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    "headline": "One Brain Representation Found More Genetic Loci",
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    "dek": "MEVA joined cortical surface geometry to MRI volumes before using the learned features in UK Biobank association studies.",
    "summary": "MEVA joined cortical surface geometry to MRI volumes before using the learned features in UK Biobank association studies.",
    "body_text": "MEVA encodes voxel intensity together with cortical curvature and thickness from a surface mesh into one self-supervised representation. The combined inputs produced modest gains in age and sex prediction over either modality alone. Used as phenotypes for genome-wide association studies in the UK Biobank, the joint features revealed more genome-wide significant loci than volume-only or mesh-only features, suggesting that the two anatomical views carry complementary heritable variation.",
    "why_it_matters": "MEVA joined cortical surface geometry to MRI volumes before using the learned features in UK Biobank association studies.",
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      "Used as phenotypes for genome-wide association studies in the UK Biobank, the joint features revealed more genome-wide significant loci than volume-only or mesh-only features, suggesting that the two anatomical views carry complementary heritable variation."
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        "qualification": "Used as phenotypes for genome-wide association studies in the UK Biobank, the joint features revealed more genome-wide significant loci than volume-only or mesh-only features, suggesting that the two anatomical views carry complementary heritable variation."
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    "tags": [
      "brain MRI",
      "genetics",
      "self-supervised learning"
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      "source_id": "source-2026-10-03-005",
      "title": "arXiv preprint 2610.02114",
      "publisher": "arXiv",
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    "title": "One Brain Representation Found More Genetic Loci",
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