Statistical Science

The Coordinate-Based Meta-Analysis of Neuroimaging Data

Pantelis Samartsidis, Silvia Montagna, Timothy D. Johnson, and Thomas E. Nichols

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Abstract

Neuroimaging meta-analysis is an area of growing interest in statistics. The special characteristics of neuroimaging data render classical meta-analysis methods inapplicable and therefore new methods have been developed. We review existing methodologies, explaining the benefits and drawbacks of each. A demonstration on a real dataset of emotion studies is included. We discuss some still-open problems in the field to highlight the need for future research.

Article information

Source
Statist. Sci., Volume 32, Number 4 (2017), 580-599.

Dates
First available in Project Euclid: 28 November 2017

Permanent link to this document
https://projecteuclid.org/euclid.ss/1511838029

Digital Object Identifier
doi:10.1214/17-STS624

Mathematical Reviews number (MathSciNet)
MR3730523

Zentralblatt MATH identifier
1383.62288

Keywords
Meta-analysis neuroimaging functional magnetic resonance imaging

Citation

Samartsidis, Pantelis; Montagna, Silvia; Johnson, Timothy D.; Nichols, Thomas E. The Coordinate-Based Meta-Analysis of Neuroimaging Data. Statist. Sci. 32 (2017), no. 4, 580--599. doi:10.1214/17-STS624. https://projecteuclid.org/euclid.ss/1511838029


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Supplemental materials

  • Supplement to “The coordinate-based meta- analysis of neuroimaging data”. The supplementary material includes the results of the simulation study of Section 4.1 using the MKDA and SDM kernels. MCMC convergence diagnostics for the analysis of the emotions data in Section 4.2 with the BHICP are also presented.