Literature DB >> 12768594

Novel ROC-type method for testing the efficiency of multivariate statistical methods in fMRI.

Rajesh R Nandy1, Dietmar Cordes.   

Abstract

The receiver operating characteristic (ROC) method is a useful and popular tool for testing the efficiency of various diagnostic tests applicable to functional MRI (fMRI) data. Typically, the diagnostic tests are applied on simulated and pseudo-human fMRI data, and the area under the ROC curve is used as a measure of the efficiency of the diagnostic test. The effectiveness of such a method depends on how well the simulated data approximate the real data. For multivariate statistical methods, however, this technique is usually inadequate, as the spatial dependence among voxels is ignored for simulated data. In this work a modified ROC method using real fMRI data with a broader scope is proposed. This method can be applied to most fMRI postprocessing techniques, including multivariate analyses such as canonical correlation analysis (CCA). Also, the relationship of the modified ROC method with the conventional ROC method is discussed in detail. Copyright 2003 Wiley-Liss, Inc.

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Year:  2003        PMID: 12768594     DOI: 10.1002/mrm.10469

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  8 in total

1.  A Java-based fMRI processing pipeline evaluation system for assessment of univariate general linear model and multivariate canonical variate analysis-based pipelines.

Authors:  Jing Zhang; Lichen Liang; Jon R Anderson; Lael Gatewood; David A Rottenberg; Stephen C Strother
Journal:  Neuroinformatics       Date:  2008-05-28

2.  Evaluation and comparison of GLM- and CVA-based fMRI processing pipelines with Java-based fMRI processing pipeline evaluation system.

Authors:  Jing Zhang; Lichen Liang; Jon R Anderson; Lael Gatewood; David A Rottenberg; Stephen C Strother
Journal:  Neuroimage       Date:  2008-04-03       Impact factor: 6.556

3.  Multivariate group-level analysis for task fMRI data with canonical correlation analysis.

Authors:  Xiaowei Zhuang; Zhengshi Yang; Karthik R Sreenivasan; Virendra R Mishra; Tim Curran; Rajesh Nandy; Dietmar Cordes
Journal:  Neuroimage       Date:  2019-03-17       Impact factor: 6.556

4.  A preliminary study of functional abnormalities in aMCI subjects during different episodic memory tasks.

Authors:  Mingwu Jin; Victoria S Pelak; Tim Curran; Rajesh R Nandy; Dietmar Cordes
Journal:  Magn Reson Imaging       Date:  2012-03-03       Impact factor: 2.546

5.  Comparison of fMRI analysis methods for heterogeneous BOLD responses in block design studies.

Authors:  Jia Liu; Ben A Duffy; David Bernal-Casas; Zhongnan Fang; Jin Hyung Lee
Journal:  Neuroimage       Date:  2016-12-16       Impact factor: 6.556

6.  Optimizing the performance of local canonical correlation analysis in fMRI using spatial constraints.

Authors:  Dietmar Cordes; Mingwu Jin; Tim Curran; Rajesh Nandy
Journal:  Hum Brain Mapp       Date:  2011-08-30       Impact factor: 5.038

7.  3D spatially-adaptive canonical correlation analysis: Local and global methods.

Authors:  Zhengshi Yang; Xiaowei Zhuang; Karthik Sreenivasan; Virendra Mishra; Tim Curran; Richard Byrd; Rajesh Nandy; Dietmar Cordes
Journal:  Neuroimage       Date:  2017-12-14       Impact factor: 6.556

8.  Extending local canonical correlation analysis to handle general linear contrasts for FMRI data.

Authors:  Mingwu Jin; Rajesh Nandy; Tim Curran; Dietmar Cordes
Journal:  Int J Biomed Imaging       Date:  2012-01-23
  8 in total

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