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

Ben Wu, Subhadip Pal, Jian Kang, Ying Guo

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)1122-1126
Number of pages5
Issue number3
Publication statusPublished - Sept 2022
Externally publishedYes

ASJC Scopus subject areas

  • Statistics and Probability
  • General Biochemistry,Genetics and Molecular Biology
  • General Immunology and Microbiology
  • General Agricultural and Biological Sciences
  • Applied Mathematics


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