Rejoinder to discussions of "distributional independent component analysis for diverse neuroimaging modalities". Issue 3 (15th November 2021)

• Record Type: Journal Article
• Authors: Wu, Ben; Pal, Subhadip; Kang, Jian; Guo, Ying
• Is Part Of: Biometrics. Volume 78:Issue 3(2022)
• Page Start: 1122
• Page End: 1126
• Publication Date: 2021-11-15
• Subjects: Biometry -- Periodicals; 570.15195
• DOI: 10.1111/biom.13588
• Languages: English
• ISSNs: 0006-341X

Abstract

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.