ArticleHuman brain mapping2020
Sex classification using long-range temporal dependence of resting-state functional MRI time series.
Article in Human brain mapping, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- The progression of sex differences in brain networks across the lifespan.bioRxiv : the preprint server for biology · 2026Article
- Sex Classification Based on the Functional Connectivity Patterns of the Language Network: A Resting State fMRI Study.Human brain mapping · 2026Article
- Reproducible Effects of Sex and Acquisition Order on Multiple Global Signal Metrics: Implications for Functional Connectivity Studies of Phenotypic Individual Differences Using fMRI.Brain and behavior · 2025Article
- Prediction of Verbal Abilities From Brain Connectivity Data Across the Lifespan Using a Machine Learning Approach.Human brain mapping · 2025Article
- Protective role of parenthood on age-related brain function in mid- to late-life.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Functional brain networks are associated with both sex and gender in children.Science advances · 2024Article
- Explainable Multimodal Graph Isomorphism Network for Interpreting Sex Differences in Adolescent Neurodevelopment.Applied sciences (Basel, Switzerland) · 2024Article
- Functional brain networks are associated with both sex and gender in children.bioRxiv : the preprint server for biology · 2023Article
- A transformer model for learning spatiotemporal contextual representation in fMRI data.Network neuroscience (Cambridge, Mass.) · 2023Article
- The sleep EEG envelope is a novel, neuronal firing-based human biomarker.Scientific reports · 2022Article
- On the Spatial Distribution of Temporal Complexity in Resting State and Task Functional MRI.Entropy (Basel, Switzerland) · 2022Article
- Machine Learning Evidence for Sex Differences Consistently Influences Resting-State Functional Magnetic Resonance Imaging Fluctuations Across Multiple Independently Acquired Data Sets.Brain connectivity · 2022Article
- An attention-based hybrid deep learning framework integrating brain connectivity and activity of resting-state functional MRI data.Medical image analysis · 2022Article
- Differences in network properties of the structural connectome in bipolar and unipolar depression.Psychiatry research. Neuroimaging · 2022Article
- Article
- Scan Once, Analyse Many: Using Large Open-Access Neuroimaging Datasets to Understand the Brain.Neuroinformatics · 2022Article
- Heritability and interindividual variability of regional structure-function coupling.Nature communications · 2021Article
- Sex classification using long-range temporal dependence of resting-state functional MRI time series.Human brain mapping · 2020Article
- Article
- Because the machine can discriminate: How machine learning serves and transforms biological explanations of human difference.Big data & societyArticle
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Authors and funding
4 authors.
Funding
Abstract
A thorough understanding of sex differences that exist in the brains of healthy individuals is crucial for the study of neurological illnesses that exhibit phenotypic differences between males and females. Here we evaluate sex differences in regional temporal dependence of resting-state brain activity in 195 adult male-female pairs strictly matched for total grey matter volume from the Human Connectome Project. We find that males have more persistent temporal dependence in regions within temporal, parietal, and occipital cortices. Machine learning algorithms trained on regional temporal dependence measures achieve sex classification accuracies up to 81%. Regions with the strongest feature importance in the sex classification task included cerebellum, amygdala, and frontal and occipital cortices. Secondarily, we show that even after strict matching of total gray matter volume, significant volumetric sex differences persist; males have larger absolute cerebella, hippocampi, parahippocampi, thalami, caudates, and amygdalae while females have larger absolute cingulates, precunei, and frontal and parietal cortices. Sex classification based on regional volume achieves accuracies up to 85%, highlighting the importance of strict volume-matching when studying brain-based sex differences. Differential patterns in regional temporal dependence between the sexes identifies a potential neurobiological substrate or environmental effect underlying sex differences in functional brain activation patterns.
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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 OpenQuestion graph.