ArticleBrain structure & function2018
Whole mouse brain structural connectomics using magnetic resonance histology.
Article in Brain structure & function, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.
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Who cites it
51 citing papers in PubMed.
- A hierarchical framework for cortical and subcortical gray-matter parcellation across rodents, primates, and humans.Nature communications · 2026Article
- Magnetic resonance microscopy maps widespread effects of Alzheimer's disease on brain structures and behavior in mice.Nature neuroscience · 2026Article
- Mouse white matter matters: cortical origins and spatial organization of mouse white matter tracts.Brain structure & function · 2026Article
- Neuroimaging biomarkers of neuroprotection: Impact of voluntary versus enforced exercise in Alzheimer's disease models.Magnetic resonance imaging · 2025Article
- The Duke Mouse Brain Atlas: MRI and light sheet microscopy stereotaxic atlas of the mouse brain.Science advances · 2025Article
- Brain iron accumulation in neurodegenerative disorders: Does air pollution play a role?Particle and fibre toxicology · 2025Article
- Computational Generation of Long-range Axonal Morphologies.Neuroinformatics · 2025Article
- Network biomarkers of Alzheimer's disease risk derived from joint volume and texture covariance patterns in mouse models.PloS one · 2025Article
- Stroke-induced neuroplasticity in spiny mice in the absence of tissue regeneration.NPJ Regenerative medicine · 2024Article
- Brain network fingerprints of Alzheimer's disease risk factors in mouse models with humanized APOE alleles.Magnetic resonance imaging · 2024Article
- Diffusion tractography of kidney by high angular resolution diffusion imaging.Magnetic resonance letters · 2024Article
- High-resolution diffusion magnetic resonance imaging and spatial-transcriptomic in developing mouse brain.NeuroImage · 2024Article
- APOE, Immune Factors, Sex, and Diet Interact to Shape Brain Networks in Mouse Models of Aging.bioRxiv : the preprint server for biology · 2024Article
- Feature attention graph neural network for estimating brain age and identifying important neural connections in mouse models of genetic risk for Alzheimer's disease.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Multivariate investigation of aging in mouse models expressing the Alzheimer's protective APOE2 allele: integrating cognitive metrics, brain imaging, and blood transcriptomics.Brain structure & function · 2024Article
- MR histology reveals tissue features beneath heterogeneous MRI signal in genetically engineered mouse models of sarcoma.Frontiers in oncology · 2024Article
- Integrating multimodality magnetic resonance imaging to the Allen Mouse Brain Common Coordinate Framework.NMR in biomedicine · 2023Article
- Merged magnetic resonance and light sheet microscopy of the whole mouse brain.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Prenatal heroin exposure alters brain morphology and connectivity in adolescent mice.NMR in biomedicine · 2023Article
- Evaluation of kernel low-rank compressed sensing in preclinical diffusion magnetic resonance imaging.Frontiers in neuroscience · 2023Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Diffusion tensor histology holds great promise for quantitative characterization of structural connectivity in mouse models of neurological and psychiatric conditions. There has been extensive study in both the clinical and preclinical domains on the complex tradeoffs between the spatial resolution, the number of samples in diffusion q-space, scan time, and the reliability of the resultant data. We describe here a method for accelerating the acquisition of diffusion MRI data to support quantitative connectivity measurements in the whole mouse brain using compressed sensing (CS). The use of CS allows substantial increase in spatial resolution and/or reduction in scan time. Compared to the fully sampled results at the same scan time, the subtle anatomical details of the brain, such as cortical layers, dentate gyrus, and cerebellum, were better visualized using CS due to the higher spatial resolution. Compared to the fully sampled results at the same spatial resolution, the scalar diffusion metrics, including fractional anisotropy (FA) and mean diffusivity (MD), showed consistently low error across the whole brain (< 6.0%) even with 8.0 times acceleration. The node properties of connectivity (strength, cluster coefficient, eigenvector centrality, and local efficiency) demonstrated correlation of better than 95.0% between accelerated and fully sampled connectomes. The acceleration will enable routine application of this technology to a wide range of mouse models of neurologic diseases.
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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.