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A likelihood ratio approach for functional localization in fMRI.

Jasper Degryse1, Beatrijs Moerkerke1

  • 1Department of Data Analysis, Ghent University, H. Dunantlaan 1, 9000 Gent, Belgium.

Journal of Neuroscience Methods
|October 20, 2019
PubMed
Summary

The maximized likelihood ratio (mLR) method enhances fMRI analysis by creating accurate functional regions of interest (fROIs). This novel approach balances statistical errors for reliable results.

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Area of Science:

  • Neuroimaging
  • Statistical analysis
  • Brain mapping

Background:

  • Functional regions of interest (fROIs) are crucial for enhancing fMRI data analysis power.
  • Defining fROIs requires balancing false positives and negatives for spatial accuracy and unbiased results.
  • Individual-specific fROI definition must adapt to each subject's activation levels.

Purpose of the Study:

  • To investigate the benefits of the maximized likelihood ratio (mLR) method for defining fROIs.
  • To assess the mLR method's ability to balance statistical errors in fMRI analysis.
  • To compare the mLR method against existing statistical approaches.

Main Methods:

  • The study utilizes the maximized likelihood ratio (mLR) method, based on likelihood ratios comparing alternative and null hypotheses.
Keywords:
Alternative hypothesisEffect sizeFMRIFunctional ROILikelihood ratioLocalizer task

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  • The mLR method assesses statistical evidence for activation relative to a predefined effect size.
  • Simulations and real fMRI data were used to evaluate the mLR method's performance.

    • Main Results:

    • The mLR method demonstrates cumulative evidence for active voxels with effect sizes exceeding the alternative hypothesis.
    • An optimal balance between Type I and Type II errors is achieved when the alternative hypothesis underestimates the true effect size.
    • The mLR method shows comparable or superior performance to FDR-corrected NHST and regular LRT in detecting relevant voxels and managing error trade-offs.

    Conclusions:

    • The maximized likelihood ratio (mLR) method generates spatially accurate and practically relevant functional regions of interest (fROIs).
    • The mLR method offers an improved approach for defining fROIs in fMRI studies.
    • This method contributes to more reliable and precise fMRI data interpretation.