ArticleNeuroImage2011
Microscopic diffusion tensor atlas of the mouse brain.
Article in NeuroImage, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
38 citing papers in PubMed, 56 citations in OpenAlex.
- Anatomically aware simulation of patient-specific glioblastoma xenografts.PLoS computational biology · 2026Article
- Cellular deconvolution of the brain with topological magnetic resonance image analysis.bioRxiv : the preprint server for biology · 2025Article
- The Duke Mouse Brain Atlas: MRI and light sheet microscopy stereotaxic atlas of the mouse brain.Science advances · 2025Article
- Intrinsic Gene Expression Correlates of the Biophysically Modeled Diffusion Magnetic Resonance Imaging Signal.Biological psychiatry global open science · 2025Article
- A diffusion tensor imaging white matter atlas of the domestic canine brain.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Review
- Image-guided subject-specific modeling of glymphatic transport and amyloid deposition.Computer methods in applied mechanics and engineering · 2023Article
- Towards reliable reconstruction of the mouse brain corticothalamic connectivity using diffusion MRI.NeuroImage · 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
- Diffusion radiomics for subtyping and clustering in autism spectrum disorder: A preclinical study.Magnetic resonance imaging · 2023Article
- Heterotopic connectivity of callosal dysgenesis in mice and humans.Frontiers in neuroscience · 2023Article
- Increased expression of SLC25A1/CIC causes an autistic-like phenotype with altered neuron morphology.Brain : a journal of neurology · 2022Article
- SLC13A5/sodium-citrate co-transporter overexpression causes disrupted white matter integrity and an autistic-like phenotype.Brain communications · 2022Article
- Article
- Trimethylamine N-Oxide Reduces Neurite Density and Plaque Intensity in a Murine Model of Alzheimer's Disease.Journal of Alzheimer's disease : JAD · 2022Article
- Structural and Functional Hippocampal Correlations in Environmental Enrichment During the Adolescent to Adulthood Transition in Mice.Frontiers in systems neuroscience · 2021Article
- Microglial Density Alters Measures of Axonal Integrity and Structural Connectivity.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2020Article
- Cytoarchitecture of the mouse brain by high resolution diffusion magnetic resonance imaging.NeuroImage · 2020Article
- Stereotaxic Diffusion Tensor Imaging White Matter Atlas for theFrontiers in neuroanatomy · 2020Article
- Whole mouse brain connectomics.The Journal of comparative neurology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Eight diffusion tensor imaging (DTI) datasets of normal adult C57BL/6J mouse brains were acquired with an isotropic Nyquist limited resolution of 43 μm (voxel volume ~80 pl). Each specimen was scanned with a b0 image and 6 diffusion-weighted images. T1- and T2*-weighted data were acquired with each specimen to aid nonlinear registration of the data to a common reference space (called "Waxholm Space"). We identified 80 different discrete landmarks in Waxholm Space to provide the gold standard for measuring the registration quality. The accuracy of the registration was established by measuring displacement of the 80 landmarks in each registered brain from the same landmarks in the reference brain. The accuracy was better than 130 μm for 95% of the landmarks (overall landmark displacement is 65±40 μm, n=640). Mean and coefficient of variation atlases of DTI indices were generated with potential application for both voxel-based and region of interest-based analysis. To examine consistency of DTI data among individual subjects in this study and difference in diffusion indices between separate brain structures within each subject, averaged values of DTI indices (axial diffusivity, radial diffusivity, fractional anisotropy, and angular deviation of the primary eigenvector) were computed in 9 white matter structures in each brain. The variation of the DTI indices across the population was very small, e.g., ~5% for axial diffusivity for each white matter structure, enabling confident differentiation of differences in these structures within each subject. ANOVA tests indicated that the current protocol is able to provide consistent DTI data of individual brains (p>0.25), and distinguish difference of diffusion indices between white matter structures (p<0.001). Power analysis was also performed to provide an estimate of the number of specimens required to detect a 10% change of the DTI indices in each white matter structure. The data provide a critical addition to Waxholm Space, the International Neuroinformatics Coordinating Facility (www.incf.org) online comprehensive atlas of the mouse brain.
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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.