Design D-Optimal Event-Related Functional Magnetic Resonance Imaging Experiments
| Autor: | Ming-Hung Kao, Moein Saleh, Rong Pan |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Statistics and Probability
medicine.diagnostic_test Computer science Event-related functional magnetic resonance imaging Linear model Design matrix D optimal 01 natural sciences 010104 statistics & probability 03 medical and health sciences 0302 clinical medicine medicine 0101 mathematics Statistics Probability and Uncertainty Greedy algorithm Functional magnetic resonance imaging Design space Algorithm 030217 neurology & neurosurgery |
| Zdroj: | Journal of the Royal Statistical Society Series C: Applied Statistics. 66:73-91 |
| ISSN: | 1467-9876 0035-9254 |
| DOI: | 10.1111/rssc.12151 |
| Popis: | Summary New computer algorithms for finding D-optimal designs of stimulus sequence for functional magnetic resonance imaging (MRI) experiments are proposed. Although functional MRI data are commonly analysed by linear models, the construction of a functional MRI design matrix is much more complicated than in conventional experimental design problems. Inspired by the widely used exchange algorithm technique, our proposed approach implements a greedy search strategy over the vast functional MRI design space for a D-optimal design. Compared with a recently proposed genetic algorithm, our algorithms are superior in terms of computing time and achieved design efficiency in both single-objective and multiobjective problems. In addition, the algorithms proposed are sufficiently flexible to incorporate a constraint that requires the exact number of appearances of each type of stimulus in a design. This realistic design issue is unfortunately not well handled by existing methods. |
| Databáze: | OpenAIRE |
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