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Related Experiment Video

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Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images (SDM-PSI)

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images (SDM-PSI)

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Parametric coordinate-based meta-analysis: valid effect size meta-analysis of studies with differing statistical

Sergi G Costafreda¹

¹Department of Old Age Psychiatry, Institute of Psychiatry, King's College London, Box PO 070, De Crespigny Park, SE5 8AF London, UK. sergi.1.costafreda@kcl.ac.uk

Journal of Neuroscience Methods

|August 11, 2012

Summary

Parametric coordinate-based meta-analysis (PCM) offers valid quantitative summaries from neuroimaging studies. This method integrates subthreshold data to improve accuracy, outperforming existing techniques for diverse statistical thresholds.

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Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images (SDM-PSI)

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Area of Science:

Neuroimaging
Neuroscience
Biostatistics

Background:

Coordinate-based meta-analysis (CBMA) synthesizes neuroimaging findings.
Existing CBMA methods treat studies with varying statistical thresholds as equivalent.
This limitation can impact the validity of quantitative literature summaries.

Purpose of the Study:

To introduce Parametric Coordinate-Based Meta-Analysis (PCM).
To address the limitation of differing statistical thresholds in CBMA.
To provide asymptotically unbiased meta-analytical summaries.

Main Methods:

PCM computes estimates from thresholded neuroimaging data.
It integrates significant findings with subthreshold measurement information.
Validation performed using simulated and real depression neuroimaging data.

Main Results:

PCM produces asymptotically unbiased meta-analytical summaries.
It demonstrates comparable or superior sensitivity to existing CBMA methods.
PCM shows high agreement with meta-analyses of unthresholded volumetric data.

Conclusions:

PCM is a powerful meta-analysis approach for neuroimaging.
It generates valid, unbiased effect-size summaries across diverse statistical thresholds.
PCM can integrate both whole-brain and region-of-interest studies.