000			04292nam a22004815i 4500
001			978-0-387-78191-4
003			DE-He213
005			20251006084418.0
007			cr nn 008mamaa
008			100301s2008 xxu| s |||| 0|eng d
020			_a9780387781914
020			_a99780387781914
024	7		_a10.1007/978-0-387-78191-4 _2doi
100	1		_aLazar, Nicole. _eauthor.
245	1	4	_aThe Statistical Analysis of Functional MRI Data _h[electronic resource] / _cby Nicole Lazar.
264		1	_aNew York, NY : _bSpringer New York, _c2008.
300			_bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aStatistics for Biology and Health, _x1431-8776
505	0		_aThe 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 "Thresholding" -- Additional Statistical Issues -- Case Study: Eye Motion Data.
520			_aOne 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	_aSTATISTICS.
650		0	_aNEUROSCIENCES.
650		0	_aBIOINFORMATICS.
650		0	_aPSYCHOLOGICAL TESTS AND TESTING.
650	1	4	_aSTATISTICS.
650	2	4	_aPSYCHOLOGICAL METHODS/EVALUATION.
650	2	4	_aSIGNAL, IMAGE AND SPEECH PROCESSING.
650	2	4	_aBIOINFORMATICS.
650	2	4	_aSTATISTICS FOR LIFE SCIENCES, MEDICINE, HEALTH SCIENCES.
650	2	4	_aNEUROSCIENCES.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387781907
830		0	_aStatistics for Biology and Health, _x1431-8776
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-387-78191-4 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SMA
942			_2ddc _cER
999			_c59056 _d59056