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Evaluation of thresholding methods for activation likelihood estimation meta-analysis via large-scale simulations.

Lennart Frahm1,2, Edna C Cieslik2,3, Felix Hoffstaedter2,3

  • 1Department of Psychiatry, Psychotherapy and Psychosomatics, School of Medicine, RWTH Aachen University, Aachen, Germany.

Human Brain Mapping
|May 10, 2022
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Summary

Threshold-free cluster enhancement (TFCE) is not recommended for Activation Likelihood Estimation (ALE) neuroimaging meta-analyses. While valid, TFCE offers no sensitivity advantage over standard cluster-level FWE correction and is computationally intensive.

Keywords:
FWEfamily-wise errormultiple comparison correctionneuroimaging meta-analysissignificance thresholdingthreshold-free cluster enhancement cluster extent

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Area of Science:

  • Neuroimaging
  • Cognitive Neuroscience
  • Statistical Analysis

Background:

  • Threshold-free cluster enhancement (TFCE) is a popular statistical inference method in neuroimaging.
  • TFCE is known for higher sensitivity and not requiring voxel-level thresholds compared to other methods.
  • Activation Likelihood Estimation (ALE) is a common method for coordinate-based neuroimaging meta-analysis.

Purpose of the Study:

  • To evaluate the applicability and performance of TFCE in ALE meta-analyses.
  • To compare TFCE against voxel-level and cluster-level family-wise error (FWE) correction methods.
  • To determine if TFCE offers advantages over existing correction methods in ALE.

Main Methods:

  • Conducted large-scale simulations using over 200,000 artificial meta-analysis datasets.
  • Varied the number of experiments and spatial convergence across datasets.
  • Applied ALE to datasets and compared TFCE with voxel-level and cluster-level FWE correction.

Main Results:

  • All three methods (TFCE, cFWE, voxel-level FWE) produced valid results with minimal spurious findings.
  • TFCE sensitivity was comparable to cluster-level FWE (cFWE) but slightly worse in some scenarios.
  • cFWE produced the largest clusters, followed by TFCE, while voxel-level FWE yielded the smallest, most specific clusters.

Conclusions:

  • TFCE does not outperform standard cFWE correction in ALE meta-analyses.
  • TFCE is computationally more expensive than cFWE.
  • The general use of TFCE for ALE meta-analysis is not recommended due to lack of superior performance and increased computational cost.