Description:
Quality control (QC) has long been an important part of FMRI processing, but it is typically underreported and too often underappreciated, whether for small or large, public or local datasets. This project aims to showcase examples of QC practices across institutions and to foster discussions within the field. Here, we welcome researchers and developers across the globe to describe their QC methods in detail and to show them "in action" for a varied dataset acquired across multiple sites and scanners.
Current imaging practices and acquisition details vary widely across the neuroimaging community, depending on study aims, available hardware and more. QC procedures then typically vary along with these different acquisitions (for example, different criteria are relevant to single- or multi-echo data), as well as by software used and by the people interpreting it. The current project focuses on what is likely the most common MRI acquisition protocol both historically and today: non-accelerated (single-band) FMRI. QC for single-band EPI datasets is in some ways the foundation for all others; it is something that all neuroimaging researchers will encounter either directly or indirectly through the literature, making it the ideal target for the current project. To provide a common set of examples with which to demonstrate different QC practices, we have gathered data from several open, public FMRI repositories: specifically, datasets which have already been used in many studies and can be considered fairly representative of MRI data forming the basis of studies in the field.
We welcome researchers to present their quality control assessments of the subjects in the provided data collection, listing which would be included or excluded from further analyses, and which might be considered borderline or "uncertain." Both task and several resting state cohorts are included, and participating researchers can choose to examine either or both of these types of data.
The goals of this project are:
- for researchers to be detailed and didactic about their quality control methods
- to present possible QC pipelines (with an emphasis on visualization and understanding) in the context of several "real world" data packages
- more broadly to share ideas of quality control among all researchers
We welcome submissions of Original Research, Methods, Brief Research Reports, and Technology and Code articles focusing on the quality control (QC) of this project's provided resting state FMRI data, task-based FMRI data, or both sets. The data details and download links are provided in the accompanying OSF page, along with descriptive items to be included in the submitted articles.
We fully expect that no two groups perform QC the same way, and we note that there is no single "correct" set of QC steps nor one "correct" set of answers for categorizing subjects. We expect the results to show a diverse set of tools and ideas that can be applied generally to FMRI studies and to enrich the wider neuroscience community with useful ways to look at and understand their data. One main result of this project will be an assemblage of QC criteria from active researchers around the FMRI community, with detailed descriptions and examples.
Please see the following webpage to download the project data, and for a description of details to include in the final project write-up submitted to the journal:
https://osf.io/qaesm/