Chapter

Statistical analysis of activation images

Keith J. Worsley

in Functional Magnetic Resonance Imaging

Published in print November 2001 | ISBN: 9780192630711
Published online March 2012 | e-ISBN: 9780191724770 | DOI: http://dx.doi.org/10.1093/acprof:oso/9780192630711.003.0014
Statistical analysis of activation images

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Statistical analysis is concerned with making inference about underlying patterns in data that often contain a large amount of random error. This chapter begins by building up a model of the functional magnetic resonance imaging (fMRI) data, and discusses the haemodynamic response to the stimulus and then the random error. It deals with estimating the parameters of these models, assessing their variability and making decisions about whether the fMRI data shows any evidence of a blood oxygenation level dependent (BOLD) response to the stimulus. The chapter discusses in detail the methods for estimating both the signal and noise parameters, and also analyses the question of how to optimally design the experiment in order for the data to contain the maximum possible amount of extractable information.

Keywords: statistical analysis; haemodynamic response; signal parameters; noise parameters; random error; activation images

Chapter.  11598 words.  Illustrated.

Subjects: Neuroscience

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