Coordinate Network Mapping: An Emerging Approach for Morphometric Meta-Analysis.
Coordinate Network Mapping: An Emerging Approach for Morphometric Meta-Analysis.
复制标题
坐标网络映射：形态计量荟萃分析的新兴方法。
DOI：
10.1176/appi.ajp.2021.21100987
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Fox,MichaelD
中科院分区：
文献类型：
--
作者：
Taylor,JosephJ;Siddiqi,ShanH;Fox,MichaelD
Neuroimaging is one of many research fields that have been appropriately scrutinized for irreproducible results (1–3). Such scrutiny highlights underlying methodological and statistical issues that limit neuroimaging’s impact on psychiatric diagnosis and treatment (4, 5). Some of these issues may be addressed with larger sample sizes. Neuroimaging consortia facilitate large-scale data collection and harmonization, resulting in data sets with thousands of patients (6). However, cost and time remain noteworthy barriers to this approach. Metaanalysis is a complementary approach that may help circumvent these barriers while also boosting statistical power. There are various strategies for conducting a neuroimaging meta-analysis, most of which involve harvesting the coordinates of peak structural or functional changes from published studies. The most popular coordinate-based meta-analytic method is activation or anatomic likelihood estimation (ALE), which evaluates the spatial convergence of coordinates associated with a given disorder (7). ALE searches for this spatial convergence across brain regions. However, coordinate convergence onto a single brain region may not tell the full story; many symptoms and disorders may map to brain circuits better than they do to individual brain regions (3, 8, 9).In this issue of the Journal, Zhukovsky et al.(10) use a relatively new meta-analytic technique called coordinate network mapping. This technique leverages the human connectome, a normative wiring diagram of the human brain, to map coordinates onto brain circuits rather than individual brain regions (3, 8, 9). Zhukovsky et al. begin by highlighting a recent multimodal ALE meta-analysis that found no significant coordinate convergence in patients with major depressive disorder (11). Do the results from the studies in this previous metaanalysis fail to converge, or is it possible that they actually have something in common? Zhukovsky et al. address this question by conducting an updated systematic review and meta-analysis of adults with major depressive disorder, older adults with late-life depression, and control participants without psychiatric diagnoses. Data from 14,318 participants in 143 studies were analyzed in two ways: conventional ALE meta-analysis and coordinate network mapping.
