Book contents
- Frontmatter
- Contents
- Preface
- 1 Introduction
- 2 Image processing basics
- 3 Preprocessing fMRI data
- 4 Spatial normalization
- 5 Statistical modeling: Single subject analysis
- 6 Statistical modeling: Group analysis
- 7 Statistical inference on images
- 8 Modeling brain connectivity
- 9 Multivoxel pattern analysis and machine learning
- 10 Visualizing, localizing, and reporting fMRI data
- Appendix A A Review of the General Linear Model
- Appendix B Data organization and management
- Appendix C Image formats
- Bibliography
- Index
10 - Visualizing, localizing, and reporting fMRI data
Published online by Cambridge University Press: 01 June 2011
- Frontmatter
- Contents
- Preface
- 1 Introduction
- 2 Image processing basics
- 3 Preprocessing fMRI data
- 4 Spatial normalization
- 5 Statistical modeling: Single subject analysis
- 6 Statistical modeling: Group analysis
- 7 Statistical inference on images
- 8 Modeling brain connectivity
- 9 Multivoxel pattern analysis and machine learning
- 10 Visualizing, localizing, and reporting fMRI data
- Appendix A A Review of the General Linear Model
- Appendix B Data organization and management
- Appendix C Image formats
- Bibliography
- Index
Summary
The dimensionality of fMRI data is so large that, in order to understand the data, it is necessary to use visualization tools that make it easier to see the larger patterns in the data. Parts of this chapter are adapted from Devlin & Poldrack (2007) and Poldrack (2007).
Visualizing activation data
It is most useful to visualize fMRI data using a tool that provides simultaneous viewing in all three canonical orientations at once (see Figure 10.1), which is available in all of the major analysis packages.
Because we wish to view the activation data overlaid on brain anatomy, it is necessary to choose an anatomical image to serve as an underlay. This anatomical image should be as faithful as possible to the functional image being overlaid. When viewing an individual participant's activation, the most accurate representation is obtained by overlaying the statistical maps onto that individual's own anatomical scan coregistered to the functional data. When viewing activation from a group analysis, the underlay should reflect the anatomical variability in the group as well as the smoothing that has been applied to the fMRI data. Overlaying the activation on the anatomical image from a single subject, or on a single-subject image, implies a degree of anatomical precision that is not actually present in the functional data. Instead, the activation should be visualized on an average structural image from the group coregistered to the functional data, preferably after applying the same amount of spatial smoothing as was applied to the functional data.
- Type
- Chapter
- Information
- Handbook of Functional MRI Data Analysis , pp. 173 - 190Publisher: Cambridge University PressPrint publication year: 2011