Enhance fMRI Data Analysis by RAICAR
Guozhen Dong, Zirui Huang, Zhi Yang, Xuchu Weng, Peipei Wang · 2009
A new method was introduced to enhance fMRI data analysis by reproducibility-based ICA. Using this new method, unreliable components were first identified and removed by computing reproducibility index from multiple ICA realizations. The remaining components were further denoised by eliminating known artifacts according to given criteria. The resultant data were enhanced in terms of statistical power. A simulation was presented to demonstrate the capability of the method to extract true components from noisy data, and an experimental dataset was used to examine the performance of the method in real contexts.