Literature DB >> 34780668

Rejoinder to discussions of "distributional independent component analysis for diverse neuroimaging modalities".

Ben Wu1, Subhadip Pal2, Jian Kang3, Ying Guo4.   

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.
© 2021 The Authors. Biometrics published by Wiley Periodicals LLC on behalf of International Biometric Society.

Entities:  

Mesh:

Year:  2021        PMID: 34780668      PMCID: PMC9107522          DOI: 10.1111/biom.13588

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   1.701


  7 in total

1.  A hierarchical independent component analysis model for longitudinal neuroimaging studies.

Authors:  Yikai Wang; Ying Guo
Journal:  Neuroimage       Date:  2019-01-09       Impact factor: 6.556

2.  INVESTIGATING DIFFERENCES IN BRAIN FUNCTIONAL NETWORKS USING HIERARCHICAL COVARIATE-ADJUSTED INDEPENDENT COMPONENT ANALYSIS.

Authors:  Ran Shi; Ying Guo
Journal:  Ann Appl Stat       Date:  2017-01-05       Impact factor: 2.083

3.  Discussion on "Distributional independent component analysis for diverse neuroimaging modalities" by Ben Wu, Subhadip Pal, Jian Kang, and Ying Guo.

Authors:  Heather Shappell; Sean L Simpson
Journal:  Biometrics       Date:  2022-03-15       Impact factor: 1.701

4.  Discussion on "distributional independent component analysis for diverse neuroimaging modalities" by Ben Wu, Subhadip Pal, Jian Kang, and Ying Guo.

Authors:  Beatrijs Moerkerke; Ruth Seurinck
Journal:  Biometrics       Date:  2021-11-15       Impact factor: 1.701

5.  Discussion on "distributional independent component analysis for diverse neuroimaging modalities" by Ben Wu, Subhadip Pal, Jian Kang, and Ying Guo.

Authors:  Kan Keeratimahat; Thomas E Nichols
Journal:  Biometrics       Date:  2021-11-15       Impact factor: 1.701

6.  Distributional independent component analysis for diverse neuroimaging modalities.

Authors:  Ben Wu; Subhadip Pal; Jian Kang; Ying Guo
Journal:  Biometrics       Date:  2021-11-15       Impact factor: 1.701

7.  A hierarchical model for probabilistic independent component analysis of multi-subject fMRI studies.

Authors:  Ying Guo; Li Tang
Journal:  Biometrics       Date:  2013-08-22       Impact factor: 2.571

  7 in total

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