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We propose a novel, efficient approach for obtaining high-quality experimental designs for event-related functional magnetic resonance imaging (ER-fMRI), a popular brain mapping technique. Our proposed approach combines a greedy hill-climbing algorithm and a cyclic permutation method. When searching for optimal ER-fMRI designs, the proposed approach focuses only on a promising restricted class of designs with equal frequency of occurrence across stimulus types. The computational time is significantly reduced. We demonstrate that our proposed approach is very efficient compared with a recently proposed genetic algorithm approach. We also apply our approach in obtaining designs that are robust against misspecification of error correlations.
- Kao, Ming-Hung (Author)
- Mittelmann, Hans (Author)
- College of Liberal Arts and Sciences (Contributor)
Kao, Ming-Hung, & Mittelmann, Hans D. (2014). A fast algorithm for constructing efficient event-related functional magnetic resonance imaging designs. JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 84(11), 2391-2407. http://dx.doi.org/10.1080/00949655.2013.804524
- 2014-12-04 03:40:03
- 2021-11-02 11:54:28
- 3 years ago