The dissemination of brain imaging guidelines and recommendations

Many neuroimaging guidelines and recommendations have been published in the literature to guide fellow researchers to conduct and report research findings in a standardized manner. It was largely unknown if they were cited or read by the scientific community. Analyses were conducted to assess their impact in terms of citations, Twitter posts, and Mendeley reads. Web of Science Core Collection database was accessed to identify relevant publications. The number of their Twitter posts and Mendeley reads were recorded from Altmetric and Mendeley databases respectively. Spearman correlation tests were conducted to evaluate if the citation count had a relationship with these metrics. When all 1786 publications were considered, citation count had a strong positive correlation with Mendeley reads (rho = 0.602, p < 0.001), but a weak negative correlation with Twitter posts (rho = −0.085, p < 0.001). When publications in the 2010 s were specifically considered, citation count had an even stronger positive correlation with Mendeley reads (rho = 0.712, P < 0.001), whereas the correlation with Twitter posts became positive but still weak (rho = 0.072, P = 0.012). Temporal profiles of citation and Mendeley counts showed that these guidelines and recommendations had a relatively stable influence in the field for years after being published.

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1786 publications providing neuroimaging guidelines and recommendations were analyzed.

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Citation count had a strong positive correlation with Mendeley reads.

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Citation count had a weak negative correlation with Twitter posts.

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It had a weak positive correlation with Twitter posts for publications in the 2010s.

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Temporal profiles of citation and Mendeley counts showed their stable influence.

Ten simple rules for neuroimaging meta-analysis

Neuroimaging 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.