ArticleDevelopmental cognitive neuroscience2022
Benchmarking common preprocessing strategies in early childhood functional connectivity and intersubject correlation fMRI.
Article in Developmental cognitive neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed.
- Nine minutes is enough: An accelerated fMRI protocol for reliable connectivity mapping in healthy young adults.Dialogues in clinical neuroscience · 2027Article
- Feature selection leads to divergent neurobiological interpretations of brain-based machine learning biomarkers.Nature human behaviour · 2026Article
- An Examination of Task-Evoked fMRI Data Processing in Functional Connectivity.Journal of neuroscience research · 2026Article
- Subcortical resting state functional connectivity as a neural marker of first onset internalizing disorder in high-risk youth.Neuroimage. Reports · 2025Article
- Overlooked features lead to divergent neurobiological interpretations of brain-based machine learning biomarkers.bioRxiv : the preprint server for biology · 2025Article
- Article
- Differences in Head Motion During Functional Magnetic Resonance Imaging Across Pediatric Neuropsychiatric Disorders.Biological psychiatry global open science · 2025Article
- Multimodal identification of the mouse brain using simultaneous CaCommunications biology · 2025Article
- Measuring the effects of motion corruption in fetal fMRI.Human brain mapping · 2025Article
- Denoising strategies of functional connectivity MRI data in lesional and non-lesional brain diseases.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- How much is "enough"? Considerations for functional connectivity reliability in pediatric naturalistic fMRI.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Intellectual Development in Mexican Preterm Children at Risk of Perinatal Brain Damage: A Longitudinal Study.Children (Basel, Switzerland) · 2024Article
- How do tasks impact the reliability of fMRI functional connectivity?Human brain mapping · 2024Article
- A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- Development of the Functional Connectome Topology in Adolescence: Evidence from Topological Data Analysis.eNeuro · 2023Article
- Inattentive and hyperactive traits differentially associate with interindividual functional synchrony during video viewing in young children without ADHD.Cerebral cortex communications · 2022Article
- Association between circulating biomarkers of one-carbon metabolism and glymphatic system function in cognitive decline of Alzheimer's disease.Frontiers in neurologyArticle
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7 authors.
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Abstract
Preprocessing choices present a particular challenge for researchers working with functional magnetic resonance imaging (fMRI) data from young children. Steps which have been shown to be important for mitigating head motion, such as censoring and global signal regression (GSR), remain controversial, and benchmarking studies comparing preprocessing pipelines have been conducted using resting data from older participants who tend to move less than young children. Here, we conducted benchmarking of fMRI preprocessing steps in a population with high head-motion, children aged 4-8 years, leveraging a unique longitudinal, passive viewing fMRI dataset. We systematically investigated combinations of global signal regression (GSR), volume censoring, and ICA-AROMA. Pipelines were compared using previously established metrics of noise removal as well as metrics sensitive to recovery of individual differences (i.e., connectome fingerprinting), and stimulus-evoked responses (i.e., intersubject correlations; ISC). We found that: 1) the most efficacious pipeline for both noise removal and information recovery included censoring, GSR, bandpass filtering, and head motion parameter (HMP) regression, 2) ICA-AROMA performed similarly to HMP regression and did not obviate the need for censoring, 3) GSR had a minimal impact on connectome fingerprinting but improved ISC, and 4) the strictest censoring approaches reduced motion correlated edges but negatively impacted identifiability.
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