Principles of diffusion tensor imaging and its applications to basic neuroscience research
Open accessAbstract
The brain contains more than 100 billion neurons that communicate with each other via axons for the formation of complex neural networks. The structural mapping of such networks during health and disease states is essential for understanding brain function. However, our understanding of brain structural connectivity is surprisingly limited, due in part to the lack of noninvasive methodologies to study axonal anatomy. Diffusion tensor imaging (DTI) is a recently developed MRI technique that can measure macroscopic axonal organization in nervous system tissues. In this article, the principles of DTI methodologies are explained, and several applications introduced, including visualization of axonal tracts in myelin and axonal injuries as well as human brain and mouse embryonic development. The strengths and limitations of DTI and key areas for future research and development are also discussed.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
WM integrity can be affected by many different parameters including axon packing density, axon caliber, myelination, microglia, inflammation, and tissue architecture.
“This has led to considerable debate, since the inception of DTI, over the biological significance of these DTI-derived measures since WM integrity can be affected by many different parameters including axon packing density, axon caliber, myelination, microglia, inflammation, and tissue architecture (Mori and Zhang, 2006; Le Bihan and Johansen-Berg, 2012; Jones et al., 2013).”
From The role of myelination in measures of white matter integrity: Combination of diffusion tensor imaging and two-photon microscopy of CLARITY intact brains (2017) · cites this paper as Mori and Zhang, 2006
DTI is the most commonly employed diffusion model and utilizes the magnitude and orientation of anisotropic water diffusion to estimate the WM structure of brain tissue, producing maps of macroscopic axonal organization.
“Diffusion tensor imaging (DTI) is the most commonly employed diffusion model and utilizes the magnitude and orientation of anisotropic water diffusion to estimate the WM structure of brain tissue, thereby producing maps of macroscopic axonal organization in the brain (Basser and Pierpaoli, 1996; Le Bihan et al., 2001; Mori and Zhang, 2006).”
From The role of myelination in measures of white matter integrity: Combination of diffusion tensor imaging and two-photon microscopy of CLARITY intact brains (2017) · cites this paper as Mori and Zhang, 2006
Cites
The basis of anisotropic water diffusion in the nervous system—A technical review.
Beaulieu, C. (2002) · NMR in Biomedicine · doi:10.1002/nbm.782 · Cited by 4,653 · see citing works
Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water
Song, S.-K., Sun, S.-W., Ramsbottom, M. J., Chang, C., Russell, J., & Cross, A. H. (2002) · NeuroImage · doi:10.1006/nimg.2002.1267 · Cited by 2,582 · see citing works
Diffusion Tensor Imaging and Axonal Tracking in the Human Brainstem
Stieltjes, B., Kaufmann, W. E., van Zijl, P. C. M., Fredericksen, K., Pearlson, G. D., Solaiyappan, M., & Mori, S. (2001) · NeuroImage · doi:10.1006/nimg.2001.0861 · Cited by 492 · see citing works
Self-citationApplications of diffusion‐weighted and diffusion tensor MRI to white matter diseases – a review
Horsfield, M. A., & Jones, D. K. (2002) · NMR in Biomedicine · doi:10.1002/nbm.787 · Cited by 468 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Resting-State Functional Connectivity Reflects Structural Connectivity in the Default Mode Network
Greicius, M. D., Supekar, K., Menon, V., & Dougherty, R. F. (2009) · Cerebral Cortex · doi:10.1093/cercor/bhn059 · Cited by 2,175 · see citing works
Neuroplasticity Subserving Motor Skill Learning
Dayan, E., & Cohen, L. G. (2011) · Neuron · doi:10.1016/j.neuron.2011.10.008 · Cited by 1,408 · see citing works
Multiplexed echo planar imaging for sub-second whole brain FMRI and fast diffusion imaging
Feinberg, D. A., Moeller, S., Smith, S. M., Auerbach, E., Ramanna, S., Glasser, M. F., Miller, K. L., Ugurbil, K., & Yacoub, E. (2010) · PLoS ONE · doi:10.1371/journal.pone.0015710 · Cited by 1,296 · see citing works
Jeurissen, B., Leemans, A., Tournier, J., Jones, D. K., & Sijbers, J. (2013) · Human Brain Mapping · doi:10.1002/hbm.22099 · Cited by 1,088 · see citing works
Uğurbil, K., Xu, J., Auerbach, E. J., Moeller, S., Vu, A. T., Duarte-Carvajalino, J. M., Lenglet, C., Wu, X., Schmitter, S., Van de Moortele, P. F., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.012 · Cited by 812 · see citing works
Tamnes, C. K., Østby, Y., Fjell, A. M., Westlye, L. T., Due-Tønnessen, P., & Walhovd, K. B. (2010) · Cerebral Cortex · doi:10.1093/cercor/bhp118 · Cited by 779 · see citing works
Pain and the brain: specificity and plasticity of the brain in clinical chronic pain
Apkarian, V. A., Hashmi, J. A., & Baliki, M. N. (2011) · Pain · doi:10.1016/j.pain.2010.11.010 · Cited by 782 · see citing works
Wolff, J. J., Gu, H., Gerig, G., Elison, J. T., Styner, M., Gouttard, S., Botteron, K. N., Dager, S. R., Dawson, G., Estes, A. M., et al. (2012) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2011.11091447 · Cited by 671 · see citing works
Taubert, M., Draganski, B., Anwander, A., Müller, K., Horstmann, A., Villringer, A., & Ragert, P. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.2567-10.2010 · Cited by 514 · see citing works
Beyond the arcuate fasciculus: consensus and controversy in the connectional anatomy of language
Dick, A. S., & Tremblay, P. (2012) · Brain · doi:10.1093/brain/aws222 · Cited by 470 · see citing works
Tate, M. C., Herbet, G., Moritz-Gasser, S., Tate, J. E., & Duffau, H. (2014) · Brain · doi:10.1093/brain/awu168 · Cited by 377 · see citing works
Central mechanisms of pain revealed through functional and structural MRI
Davis, K. D., & Moayedi, M. (2013) · Journal of Neuroimmune Pharmacology · doi:10.1007/s11481-012-9386-8 · Cited by 376 · see citing works
Karlsgodt, K. H., van Erp, T. G. M., Poldrack, R. A., Bearden, C. E., Nuechterlein, K. H., & Cannon, T. D. (2008) · Biological Psychiatry · doi:10.1016/j.biopsych.2007.06.017 · Cited by 335 · see citing works
Review of neuroimaging in autism spectrum disorders: what have we learned and where we go from here
Anagnostou, E., & Taylor, M. J. (2011) · Molecular Autism · doi:10.1186/2040-2392-2-4 · Cited by 321 · see citing works
Structural and functional brain abnormalities in chronic low back pain: a systematic review
Kregel, J., Meeus, M., Malfliet, A., Dolphens, M., Danneels, L., Nijs, J., & Cagnie, B. (2015) · Seminars in Arthritis and Rheumatism · doi:10.1016/j.semarthrit.2015.05.002 · Cited by 315 · see citing works
Eluvathingal, T. J., Hasan, K. M., Kramer, L., Fletcher, J. M., & Ewing-Cobbs, L. (2007) · Cerebral Cortex · doi:10.1093/cercor/bhm003 · Cited by 288 · see citing works
Phillips, M. L., Chase, H. W., Sheline, Y. I., Etkin, A., Almeida, J. R. C., Deckersbach, T., & Trivedi, M. H. (2015) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2014.14010076 · Cited by 267 · see citing works
Gur, R. E., Moore, T. M., Rosen, A. F. G., Barzilay, R., Roalf, D. R., Calkins, M. E., Ruparel, K., Scott, J. C., Almasy, L., Satterthwaite, T. D., et al. (2019) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2019.0943 · Cited by 239 · see citing works
Fast track to the neocortex: A memory engram in the posterior parietal cortex
Brodt, S., Gais, S., Beck, J., Erb, M., Scheffler, K., & Schönauer, M. (2018) · Science · doi:10.1126/science.aau2528 · Cited by 224 · see citing works
Silk, T. J., Vance, A., Rinehart, N., Bradshaw, J. L., & Cunnington, R. (2009) · Human Brain Mapping · doi:10.1002/hbm.20703 · Cited by 243 · see citing works
Dauguet, J., Peled, S., Berezovskii, V., Delzescaux, T., Warfield, S. K., Born, R., & Westin, C.-F. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.04.067 · Cited by 233 · see citing works
Connectivity in Autism: A Review of MRI Connectivity Studies
Rane, P., Cochran, D., Hodge, S. M., Haselgrove, C., Kennedy, D. N., & Frazier, J. A. (2015) · Harvard Review of Psychiatry · doi:10.1097/hrp.0000000000000072 · Cited by 234 · see citing works
Phan, K. L., Orlichenko, A., Boyd, E., Angstadt, M., Coccaro, E. F., Liberzon, I., & Arfanakis, K. (2009) · Biological Psychiatry · doi:10.1016/j.biopsych.2009.02.028 · Cited by 226 · see citing works
Neuronal effects following working memory training.
Buschkuehl, M., Jaeggi, S. M., & Jonides, J. (2012) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2011.10.001 · Cited by 212 · see citing works
Palacios, E. M., Owen, J. P., Yuh, E. L., Wang, M. B., Vassar, M. J., Ferguson, A. R., Diaz-Arrastia, R., Giacino, J. T., Okonkwo, D. O., Robertson, C. S., et al. (2020) · Science Advances · doi:10.1126/sciadv.aaz6892 · Cited by 194 · see citing works
Feldstein Ewing, S. W., Sakhardande, A., & Blakemore, S.-J. (2014) · NeuroImage: Clinical · doi:10.1016/j.nicl.2014.06.011 · Cited by 185 · see citing works
Chang, E. H., Argyelan, M., Aggarwal, M., Chandon, T.-S. S., Karlsgodt, K. H., Mori, S., & Malhotra, A. K. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2016.11.068 · Cited by 186 · see citing works
Self-citationČeko, M., Shir, Y., Ouellet, J. A., Ware, M. A., Stone, L. S., & Seminowicz, D. A. (2015) · Human Brain Mapping · doi:10.1002/hbm.22757 · Cited by 171 · see citing works
Faria, A. V., Zhang, J., Oishi, K., Li, X., Jiang, H., Akhter, K., Hermoye, L., Lee, S.-K., Hoon, A., & Stashinko, E. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.04.238 · Cited by 180 · see citing works
Self-citationExploring early human brain development with structural and physiological neuroimaging
Vasung, L., Abaci Turk, E., Ferradal, S. L., Sutin, J., Stout, J. N., Ahtam, B., Lin, P.-Y., & Grant, P. E. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2018.07.041 · Cited by 177 · see citing works
Altered white matter microstructure in children with attention-deficit/hyperactivity disorder
Nagel, B. J., Bathula, D., Herting, M., Schmitt, C., Kroenke, C. D., Fair, D., & Nigg, J. T. (2011) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2010.12.003 · Cited by 178 · see citing works
Adult age differences in functional connectivity during executive control
Madden, D. J., Costello, M. C., Dennis, N. A., Davis, S. W., Shepler, A. M., Spaniol, J., Bucur, B., & Cabeza, R. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.04.249 · Cited by 152 · see citing works
Ray, S., Miller, M., Karalunas, S., Robertson, C., Grayson, D. S., Cary, R. P., Hawkey, E., Painter, J. G., Kriz, D., Fombonne, E., et al. (2014) · Human Brain Mapping · doi:10.1002/hbm.22603 · Cited by 149 · see citing works
Biomarkers used in Alzheimer’s disease diagnosis, treatment, and prevention
Mahaman, Y. A. R., Embaye, K. S., Huang, F., Li, L., Zhu, F., Wang, J.-Z., Liu, R., Feng, J., & Wang, X. (2022) · Ageing Research Reviews · doi:10.1016/j.arr.2021.101544 · Cited by 149 · see citing works
Eng, G. K., Sim, K., & Chen, S.-H. A. (2015) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2015.03.002 · Cited by 148 · see citing works
Histological validation of high-resolution DTI in human post mortem tissue
Seehaus, A., Roebroeck, A., Bastiani, M., Fonseca, L., Bratzke, H., Lori, N., Vilanova, A., Goebel, R., & Galuske, R. (2015) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2015.00098 · Cited by 149 · see citing works
White matter brain and trigeminal nerve abnormalities in temporomandibular disorder
Moayedi, M., Weissman-Fogel, I., Salomons, T. V., Crawley, A. P., Goldberg, M. B., Freeman, B. V., Tenenbaum, H. C., & Davis, K. D. (2012) · Pain · doi:10.1016/j.pain.2012.04.003 · Cited by 144 · see citing works
Information processing architecture of functionally defined clusters in the macaque cortex
Shen, K., Bezgin, G., Hutchison, R. M., Gati, J. S., Menon, R. S., Everling, S., & McIntosh, A. R. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.2709-12.2012 · Cited by 123 · see citing works
Abnormal Anatomical Connectivity between the Amygdala and Orbitofrontal Cortex in Conduct Disorder
Passamonti, L., Fairchild, G., Fornito, A., Goodyer, I. M., Nimmo-Smith, I., Hagan, C. C., & Calder, A. J. (2012) · PLoS ONE · doi:10.1371/journal.pone.0048789 · Cited by 123 · see citing works
White matter maturation is associated with the emergence of Theory of Mind in early childhood
Grosse Wiesmann, C., Schreiber, J., Singer, T., Steinbeis, N., & Friederici, A. D. (2017) · Nature Communications · doi:10.1038/ncomms14692 · Cited by 114 · see citing works
Advances in microstructural diffusion neuroimaging for psychiatric disorders
Pasternak, O., Kelly, S., Sydnor, V. J., & Shenton, M. E. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.04.051 · Cited by 116 · see citing works
Vasa, R. A., Mostofsky, S. H., & Ewen, J. B. (2016) · Biological Psychiatry: Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2016.02.003 · Cited by 97 · see citing works
Associations between white matter microstructure and infants' working memory
Short, S. J., Elison, J. T., Goldman, B. D., Styner, M., Gu, H., Connelly, M., Maltbie, E., Woolson, S., Lin, W., Gerig, G., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2012.09.021 · Cited by 105 · see citing works
Carballedo, A., Amico, F., Ugwu, I., Fagan, A. J., Fahey, C., Morris, D., Meaney, J. F., Leemans, A., & Frodl, T. (2012) · American Journal of Medical Genetics Part B: Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32060 · Cited by 95 · see citing works
Multi-scale enhanced graph convolutional network for mild cognitive impairment detection
Lei, B., Zhu, Y., Yu, S., Hu, H., Xu, Y., Yue, G., Wang, T., Zhao, C., Chen, S., Yang, P., et al. (2023) · Pattern Recognition · doi:10.1016/j.patcog.2022.109106 · Cited by 96 · see citing works
Zhang, J., Jones, M. V., McMahon, M. T., Mori, S., & Calabresi, P. A. (2012) · Magnetic Resonance in Medicine · doi:10.1002/mrm.23032 · Cited by 88 · see citing works
Self-citationWestlye, L. T., Walhovd, K. B., Bjørnerud, A., Due-Tønnessen, P., & Fjell, A. M. (2009) · Cerebral Cortex · doi:10.1093/cercor/bhn084 · Cited by 80 · see citing works
Peterson, D. J., Ryan, M., Rimrodt, S. L., Cutting, L. E., Denckla, M. B., Kaufmann, W. E., & Mahone, E. M. (2011) · Journal of Child Neurology · doi:10.1177/0883073811405662 · Cited by 81 · see citing works
Walhovd, K. B., Westlye, L. T., Moe, V., Slinning, K., Due-Tønnessen, P., Bjørnerud, A., van der Kouwe, A., Dale, A. M., & Fjell, A. M. (2010) · American Journal of Neuroradiology · doi:10.3174/ajnr.a1957 · Cited by 82 · see citing works
Magnetic Resonance-Based Imaging in Animal Models of Fetal Alcohol Spectrum Disorder
O’Leary-Moore, S. K., Parnell, S. E., Lipinski, R. J., & Sulik, K. K. (2011) · Neuropsychology Review · doi:10.1007/s11065-011-9164-z · Cited by 77 · see citing works
Structural insights into the rodent CNS via diffusion tensor imaging.
Zhang, J., Aggarwal, M., & Mori, S. (2012) · Trends in Neurosciences · doi:10.1016/j.tins.2012.04.010 · Cited by 73 · see citing works
Self-citationAlterations in white matter pathways in Angelman syndrome
PETERS, S. U., KAUFMANN, W. E., BACINO, C. A., ANDERSON, A. W., ADAPA, P., CHU, Z., YALLAMPALLI, R., TRAIPE, E., HUNTER, J. V., & WILDE, E. A. (2011) · Developmental Medicine & Child Neurology · doi:10.1111/j.1469-8749.2010.03838.x · Cited by 69 · see citing works
Shang, C. Y., Wu, Y. H., Gau, S. S., & Tseng, W. Y. (2013) · Psychological Medicine · doi:10.1017/s0033291712001869 · Cited by 69 · see citing works
Grieve, S. M., Korgaonkar, M. S., Clark, C. R., & Williams, L. M. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.12.087 · Cited by 64 · see citing works
Abnormal Language Pathway in Children With Angelman Syndrome
Wilson, B. J., Sundaram, S. K., Huq, A. H. M., Jeong, J.-W., Halverson, S. R., Behen, M. E., Bui, D. Q., & Chugani, H. T. (2011) · Pediatric Neurology · doi:10.1016/j.pediatrneurol.2010.12.002 · Cited by 60 · see citing works
Gogliettino, A. R., Potenza, M. N., & Yip, S. W. (2016) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2016.02.015 · Cited by 56 · see citing works
Na, K.-S., Won, E., Kang, J., Kim, A., Choi, S., Tae, W.-S., Kim, Y.-K., Lee, M.-S., Joe, S.-H., & Ham, B.-J. (2018) · Neuropharmacology · doi:10.1016/j.neuropharm.2018.04.030 · Cited by 50 · see citing works
Chen, H., Liu, T., Zhao, Y., Zhang, T., Li, Y., Li, M., Zhang, H., Kuang, H., Guo, L., Tsien, J. Z., et al. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.04.050 · Cited by 46 · see citing works
Unique white matter microstructural patterns in ADHD presentations—a diffusion tensor imaging study
Svatkova, A., Nestrasil, I., Rudser, K., Goldenring Fine, J., Bledsoe, J., & Semrud‐Clikeman, M. (2016) · Human Brain Mapping · doi:10.1002/hbm.23243 · Cited by 44 · see citing works
The Role of Exercise-Induced Cardiovascular Adaptation in Brain Health
Tarumi, T., & Zhang, R. (2015) · Exercise and Sport Sciences Reviews · doi:10.1249/jes.0000000000000063 · Cited by 42 · see citing works
Arreguin, A. J., & Colognato, H. (2020) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2020.00118 · Cited by 39 · see citing works
Lischke, A., Domin, M., Freyberger, H. J., Grabe, H. J., Mentel, R., Bernheim, D., & Lotze, M. (2017) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2017.00196 · Cited by 35 · see citing works
Developing new pharmacotherapies for autism
Ecker, C., Spooren, W., & Murphy, D. (2013) · Journal of Internal Medicine · doi:10.1111/joim.12113 · Cited by 31 · see citing works
Snow, W. M., Dale, R., O’Brien-Moran, Z., Buist, R., Peirson, D., Martin, M., & Albensi, B. C. (2017) · Journal of Alzheimer s Disease · doi:10.3233/jad-170136 · Cited by 29 · see citing works
Hagmann, C., Singer, J., Latal, B., Knirsch, W., & Makki, M. (2016) · Journal of Child Neurology · doi:10.1177/0883073815591214 · Cited by 27 · see citing works
Elevated diffusion anisotropy in gray matter and the degree of brain compression: Clinical article
Osuka, S., Matsushita, A., Ishikawa, E., Saotome, K., Yamamoto, T., Marushima, A., Satou, N., Zaboronok, A., Masumoto, T., & Matsumura, A. (2012) · Journal of Neurosurgery · doi:10.3171/2012.4.jns112305 · Cited by 24 · see citing works
Towards reliable reconstruction of the mouse brain corticothalamic connectivity using diffusion MRI
Arefin, T. M., Lee, C. H., Liang, Z., Rallapalli, H., Wadghiri, Y. Z., Turnbull, D. H., & Zhang, J. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120111 · Cited by 17 · see citing works
Self-citationDen Braber, A., Van ‘t Ent, D., Stoffers, D., Linkenkaer-Hansen, K., I. Boomsma, D., & J.C. de Geus, E. (2013) · International Journal of Psychological Research · doi:10.21500/20112084.712 · Cited by 11 · see citing works
- Authors
- Mori, S., & Zhang, J.
- Affiliations
- Kennedy Krieger Institute (US)
- Johns Hopkins University (US)
- Corresponding author
- Mori, Susumu
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2006-09
- Volume
- 51
- Issue
- 5
- Pages
- 527-539
- ISSN
- 0896-6273 (ISSN-L)
- OpenAlex
- W2156295356
- Cited by
- 1,708
- References
- 4
- Citations by year
- 2026: 58 · 2025: 59 · 2024: 54 · 2023: 60 · 2022: 94 · 2021: 101 · 2020: 112 · 2019: 106 · 2018: 100 · 2017: 131 · 2016: 105 · 2015: 106 · 2014: 105 · 2013: 94 · 2012: 95
- FWCI
- 43.93
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 2511 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Neuron (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute on Aging (R01AG020012, AG 20012)
- National Institute of Environmental Health Sciences (ES 012665, R01ES012665)
- National Institute of Biomedical Imaging and Bioengineering (R01EB003543, EB 003543)
- National Center for Research Resources (RR-15241, P41RR015241)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- diffusion tensor imaging, structural brain connectivity, axonal tracts, myelin, axonal injury, brain development, mouse embryo development, white matter, non-invasive brain imaging
- MeSH terms
- Animals, Axons, Brain, Brain Injuries, Contrast Media, Humans, Image Enhancement, Magnetic Resonance Imaging, Myelin Sheath, Diffusion Magnetic Resonance Imaging, Mice
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
