Book contents
- Frontmatter
- Contents
- Preface
- Introduction
- PART I AN OVERVIEW OF FUNCTIONAL MAGNETIC RESONANCE IMAGING
- PART II PRINCIPLES OF MAGNETIC RESONANCE IMAGING
- PART III PRINCIPLES OF FUNCTIONAL MAGNETIC RESONANCE IMAGING
- IIIA Perfusion Imaging
- IIIB The Nature of the Blood Oxygenation Level Dependent Effect
- 16 The Nature of the Blood Oxygenation Level Dependent Effect
- 17 Mapping Brain Activation with BOLD-fMRI
- 18 Statistical Analysis of BOLD Data
- 19 Efficient Design of BOLD Experiments
- Appendix: The Physics of NMR
- Index
19 - Efficient Design of BOLD Experiments
from IIIB - The Nature of the Blood Oxygenation Level Dependent Effect
Published online by Cambridge University Press: 05 September 2013
- Frontmatter
- Contents
- Preface
- Introduction
- PART I AN OVERVIEW OF FUNCTIONAL MAGNETIC RESONANCE IMAGING
- PART II PRINCIPLES OF MAGNETIC RESONANCE IMAGING
- PART III PRINCIPLES OF FUNCTIONAL MAGNETIC RESONANCE IMAGING
- IIIA Perfusion Imaging
- IIIB The Nature of the Blood Oxygenation Level Dependent Effect
- 16 The Nature of the Blood Oxygenation Level Dependent Effect
- 17 Mapping Brain Activation with BOLD-fMRI
- 18 Statistical Analysis of BOLD Data
- 19 Efficient Design of BOLD Experiments
- Appendix: The Physics of NMR
- Index
Summary
IMPLICATIONS OF THE GENERAL LINEAR MODEL FOR THE DESIGN OF fMRI EXPERIMENTS
The Sensitivity for Detection of Weak Activations
The general linear model discussed in Chapter 18 is a powerful and highly flexible technique for analyzing Blood Oxygenation Level Dependent (BOLD) data to estimate the strength and significance of activations. In addition, it provides a useful framework for designing functional magnetic resonance imaging (fMRI) experiments and comparing the sensitivity of different experimental paradigms. For most fMRI applications, the goal is to detect a weak signal change associated with the stimulus, and a direct measure of the sensitivity is the signal-to-noise ratio (SNR) of the measured activation amplitude. Much of the discussion of the general linear model in Chapter 18 was geared toward deriving expressions for the SNR and for the associated statistical measures such as t and F. This chapter focuses on the implications of these SNR considerations for the design of fMRI experiments. From the arguments made in Chapter 18 for the case of a known hemodynamic response represented by a single model function M, the SNR is given by the simple expression aM/σ. The vector M is the unit amplitude response to the stimulus pattern with the mean removed, and M is the amplitude of M. The true amplitude of the response in the data is a, and σ is the standard deviation of the noise added in to each measurement. The intrinsic activation amplitude a is set by brain physiology, and the noise standard deviation σ is set by the imaging hardware and the pulse sequence used for image acquisition, so we can think of these as being fixed aspects of the experiment.
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- Introduction to Functional Magnetic Resonance ImagingPrinciples and Techniques, pp. 473 - 492Publisher: Cambridge University PressPrint publication year: 2002
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