{
  "abstract": "Cell types represent groups of cells with shared anatomical and functional properties. Traditional brain cell type atlases rely on single-cell sequencing, which provides molecular detail but lacks whole-brain, isotropic resolution. Diffusion magnetic resonance imaging (dMRI) offers a complementary approach for probing cytoarchitecture and myeloarchitecture, with quantitative metrics increasingly used as biomarkers of brain development and neurodegenerative disorders. However, the capacity of dMRI to predict cell types remains unclear. Here, we develop a multimodal framework by integrating high-resolution dMRI and three-dimensional light-sheet microscopy of adult mouse brains through registration to the Allen Mouse Brain Common Coordinate Framework. We investigate correlations between dMRI and spatial transcriptomics-derived cell types and generate a whole-brain neuronal cell type atlas at 10 µm isotropic resolution using deep learning. Together, these results establish an efficient, high-resolution strategy for brain neuron atlas generation and underscore the potential of advanced imaging techniques to illuminate cellular mechanisms of the brain.",
  "abstract_shown": true,
  "affiliations": [
    "Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, USA",
    "Missouri Southern State University, Joplin, USA",
    "Department of Computer Science, Purdue University, West Lafayette, USA",
    "Department of Biostatistics and Health Data Science, Indiana University, Indianapolis, USA",
    "Department of Surgery, University of Minnesota, Minneapolis, USA",
    "Department of Neurology, Duke University Medical Center, Durham, USA",
    "Center for In Vivo Microscopy, Department of Radiology, Duke University, Durham, USA",
    "Department of Biomedical Engineering, Duke University, Durham, USA",
    "Department of Biomedical Engineering, UT Southwestern Medical Center, Dallas, USA",
    "Peter O’Donnell Brain Institute, UT Southwestern Medical Center, Dallas, USA"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 11,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Xinyue Han",
      "orcid": "0000-0002-8082-0863"
    },
    {
      "affs": [
        0
      ],
      "name": "Rui Hu"
    },
    {
      "affs": [
        0
      ],
      "name": "Zhuoheng Liu"
    },
    {
      "affs": [
        0
      ],
      "name": "Jie Chen"
    },
    {
      "affs": [
        1
      ],
      "name": "Mubashir Jafry",
      "orcid": "0009-0003-7945-0265"
    },
    {
      "affs": [
        2
      ],
      "name": "Haoyu Song"
    },
    {
      "affs": [
        3
      ],
      "name": "Yi Zhao",
      "orcid": "0000-0003-4766-5934"
    },
    {
      "affs": [
        4
      ],
      "name": "Mingquan Lin"
    },
    {
      "affs": [
        5
      ],
      "name": "Leonard E. White"
    },
    {
      "affs": [
        6,
        7
      ],
      "name": "G. Allan Johnson",
      "orcid": "0000-0002-7606-5447"
    },
    {
      "affs": [
        0,
        8,
        9
      ],
      "name": "Nian Wang",
      "orcid": "0000-0001-6547-8580"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/2p3wmsaz0svmg.bib",
  "cited_by": 0,
  "doi": "10.1038/s42003-026-10608-y",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13720108/",
  "id": "2p3wmsaz0svmg",
  "issns": [
    "2399-3642"
  ],
  "landing_url": "https://doi.org/10.1038/s42003-026-10608-y",
  "language": "en",
  "licence": "CC-BY-NC-ND-4.0",
  "licence_label": "CC BY-NC-ND 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Article"
    ],
    [
      "openalex",
      "2741|Advanced Neuroimaging Techniques and Applications"
    ]
  ],
  "openalex": "W7167581199",
  "pdf_url": null,
  "pmcid": "PMC13720108",
  "pmid": "42414549",
  "published": "2026-07-07",
  "publisher": "Nature Publishing Group",
  "ris": "https://research.draconitic.com/paper/2p3wmsaz0svmg.ris",
  "sources": [
    {
      "first_seen": "2026-11-02T12:23:57Z",
      "native_id": "PMC13720108",
      "source": "pmc",
      "url": "https://doi.org/10.1038/s42003-026-10608-y"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2741|Advanced Neuroimaging Techniques and Applications",
      "subfield": "imaging"
    }
  ],
  "title": "High-resolution mri guided whole mouse brain neuronal cell type atlas using deep learning",
  "title_text": "High-resolution mri guided whole mouse brain neuronal cell type atlas using deep learning",
  "type": "peer-reviewed",
  "updated_at": "2026-11-03T12:21:03Z",
  "url": "https://research.draconitic.com/paper/2p3wmsaz0svmg",
  "venue": "Communications Biology",
  "versions": []
}