A B S T R A C TNeuroimaging has evolved into a widely used method to investigate the functional neuroanatomy, brain-behaviour relationships, and pathophysiology of brain disorders, yielding a literature of more than 30,000 papers. With such an explosion of data, it is increasingly difficult to sift through the literature and distinguish spurious from replicable findings. Furthermore, due to the large number of studies, it is challenging to keep track of the wealth of findings. A variety of meta-analytical methods (coordinate-based and image-based) have been developed to help summarise and integrate the vast amount of data arising from neuroimaging studies. However, the field lacks specific guidelines for the conduct of such meta-analyses. Based on our combined experience, we propose best-practice recommendations that researchers from multiple disciplines may find helpful. In addition, we provide specific guidelines and a checklist that will hopefully improve the transparency, traceability, replicability and reporting of meta-analytical results of neuroimaging data.

Meta-analyses are essential to summarize the results of the growing number of neuroimaging studies in psychiatry, neurology and allied disciplines. Image-based meta-analyses use full image information (i.e. the statistical parametric maps) and well-established statistics, but images are rarely available making them highly unfeasible. Peak-probability meta-analyses such as activation likelihood estimation (ALE) or multilevel kernel density analysis (MKDA) are more feasible as they only need reported peak coordinates. Signed-differences methods, such as signed differential mapping (SDM) build upon the positive features of existing peak-probability methods and enable meta-analyses of studies comparing patients with controls. In this paper we present a new version of SDM, named Effect Size SDM (ES-SDM), which enables the combination of statistical parametric maps and peak coordinates and uses well-established statistics. We validated the new method by comparing the results of an ES-SDM meta-analysis of studies on the brain response to fearful faces with the results of a pooled analysis of the original individual data. The results showed that ES-SDM is a valid and reliable coordinate-based method, whose performance might be additionally increased by including statistical parametric maps. We anticipate that ES-SDM will be a helpful tool for researchers in the fields of psychiatry, neurology and allied disciplines.

Twelve data-sets comprising 401 people with OCD and 376 healthy controls met inclusion criteria. A new improved voxel-based meta-analytic method, signed differential mapping (SDM), was developed to examine regions of increased and decreased grey matter volume in the OCD group v. control group. Results No between-group differences were found in global grey matter volumes. People with OCD had increased regional grey matter volumes in bilateral lenticular nuclei, extending to the caudate nuclei, as well as decreased volumes in bilateral dorsal medial frontal/anterior cingulate gyri. A descriptive analysis of quartiles, a sensitivity analysis as well as analyses of subgroups further confirmed these findings. Meta-regression analyses showed that studies that included individuals with more severe OCD were significantly more likely to report increased grey matter volumes in the basal ganglia. No effect of current antidepressant treatment was observed. Conclusions The results support a dorsal prefrontal-striatal model of the disorder and raise the question of whether functional alterations in other brain regions commonly associated with OCD, such as the orbitofrontal cortex, may reflect secondary compensatory strategies. Whether the reported differences between participants with OCD and controls precede the onset of the symptoms and whether they are specific to OCD remains to be established.

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The complex clinical presentation of OCD can be summarized with a few consistent, temporally stable symptom dimensions. These can be understood as a spectrum of potentially overlapping syndromes that may 1) coexist in any patient, 2) be continuous with normal obsessive-compulsive phenomena, and 3) extend beyond the traditional nosological boundaries of OCD. Although the dimensional structure of obsessive-compulsive symptoms is imperfect, this quantitative approach to phenotypic traits has the potential to advance our understanding of OCD and may aid in the identification of more robust endophenotypes. The need for a dimensional rating scale and suggestions for future research aimed at reducing the burden of this disorder are discussed.