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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“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
Probabilistic diffusion tractography with multiple fibre orientations: What can we gain?
Behrens, T. E. J., Berg, H. J., Jbabdi, S., Rushworth, M. F. S., & Woolrich, M. W. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.09.018 · Cited by 3,471
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
Sorted by citations
Items 1,901–2,000 of 2,327
Dipnall, L. M., Fuelscher, I. T., Yang, J. Y. M., Chen, J., Craig, J. M., Anderson, V. A., Efron, D., & Silk, T. J. (2025) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2025.07.012 · Cited by 2
Braaß, H., Reiter, N., Backhaus, W., Wróbel, P. P., Quandt, F., Schulz, R., Gerloff, C. P., & Higgen, F. L. (2025) · Scientific Reports · doi:10.1038/s41598-025-19143-y · Cited by 2
White Matter Networks of Phonological Awareness in Chinese Readers
Zhang, X., Zhao, Y., Chen, S., Huang, Z., & Zhao, J. (2025) · Brain and Behavior · doi:10.1002/brb3.70781 · Cited by 2
“2002; Jones et al., 2013).”
McDermott, K., Dieckhaus, L., Comrie, C. J., Sandrin, V., Hutchinson, E. B., & Barnes, C. A. (2025) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2025.09.009 · Cited by 2
A Multimodal Deep Learning Approach for White Matter Shape Prediction in Diffusion MRI Tractography
Lo, Y., Chen, Y., Liu, D., Zekelman, L., Rushmore, J., Yogesh Rathi, A., Makris, N., Golby, A. J., Zhang, F., Cai, W., et al. (2025) · Human Brain Mapping · doi:10.1002/hbm.70396 · Cited by 2
Comparison of structural connectivity metrics for multimodal brain image analysis
Bajammal, M., Yoldemir, B., & Rafeef Abugharbieh, A. (2015) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2015.7164024 · Cited by 2
“We speculate that the reason for the observed low average FA correlation can be attributed to the large number of factors affecting local diffusion anisotropy [9].”
BackgroundMethodInfluentialAdaptive algorithms to map how brain trauma affects anatomical connectivity in children
Dennis, E. L., Prasad, G., Babikian, T., Kernan, C., Mink, R. B., Babbitt, C. J., Johnson, J. L., Giza, C. C., Asarnow, R. F., & Thompson, P. M. (2015) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.2207574 · Cited by 2
Bohland, J. W. (2016) · Biological Psychiatry · doi:10.1016/j.biopsych.2016.02.020 · Cited by 2
Visualization of MRI Diffusion Data by a Multi-Kernel LIC Approach with Anisotropic Glyph Samples
Höller, M., Klose, U., Groeschel, S., et al. (2016) · Mathematics and visualization · doi:10.1007/978-3-319-24523-2_7 · Cited by 2
“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 [9, 18].”
BackgroundXu, T., Feng, Y., Wu, Y., Zeng, Q., Zhang, J., He, J., & Zhuge, Q. (2017) · PLoS ONE · doi:10.1371/journal.pone.0168864 · Cited by 2
“The true fODFs are gathers of delta function pointing along fiber orientations, and zero in all other orientations [32].”
BackgroundTao, L., Qian, Z., Yang, Y., Liu, H., & Xue, L. (2017) · Journal of Biomedical Photonics & Engineering · doi:10.18287/jbpe17.03.030301 · Cited by 2
Brain Morphometry: Schizophrenia
Chiapponi, C., Rossi, P. D., Piras, F., Gili, T., & Spalletta, G. (2018) · Neuromethods · doi:10.1007/978-1-4939-7647-8_19 · Cited by 2
Klucken, T., León, I. T., Blecker, C. R., Kruse, O., Tobias Stalder, A., & Stark, R. M. (2018) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2018.00080 · Cited by 2
“Correspondingly, several authors have suggested to avoid the term ’’white matter microstructure integrity’’ since alterations in FA-values are not necessarily based on integrity (Jones et al., 2013).”
BackgroundCompositional measures of diffusion anisotropy and asymmetry
Cieslak, M., Meiring, W., Brennan, T., et al. (2018) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2018.8363537 · Cited by 2
“” Voxel-wise FA values were observed to be lower in some situations when disease or injury affected white matter, but recent results show that relatively low FA values are also observed in healthy white matter voxels when multiple fibers cross within the same voxel, complicating general interpretation of FA values [3,…”
BackgroundResultKurki, T. J. I., & Heiskanen, L. (2018) · Neuroradiology · doi:10.1007/s00234-018-2068-3 · Cited by 2
Effect of Prenatal Organic Solvent Exposure on Structural Connectivity at Childhood
Coloigner, J., Binter, A.-C., Bannier, É., et al. (2019) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2019.8759473 · Cited by 2
“Diffusion-weighted imaging (DWI) can quantitatively assess the microstructural characteristics of white matter (WM) tracts [13, 14].”
BackgroundOliviero, S., & Gratta, C. D. (2021) · Magnetic Resonance Materials in Physics Biology and Medicine · doi:10.1007/s10334-020-00899-5 · Cited by 2
“axial diffusivity (AD), radial diffusivity (RD), mean diffusivity (MD), and fractional anisotropy (FA), are combinations of the eigenvalues according to the formulas in [11] that summarize the diffusion properties of tissues and their degree of anisotropy; they have shown higher sensitivity to tissue structural change…”
BackgroundRaffin, J., Rolland, Y., He, L., Perus, L., Mangin, J., Gabelle, A., Giudici, K. V., Vellas, B. J., & Barreto, P. D. S. (2021) · Maturitas · doi:10.1016/j.maturitas.2021.06.010 · Cited by 2
Advanced Diffusion MRI for prediction of Stroke Recovery
Hui, E. S. (2023) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.28523 · Cited by 3
Bergamino, M., Aslam, S., Knittel, J. J., Alhilali, L., & Stokes, A. (2023) · Journal of Integrative Neuroscience · doi:10.31083/j.jin2205114 · Cited by 4
Li, Y., Zhu, H., Liu, Y., Ding, Y., Li, S., Li, L., Zhang, J., Jiang, J., Shen, N., & Zhu, W. (2024) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.29561 · Cited by 2
“11 This leads to dif fi culties in characterizing the heterogeneous microenvironment of glioma-affected NAWM, where water diffusion may not follow a Gaussian pattern due to cellular structures, crossing fi bers, and microstructural damage.”
Robust intra-individual estimation of structural connectivity by Principal Component Analysis
Konopleva, L. V., Il'yasov, K. A., Teo, S. J., Coenen, V. A., Kaller, C. P., & Reisert, M. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117483 · Cited by 2
Liu, L., Gao, S., Li, S., et al. (2020) · Acta Physica Sinica · doi:10.7498/aps.69.20191346 · Cited by 2
The impact of susceptibility correction on diffusion metrics in adolescents
Lahti, K., Parkkola, R. K., Jääsaari, P., Haataja, L. M., Saunavaara, V., On behalf of the PIPARI Study Group, Ahtola, A., Ekblad, M. O., Ekblad, S., Ekholm, E. M. K., et al. (2021) · Pediatric Radiology · doi:10.1007/s00247-021-05000-3 · Cited by 2
“The diffusion properties of white matter are affected by myelination and axonal features, for example, but the metrics are also influenced by the tract volume and iron and water content inside a voxel [3, 7].”
BackgroundApplications of MRI connectomics
Damoiseaux, J. S., Altmann, A., Richiardi, J., & Sadaghiani, S. (2021) · Advances in magnetic resonance technology and applications · doi:10.1016/b978-0-12-822479-3.00034-8 · Cited by 2
Robust diffusion imaging framework for clinical studiesPreprint
Maximov, I. I., Grinberg, F., Neuner, I., et al. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1502.04967 · Cited by 2
“Conventional DTI tools that use robust estimators are well known and frequently used, in particular, RESTORE which is a recommended method (Jones et al., 2012).”
MethodInfluentialLyall, D. M., Cox, S. R., Lyall, L. M., Celis-Morales, C. A., Cullen, B., Mackay, D., Ward, J., Strawbridge, R. J., McIntosh, A. M., Sattar, N. A., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/230524 · Cited by 2
“Water molecules tend to diffuse with greater directional coherence and lower magnitude when constrained by tightly-packed fibres (such as well-myelinated axons) as well as by cell membranes, microtubules and other structures; lower FA and higher MD are generally considered to reflect poorer / less ‘healthy’ white matt…”
BackgroundUncovering a role for the dorsal hippocampal commissure in episodic memoryPreprint
Postans, M., Parker, G., Lundell, H., Ptito, M., Hamandi, K., Gray, W., Aggleton, J. P., Dyrby, T. B., Jones, D. K., & Winter, M. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/415158 · Cited by 2
Self-citationGilani, N., Hildebrand, S., Schueth, A., & Roebroeck, A. F. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/626945 · Cited by 2
“It is generally better to make more conservative statements about parameters derived from diffusion-weighted imaging of white matter [74]; this is also applicable to a complex mixture such as the cortex where four different cellular microstructures simultaneously affect the diffusion.”
BackgroundDCP: a pipeline toolbox for diffusion connectomePreprint
Huang, W., & Shu, N. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.04.16.044453 · Cited by 2
“These issues have been well discussed by a few recent articles (Jones and Cercignani, 2010; Jones et al., 2013).”
BackgroundCollegiate athlete brain data for white matter mapping and network neurosciencePreprint
Caron, B. A., Stuck, R., McPherson, B. C., Bullock, D. N., Kitchell, L. M., Faskowitz, J., Kellar, D., Cheng, H., Newman, S. D., Port, N., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.08.25.267005 · Cited by 1
The structure of hippocampal circuitry relates to rapid category learning in humansPreprint
Schlichting, M. L., Gumus, M., Zhu, T., & Mack, M. L. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.05.14.444187 · Cited by 2
Siffredi, V., Liverani, M. C., Ville, D. V. D., Freitas, L. G. A., Tolsa, C. B., Hüppi, P. S., & Leuchter, R. H. (2021) · medRxiv · doi:10.1101/2021.10.20.21265246 · Cited by 2
Personalized circuit modeling captures variation in cortical functional connectivityPreprint
Cooper, R. A., Demirtaş, M., Burt, J. B., Howell, A. M., Ji, J., Repovš, G., Sotiropoulos, S. N., Anticevic, A., & Murray, J. D. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.02.19.581085 · Cited by 2
Lee, W. Y., Park, H., Moon, S., Oh, S., Lee, J., Kim, M., & Kwon, J. S. (2023) · Psychiatry Investigation · doi:10.30773/pi.2022.0334 · Cited by 1
Marchese, S. M., Palesi, F., Nigri, A., et al. (2023) · Frontiers in Neurology · doi:10.3389/fneur.2023.1279616 · Cited by 1
“The neuropathological hallmarks of cerebellar ataxia concern brain regions volume and white matter (WM) microstructure, which is frequently investigated using diffusion MRI to reconstruct and assess the integrity of WM axonal tracts (17, 18).”
BackgroundHwang, S., Lee, T. C. M., Paul, D., & Peng, J. (2024) · The Annals of Applied Statistics · doi:10.1214/23-aoas1781 · Cited by 1
Motivation levels and white matter microstructure in children living with HIV
Wedderburn, C. J., Sevenoaks, T., Fouché, J., Phillips, N. J., Lawn, S. D., Stein, D. J., & Hoare, J. (2024) · Scientific Reports · doi:10.1038/s41598-024-54411-3 · Cited by 1
“In this case, findings in children may be separate to adults, and we hypothesise that decreased FA may represent more axons with increased numbers of crossing fibres in the white matter matrix causing a paradoxical decrease in FA 46 .”
Duanmu, X.-J., Wen, J.-Q., Qin, J.-Y., Tan, S.-J., Wu, C.-Q., Yuan, W.-J., Zheng, Q.-S., Zhou, C., Wu, H.-T., Chen, J.-W., et al. (2024) · Parkinsonism & Related Disorders · doi:10.1016/j.parkreldis.2024.106559 · Cited by 1
González‐Escamilla, G., Othman, A. E., Rotaru, L., Winter, Y., & Groppa, S. (2024) · Neuromethods · doi:10.1007/978-1-0716-4083-8_11 · Cited by 1
Tang, B., Cao, H., Deng, S., Zhang, W., Zhao, Y., Gong, Q., Gu, S., & Lui, S. (2024) · Journal of Affective Disorders · doi:10.1016/j.jad.2024.10.067 · Cited by 1
Minnigulova, A., Karpychev, V., Юрьевна, Д. Е., Станиславаовна, П. Д., Sorokin, A. B., Анатольевна, Т. С., Mamokhina, U. A., Касимовна, Д. К., Dragoy, O., & Arutiunian, V. (2025) · Behavioural Brain Research · doi:10.1016/j.bbr.2024.115414 · Cited by 5
Dugan, R., Ramakrishnapillai, S., Amant, J. S., Murray, K. B., McKlveen, K., Naseri, M., Madden, K., Bazzano, L., & Carmichael, O. T. (2025) · NeuroImage · doi:10.1016/j.neuroimage.2025.121034 · Cited by 1
“…are well studied, including its inability to resolve multiple white matter fiber directions within a single location, and the lack of direct connection between diffusion tensor summary metrics and biological properties such as myelination, fiber density, and fiber dispersion (Jones et al., 2013).”
Nasir, Z. A. M., Sapiai, N. A., Fadzil, N. A., Idris, Z., & Suliman, M. A. (2025) · The Egyptian Journal of Radiology and Nuclear Medicine · doi:10.1186/s43055-025-01442-z · Cited by 1
“Instead, they encompass multiple diffusion parameters to collectively represent the state of several tissue attributes, including myelinization, axonal direction, and axonal density [27].”
Konwar, S., Manca, R., Marco, M. D., Soininen, H. S., & Venneri, A. (2025) · Journal of Alzheimer s Disease · doi:10.1177/13872877251320660 · Cited by 1
Cognitive-and lifestyle-related microstructural variation in the ageing human hippocampus
Agyekum, T., García, C. L., Fay, F., Parent, O., Bussy, A., Devenyi, G. A., & Chakravarty, M. M. (2025) · Brain Structure and Function · doi:10.1007/s00429-025-02908-6 · Cited by 2
“FA and MD are diffusion MRI derived metrics that have been known to describe axon geometry and axon density, respectively (Alexander et al. 2007; Jones et al. 2013; Tardif et al. 2016; Patel et al. 2020).”
InfluentialVilla, M., Koirala, N., Perdue, M. V., Branum‐Martin, L., & Landi, N. (2025) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2025.101561 · Cited by 2
“Details on how these measures are obtained for each tract are described elsewhere in detail (e.g., Koirala et al., 2021; Pierpaoli et al., 1996, Beaulieu, 2002, Jones et al., 2013; Zhang et al., 2012; Zhang et al., 2011).”
Jacobs, N. P. T., van der Krogt, M. M., Buizer, A. I., et al. (2025) · Brain Structure and Function · doi:10.1007/s00429-025-02937-1 · Cited by 1
“Despite all limitations of this simplified interpretation (Jones et al. 2013; Vos et al. 2012), the FA values of all CP participants increased in the direction of values observed for TD children.”
Fixel-based evidence for preserved white matter asymmetry in human situs inversus totalis
Karlsson, E. M., Verhelst, H., & Vingerhoets, G. (2025) · Brain Structure and Function · doi:10.1007/s00429-025-02931-7 · Cited by 1
“This can result in inaccurate measurements and poor reconstruction of white matter pathways, especially in areas with crossing, branching, or densely packed fibers (Jones et al. 2013).”
Boons, J. H. C., Dingemanse, G., Vinke, E. J., Kremer, B., Vernooij, M. W., & Goedegebure, A. (2025) · GeroScience · doi:10.1007/s11357-025-01707-5 · Cited by 1
“FA reflects the degree of anisotropy; it quantifies the directional movement along the axonal fibers and may reflect effective mye-lination and axonal integrity [12].”
White matter correlates of autonomic cardiac dysfunction in anorexia nervosa
de la Cruz, F., Makris, N., Schumann, A., Legarreta, J. H., Chen, Y., Rieger, K., Giuliano, M. D., Zurrin, R., Billah, T., Kim, N. J., et al. (2025) · Autonomic Neuroscience · doi:10.1016/j.autneu.2025.103307 · Cited by 1
“While higher FA is generally associated with better microstructural properties such as enhanced myelination or axonal density (Basser and Pierpaoli, 2011), it may also reflect reduced structural complexity due to selective axonal loss or pruning (Jones et al., 2013).”
Grimm, K., Braaß, H., Sadeghi, F., et al. (2025) · Journal of Neurology · doi:10.1007/s00415-025-13186-x · Cited by 1
“Third, FA reflects the restriction of water molecule diffusion along the axis of the applied gradient, averaged over the voxel [47].”
Quantitative tractography: joys and sorrows
Daducci, A., & Schiavi, S. (2025) · Brain Structure and Function · doi:10.1007/s00429-025-02939-z · Cited by 1
“…as fundamental limitations have been recently identified about its effectiveness: (i) the reconstructions are not truly quantitative (Jones 2010; Jones et al. 2013; Smith et al. 2020), and (ii) their anatomical accuracy might be poor when not enough information about the pathways is available,…”
Loução, R., Köcher, M., Brandt, G. A., Petry‐Schmelzer, J. N., Barbe, M. T., Dafsari, H. S., Mana, J., Jech, R., Wirths, J., Visser-Vandewalle, V. E. R. M., et al. (2025) · Stereotactic and Functional Neurosurgery · doi:10.1159/000546716 · Cited by 2
“…it is a well-known limitation of tractography that this is not the case: MR acquisition parameters, image quality, processing pipeline, pathway length, and underlying microstructure will all heavily influence the number of reconstructed streamlines, therefore confounding the analysis [52, 53].”
Myelin water and tensor‐valued diffusion imaging: (How) are they related?
Balaji, S., Dvorak, A. V., Wiley, N., MacMillan, E. L., Traboulsee, A. L., Vavasour, I. M., Gilbert, G., Moore, G. R. W., Li, D. K. B., Laule, C., et al. (2025) · Magnetic Resonance in Medicine · doi:10.1002/mrm.30620 · Cited by 1
Stammen, C., Penate, J. S., Metzen, D., Hönscher, M. J., Fraenz, C., Schlüter, C., Güntürkün, O., Kumsta, R., & Genç, E. (2025) · Cerebral Cortex · doi:10.1093/cercor/bhaf199 · Cited by 2
Brain microstructure alterations in bipolar disorder subtypes revealed by diffusion kurtosis imaging
Nakaya, M., Kamiya, K., Kurokawa, R., Kunimatsu, A., Suzuki, Y., Koike, S., Okada, N., Kasai, K., & Abe, O. (2025) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2025.07.006 · Cited by 2
Kyriazis, D. A., Uji, M., Bouyagoub, S., Cercignani, M., Ford, P. R., & Sigala, N. (2025) · Journal of Integrative Neuroscience · doi:10.31083/jin36224 · Cited by 2
Yang, C., Han, J., Sun, N., Liu, P., Zhang, K., Zhang, A., & Liu, Z. (2025) · CNS Spectrums · doi:10.1017/s1092852925000252 · Cited by 1
“34,35 MD measures the overall diffusion restriction in a voxel and is sensitive to disruption of either axonal or myelin integrity.”
Usuda, N., Sugawara, S. K., Tazoe, T., et al. (2025) · Neuroscience Research · doi:10.1016/j.neures.2025.104954 · Cited by 1
Brain structure–function coupling – relationship with language lateralisation
Andrulyte, I., Zago, L., Jobard, G., Lemaître, H., Taylor, P. N., Rheault, F., Joliot, M., Petit, L., & Keller, S. S. (2026) · Cortex · doi:10.1016/j.cortex.2026.08.001 · Cited by 1
The role of structural connectivity on brain function through a Markov model of signal transmission
Razban, R. M., Banerjee, A., Mujica-Parodi, L. R., & Bahar, İ. (2025) · PLoS ONE · doi:10.1371/journal.pone.0331085 · Cited by 1
“…MRI (dMRI) have been compared to resting-state functional MRI (fMRI) data. dMRI can measure the number of white matter tracts between brain regions [13], and describes the connectome. fMRI, on the other hand, measures time-series of regional activity, which reflects region-dependent brain function…”
Kasiri, M., Abe, S., Soroushmojdehi, R., Hernández‐Martín, E., Mousavi, S. A. S., & Sanger, T. D. (2025) · Brain Communications · doi:10.1093/braincomms/fcaf336 · Cited by 1
“37 (iv) Fibre tract length indicates the total length of individual fibre tracts connecting two regions of interest and provides insights into the spatial extent or reach of neural pathways.”
Bliakharskaia, E., Chiarelli, A. M., Patitucci, E., Carriero, M., Censo, D. D., Biondetti, E., Gratta, C. D., Capuani, S., Palombo, M., Tomassini, V., et al. (2025) · NeuroImage · doi:10.1016/j.neuroimage.2025.121466 · Cited by 1
“Even for the diffusion direction with the highest signal attenuation (that is [1 0 0], corresponding to the orientation of the most coherent fibers in the corpus callosum) the SNR remains above the inferior limit allowed for the reliability of DW data (SNR = 3), according to Jones et al. (Jones et al., 2013).”
Tractography-guided EMG Biofeedback in Stroke: An Exploratory Study of Plasticity and Motor Outcomes
Janmohamamdi, S., Batouli, S. A. H., Ghabaee, M., Yoonessi, A., Hadjighassem, M., Akbarfahimi, N., Shafaghi, L., Ziaa, M. J., & Torkaman‐Boutorabi, A. (2025) · Archives of Neuroscience · doi:10.5812/ans-164682 · Cited by 1
Widespread Alterations in White Matter Microstructure in Autism: A Multilevel Meta-Analysis
Yoon, C. D., Alexander, A. L., Travers, B. G., Lainhart, J. E., & Dean, D. C. (2026) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2026.08.002 · Cited by 2
Yoon, C. D., & Dean, D. C. (2025) · Autism Research · doi:10.1002/aur.70122 · Cited by 3
“For instance, DTI lacks the specificity needed to distinguish between different types of microstructural changes (Andica et al. 2020; Jones et al. 2013), such as changes to fiber organization, axonal damage, or myelin abnormalities.”
Sasabayashi, D., Seitz‐Holland, J., Yogesh Rathi, A., Kim, N. J., Cho, K. I. K., Mohandass, D., Billah, T., Haidar, A., Kotler, E., Karayumak, S. C., et al. (2025) · Schizophrenia Bulletin · doi:10.1093/schbul/sbaf172 · Cited by 1
Pasion, R., Amaoui, S., Paiva, T. O., Macedo, I., Bourbon‐Teles, J., Duarte, J. V., Pinto, T. M., Costa, R. A., Lamela, D. J. P. D. V., Jongenelen, I., et al. (2025) · European Child & Adolescent Psychiatry · doi:10.1007/s00787-025-02864-w · Cited by 1
“RD maps were also computed and analyzed as they provide complementary infor - mation, offering insights into myelin loss and crossing fibers from other bundles, thereby enhancing the interpretability of WM tracts characterization [ 42].”
InfluentialGuerra, R. B., Peñate-Castro, W., Díaz-Velis, E. F., Pérez, C. S., Alfonso, S. B., Hernández, M. H., Fleta, J. L. H., & Molina, J. M. (2025) · Brain Science · doi:10.3390/brainsci15111155 · Cited by 1
“Reconstructions with implausible trajectories or motion artifacts were repeated following the quality control procedures described in recent reviews of diffusion MRI [34,35].”
Decoding brain structure-function dynamics in health and in psychosis via an autoencoder
Cai, Q., Thomas, H., Hyde, V., Laguna, P. A. L., McNabb, C. B., Singh, K. D., Jones, D. K., & Messaritaki, E. (2025) · Scientific Reports · doi:10.1038/s41598-025-24232-z · Cited by 2
Self-citationMaiani, M., Lahey, N., Bardhi, M., et al. (2025) · Journal of Child Neurology · doi:10.1177/08830738251394438 · Cited by 1
Licandro, R., Olchanyi, M., da Silva, L. F. F., van der Kouwe, A. J. W., Jaimes, C. E., Ngo, N. X., Kelley, W., Folkerth, R. D., Haynes, R. L., Edlow, B. L., et al. (2025) · Human Brain Mapping · doi:10.1002/hbm.70422 · Cited by 1
“These results are subject to the inherent and well-known limitations of diffusion MRI tractography (Grisot et al. 2021; Jbabdi and Johansen-Berg 2011; Jones et al. 2013; Maier-Hein et al. 2017; Thomas et al. 2014).”
Gonçalves, P. D., Woodruff, J. O., Pedro, M. O. P., van Dijk, M. T., Bruzelius, E., Martins, S. S., Bandoli, G., Potter, A., Cioffredi, L., Talati, A., et al. (2025) · Biological Psychiatry Global Open Science · doi:10.1016/j.bpsgos.2025.100624 · Cited by 1
“…indicates more directionally constrained diffusion of water molecules, which has been interpreted to reflect greater coherence or organization of white matter tracts but can also be influenced by axonal density, myelination, fiber packing, or crossing fibers, and, in some cases, pathology (54–59).”
Cortical white matter: no longer a silent partner
Rockland, K. S., & Rushmore, J. (2026) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2025.1726067 · Cited by 1
Dor, N. B., Sighinolfi, G., Rosetti, V., et al. (2026) · Life · doi:10.3390/life16010115 · Cited by 1
“However, interpreting these changes is complex, particularly when considered in isolation and without strong a priori hypotheses regarding the potential neurophysiological origins of the alterations, as they may be attributed to various factors [9].”
Zhang, J., Song, Y., & Tan, L. (2026) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2025.1726577 · Cited by 1
Alotaibi, A. M., Orfali, R. S., Alorainy, A. I., Alosaimi, M. H., Alshanawani, M., Alwtban, A. A., Bentall, R. P., & Meyer, G. (2026) · NeuroImage · doi:10.1016/j.neuroimage.2026.121733 · Cited by 1
Structural network topology and cognitive control in very preterm born young adults
Marek, M. J., Dieter Wolke, C., Sorg, C., Wendt, J., Menegaux, A., Hedderich, D. M., Bartmann, P., Burkhardt, M., Hildebrandt, A., & Heep, A. (2026) · NeuroImage Clinical · doi:10.1016/j.nicl.2026.103952 · Cited by 1
“While it is among the most advanced and widely used approaches for reconstructing white matter pathways in vivo, it does not provide a direct one-to-one mapping of biological acons (Jeurissen et al., 2019; Jones et al., 2013).”
Birk, F., Tesh, H., Aghaeifar, A., Klinkowski, S., Valsala, P. I., Mueller, S., Brodt, S., Scheffler, K., & Heule, R. (2026) · Magnetic Resonance in Medicine · doi:10.1002/mrm.70255 · Cited by 2
“Our in vivo analysis assumes a single dominant fiber orientation per voxel, thus not considering crossing fibers or fiber dispersion,knowntoaffectsignalcontrast[106]andshowntoconfound orientation-dependent relaxation measurements [43, 98].”
Bouzouina, A., Gruber, M., Zhao, T., Schiweck, C., Aichholzer, M., Uckermark, C., Claaß, L. V., Stein, F., Winter, N. R., Meinert, S., et al. (2026) · Neuroscience Applied · doi:10.1016/j.nsa.2026.106984 · Cited by 1
“…of diffusion MRI – based tractography for reconstructing connections involving small subcortical nuclei, which are particularly susceptible to partial-volume effects, registration inac-curacies, and tractography-related false-positive connections (Jones et al., 2013; Maier-Hein et al., 2017).”
Shimizu, T., Sato, H., Sanada, T., Saito, M., Mitsui, N., Hiroshima, S., & Kinoshita, M. (2026) · Journal of Neuro-Oncology · doi:10.1007/s11060-026-05471-0 · Cited by 1
“While it offers intuitive visualization of white matter trajectories, it remains susceptible to false positives and cannot capture crossing fibers with high precision [29].”
Payas, A., Seber, T., Çiçek, F., Kocaman, H., Yıldırım, H., BUDAK, M., & Uçar, İ. (2026) · Brain Mechanisms · doi:10.1016/j.bramec.2026.202543 · Cited by 1
Martinez, J. D., Mooshagian, E., Wang, H., Karlsgodt, K. H., Uddin, L. Q., & Nomi, J. S. (2026) · Brain Structure and Function · doi:10.1007/s00429-026-03091-y · Cited by 1
Klein, C. C., Berger, P., Wiesmann, C. G., & Friederici, A. D. (2026) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2026.101715 · Cited by 2
“As this measure is influenced by the curvature, length, and branching of the underlying fiber pathways, which makes its biological interpretation challenging (Jones et al., 2013), we report these preregistered analyses in the Supplementary Material.”
White matter microstructure of sensorimotor projection fibers in chronic low back pain
Gilliam, J. R., Vendemia, J. M. C., Baty, Z., Silfies, S. P., & Coombes, S. A. (2026) · PAIN Reports · doi:10.1097/pr9.0000000000001435 · Cited by 1
“38,39,58 In addition, any cerebrospinal fluid (CSF) or edema in a voxel will be modeled alongside intracellular water, without distinction between them.”
Tian, Y., & Whitwell, J. L. (2026) · NeuroImage · doi:10.1016/j.neuroimage.2026.121984 · Cited by 2
Multimodal diffusion MRI biomarkers of white matter alterations and clinical impairment in mTBI
Bergamino, M., Ott, L. R., McElvogue, M. M., Jha, R., Moreno, C., & Stokes, A. M. (2026) · Frontiers in Neuroscience · doi:10.3389/fnins.2026.1822384 · Cited by 1
AI and radiomics for improving the medical workflow for Multiple Sclerosis
Cipriani, A., Polsinelli, M., & Placidi, G. (2026) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2026.109475 · Cited by 1
Zhou, X., Wang, J., Yang, X., Huang, J., Fan, H., Wang, S., & Si, F. (2026) · Neuroscience · doi:10.1016/j.neuroscience.2026.06.014 · Cited by 1
Altieri, R., Ugga, L., Bianconi, A., Caneva, S., Caranci, F., Cirillo, G., Cofano, F., Corvino, S., DIVITIIS, O. D., Pepa, G. M. D., et al. (2026) · Journal of Neuro-Oncology · doi:10.1007/s11060-026-05691-4 · Cited by 1
“Similar mechanical effects have been observed in previous morphometric studies of extra-axial tumors, emphasizing that deterministic tractography may not fully disentangle true microstructural injury from deformation-related signal alterations [ 21 – 23 ].”
Hausmann, A. C., Querbach, S. K., Rubbert, C., Schnitzler, A., Caspers, J., & Hartmann, C. (2026) · Scientific Reports · doi:10.1038/s41598-026-65470-z · Cited by 1
Mishra, S., Pettigrew, C. A., Ugonna, C., Chen, N., Frye, J. B., Doyle, K. P., Ryan, L., Albert, M., Ho, S. G., Moghekar, A., et al. (2026) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2026.09.009 · Cited by 2
Scherrer, B., Afacan, O., Stamm, A., Singh, J. M., & Warfield, S. K. (2015) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.2082387 · Cited by 1
“Therefore, while DTI is, to some extent, sensitive to detecting microstructural changes in disease, it shows poor specificity in depicting the precise nature of these changes.(9,10)”
BackgroundActualité en neuro-imagerie du Trouble Déficit d’Attention/Hyperactivité
Beggiato, A., & Cortese, S. (2014) · Annales Médico-psychologiques revue psychiatrique · doi:10.1016/j.amp.2014.03.008 · Cited by 1
High-angular diffusion MRI in reward-based psychiatric disorders
Yu, W., Lv, Q., Zhang, C., Shen, Z., Sun, B., & Wang, Z. (2014) · Springer eBooks · doi:10.1007/978-94-017-9576-0_2 · Cited by 1
Accounting for the Developing Brain
Wolff, J. J. (2016) · Springer eBooks · doi:10.1007/978-3-319-28492-7_29 · Cited by 1
A self-adaptive local feature extraction based magnetic resonance imaging
Zhang, J., Xu, T., Feng, Y., et al. (2016) · Chinese Control and Decision Conference (CCDC) · doi:10.1109/ccdc.2016.7532179 · Cited by 1
“Diffusion weighted MRI (DW-MRI) is currently the only method capable of mapping the fiber architecture of tissue in vivo and, as such, it has triggered tremendous hopes and expectations [1].”
BackgroundSaarela, C., Karrasch, M., Ilvesmäki, T., et al. (2016) · Neuroreport · doi:10.1097/wnr.0000000000000704 · Cited by 1
Chapter 14 Brain network organization in ASD
Müller, R., & Carper, R. A. (2016) · CRC Press eBooks · doi:10.1201/9781315371375-15 · Cited by 1
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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