Rejoinder to discussions of “distributional independent component analysis for diverse neuroimaging modalities”

Ben Wu, Subhadip Pal, Jian Kang and Ying Guo

Biometrics, 2022, vol. 78, issue 3, 1122-1126

Abstract: We thank the editors for organizing the discussions and the discussants for insightful comments. Our rejoinder provides results and comments to address the questions raised in the discussions. Specifically, we present results showing DICA largely demonstrates better or comparable stability as compared with standard ICA. We also validate the DICA in real fMRI application by showing DICA generally shows higher reliability in reproducibly recovering major brain functional networks as compared with the standard ICA. We provide details on the computational complexity of the method. The computational cost of DICA is very reasonable with the analysis of the fMRI and DTI data easily implementable on a PC or laptop. Finally, we include discussions on several directions for extending the DICA framework in the future.

Date: 2022
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