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Library,Documentation and Information Science Division

“A research journal serves that narrow

borderland which separates the known from the unknown”

-P.C.Mahalanobis


The Statistical Analysis of Functional MRI Data (Record no. 425791)

MARC details
000 -LEADER
fixed length control field 05072nam a22005895i 4500
020 ## - INTERNATIONAL STANDARD BOOKNUMBER
International Standard Book Number 9780387781914
-- 978-0-387-78191-4
024 7# -
-- 10.1007/978-0-387-78191-4
-- doi
040 ## -
-- ISI Library, Kolkata
050 #4 -
-- R895-920
072 #7 -
-- MMPH
-- bicssc
072 #7 -
-- MED008000
-- bisacsh
072 #7 -
-- MKSH
-- thema
072 #7 -
-- MKS
-- thema
082 04 - DEWEYDECIMAL CLASSIFICATION NUMBER
Classification number 616.0757
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Lazar, Nicole.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
245 14 - TITLE STATEMENT
Title The Statistical Analysis of Functional MRI Data
Medium [electronic resource] /
Statement of responsibility, etc by Nicole Lazar.
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 New York, NY :
Name of producer, publisher, distributor, manufacturer Springer New York,
Date of production, publication, distribution, manufacture 2008.
300 ## -
-- XIV, 299 p.
-- 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# -
-- Statistics for Biology and Health,
-- 1431-8776
505 0# -
-- The Science of fMRI -- Design of fMRI Experiments -- Noise and Data Preprocessing -- Statistical Issues in fMRI Data Analysis -- Basic Statistical Analysis -- Temporal, Spatial, and Spatiotemporal Models -- Multivariate Approaches -- Basis Function Approaches -- Bayesian Methods in fMRI -- Multiple Testing in fMRI: The Problem of #x201C;Thresholding#x201D; -- Additional Statistical Issues -- Case Study: Eye Motion Data.
520 ## -
-- One of the most intriguing questions facing modern science is the inner workings of the human brain. Functional magnetic resonance imaging (fMRI) is a powerful tool used to study the human brain in action. The data produced from mapping the active processes within the brain present many challenges to statisticians, computer scientists, engineers and other data analysts, due to their complex structure and the ever-increasing sophistication of the scientific questions being posed by researchers. This book represents the first in-depth discussion of statistical methodology, which it couples with an introduction to the scientific background needed to understand the data. Starting from the basic science - where fMRI data come from, why they are so complicated, and the role statistics can play in designing and interpreting experiments - the book gives a detailed survey of the numerous methods that have been applied in the last fifteen years. The analysis of fMRI data features many of the major issues of concern in modern statistics, such as high dimensionality, multiple testing, and visualization. The array of techniques examined in the book ranges from the simple two-sample t-test and the general linear model to hierarchical spatiotemporal models, multivariate methods such as principal components analysis, and Bayesian approaches as they have been used in fMRI. Software, including descriptions of the most popular freeware packages and their capabilities, is also discussed. This book offers researchers who are interested in the analysis of fMRI data a detailed discussion from a statistical perspective that covers the entire process from data collection to the graphical presentation of results. The book is a valuable resource for statisticians who want to learn more about this growing field, and for neuroscientists who want to learn more about how their data can be analyzed. Nicole A. Lazar is Professor of Statistics at the University of Georgia and affiliated faculty of the Center for Health Statistics, University of Illinois at Chicago. She is a prominent researcher in this area, a contributor to the FIASCO software for fMRI data analysis, and heads an fMRI statistics research group at the University of Georgia.
650 #0 -
-- Radiology, Medical.
650 #0 -
-- Neurosciences.
650 #0 -
-- Statistics.
650 #0 -
-- Bioinformatics.
650 #0 -
-- Psychological tests and testing.
650 14 -
-- Imaging / Radiology.
-- http://scigraph.springernature.com/things/product-market-codes/H29005
650 24 -
-- Neurosciences.
-- http://scigraph.springernature.com/things/product-market-codes/B18006
650 24 -
-- Statistics for Life Sciences, Medicine, Health Sciences.
-- http://scigraph.springernature.com/things/product-market-codes/S17030
650 24 -
-- Bioinformatics.
-- http://scigraph.springernature.com/things/product-market-codes/L15001
650 24 -
-- Signal, Image and Speech Processing.
-- http://scigraph.springernature.com/things/product-market-codes/T24051
650 24 -
-- Psychological Methods/Evaluation.
-- http://scigraph.springernature.com/things/product-market-codes/Y20040
710 2# -
-- SpringerLink (Online service)
773 0# -
-- Springer eBooks
776 08 -
-- Printed edition:
-- 9781441926791
776 08 -
-- Printed edition:
-- 9780387569840
776 08 -
-- Printed edition:
-- 9780387781907
830 #0 -
-- Statistics for Biology and Health,
-- 1431-8776
856 40 -
-- https://doi.org/10.1007/978-0-387-78191-4
912 ## -
-- ZDB-2-SMA
950 ## -
-- Mathematics and Statistics (Springer-11649)

No items available.

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