Using high-resolution quantitative mapping of R1 as an index of cortical myelination

Lutti, Antoine; Dick, Frederic; Sereno, Martin I.; Weiskopf, Nikolaus

doi:10.1016/j.neuroimage.2013.06.005

Cited by 346Advanced MRI Techniques and ApplicationsAdvanced Neuroimaging Techniques and ApplicationsFunctional Brain Connectivity Studies

Using high-resolution quantitative mapping of R1 as an index of cortical myelination

Lutti, Antoine, Dick, Frederic, Sereno, Martin I., Weiskopf, Nikolaus·2014·NeuroImage

DOI 10.1016/j.neuroimage.2013.06.005

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Abstract

A fundamental tenet of neuroscience is that cortical functional differentiation is related to the cross-areal differences in cyto-, receptor-, and myeloarchitectonics that are observed in ex-vivo preparations. An ongoing challenge is to create noninvasive magnetic resonance (MR) imaging techniques that offer sufficient resolution, tissue contrast, accuracy and precision to allow for characterization of cortical architecture over an entire living human brain. One exciting development is the advent of fast, high-resolution quantitative mapping of basic MR parameters that reflect cortical myeloarchitecture. Here, we outline some of the theoretical and technical advances underlying this technique, particularly in terms of measuring and correcting for transmit and receive radio frequency field inhomogeneities. We also discuss new directions in analytic techniques, including higher resolution reconstructions of the cortical surface. We then discuss two recent applications of this technique. The first compares individual and group myelin maps to functional retinotopic maps in the same individuals, demonstrating a close relationship between functionally and myeloarchitectonically defined areal boundaries (as well as revealing an interesting disparity in a highly studied visual area). The second combines tonotopic and myeloarchitectonic mapping to localize primary auditory areas in individual healthy adults, using a similar strategy as combined electrophysiological and post-mortem myeloarchitectonic studies in non-human primates.

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Many investigators regard R1 (1/T1) as the best MR measure of myelin content.
“many investigators consider R1 (1/T1) to be the best MR measure of myelin content (Stüber et al., 2014; Lutti et al., 2013).”
From Multi-modal characterization of rapid anterior hippocampal volume increase associated with aerobic exercise (2016) · cites this paper as Lutti et al., 2013

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Increased SNR and reduced distortions by averaging multiple gradient echo signals in 3D FLASH imaging of the human brain at 3T
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Fast high‐resolution T 1 mapping of the human brain
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Correction forB1 andB0 variations in quantitativeT2 measurements using MRI
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A note on myeloarchitectonics
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A New Method for Fast Multislice T1 Mapping
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Do the Congenitally Blind Have a Stria of Gennari? First Intracortical Insights In Vivo
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Optimizing T1-weighted imaging of cortical myelin content at 3.0T
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Correspondence of human visual areas identified using functional and anatomical MRI in vivo at 7 T
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Simultaneous variable flip angle–actual flip angle imaging method for improved accuracy and precision of three‐dimensional T1 and B1 measurements
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Fast and accurate measurements of T1 using a multi‐readout single inversion‐recovery sequence
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Rapid radiofrequency field mapping in vivo using single‐shot STEAM MRI
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Identification of signal bias in the variable flip angle method by linear display of the algebraic ernst equation
Helms, G., Dathe, H., Weiskopf, N., & Dechent, P. (2011) · Magnetic Resonance in Medicine · doi:10.1002/mrm.22849 · Cited by 39 · see citing works
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The Intrinsic Shape of Human and Macaque Primary Visual Cortex
Hinds, O., Polimeni, J. R., Rajendran, N., Balasubramanian, M., Wald, L. L., Augustinack, J. C., Wiggins, G. C., Rosas, H. D., Fischl, B. R., & Schwartz, E. (2008) · Cerebral Cortex · doi:10.1093/cercor/bhn016 · Cited by 38 · see citing works
T1 corrected B1 mapping using multi‐TR gradient echo sequences
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Combined prospective and retrospective motion correction to relax navigator requirements
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Rapid high-resolution three-dimensional mapping of T1 and age-dependent variations in the non-human primate brain using magnetization-prepared rapid gradient-echo (MPRAGE) sequence
Liu, J. V., Bock, N. A., & Silva, A. C. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.02.075 · Cited by 31 · see citing works
Conditions for the driven equilibrium single pulse observation of spin-lattice relaxation times
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Die Myeloarchitektonik des Isocortex temporalis beim Menschen
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A novel method for simultaneous 3D B1 and T1 mapping: the method of slopes (MoS)
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Über die Bedeutung und Reichweite des Lokalisationsprinzips im Nervensystem
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Delineating extrastriate visual area MT(V5) using cortical myeloarchitecture
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Improved encoding pulses for Bloch–Siegert mapping
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Rapid methods for concurrent measurement of the RF‐pulse flip angle and the longitudinal relaxation time
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DREAM--a novel approach for robust, ultrafast, multislice B₁ mapping.
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A New Approach for Creating Customizable Cytoarchitectonic Probabilistic Maps without a Template
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High-resolution quantitative T1 maps of the human stria of Gennari at 7 Tesla
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How much resolution is needed for in-vivo analysis of cortical myeloarchitecture?
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Grieve (2000) · doi:10.1002/(sici)1522-2594(200005)43:5
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Wansapura (1999) · doi:10.1002/(sici)1522-2586(199904)9:4
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Jones (1999) · doi:10.1002/(sici)1522-2594(199907)42:1
High-resolution intersubject averaging and a coordinate system for the cortical surface
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Hierarchy of transcriptomic specialization across human cortex captured by structural neuroimaging topography
Burt, J. B., Demirtaş, M., Eckner, W. J., Navejar, N. M., Ji, J. L., Martin, W. J., Bernacchia, A., Anticevic, A., & Murray, J. D. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0195-0 · Cited by 657 · see citing works
Adolescence is associated with genomically patterned consolidation of the hubs of the human brain connectome
Whitaker, K. J., Vértes, P. E., Romero-García, R., Váša, F., Moutoussis, M., Prabhu, G., Weiskopf, N., Callaghan, M. F., Wagstyl, K., Rittman, T., et al. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1601745113 · Cited by 506 · see citing works
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Predicting brain-age from multimodal imaging data captures cognitive impairment
Liem, F., Varoquaux, G. P., Kynast, J., Beyer, F., Masouleh, S. K., Huntenburg, J. M., Lampe, L., Rahim, M., Abraham, A., Craddock, R. C., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.11.005 · Cited by 502 · see citing works
Imaging-based parcellations of the human brain
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Lifespan maturation and degeneration of human brain white matter
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Apparent thinning of human visual cortex during childhood is associated with myelination
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On the accuracy of T1 mapping: Searching for common ground
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A Systematic Relationship Between Functional Connectivity and Intracortical Myelin in the Human Cerebral Cortex
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The Functional Neuroanatomy of Human Face Perception
Kalanit Grill-spector, A., Weiner, K. S., Kay, K., & Gomez, J. (2017) · Annual Review of Vision Science · doi:10.1146/annurev-vision-102016-061214 · Cited by 265 · see citing works
hMRI – A toolbox for quantitative MRI in neuroscience and clinical research
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Human motor cortical beta bursts relate to movement planning and response errors
Little, S. J., Bonaiuto, J. J., Barnes, G. R., & Bestmann, S. (2019) · PLoS Biology · doi:10.1371/journal.pbio.3000479 · Cited by 244 · see citing works
Why diffusion tensor MRI does well only some of the time: variance and covariance of white matter tissue microstructure attributes in the living human brain
De Santis, S., Drakesmith, M., Bells, S., Assaf, Y., & Jones, D. K. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.12.003 · Cited by 231 · see citing works
Tonotopic mapping of human auditory cortex
Sàenz, M., & Langers, D. R. M. (2013) · Hearing Research · doi:10.1016/j.heares.2013.07.016 · Cited by 222 · see citing works
Ultra-high field MRI: Advancing systems neuroscience towards mesoscopic human brain function
Dumoulin, S. O., Fracasso, A., van der Zwaag, W., Siero, J. C. W., & Petridou, N. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.01.028 · Cited by 216 · see citing works
Iron, myelin, and the brain: neuroimaging meets neurobiology
Möller, H. E., Bossoni, L., Connor, J. R., Crichton, R. R., Does, M. D., Ward, R. J., Zecca, L., Zucca, F. A., & Ronen, I. (2019) · Trends in Neurosciences · doi:10.1016/j.tins.2019.03.009 · Cited by 207 · see citing works
Advances in MRI-based computational neuroanatomy
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Microstructural proliferation in human cortex is coupled with the development of face processing
Gomez, J., Barnett, M., Natu, V. S., Mezer, A., Palomero‐Gallagher, N., Weiner, K. S., Amunts, K., Zilles, K., & Kalanit Grill-spector, A. (2017) · Science · doi:10.1126/science.aag0311 · Cited by 173 · see citing works
Structural Neuroimaging of Anorexia Nervosa: Future Directions in the Quest for Mechanisms Underlying Dynamic Alterations
King, J. A., Frank, G., Thompson, P. M., & Ehrlich, S. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.08.011 · Cited by 164 · see citing works
Gray matter myelination of 1555 human brains using partial volume corrected MRI images
Shafee, R., Buckner, R. L., & Fischl, B. R. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.10.054 · Cited by 158 · see citing works
Rapid and widespread white matter plasticity during an intensive reading intervention
Huber, E., Donnelly, P. M., Rokem, A., & Yeatman, J. D. (2018) · Nature Communications · doi:10.1038/s41467-018-04627-5 · Cited by 158 · see citing works
Multi-modal characterization of rapid anterior hippocampal volume increase associated with aerobic exercise
Thomas, A. G., Dennis, A., Rawlings, N. B., Stagg, C. J., Matthews, L., Morris, M., Kolind, S. H., Foxley, S., Jenkinson, M., Nichols, T. E., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.10.090 · Cited by 152 · see citing works
“…the majority of our imaging measures supported an increase in myelination within anterior hippocampus, the lack of an increase in T1 is a surprising and notable exception as many investigators consider R1 (1/T1) to be the best MR measure of myelin content (Stüber et al., 2014; Lutti et al., 2013).”
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Myelination of the brain in Major Depressive Disorder: An in vivo quantitative magnetic resonance imaging study
Sacchet, M. D., & Gotlib, I. H. (2017) · Scientific Reports · doi:10.1038/s41598-017-02062-y · Cited by 145 · see citing works
Inferring brain tissue composition and microstructure via MR relaxometry
Does, M. D. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2017.12.087 · Cited by 137 · see citing works
Specific white matter tissue microstructure changes associated with obesity
Kullmann, S., Callaghan, M. F., Heni, M., Weiskopf, N., Scheffler, K., Häring, H.-U., Fritsche, A., Veit, R., & Preissl, H. T. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.10.006 · Cited by 134 · see citing works
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So You Want to Image Myelin Using MRI: An Overview and Practical Guide for Myelin Water Imaging
Lee, J., Hyun, J., Lee, J., Choi, E., Shin, H., Min, K., Nam, Y., Kim, H. J., & Oh, S. (2021) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.27059 · Cited by 134 · see citing works
Microstructural imaging of human neocortex in vivo
Edwards, L., Kirilina, E. P., Mohammadi, S., & Weiskopf, N. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.02.055 · Cited by 122 · see citing works
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New tissue priors for improved automated classification of subcortical brain structures on MRI
Lorio, S., Fresard, S., Adaszewski, S., Kherif, F., Chowdhury, R., Frackowiak, R. S. J., Ashburner, J., Helms, G., Weiskopf, N., Lutti, A., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.01.062 · Cited by 132 · see citing works
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Advances in noninvasive myelin imaging
Heath, F. C., Hurley, S. A., Johansen‐Berg, H., & Sampaio‐Baptista, C. (2017) · Developmental Neurobiology · doi:10.1002/dneu.22552 · Cited by 130 · see citing works
Advanced MRI techniques to improve our understanding of experience-induced neuroplasticity
Tardif, C. L., Gauthier, C. J., Steele, C. J., Bazin, P.-L., Schäfer, A., Schaefer, A., Turner, R., & Villringer, A. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.08.047 · Cited by 127 · see citing works
A cytoarchitecture-driven myelin model reveals area-specific signatures in human primary and secondary areas using ultra-high resolution in-vivo brain MRI
Dinse, J., Härtwich, N., Wähnert, M., Tardif, C. L., Schäfer, A., Geyer, S., Preim, B., Turner, R., & Bazin, P. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.04.023 · Cited by 126 · see citing works
Rapid and specific gray matter changes in M1 induced by balance training
Taubert, M., Mehnert, J., Pleger, B., & Villringer, A. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.03.017 · Cited by 115 · see citing works
Laminar imaging of positive and negative BOLD in human visual cortex at 7 T
Fracasso, A., Luijten, P. R., Dumoulin, S. O., & Petridou, N. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.02.038 · Cited by 117 · see citing works
Evolution of white matter tract microstructure across the life span
Slater, D. A., Melie‐Garcia, L., Preisig, M., Kherif, F., Lutti, A., & Draganski, B. (2019) · Human Brain Mapping · doi:10.1002/hbm.24522 · Cited by 119 · see citing works
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Clarifying Human White Matter
Wandell, B. A. (2016) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-070815-013815 · Cited by 112 · see citing works
Effects of aging on $$T_{1}$$ T 1 , $$T_{2}^{*}$$ T 2 ∗ , and QSM MRI values in the subcortex
Keuken, M. C., Bazin, P., Backhouse, K., Beekhuizen, S., Himmer, L., Kandola, A. A., Lafeber, J. J., Prochazkova, L., Trutti, A. C., Schäfer, A., et al. (2017) · Brain Structure and Function · doi:10.1007/s00429-016-1352-4 · Cited by 112 · see citing works
Cross-species cortical alignment identifies different types of anatomical reorganization in the primate temporal lobe
Eichert, N., Robinson, E. C., Bryant, K., Jbabdi, S., Jenkinson, M., Li, L., Krug, K., Watkins, K. E., & Mars, R. B. (2020) · eLife · doi:10.7554/elife.53232 · Cited by 110 · see citing works
Relationships between cortical myeloarchitecture and electrophysiological networks
Hunt, B. A. E., Tewarie, P. K. B., Mougin, O. E., Geades, N., Jones, D. K., Singh, K. D., Morris, P. G., Gowland, P. A., & Brookes, M. J. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1608587113 · Cited by 103 · see citing works
White matter myelination during early infancy is linked to spatial gradients and myelin content at birth
Grotheer, M., Rosenke, M., Wu, H., Kular, H., Querdasi, F. R., Natu, V. S., Yeatman, J. D., & Kalanit Grill-spector, A. (2022) · Nature Communications · doi:10.1038/s41467-022-28326-4 · Cited by 114 · see citing works
Development of high‐resolution 3D MR fingerprinting for detection and characterization of epileptic lesions
Ma, D., Jones, S. E., Deshmane, A., Sakaie, K., Pierre, E. Y., Larvie, M., McGivney, D., Blümcke, I., Krishnan, B., Lowe, M. J., et al. (2018) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.26319 · Cited by 106 · see citing works
Integrated and efficient diffusion-relaxometry using ZEBRA
Hutter, J. M., Slator, P. J., Christiaens, D., Teixeira, R. P. A. G., Roberts, T. A., Jackson, L. H., Price, A. N., Malik, S., & Hajnal, J. V. (2018) · Scientific Reports · doi:10.1038/s41598-018-33463-2 · Cited by 98 · see citing works
A subject-specific framework for in vivo myeloarchitectonic analysis using high resolution quantitative MRI
Wähnert, M., Dinse, J., Andreas Schäfer, A., Geyer, S., Bazin, P., Turner, R., & Tardif, C. L. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.10.001 · Cited by 102 · see citing works
Comparing functional MRI protocols for small, iron‐rich basal ganglia nuclei such as the subthalamic nucleus at 7 T and 3 T
de Hollander, G., Keuken, M. C., van der Zwaag, W., Forstmann, B. U., & Trampel, R. (2017) · Human Brain Mapping · doi:10.1002/hbm.23586 · Cited by 101 · see citing works
A general linear relaxometry model of R1 using imaging data
Callaghan, M. F., Helms, G., Lutti, A., Mohammadi, S., & Weiskopf, N. (2014) · Magnetic Resonance in Medicine · doi:10.1002/mrm.25210 · Cited by 100 · see citing works
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An evaluation of prospective motion correction (PMC) for high resolution quantitative MRI
Callaghan, M. F., Josephs, O., Herbst, M., Zaitsev, M., Todd, N., & Weiskopf, N. (2015) · Frontiers in Neuroscience · doi:10.3389/fnins.2015.00097 · Cited by 100 · see citing works
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A new myeloarchitectonic map of the human neocortex based on data from the Vogt–Vogt school
Nieuwenhuys, R., Broere, C. A. J., & Cerliani, L. (2014) · Brain Structure and Function · doi:10.1007/s00429-014-0806-9 · Cited by 99 · see citing works
In-vivo magnetic resonance imaging (MRI) of laminae in the human cortex
Trampel, R., Bazin, P., Pine, K., & Weiskopf, N. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.09.037 · Cited by 98 · see citing works
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Neurobiological origin of spurious brain morphological changes: A quantitative MRI study
Lorio, S., Kherif, F., Ruef, A., Melie‐García, L., Frackowiak, R. S. J., Ashburner, J., Helms, G., Lutti, A., & Draganski, B. (2016) · Human Brain Mapping · doi:10.1002/hbm.23137 · Cited by 96 · see citing works
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Nighres: processing tools for high-resolution neuroimaging
Huntenburg, J. M., Steele, C. J., & Bazin, P. (2018) · GigaScience · doi:10.1093/gigascience/giy082 · Cited by 91 · see citing works
Mapping Human Laryngeal Motor Cortex during Vocalization
Eichert, N., Papp, D., Mars, R. B., & Watkins, K. E. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa182 · Cited by 89 · see citing works
A map of the human neocortex showing the estimated overall myelin content of the individual architectonic areas based on the studies of Adolf Hopf
Nieuwenhuys, R., & Broere, C. A. J. (2016) · Brain Structure and Function · doi:10.1007/s00429-016-1228-7 · Cited by 86 · see citing works
Probing myelin content of the human brain with MRI: A review
Piredda, G. F., Hilbert, T., Thiran, J., & Kober, T. (2020) · Magnetic Resonance in Medicine · doi:10.1002/mrm.28509 · Cited by 84 · see citing works
Quantitative MRI provides markers of intra-, inter-regional, and age-related differences in young adult cortical microstructure
Carey, D., Caprini, F., Allen, M., Lutti, A., Weiskopf, N., Rees, G. E., Callaghan, M. F., & Dick, F. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.11.066 · Cited by 85 · see citing works
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Authors: Lutti, A., Dick, F., Sereno, M. I., & Weiskopf, N.
Affiliations: Wellcome Centre for Human Neuroimaging (GB)
University of London (GB)
Corresponding author: Lutti, Antoine
ORCID: Lutti, Antoine
Dick, Frederic
Sereno, Martin I.
Weiskopf, Nikolaus
Venue: NeuroImage
Publisher: Elsevier BV
Published: 2014-06
Volume: 93
Pages: 176-188
ISSN: 1053-8119 (ISSN-L)
DOI: 10.1016/j.neuroimage.2013.06.005
OpenAlex: W1991534565
Cited by: 346
References: 139
Citations by year: 2026: 20 · 2025: 28 · 2024: 18 · 2023: 26 · 2022: 37 · 2021: 29 · 2020: 27 · 2019: 27 · 2018: 36 · 2017: 38 · 2016: 28 · 2015: 17 · 2014: 11 · 2013: 4
FWCI: 2.84
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: NeuroImage (publishedVersion)
PubMed (publishedVersion)
BIROn (Birkbeck, University of London) (submittedVersion)
UCL Discovery (University College London) (submittedVersion)
IRIS (submittedVersion)
MPG.PuRe (Max Planck Society) (submittedVersion)
SERVAL (Université de Lausanne) (submittedVersion)
Funders: Wellcome Trust (091593)
Topics: Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Keywords: cortical myelination, myeloarchitecture, quantitative MRI, R1 mapping, cortical surface reconstruction, retinotopic map, tonotopic map, functional differentiation, non-invasive brain imaging
MeSH terms: Brain Mapping, Cerebral Cortex, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Myelin Sheath

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Using high-resolution quantitative mapping of R1 as an index of cortical myelination

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