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“A research journal serves that narrow

borderland which separates the known from the unknown”

-P.C.Mahalanobis


Advanced Data Analysis in Neuroscience (Record no. 427290)

MARC details
000 -LEADER
fixed length control field 05120nam a22005535i 4500
020 ## - INTERNATIONAL STANDARD BOOKNUMBER
International Standard Book Number 9783319599762
-- 978-3-319-59976-2
024 7# -
-- 10.1007/978-3-319-59976-2
-- doi
040 ## -
-- ISI Library, Kolkata
050 #4 -
-- QA276-280
072 #7 -
-- PBT
-- bicssc
072 #7 -
-- MED090000
-- bisacsh
072 #7 -
-- PBT
-- thema
072 #7 -
-- MBNS
-- thema
082 04 - DEWEYDECIMAL CLASSIFICATION NUMBER
Classification number 519.5
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Durstewitz, Daniel.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
245 10 - TITLE STATEMENT
Title Advanced Data Analysis in Neuroscience
Medium [electronic resource] :
Remainder of title Integrating Statistical and Computational Models /
Statement of responsibility, etc by Daniel Durstewitz.
942 ## - ADDED ENTRY ELEMENTS(KOHA)
Koha item type E-BOOKS
100 1# - MAIN ENTRY--PERSONAL NAME
-- author.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE STATEMENTS
Place of production, publication, distribution, manufacture Cham :
Name of producer, publisher, distributor, manufacturer Springer International Publishing :
-- Imprint: Springer,
Date of production, publication, distribution, manufacture 2017.
300 ## -
-- XXV, 292 p. 76 illus., 66 illus. in color.
-- online resource.
336 ## - CONTENT TYPE
Content Type Term text
Content Type Code txt
Source rdacontent
337 ## - MEDIA TYPE
Media Type Term computer
Media Type Code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier Type Term online resource
Carrier Type Code cr
Source rdacarrier
347 ## -
-- text file
-- PDF
-- rda
490 1# -
-- Bernstein Series in Computational Neuroscience,
-- 2520-159X
520 ## -
-- 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    .
650 #0 -
-- Statistics.
650 #0 -
-- Mathematical statistics.
650 #0 -
-- Neurosciences.
650 #0 -
-- Statistical methods.
650 14 -
-- Statistics for Life Sciences, Medicine, Health Sciences.
-- http://scigraph.springernature.com/things/product-market-codes/S17030
650 24 -
-- Statistical Theory and Methods.
-- http://scigraph.springernature.com/things/product-market-codes/S11001
650 24 -
-- Neurosciences.
-- http://scigraph.springernature.com/things/product-market-codes/B18006
650 24 -
-- Mathematical and Computational Biology.
-- http://scigraph.springernature.com/things/product-market-codes/M31000
650 24 -
-- Biostatistics.
-- http://scigraph.springernature.com/things/product-market-codes/L15020
710 2# -
-- SpringerLink (Online service)
773 0# -
-- Springer eBooks
776 08 -
-- Printed edition:
-- 9783319599748
776 08 -
-- Printed edition:
-- 9783319599755
776 08 -
-- Printed edition:
-- 9783319867502
830 #0 -
-- Bernstein Series in Computational Neuroscience,
-- 2520-159X
856 40 -
-- https://doi.org/10.1007/978-3-319-59976-2
912 ## -
-- ZDB-2-SMA
950 ## -
-- Mathematics and Statistics (Springer-11649)

No items available.

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