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Decisions made during the analysis or reporting of an fMRI study influence the eligibility of that study to be entered into a meta-analysis. In a meta-analysis, results of different studies on the same topic are combined. To combine the results, it is necessary that all studies provide equivalent pieces of information. However, in task-based fMRI studies we see a large variety in reporting styles. Several specific meta-analysis methods have been developed to deal with the reporting practices occurring in task-based fMRI studies, therefore each requiring a specific type of input. In this manuscript we provide an overview of the meta-analysis methods and the specific input they require. Subsequently we discuss how decisions made during the study influence the eligibility of a study for a meta-analysis and finally we formulate some recommendations about how to report an fMRI study so that it complies with as many meta-analysis methods as possible. [ABSTRACT FROM AUTHOR]

What are the standards for the reporting methods and results of fMRI studies, and how have they evolved over the years? To answer this question we reviewed 160 papers published between 2004 and 2019. Reporting styles for methods and results of fMRI studies can differ greatly between published studies. However, adequate reporting is essential for the comprehension, replication and reuse of the study (for instance in a meta-analysis). To aid authors in reporting the methods and results of their task-based fMRI study the COBIDAS report was published in 2016, which provides researchers with clear guidelines on how to report the design, acquisition, preprocessing, statistical analysis and results (including data sharing) of fMRI studies (Nichols et al. in Best Practices in Data Analysis and Sharing in Neuroimaging using fMRI, 2016). In the past reviews have been published that evaluate how fMRI methods are reported based on the 2008 guidelines, but they did not focus on how task based fMRI results are reported. This review updates reporting practices of fMRI methods, and adds an extra focus on how fMRI results are reported. We discuss reporting practices about the design stage, specific participant characteristics, scanner characteristics, data processing methods, data analysis methods and reported results. [ABSTRACT FROM AUTHOR]

Within the neuroimaging community, coordinate based meta-analyses (CBMAs) are essential for aggregating findings across studies and testing whether those studies report similar anatomical locations. This approach has been predominantly applied to studies that focus on whether activation of a brain region is associated with a given psychological process. In a recent paper, we used CBMA to examine a distinct set of studies-that is, those focusing on whether connectivity between brain regions is modulated by a given psychological process (Smith et al. [2016]: Hum Brain Mapp 37:2904-2917). Specifically, we reviewed 284 studies examining brain connectivity with psychophysiological interactions (PPI). Our meta-analytic results indicated that PPI yields connectivity patterns that are consistent across studies and that can be specific for a given psychological process and seed region. After publication of our findings, we learned that the analysis software we used to conduct our CBMAs (GingerALE v2.3.3) contained an implementation error that led to results that were more liberal than intended. Here, we comment on the impact of this implementation error on the results of our paper, new recommendations for sample sizes in CBMAs, and the importance of communication between software users and developers. We show that our key claims are supported in a reanalysis and that our results are robust to new guidelines on sample sizes. Hum Brain Mapp 38:588-591, 2017. © 2016 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Much of the work in cognitive neuroscience is shifting from a focus on single brain regions to a focus on the connectivity between multiple brain regions. These inter-regional connectivity patterns contribute to a wide range of behaviors and are studied with models of functional integration. The rapid expansion of the literature on functional integration offers an opportunity to scrutinize the consistency and specificity of one of the most popular approaches for quantifying connectivity: psychophysiological interaction (PPI) analysis. We performed coordinate-based meta-analyses on 284 PPI studies, which allowed us to test (a) whether those studies consistently converge on similar target regions and (b) whether the identified target regions are specific to the chosen seed region and psychological context. Our analyses revealed two key results. First, we found that different types of PPI studies-e.g., those using seeds such as amygdala and dorsolateral prefrontal cortex (DLPFC) and contexts such as emotion and cognitive control, respectively-each consistently converge on similar target regions, thus supporting the reliability of PPI as a tool for studying functional integration. Second, we also found target regions that were specific to the chosen seed region and psychological context, indicating distinct patterns of brain connectivity. For example, the DLPFC seed reliably contributed to a posterior cingulate cortex target during cognitive control but contributed to an amygdala target in other contexts. Our results point to the robustness of PPI while highlighting common and distinct patterns of functional integration, potentially advancing models of brain connectivity. Hum Brain Mapp 37:2904-2917, 2016. © 2016 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]