ArticleDevelopmental cognitive neuroscience2025
Statistical properties of functional connectivity MRI enrichment analysis in school-age autism research.
Article in Developmental cognitive neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Prenatal neural network organization and later executive function development.Developmental cognitive neuroscience · 2026Article
- Fetal functional connectivity prospectively associates with autistic traits in toddlerhood.NeuroImage. Clinical · 2026Article
- Functional connectivity between the visual and salience networks and autistic social features at school-age.Journal of neurodevelopmental disorders · 2025Article
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Authors and funding
19 authors.
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Abstract
Mass univariate testing on functional connectivity MRI (fcMRI) data is limited by difficulties achieving experiment-wide significance. Recent work addressing this problem has used enrichment analysis, which aggregates univariate screening statistics for a set of variables into a single enrichment statistic. There have been promising results using this method to explore fcMRI-behavior associations. However, there has not yet been a rigorous examination of the statistical properties of enrichment analysis when applied to fcMRI data. Establishing power for fcMRI enrichment analysis will be important for future neuropsychiatric and cognitive neuroscience study designs that plan to include this method. Here, we use realistic simulation methods, which mimic the covariance structure of fcMRI data, to examine the false positive rate and statistical power of one technique for enrichment analysis, over-representation analysis. We find it can attain high power even for moderate effects and sample sizes, and it strongly outperforms univariate analysis. The false positive rate associated with permutation testing is robust.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.