ArticleFrontiers in neuroscience2022
Quality control practices in FMRI analysis: Philosophy, methods and examples using AFNI.
Article in Frontiers in neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Highlight results, don't hide them: Enhance interpretation, reduce biases and improve reproducibility.NeuroImage · 2023Pooled it
- Go figure: transparency in neuroscience images preserves context and clarifies interpretation.Nature methods · 2026Review
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- A new fMRI quality metric using multi-echo information: Theory, validation and implications.bioRxiv : the preprint server for biology · 2026Article
- Effects of predicted Khamisiyah exposure on default mode network resting state functional connectivity in Gulf War Veterans.Frontiers in toxicology · 2026Article
- Feasibility of Integrating Real-Time fMRI Neurofeedback with rTMS: Study Design, Preliminary Results, and Technical Challenges.Aperture neuro · 2026Article
- The first comprehensive case study of early-emerging prosopometamorphopsia.bioRxiv : the preprint server for biology · 2025Article
- Applying Bayesian Multilevel Modeling to Single Trial Dynamics: A Demonstration in Aversive Conditioning.Human brain mapping · 2025Article
- Adolescent cognitive control processing is associated with anxiety in young adulthood during the COVID-19 pandemic.Cognitive, affective & behavioral neuroscience · 2025Article
- Developmental prosopagnosics have normal spatial integration in posterior ventral face-selective regions.bioRxiv : the preprint server for biology · 2025Article
- Brain and Behavior in Persuasion: The Role of Affective-Cognitive Matching.Psychophysiology · 2025Article
- The neural basis of intuitive approximate number system in board game Go (Baduk) experts.Scientific reports · 2025Article
- Brain structural magnetic resonance imaging predictors of brief intervention response in individuals with alcohol use disorder.Alcohol and alcoholism (Oxford, Oxfordshire) · 2025Article
- Abnormal Brain Functional Connectivity in Patients with Chronic Obstructive Pulmonary Disease and Correlations with Clinical and Cognitive Parameters.International journal of chronic obstructive pulmonary disease · 2025Article
- Processing, evaluating, and understanding FMRI data with afni_proc.py.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Article
- A Set of FMRI Quality Control Tools in AFNI: Systematic, in-depth, and interactive QC with afni_proc.py and more.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Solving the Pervasive Problem of Protocol Non-Compliance in MRI using an Open-Source tool mrQA.Neuroinformatics · 2024Article
- A Set of FMRI Quality Control Tools in AFNI: Systematic, in-depth and interactive QC with afni_proc.py and more.bioRxiv : the preprint server for biology · 2024Article
- Article
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3 authors.
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Abstract
Quality control (QC) is a necessary, but often an under-appreciated, part of FMRI processing. Here we describe procedures for performing QC on acquired or publicly available FMRI datasets using the widely used AFNI software package. This work is part of the Research Topic, "Demonstrating Quality Control (QC) Procedures in fMRI." We used a sequential, hierarchical approach that contained the following major stages: (1) GTKYD (getting to know your data, esp. its basic acquisition properties), (2) APQUANT (examining quantifiable measures, with thresholds), (3) APQUAL (viewing qualitative images, graphs, and other information in systematic HTML reports) and (4) GUI (checking features interactively with a graphical user interface); and for task data, and (5) STIM (checking stimulus event timing statistics). We describe how these are complementary and reinforce each other to help researchers stay close to their data. We processed and evaluated the provided, publicly available resting state data collections (7 groups, 139 total subjects) and task-based data collection (1 group, 30 subjects). As specified within the Topic guidelines, each subject's dataset was placed into one of three categories: Include, exclude or uncertain. The main focus of this paper, however, is the detailed description of QC procedures: How to understand the contents of an FMRI dataset, to check its contents for appropriateness, to verify processing steps, and to examine potential quality issues. Scripts for the processing and analysis are freely available.
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