loot Price: R2,066
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Advanced Data Analysis in Neuroscience - Integrating Statistical and Computational Models (Hardcover, 1st ed. 2017)
Series: Bernstein Series in Computational Neuroscience
Expected to ship within 12 - 17 working days
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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 explanatory
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
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