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The Statistical Analysis of Functional MRI DataStatistical Issues in fMRI Data Analysis

The Statistical Analysis of Functional MRI Data: Statistical Issues in fMRI Data Analysis Having surveyed the science of fMRI, specifically how the data are collected, experimental design, and noise, and before moving to an in-depth discussion of the many statistical techniques that have been developed (and continue to be developed) for the analysis of fMRI data, it might be helpful to take a step back and consider what the major statistical analysis questions are. This will help frame the discussion in the coming chapters, as well as provide context for that discussion. 4.1 Characteristics of the Data fMRI data acquired on a single subject are characterized by the following features: they are abundant, they are noisy, and they are highly correlated both spatially and temporally. We can think of the data with which we have to work as a time series, or more generally a movie, of the human brain in action. At each voxel of the brain, the measured data are the MR signal as it evolves over the time course of the experiment. In a typical experiment this time course may be hundreds of time points long, with an image being acquired at each time point. The number of spatial points for which data are available will usually be in http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

The Statistical Analysis of Functional MRI DataStatistical Issues in fMRI Data Analysis

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Publisher
Springer New York
Copyright
© Springer-Verlag New York 2008
ISBN
978-0-387-78190-7
Pages
1 –11
DOI
10.1007/978-0-387-78191-4_4
Publisher site
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Abstract

Having surveyed the science of fMRI, specifically how the data are collected, experimental design, and noise, and before moving to an in-depth discussion of the many statistical techniques that have been developed (and continue to be developed) for the analysis of fMRI data, it might be helpful to take a step back and consider what the major statistical analysis questions are. This will help frame the discussion in the coming chapters, as well as provide context for that discussion. 4.1 Characteristics of the Data fMRI data acquired on a single subject are characterized by the following features: they are abundant, they are noisy, and they are highly correlated both spatially and temporally. We can think of the data with which we have to work as a time series, or more generally a movie, of the human brain in action. At each voxel of the brain, the measured data are the MR signal as it evolves over the time course of the experiment. In a typical experiment this time course may be hundreds of time points long, with an image being acquired at each time point. The number of spatial points for which data are available will usually be in

Published: Jun 7, 2008

Keywords: Gray Matter; Hemodynamic Response; fMRI Data; Statistical Issue; Bold Response

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