Chapter 11

Self-assessment Questions

1. What is the difference between descriptive and inferential statistics? Which do we use to assess statistical significance in fMRI?
2. What are Type I and Type II errors? Which is typically minimized in fMRI data analysis?
3. Describe the basic principles of a t test. In what sorts of analyses are t tests most commonly used?
4. What are the advantages and disadvantages of the Kolmogorov-Smirnov test compared to the t test?
5. What are the basic principles of a correlation analysis? Over what range do correlation coefficients vary?
6. What are the effects of signal averaging upon a correlation analysis?
7. What does a Fourier transform due to a time series of data?
8. What is the Nyquist Sampling Theorem? Why is it important for fMRI?
9. What is the difference between radiological and neurological conventions for displaying MRI data?
10. What are the principles of the General Linear Model? How do we evaluate the significance of activity using the GLM?
11. What is a design matrix?
12. What are nuisance factors, and why might they be included in an analysis model?
13. What are the assumptions of the General Linear Model? How valid are these assumptions for fMRI?
14. What are data-driven analyses? What advantages and disadvantages do they present for fMRI?
15. What is the multiple comparisons problem?
16. What are the major ways of ameliorating the multiple comparisons problem?
17. What are region of interest analyses? What advantages and disadvantages do they have relative to voxelwise analyses?
18. What is the difference between fixed-effects and random-effects analyses? Which is considered more appropriate for generalizing fMRI results to the population from which the subjects were drawn?
19. What challenges must be overcome in order to use fMRI as a diagnostic tool for pre-surgical patients?