Input permutation method to detect active voxels in fMRI study

Sang H. Lee, Johan Lim, Do Hwan Park, Bharat B. Biswal, Eva Petkova

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Correctly identifying voxels or regions of interest (ROI) that actively respond to a given stimulus is often an important objective/step in many functional magnetic resonance imaging (fMRI) studies. In this article, we study a nonparametric method to detect active voxels, which makes minimal assumption about the distribution of blood oxygen level-dependent (BOLD) signals. Our proposal has several interesting features. It uses time lagged correlation to take into account the delay in response to the stimulus, due to hemodynamic variations. We introduce an input permutation method (IPM), a type of block permutation method, to approximate the null distribution of the test statistic. Also, we propose to pool the permutation-derived statistics of preselected voxels for a better approximation to the null distribution. Finally, we control multiple testing error rate using the local false discovery rate (FDR) by Efron [Correlation and large-scale simultaneous hypothesis testing. J Am Stat Assoc 102 (2007) 93-103] and Park et al. [Estimation of empirical null using a mixture of normals and its use in local false discovery rate. Comput Stat Data Anal 55 (2011) 2421-2432] to select the active voxels.

Original languageEnglish (US)
Pages (from-to)1495-1504
Number of pages10
JournalMagnetic Resonance Imaging
Issue number10
StatePublished - Dec 2012
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Biophysics
  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging


  • FMRI
  • False discovery rate
  • Input permutation method
  • Lagged correlation
  • Time delay


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