Meta-analysis in human neuroimaging: computational modeling of large-scale databases.

Abstract:

:Spatial normalization--applying standardized coordinates as anatomical addresses within a reference space--was introduced to human neuroimaging research nearly 30 years ago. Over these three decades, an impressive series of methodological advances have adopted, extended, and popularized this standard. Collectively, this work has generated a methodologically coherent literature of unprecedented rigor, size, and scope. Large-scale online databases have compiled these observations and their associated meta-data, stimulating the development of meta-analytic methods to exploit this expanding corpus. Coordinate-based meta-analytic methods have emerged and evolved in rigor and utility. Early methods computed cross-study consensus, in a manner roughly comparable to traditional (nonimaging) meta-analysis. Recent advances now compute coactivation-based connectivity, connectivity-based functional parcellation, and complex network models powered from data sets representing tens of thousands of subjects. Meta-analyses of human neuroimaging data in large-scale databases now stand at the forefront of computational neurobiology.

journal_name

Annu Rev Neurosci

authors

Fox PT,Lancaster JL,Laird AR,Eickhoff SB

doi

10.1146/annurev-neuro-062012-170320

subject

Has Abstract

pub_date

2014-01-01 00:00:00

pages

409-34

eissn

0147-006X

issn

1545-4126

journal_volume

37

pub_type

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