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Related Experiment Video

Updated: May 9, 2026

Topographical Estimation of Visual Population Receptive Fields by fMRI
06:02

Topographical Estimation of Visual Population Receptive Fields by fMRI

Published on: February 3, 2015

Post-hoc power estimation for topological inference in fMRI.

Joke Durnez1, Beatrijs Moerkerke, Thomas E Nichols

  • 1Department of Data Analysis, Ghent University, Ghent, Belgium.

Neuroimage
|August 10, 2013
PubMed
Summary

Functional MRI (fMRI) thresholding methods often reduce false positives but decrease statistical power. This study introduces a method to estimate the power of fMRI analyses, revealing potential missed activations in real studies.

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Area of Science:

  • Neuroimaging
  • Statistical analysis
  • Brain imaging analysis

Background:

  • Functional MRI (fMRI) analysis involves numerous statistical tests, necessitating thresholding to control false positives.
  • Current thresholding methods often lead to reduced statistical power, creating an imbalance between Type I and Type II errors.

Purpose of the Study:

  • To introduce a post-hoc method for estimating the statistical power of fMRI selection procedures.
  • To provide a diagnostic tool for real fMRI studies to assess potential missed activations.

Main Methods:

  • Estimating the number of activated peaks or clusters within fMRI data.
  • Developing a post-hoc procedure to evaluate the power of statistical thresholding methods.
  • Utilizing simulations and a real fMRI dataset for evaluation.
Keywords:
False negative errorsMultiple testingPowerRandom field theoryfMRI

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Last Updated: May 9, 2026

Topographical Estimation of Visual Population Receptive Fields by fMRI
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Topographical Estimation of Visual Population Receptive Fields by fMRI

Published on: February 3, 2015

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
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Detecting Pre-Stimulus Source-Level Effects on Object Perception with Magnetoencephalography

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Main Results:

  • The proposed method allows for post-hoc estimation of the power of fMRI statistical procedures.
  • Simulations and a real data example demonstrate the diagnostic utility of the method.
  • The real data example highlighted a significant lack of power in current fMRI research practices.

Conclusions:

  • Estimating activated peaks/clusters provides a valuable tool for assessing fMRI analysis power.
  • This method can improve the interpretation of fMRI results by revealing potential underpowered studies.
  • Awareness of analysis power is crucial for advancing fMRI research and avoiding missed discoveries.