ArticleHuman brain mapping2021
A simple permutation-based test of intermodal correspondence.
Article in Human brain mapping, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- The cross-site reproducibility of MRI morphometric phenotypes in psychiatric disorders.Nature neuroscience · 2026Article
- Clarifying and extending permutation tests on brain map correspondence through mixed-effects modeling.Imaging neuroscience (Cambridge, Mass.) · 2026Article
- Changes in brain connectivity and neurovascular dynamics during dexmedetomidine-induced loss of consciousness.Communications biology · 2025Article
- Mapping Individual Differences in Intermodal Coupling in Neurodevelopment.bioRxiv : the preprint server for biology · 2025Article
- The effect of spherical projection on spin tests for brain maps.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Mapping individual differences in intermodal coupling in neurodevelopment.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Converging cortical axes.Nature neuroscience · 2025Article
- Generative models of MRI-derived neuroimaging features and associated dataset of 18,000 samples.Scientific data · 2024Article
- Psychiatric neuroimaging at a crossroads: Insights from psychiatric genetics.Developmental cognitive neuroscience · 2024Review
- Similarity-based multimodal regression.Biostatistics (Oxford, England) · 2024Article
- A rigorous and versatile statistical test for correlations between stationary time series.PLoS biology · 2024Article
- Network enrichment significance testing in brain-phenotype association studies.Human brain mapping · 2024Article
- Article
- Spatial-extent inference for testing variance components in reliability and heritability studies.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Graph alignment exploiting the spatial organization improves the similarity of brain networks.Human brain mapping · 2024Article
- Network Enrichment Significance Testing in Brain-Phenotype Association Studies.bioRxiv : the preprint server for biology · 2023Article
- Evolution of cortical geometry and its link to function, behaviour and ecology.Nature communications · 2023Article
- Spatially-enhanced clusterwise inference for testing and localizing intermodal correspondence.NeuroImage · 2022Article
- Null models in network neuroscience.Nature reviews. Neuroscience · 2022Review
- Brain connectivity at rest predicts individual differences in normative activity during movie watching.NeuroImage · 2022Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Many key findings in neuroimaging studies involve similarities between brain maps, but statistical methods used to measure these findings have varied. Current state-of-the-art methods involve comparing observed group-level brain maps (after averaging intensities at each image location across multiple subjects) against spatial null models of these group-level maps. However, these methods typically make strong and potentially unrealistic statistical assumptions, such as covariance stationarity. To address these issues, in this article we propose using subject-level data and a classical permutation testing framework to test and assess similarities between brain maps. Our method is comparable to traditional permutation tests in that it involves randomly permuting subjects to generate a null distribution of intermodal correspondence statistics, which we compare to an observed statistic to estimate a p-value. We apply and compare our method in simulated and real neuroimaging data from the Philadelphia Neurodevelopmental Cohort. We show that our method performs well for detecting relationships between modalities known to be strongly related (cortical thickness and sulcal depth), and it is conservative when an association would not be expected (cortical thickness and activation on the n-back working memory task). Notably, our method is the most flexible and reliable for localizing intermodal relationships within subregions of the brain and allows for generalizable statistical inference.
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Registered trials
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 OpenQuestion graph.