The DOI matches its Crossref record; 191 of the 200 references it cites were found in a registry or an index.
White matter integrity, fiber count, and other fallacies: The do's and don'ts of diffusion MRI
Abstract
Diffusion-weighted MRI (DW-MRI) has been increasingly used in imaging neuroscience over the last decade. An early form of this technique, diffusion tensor imaging (DTI) was rapidly implemented by major MRI scanner companies as a scanner selling point. Due to the ease of use of such implementations, and the plausibility of some of their results, DTI was leapt on by imaging neuroscientists who saw it as a powerful and unique new tool for exploring the structural connectivity of human brain. However, DTI is a rather approximate technique, and its results have frequently been given implausible interpretations that have escaped proper critique and have appeared misleadingly in journals of high reputation. In order to encourage the use of improved DW-MRI methods, which have a better chance of characterizing the actual fiber structure of white matter, and to warn against the misuse and misinterpretation of DTI, we review the physics of DW-MRI, indicate currently preferred methodology, and explain the limits of interpretation of its results. We conclude with a list of 'Do's and Don'ts' which define good practice in this expanding area of imaging neuroscience.
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In the citing paper
“We caution that the behaviour of the DTI indices in the human brain, which is characterized by a high density of crossing fibre that influence DTI measures (Jeurissen et al., 2013), is only partially understood and remains speculative (Jones et al., 2013).”
From White matter diffusion alterations precede symptom onset in autosomal dominant Alzheimer’s disease (2018) · cites this paper as Jones et al., 2013
In the citing paper
“DTI alterations may stem from a variety of tissue changes including altered crossing fibres, permeability of the axonal membrane, inflammation, or oedema (Jones et al., 2013).”
From White matter diffusion alterations precede symptom onset in autosomal dominant Alzheimer’s disease (2018) · cites this paper as Jones et al., 2013
In the citing paper
“However, DTI metrics are not specific to particular cellular or molecular processes.”
From Diffusion MRI reveals amyloid plaque–associated cellular signatures through spatial transcriptomic integration (2026) · cites this paper as [16]
In the citing paper
“This limitation is often expressed as the mantra “streamline count is not quantitative.””
From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Jones et al., 2013
In the citing paper
“However, because of the difference in resolution between the measured dMRI signal and actual axon dimensions (as described in Section 3.3: “Connection density biases”), many studies have emphasized that NOS does not provide a truly quantitative measure of connection strength (Jones, 2010; Jones et al., 2013; Sotiropoulos and Zalesky, 2019; Yeh et al., 2020).”
From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Jones et al., 2013
In the citing paper
“For example, many factors (e.g., cell death, edema, gliosis, inflammation, change in myelination, increase in connectivity of crossing fibers, increase in extracellular or intracellular water, etc.) may cause changes in FA (Assaf and Pasternak, 2008; Jones et al., 2013; Le Bihan and Johansen-Berg, 2012).”
From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Jones et al., 2013
In the citing paper
“However, these measures reflect a composite of axonal organization, myelin, extracellular water, fiber geometry, and cerebrovascular injury (Beck et al., 2021; Jones et al., 2013).”
From 40 Years of diffusion MRI in the brain: From history to emerging frontiers (2026) · cites this paper as Jones et al., 2013
In the citing paper
“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 Jones et al., 2013
In the citing paper
“higher values corresponding to higher diffusivity, which is often observed in damaged tissues (Jones et al., 2013)”
From Substance abuse and white matter: Findings, limitations, and future of diffusion tensor imaging research (2019) · cites this paper as Jones et al., 2013
In the citing paper
“Changes in FA signal one or many microstructural alterations, such as Wallerian degeneration (Pierpaoli et al., 2001; Thomalla et al., 2004) or decreased neuronal membrane permeability (Jones, KnöSche, & Turner, 2013).”
From Substance abuse and white matter: Findings, limitations, and future of diffusion tensor imaging research (2019) · cites this paper as Jones, KnöSche, & Turner, 2013
In the citing paper
“Moreover, diffusion-weighted imaging has many limitations and sources of error at each step of the analysis pipeline that must be considered when interpreting results236, 237.”
From Imaging structural and functional brain development in early childhood (2018) · cites this paper as [237]
Citations
Cites
Donoho, D. L. (2006) · IEEE Transactions on Information Theory · doi:10.1109/tit.2006.871582 · Cited by 23,994
Donoho, D. L. (2004) · Cited by 16,703
Sparse MRI: The application of compressed sensing for rapid MR imaging
Lustig, M., Donoho, D., & Pauly, J. M. (2007) · Magnetic Resonance in Medicine · doi:10.1002/mrm.21391 · Cited by 6,952
MR diffusion tensor spectroscopy and imaging
Basser, P. J., Mattiello, J., & LeBihan, D. (1994) · Biophysical Journal · doi:10.1016/s0006-3495(94)80775-1 · Cited by 5,970
Generalized autocalibrating partially parallel acquisitions (GRAPPA)
Griswold, M. A., Jakob, P. M., Heidemann, R. M., Nittka, M., Jellús̆, V., Wang, J., Kiefer, B., & Haase, A. (2002) · Magnetic Resonance in Medicine · doi:10.1002/mrm.10171 · Cited by 5,311
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 4,628
Mapping the structural core of human cerebral cortex
Hagmann, P., Cammoun, L., Gigandet, X., Meuli, R., Honey, C. J., Wedeen, V. J., & Sporns, O. (2008) · PLoS Biology · doi:10.1371/journal.pbio.0060159 · Cited by 4,173
Le Bihan, D., Breton, E., Lallemand, D., Grenier, P., Cabanis, E., & Laval-Jeantet, M. (1986) · Radiology · doi:10.1148/radiology.161.2.3763909 · Cited by 3,912
Estimation of the Effective Self-Diffusion Tensor from the NMR Spin Echo
Basser, P. J., Mattiello, J., & Bihan, D. L. (1994) · Journal of Magnetic Resonance Series B · doi:10.1006/jmrb.1994.1037 · Cited by 3,656
Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging
Mori, S., Crain, B. J., Chacko, V. P., & van Zijl, P. C. M. (1999) · Annals of Neurology · doi:10.1002/1531-8249(199902)45:2 · Cited by 3,513
Research works printed but not linked: 2
- Le Bihan, 1985, In vivo magnetic resonance imaging of diffusion I, C. R. Acad. Sci. II, 301, 1109
- Tournier, 2009, How many diffusion gradient directions are required for HARDI?, Proc. Int. Soc. Magn. Reson. Med., 17, 358
Cited by
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Wang, H. R., Liu, Z.-Q., Nakua, H., Hegarty, C. E., Thies, M. B., Patel, P. K., Schleifer, C. H., Boeck, T. P., McKinney, R. A., Currin, D. L., et al. (2024) · Biological Psychiatry · doi:10.1016/j.biopsych.2024.06.011 · Cited by 9
“Associations that survived false discovery rate correction ( q , .05).”
Kwiatkowski, A., Weidler, C., Habel, U., Coverdale, N. S., Hirad, A. A., Manning, K. Y., Rauscher, A., Bazarian, J. J., Cook, D. J., Li, D. K. B., et al. (2024) · Human Brain Mapping · doi:10.1002/hbm.26811 · Cited by 8
“…to WM alterations arising for example from demyelination, axonal injury, or axonal degeneration (Alexander et al., 2011; Feldman et al., 2010; Jones et al., 2013) and have been widely used to study microstructural brain changes due to sport-related concussion and RSHI-exposure (Chamard &…”
Chavarría‐Siles, I., Fernández, G., & Posthuma, D. (2013) · Springer eBooks · doi:10.1007/978-1-4614-7447-0_8 · Cited by 7
Raybaud, C. (2016) · Child s Nervous System · doi:10.1007/s00381-016-3188-x · Cited by 7
“By contrast to this deterministic approach to tractography, technically more complex probabilistic methods are being developed [4, 5].”
BackgroundResultNees, F., Pohlack, S. T., Grimm, O., Winkelmann, T., Zidda, F., & Flor, H. (2019) · Cortex · doi:10.1016/j.cortex.2019.08.020 · Cited by 9
Chamberland, M., Winter, M., Brice, T. A. W., Jones, D. K., & Tallantyre, E. C. (2021) · Mathematics and visualization · doi:10.1007/978-3-030-73018-5_18 · Cited by 7
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Park, H. R. P., Verhelst, H., Quak, M., Jeurissen, B., & Krebs, R. (2021) · Brain Structure and Function · doi:10.1007/s00429-021-02222-x · Cited by 9
Ramphal, B., Pagliaccio, D., Thomas, L. V., He, X., & Margolis, A. E. (2021) · The Cerebellum · doi:10.1007/s12311-021-01265-4 · Cited by 7
Bergsland, N., Dwyer, M. G., Jakimovski, D., Weinstock‐Guttman, B., & Zivadinov, R. (2021) · Journal of Neuroimaging · doi:10.1111/jon.12891 · Cited by 7
Villemonteix, T., Rogers, J. C., Courbet, O., González-Madruga, K., Kohls, G., Raschle, N. M., Stadler, C., Konrad, K., Freitag, C. M., Fairchild, G. F., et al. (2021) · Brain Imaging and Behavior · doi:10.1007/s11682-021-00499-4 · Cited by 7
Kim, T., Aizenstein, H. J., Snitz, B. E., Cheng, Y., Chang, Y., Roush, R. E., Huppert, T. J., Cohen, A. D., Doman, J. M., & Becker, J. T. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.760663 · Cited by 8
Chen, Y., Bukhari, Q., Lin, T. W., & B, T. J. S. A. (2022) · Network Neuroscience · doi:10.1162/netn_a_00239 · Cited by 7
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Lariosa-Willingham, K. D., Leonoudakis, D., Bragge, T., Tolppanen, L., Nurmi, A., Flanagan, M., Gibson, J., Wilson, D. L., Stratton, J., Lehtimäki, K. K., et al. (2022) · BMC Neuroscience · doi:10.1186/s12868-022-00714-y · Cited by 7
“, orientation-dependent aspects of tissue microstructure or axonal pathology [81, 82].”
BackgroundImplicating Causal Brain Magnetic Resonance Imaging in Glaucoma Using Mendelian Randomization
Liu, K., Wu, P., Chen, B., Cai, Y., Yuan, R., & Zou, J. (2022) · Frontiers in Medicine · doi:10.3389/fmed.2022.956339 · Cited by 7
Zhang, C., Yuan, Y., Sang, T., Yu, L., Yu, Y. H., Liu, X., Zhou, W., Zeng, Q., Wang, J., Peng, G., et al. (2023) · Journal of Neuroscience Research · doi:10.1002/jnr.25179 · Cited by 8
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BackgroundMyelin plasticity during early literacy training in at-risk pre-readers
Economou, M., Bempt, F. V., Herck, S. V., Wouters, J. M., Ghesquière, P., Vanderauwera, J., & Vandermosten, M. (2023) · Cortex · doi:10.1016/j.cortex.2023.05.023 · Cited by 8
Cheng, Y., Lin, L., Jiang, S., Pei-lin, H., Zhang, J., Xin, J., Xu, H., Wang, Y., & Pan, X. (2024) · CNS Neuroscience & Therapeutics · doi:10.1111/cns.14586 · Cited by 6
“9 Alternatively, neurite orientation dispersion and density imaging (NODDI), a multi - compartment biophysical model of dMRI, can potently differentiate the measurements of the cerebrospinal fluid, extracellular fluid, and intracellular fluid.”
BackgroundFiber Visualization with LIC Maps Using Multidirectional Anisotropic Glyph Samples
Höller, M., Otto, K.-M., Klose, U., Groeschel, S., & Ehricke, H.-H. (2014) · International Journal of Biomedical Imaging · doi:10.1155/2014/401819 · Cited by 7
“In more complex fiber architectures, such as crossing, branching, and kissing fibers, diffusion tensor imaging is inadequate and may result in misleading and inaccurate interpretations [2, 3].”
BackgroundXia, M., Lin, Q., Bi, Y., & Yong He, A. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00158 · Cited by 7
“The streamline length of each edge, which represents its wiring costs (Kaiser and Hilgetag, 2006; Bullmore and Sporns, 2012), was estimated from the average length of the interconnecting streamlines in each individual network.”
BackgroundMethodTakeuchi, H., Tomita, H., Taki, Y., Kikuchi, Y., Ono, C., Yu, Z., Sekiguchi, A., Nouchi, R., Kotozaki, Y., Nakagawa, S., et al. (2019) · Brain Imaging and Behavior · doi:10.1007/s11682-018-0025-8 · Cited by 7
Boness, C. L., Korucuoglu, O., Ellingson, J. M., Merrill, A. M., McDowell, Y. E., Trela, C. J., Sher, K. J., Piasecki, T. M., & Kerns, J. G. (2019) · Experimental and Clinical Psychopharmacology · doi:10.1037/pha0000336 · Cited by 7
RetractedVeloz, M. F. V., Martín‐Román, C., Valdivieso, M. P. R., White, T. J. H., Kushner, S. A., & Zeeuw, C. I. D. (2020) · Genes Brain & Behavior · doi:10.1111/gbb.12656 · Cited by 8
“Accordingly, FA is highly sensitive to individual differences in white-matter microstructure, but limited in its specificity.(26) DTI data included in the present article were acquired during the second neuroimaging wave, which included high-resolution structural MRI, 35-direction diffusion weighted imaging, and a 6 m…”
BackgroundKristensen, T. D., Ebdrup, B. H., Hjorthøj, C. R., Mandl, R. C. W., Raghava, J. M., Jepsen, J. R. M., Fagerlund, B., Glenthøj, L. B., Wenneberg, C., Krakauer, K., et al. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.00873 · Cited by 8
“Various candidate mechanisms of activity-dependent WMreorganization has been suggested, such as long-term potentiation (55), growth of astrocytes and oligodendrocyte precursor cells (56), myelination (57), and reorganization of axons and fiber-bundles (58).”
BackgroundCao, M., Luo, Y., Wu, Z., Mazzola, C. A., Catania, L., Alvarez, T. L., Halperin, J. M., Biswal, B. B., & Li, X. (2021) · Brain Connectivity · doi:10.1089/brain.2020.0866 · Cited by 7
“The reduced sensitivity in detecting the orientations of small fibers may be owing to the relative low diffusion weighting (Jones et al., 2013).”
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Hickmott, R. A., Bosakhar, A., Quezada, S., Barresi, M., Walker, D. W., Ryan, A. L., Quigley, A. F., & Tolcos, M. (2021) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2021.102111 · Cited by 7
Law, J. B., Comstock, B. A., Richards, T. L., Traudt, C. M., Wood, T. R., Mayock, D. E., Heagerty, P. J., & Juul, S. E. (2021) · Brain Sciences · doi:10.3390/brainsci11101360 · Cited by 7
“MO complements FA by providing insight into the extent of crossing fibers and has been increasingly linked to long-term behavioral outcomes [27,28].”
Background(2013) · Elsevier eBooks · doi:10.1016/b978-0-12-398398-5.00008-4 · Cited by 7
Connecting the dots: social networks in the classroom and white matter connections in the brain
Mulder, R. H., López-Vicente, M., Hidalgo, A. P. C., Steenkamp, L. R., Güroğlu, B., Tiemeier, H. W., & Muetzel, R. L. (2022) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13647 · Cited by 7
Öztekin, I., Garic, D., Bayat, M., Hernandez, M. L., Finlayson, M. A., Graziano, P. A., & Dick, A. S. (2022) · European Journal of Neuroscience · doi:10.1111/ejn.15842 · Cited by 8
“In addition, we calculated the diffusion tensor using all acquisitions, following the recommendation of Jones, Knosche, and Turner (2013) to make use of a large number of gradient orientations, weighted against the reduction in SNR associated with higher b values (Jones, 2010).”
MethodResolving power for the diffusion orientation distribution function
Jensen, J. H., & Helpern, J. A. (2015) · Magnetic Resonance in Medicine · doi:10.1002/mrm.25900 · Cited by 7
Frost, C. P., Meyerand, M. E., Birn, R. M., Hoks, R. M., Walsh, E. C., & Abercrombie, H. C. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00256 · Cited by 8
“Most such streamlines appeared to terminate on the dorsal surface of precentral and superior frontal gyri, although precise departures of fibers from a larger tract can be difficult to resolve (e.g., Jones et al., 2013a).”
BackgroundInfluentialIndividual structural connectivity defines propagation networks in partial epilepsyPreprint
Proix, T., Bartoloméi, F., Guye, M., & Jirsa, V. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1604.08508 · Cited by 7
Variable Selection in Structural Equation Models with Regularized MIMIC ModelsPreprint
Jacobucci, R., Kievit, R., & Brandmaier, A. M. (2018) · doi:10.31234/osf.io/bxzjf · Cited by 7
Caron, B., Bullock, D., Kitchell, L., McPherson, B., Kellar, D. A., Cheng, H., Newman, S. D., Port, N. L., & Pestilli, F. (2020) · doi:10.31234/osf.io/dxaqp · Cited by 9
“Signal-to-noise ratio (SNR) was calculated on the normalized multi-shell dMRI image using DIPY’s workflow for calculating SNR (Descoteaux et al., 2011; Garyfallidis et al., 2014; Jones et al., 2013).”
MethodWang, S.-M., Wen, H., Huang, F., Sun, C.-W., Huang, C., & Wang, S. (2025) · NeuroImage Clinical · doi:10.1016/j.nicl.2025.103758 · Cited by 7
Griffa, G., Deleglise, Á., Deleglise, Á., Pino, G. D., Jacobacci, F., & Della‐Maggiore, V. (2025) · Journal of Neuroscience · doi:10.1523/jneurosci.2119-24.2025 · Cited by 9
Kievit, R., Fuhrmann, D., Borgeest, G. S., Simpson-Kent, I. L., & Henson, R. N. (2018) · Wellcome Open Research · doi:10.12688/wellcomeopenres.14241.1 · Cited by 9
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Berry, S. C., Lawrence, A. D., Lancaster, T. M., Casella, C., Aggleton, J. P., & Postans, M. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119096 · Cited by 6
Yao, S., Yang, R., Du, C., Jiang, C., Wang, Y., Peng, C., & Bai, H. (2023) · Frontiers in Oncology · doi:10.3389/fonc.2023.1089139 · Cited by 6
Chai, Y., Park, H. R., Jo, H., Seo, M. Y., Kim, H. Y., Joo, E. Y., & Kim, H. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1221290 · Cited by 7
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BackgroundBadji, A., Cedrés, N., Muehlboeck, J., Khan, W., Dhollander, T., Barroso, J., Ferreira, D., & Westman, E. (2024) · Human Brain Mapping · doi:10.1002/hbm.26618 · Cited by 5
Sex differences in patterns of white matter neuroplasticity after balance training in young adults
Kirby, E. D., Andrushko, J. W., Boyd, L. A., Koschutnig, K., & D’Arcy, R. C. N. (2024) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2024.1432830 · Cited by 8
Dissecting white matter pathways: A neuroanatomical approach
Forkel, S. J., Bortolami, C., Dulyan, L., Barrett, R. L. C., & Beyh, A. (2025) · Elsevier eBooks · doi:10.1016/b978-0-12-818894-1.00012-4 · Cited by 6
van Velzen, L. S., Čolić, L., Ceja, Z., Dauvermann, M. R., Villa, L. M., Savage, H. S., Toenders, Y. J., Dehestani, N., Zhu, A. H., Campos, A. I., et al. (2025) · Translational Psychiatry · doi:10.1038/s41398-025-03602-1 · Cited by 7
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Gicas, K. M., Cheng, A., Rawtaer, I., Willi, T. S., Panenka, W. J., Lang, D. J., Smith, G. N., Vila‐Rodriguez, F., Leonova, O., Giesbrecht, C. J., et al. (2019) · Brain and Behavior · doi:10.1002/brb3.1233 · Cited by 6
Hunt, D., Dighe, M., Gatenby, C., & Studholme, C. (2019) · Topics in Magnetic Resonance Imaging · doi:10.1097/rmr.0000000000000212 · Cited by 6
Structural connectivity differs between males and females in the brain object manipulation network
Lee, D., & Son, T. (2021) · PLoS ONE · doi:10.1371/journal.pone.0253273 · Cited by 7
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BackgroundMoody, J. F., Aggarwal, N., Dean, D., Tromp, D., Kecskemeti, S. R., Oler, J. A., Kalin, N. H., & Alexander, A. L. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.118989 · Cited by 6
Shi, Y., Zhao, Z., Tang, H., & Huang, S. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.866312 · Cited by 7
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Brichko, R., Soldan, A., Zhu, Y., Wang, M., Faria, A. V., Albert, M., & Pettigrew, C. A. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.859826 · Cited by 6
Langhein, M., Lyall, A. E., Steinmann, S., Seitz‐Holland, J., Nägele, F. L., Karayumak, S. C., Zhang, F., Rauh, J., Mußmann, M., Billah, T., et al. (2022) · The World Journal of Biological Psychiatry · doi:10.1080/15622975.2022.2112974 · Cited by 7
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BackgroundSymmetric data-driven fusion of diffusion tensor MRI: Age differences in white matter
Colmenares, A. M., Hefner, M. B., Calhoun, V. D., Salerno, E. A., Fanning, J. T., Gothe, N. P., McAuley, E., Kramer, A. F., & Burzynska, A. Z. (2023) · Frontiers in Neurology · doi:10.3389/fneur.2023.1094313 · Cited by 6
Easson, K., Khairy, M. A., Rohlicek, C. V., Saint‐Martin, C., Gilbert, G., Nguyen, K.-A., Luu, T. M., Couture, É., Nuyt, A. M., Wintermark, P., et al. (2023) · Frontiers in Neurology · doi:10.3389/fneur.2023.1167026 · Cited by 9
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Taraku, B., Zavaliangos‐Petropulu, A., Loureiro, J. R., Al‐Sharif, N., Kubicki, A., Joshi, S. H., Woods, R. P., Espinoza, R. T., Narr, K. L., & Sahib, A. K. (2023) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2023.1195763 · Cited by 7
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MacIver, C., Jones, D. K., Green, K., et al. (2024) · Neurology · doi:10.1212/wnl.0000000000209695 · Cited by 6
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Raffin, E., & Dyrby, T. B. (2013) · Monographs in clinical neuroscience/Frontiers of neurology and neuroscience/Monographs in neural sciences · doi:10.1159/000348818 · Cited by 7
Matsuoka, K., Yasuno, F., Inoue, M., Yamamoto, A., Kudo, T., Kitamura, S., Okada, K., Kiuchi, K., Kosaka, J., Iida, H., et al. (2013) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2013.11.006 · Cited by 6
Sepehrband, F., Choupan, J., Caruyer, E., Kurniawan, N. D., Gal, Y., Tieng, Q. M., McMahon, K. L., Vegh, V., Reutens, D. C., & Yang, Z. (2015) · Frontiers in Neurology · doi:10.3389/fneur.2014.00290 · Cited by 6
Conti, E. (2015) · Functional Neurology · doi:10.11138/fneur/2015.30.3.203 · Cited by 6
“However, it needs to be underlined that diffusion data, above all FA data, may not be interpreted as a direct measure of structural connectivity (Castellanos et al., 2014; Jones et al., 2013).”
A Symmetry-Based Method to Infer Structural Brain Networks from Probabilistic Tractography Data
Shadi, K., Bakhshi, S., Gutman, D. A., Mayberg, H. S., & Dovrolis, C. (2016) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2016.00046 · Cited by 9
“, the Number of Streamlines, or NoS, in deterministic tractography) should not be viewed as equivalent to “fiber count”, and similarly, the connectivity likelihoods inferred from probabilistic tractography should not be viewed as “connection strengths” (Jones et al., 2013).”
BackgroundLahti, K., Saunavaara, V., Munck, P., Uusitalo, K., Koivisto, M. A., Parkkola, R. K., Haataja, L. M., & the PIPARI Study Group (2019) · Acta Paediatrica · doi:10.1111/apa.15004 · Cited by 6
Wong, W.-W., Fang, Y., Chu, C. W., Shi, L., & Tong, R. K. (2019) · Frontiers in Neurology · doi:10.3389/fneur.2019.01111 · Cited by 7
Shafer, A. T., Benoit, J. R. A., Brown, M. R. G., Greenshaw, A., Vliet, K. J. V., Vohra, S., Dolcos, F., & Singhal, A. (2019) · Brain Imaging and Behavior · doi:10.1007/s11682-019-00211-7 · Cited by 7
Pedersini, C. A., Lingnau, A., Cardobi, N., Sánchez-López, J., Savazzi, S., & Marzi, C. A. (2020) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2020.107430 · Cited by 6
“…patients. fMRI provides information on the amplitude of the BOLD signal following specific visual motion stimuli, whilst DTI allows to estimate the integrity of large-scale white matter fibres in humans by studying their microstructural properties (Catani et al., 2012; Jones et al., 2013).”
BackgroundMethodInfluentialGosar, D., Tretnjak, V., Bregant, T., Neubauer, D., & Derganc, M. (2020) · European Journal of Paediatric Neurology · doi:10.1016/j.ejpn.2020.06.003 · Cited by 6
Optimized rectification of fiber orientation density function
Moss, H., & Jensen, J. (2020) · Magnetic Resonance in Medicine · doi:10.1002/mrm.28406 · Cited by 6
Diffusion MRI Fiber Tractography
Smith, R. E., Connelly, A., & Calamante, F. (2020) · Advances in magnetic resonance technology and applications · doi:10.1016/b978-0-12-817057-1.00023-8 · Cited by 10
Wu, W., Li, X., Yang, Z., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-84164-2 · Cited by 6
Altered regional brain white matter in dry eye patients: a brain imaging study
Luo, Y.-Q., Liang, R., Xu, S., Pan, Y., Li, Q., Shu, H., Kang, M. C., Yin, P., Zhang, L., & Shao, Y. (2022) · Aging · doi:10.18632/aging.203976 · Cited by 6
Diagnostic, Prognostic, and Advanced Imaging in Severe Traumatic Brain Injury
Edlow, B. L., & Rosenthal, E. S. (2015) · Current Trauma Reports · doi:10.1007/s40719-015-0018-7 · Cited by 6
Hou, Y., Yang, S., Wu, Y., & Lai, C. (2016) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.25127 · Cited by 6
Altered whole-brain connectivity in albinism
Welton, T., Ather, S., Proudlock, F. A., Gottlob, I., & Dineen, R. A. (2016) · Human Brain Mapping · doi:10.1002/hbm.23414 · Cited by 8
Altered white matter connectivity associated with visual hallucinations following occipital stroke
Rafique, S. A., Richards, J. R., & Steeves, J. K. E. (2018) · Brain and Behavior · doi:10.1002/brb3.1010 · Cited by 6
“…FA of the contralesional anterior thalamic radiation in the patient (Table 1), which connects the anterior and dorsomedial thalamic nuclei with the prefrontal cortex (Wakana et al., 2004), suggests changes to white matter microstructure and connectivity of this tract (Jones et al., 1999, 2013).”
Abeyasinghe, P. M., Aiello, M., Cavaliere, C., Owen, A. M., & Soddu, A. (2021) · Brain Structure and Function · doi:10.1007/s00429-020-02211-6 · Cited by 6
Rahman, N., Xu, K., Omer, M., Budde, M. D., Brown, A. M., & Baron, C. A. (2021) · PLoS ONE · doi:10.1371/journal.pone.0255711 · Cited by 6
Benitez, A. M., Hassenstab, J. J., & Bangen, K. J. (2013) · The Clinical Neuropsychologist · doi:10.1080/13854046.2013.854836 · Cited by 6
A watershed model of individual differences in fluid intelligencePreprint
Kievit, R., Davis, S., Griffiths, J., Correia, M., Cam-Can, & Henson, R. (2016) · bioRxiv · doi:10.1101/041368 · Cited by 127
“Nonetheless, it should be noted that FA is a complex measure, and the relationship between FA and white-matter health is not yet fully understood (Jones et al., 2013; Wandell, 2016).”
Variable Selection in Structural Equation Models with Regularized MIMIC ModelsPreprint
Jacobucci, R., Kievit, R., & Brandmaier, A. M. (2018) · doi:10.17605/osf.io/bxzjf · Cited by 6
Qian, W. P., Xu, X., Wu, Y., Yu, L., Wang, C., Yan, M., & Yu, R. (2025) · Frontiers in Neuroscience · doi:10.3389/fnins.2025.1552961 · Cited by 5
“This finding supports the previous speculation of Jones et al. (2013) that increased FA could stem from decreased crossing of axons, higher axon density or from higher density of glia cells such as oligodendrocytes.”
Aiello, M., Marizzoni, M., Borrelli, P., Cavaliere, C., Ribaldi, F., Garibotto, V., Scheffler, M., Jelescu, I., Jovicich, J., Catani, M., et al. (2025) · Alzheimer s & Dementia · doi:10.1002/alz.70126 · Cited by 5
“In addition, the MR diffusion protocol used in our study did not enable the performance of tractography analysis, 62 as it included just one b-shell and did not allow the use of specific techniques to control for CSF contamination, such as freewaterelimination.”
Saini, F., Ivain, P., Idris, M., Wells, J., Bianchi, L., Tamayo‐Elizalde, M., Dell’Acqua, F., & Strydom, A. (2025) · Alzheimer s & Dementia · doi:10.1002/alz.70382 · Cited by 5
Presurgical structural connectivity predicts postsurgical cognitive impairment in glioma patients
Smolders, L., Baene, W. D., Gehring, K., van der Hofstad, R., Florack, L. M. J., & Rutten, G.-J. M. (2025) · Brain Communications · doi:10.1093/braincomms/fcaf346 · Cited by 5
“85 for an overview).”
The effects of a second pregnancy on women’s brain structure and function
Straathof, M., Halmans, S., Pouwels, P. J. W., Crone, E. A., & Hoekzema, E. A. (2026) · Nature Communications · doi:10.1038/s41467-026-69370-8 · Cited by 9
Clinical connectomics: Mapping structural brain networks in disease
Zalesky, A., & Biase, M. A. D. (2026) · Neuron · doi:10.1016/j.neuron.2026.02.007 · Cited by 7
Iron accumulation and axonal damage of cerebellum in idiopathic cervical dystonia
Li, H., Zhang, M., Wu, Y., Li, Y., Feng, R., Shen, X., Wang, Y., Sun, X., Xue, W., Chen, S., et al. (2023) · European Journal of Neurology · doi:10.1111/ene.15754 · Cited by 5
“The reduced FA is linked to axonal damage, but it is also influenced by many other factors such as the morphological differences of fiber and fiber orientation dispersion [67].”
BackgroundFiber-specific white matter alterations in Parkinson's disease patients with freezing of gait.
Zhou, W.-Y., He, J.-Z., Zhang, C., Pan, Y., Sang, T., & Qiu, X. (2023) · Brain Research · doi:10.1016/j.brainres.2023.148440 · Cited by 3
Evaluation of tractography-based myelin-weighted connectivity across the lifespan
Bosticardo, S., Schiavi, S., Schaedelin, S. A., Battocchio, M., Baraković, M., Lu, P., Weigel, M., Melie‐García, L., Granziera, C., & Daducci, A. (2024) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1228952 · Cited by 6
“…between anatomical regions has been extensively adopted as a proxy for the strength of connections in the connectome (Bullmore and Bassett, 2011; Jones et al., 2013; Shi and Toga, 2017; Sotiropoulos and Zalesky, 2019); however, recent studies have questioned the quantitative nature of this…”
ResultWhite Matter Alterations of Visual Pathway in Thyroid Eye Disease: A Fixel‐Based Analysis
Jiang, M.-D., Zhang, H.-Y., Liu, Y., Song, X.-F., Song, Y., Sun, J., Tang, Y., Zhu, L., Zhou, H.-F., Li, Y.-W., et al. (2024) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.29387 · Cited by 9
Weak and unstable prediction of personality from the structural connectome
Rauland, A., Jung, K., Satterthwaite, T. D., Cieslak, M., Reetz, K., Eickhoff, S. B., & Popovych, O. V. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00416 · Cited by 5
Analysis of advanced diffusion models assessing white matter microstructure in Alzheimer’s disease
Lv, M., Zhan, K., Yang, J., Li, Y., Li, Y., Xu, X., Han, L., Feng, H., & Zhong, J. (2025) · Scientific Reports · doi:10.1038/s41598-025-09412-1 · Cited by 7
“that water molecule diffusion in the brain follows Gaussian distribution, weakening its capability to detect diffusion heterogeneity in brain tissue 10,11 .”
Höller, M., Ehricke, H.-H., Synofzik, M., Klose, U., & Groeschel, S. (2015) · Clinical Neuroradiology · doi:10.1007/s00062-015-0486-8 · Cited by 5
“Therefore, although widely applied in the medical field, the DT-based methods may produce false negative results in white matter regions with crossing fibers [2].”
BackgroundMichielse, S., Gronenschild, E. H. B. M., Domen, P. A. E., van Os, J., & Marcelis, M. C. (2017) · Brain Research · doi:10.1016/j.brainres.2017.07.002 · Cited by 5
“More advanced scan acquisitions and analysis techniques are required to accomplish this complex task (Jones et al., 2013).”
BackgroundCargnelutti, E., Maieron, M., Ius, T., Škrap, M., & Tomasino, B. (2020) · Frontiers in Neurology · doi:10.3389/fneur.2020.563259 · Cited by 5
Nickel, K., Perlov, E., Reisert, M., Runge, K., Friedel, E. B. N., Denzel, D., Ebert, D., Endres, D., Domschke, K., van Elst, L. T., et al. (2022) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2022.111464 · Cited by 5
Brignoni‐Pérez, E., Dubner, S. E., Ben‐Shachar, M., Berman, S., Mezer, A., Feldman, H. M., & Travis, K. E. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119240 · Cited by 5
Rasmussen, J. Ø., Nordholm, D., Glenthøj, L. B., Jensen, M. A., Garde, A. H., Ragahava, J. M., Jennum, P., Glenthoj, B. Y., Nordentoft, M., Baandrup, L., et al. (2022) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2022.1029149 · Cited by 5
“Lower FA is often interpreted as impaired WM microstructure (Jones et al., 2013) and have been associated with loss of axonal coherence, demyelination, or neurodegeneration (Song et al.”
Background
Metadata
- Authors
- Jones, D. K., Knösche, T. R., & Turner, R.
- Affiliations
- Cardiff University (GB)
- Max Planck Institute for Human Cognitive and Brain Sciences (DE)
- Corresponding author
- Jones, Derek K.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2013-06
- Volume
- 73
- Pages
- 239-254
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2117987496
- Semantic Scholar
- 18c1f13bf2af5a9efb0126b7bd4683fa1b786532
- Cited by
- 2,402
- References
- 200
- Citations by year
- 2026: 140 · 2025: 134 · 2024: 121 · 2023: 150 · 2022: 183 · 2021: 225 · 2020: 209 · 2019: 203 · 2018: 189 · 2017: 201 · 2016: 213 · 2015: 182 · 2014: 135 · 2013: 105
- FWCI
- 92.51
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Funders
- Wellcome Trust (096646/Z/11/Z)
- 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-weighted imaging, diffusion tensor imaging, white matter integrity, fiber count, structural connectivity
- MeSH terms
- Brain, Brain Mapping, Cell Count, Data Interpretation, Statistical, Humans, Image Processing, Computer-Assisted, Nerve Fibers, Neural Pathways, Models, Statistical, Diffusion Magnetic Resonance Imaging, Diffusion Tensor Imaging, Signal-To-Noise Ratio
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