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Related Concept Videos

Brain Imaging01:14

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic Stimulation (TMS).

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Related Experiment Video

Updated: May 21, 2026

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images (SDM-PSI)
06:26

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

Published on: November 27, 2019

Meta-analytic methods for neuroimaging data explained.

Joaquim Radua1, David Mataix-Cols

  • 1Institute of Psychiatry, King's College London, De Crespigny Park, London, UK. Joaquim.Radua@kcl.ac.uk.

Biology of Mood & Anxiety Disorders
|June 29, 2012
PubMed
Summary
This summary is machine-generated.

Neuroimaging meta-analyses synthesize study findings, revealing insights beyond individual research. This review details methods, highlighting pros and cons for consistent, robust neuroimaging research.

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Last Updated: May 21, 2026

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:

  • Neuroscience
  • Medical Imaging

Background:

  • Neuroimaging research has grown exponentially, leading to inconsistent findings.
  • Meta-analyses are crucial for summarizing literature and uncovering novel insights.

Purpose of the Study:

  • To review and compare main meta-analytic methods for neuroimaging data.
  • To discuss the advantages and disadvantages of various approaches.

Main Methods:

  • Description of meta-analytic methods for global brain volumes.
  • Discussion of region of interest (ROI)-based and label-based reviews.
  • Exploration of voxel-based meta-analytic methods and online databases.

Main Results:

  • ROI-based methods offer optimal statistics but may have biased region inclusion.
  • Voxel-based methods provide exhaustive study inclusion but are statistically limited.
  • Voxel-based meta-analysis methods are evolving for improved accuracy and robustness.

Conclusions:

  • Authors should include whole-brain studies and consistent thresholds for meta-analyses.
  • Complementary analyses are recommended to validate findings and minimize false positives.
  • Standardizing meta-analytic approaches enhances the reliability of neuroimaging research synthesis.