Test‐retest reliability estimation of functional MRI data
- 27 June 2002
- journal article
- research article
- Published by Wiley in Magnetic Resonance in Medicine
- Vol. 48 (1) , 62-70
- https://doi.org/10.1002/mrm.10191
Abstract
Functional magnetic resonance imaging (fMRI) data are commonly used to construct activation maps for the human brain. It is important to quantify the reliability of such maps. We have developed statistical models to provide precise estimates for reliability from several runs of the same paradigm over time. Specifically, our method extends the premise of maximum likelihood (ML) developed by Genovese et al. (Magn Reson Med 1997;38:497–507) by incorporating spatial context into the estimation process. Experiments indicate that our methodology provides more conservative estimates of true positives compared to those obtained by Genovese et al. The reliability estimates can be used to obtain voxel‐specific reliability measures for activated as well as inactivated regions in future experiments. We derive statistical methodology to determine optimal thresholds for region‐ and context‐specific activations. Empirical guidelines are also provided on the number of repeat scans to acquire in order to arrive at accurate reliability estimates. We report the results from experiments involving a motor paradigm performed on a single subject several times over a period of 2 months. Magn Reson Med 48:62–70, 2002.Keywords
This publication has 14 references indexed in Scilit:
- ROC Analysis of Statistical Methods Used in Functional MRI: Individual SubjectsNeuroImage, 1999
- Event-related functional MRI: Past, present, and futureProceedings of the National Academy of Sciences, 1998
- Estimating test‐retest reliability in functional MR imaging II: Application to motor and cognitive activation studiesMagnetic Resonance in Medicine, 1997
- Software tools for analysis and visualization of fMRI dataNMR in Biomedicine, 1997
- A reproducible repositioning method for serial magnetic resonance imaging studies of the brain in treatment trials for multiple sclerosisJournal of Magnetic Resonance Imaging, 1997
- Reduction of physiological fluctuations in fMRI using digital filtersMagnetic Resonance in Medicine, 1996
- Bayesian Computation and Stochastic SystemsStatistical Science, 1995
- Artifacts due to stimulus correlated motion in functional imaging of the brainMagnetic Resonance in Medicine, 1994
- Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation.Proceedings of the National Academy of Sciences, 1992
- Digital Image ProcessingJournal of Applied Statistics, 1989