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This study presents BrainEffeX, an interactive web app for estimating effect sizes in functional MRI (fMRI) studies. It provides precise estimates for common fMRI designs, aiding experimental planning and power analyses.

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Area of Science:

  • Neuroimaging
  • Cognitive Neuroscience
  • Data Science

Background:

  • Effect size estimation is vital for fMRI power analyses and experimental design.
  • fMRI data complexity and analysis techniques present unique challenges for accurate effect size estimation.
  • Existing tools may not adequately address the specific needs of fMRI effect size exploration.

Purpose of the Study:

  • To introduce an interactive web application, BrainEffeX, for exploring functional MRI (fMRI) effect maps.
  • To provide precise voxel-wise and multivariate effect size estimates for common fMRI study designs.
  • To create a collaborative, growing resource for the fMRI research community.

Main Methods:

  • Utilized large-scale fMRI datasets (n > 500) for robust effect size calculations.
  • Calculated effect sizes for typical fMRI designs: brain-behavior correlation, task vs. rest contrasts, and functional connectivity analyses.
  • Developed an interactive web application (neuroprismlab.shinyapps.io/BrainEffeX) for visualizing and exploring these effect maps.

Main Results:

  • Generated precise voxel-wise and multivariate effect size estimates from large fMRI datasets.
  • Demonstrated the application's utility across diverse fMRI analysis types, including activation and connectivity maps.
  • Established a foundational resource for understanding effect sizes in standard fMRI research paradigms.

Conclusions:

  • BrainEffeX offers a valuable tool for researchers to explore fMRI effect sizes and inform experimental design.
  • The application facilitates a deeper understanding of effect magnitudes in typical fMRI studies.
  • Encourages community contributions of large datasets to expand the resource's scope and accuracy.