Eleonora Lupi 1, Fulvia Palesi1, Anita Monteverdi2, Marta Gaviraghi1, Carolyn McNabb3, Pedro Luque Laguna3, Eirini Messaritaki3, Ilaria Gabusi4, Alessandro Daducci4, Marco Palombo3,5, Mara Cercignani3, Egidio D’Angelo1,2, Claudia A Gandini Wheeler-Kingshott
1Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
2Digital Neuroscience Centre, IRCCS Mondino Foundation, Pavia, Italy
3Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
4Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy
5School of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom
Presenting Author: Eleonora Lupi
Synopsis
Motivation:
Goals:
Approach:
Results:
Full abstract & presentation
The full text, figures, and any recorded presentation for this abstract are not shown here. Log in if you are a member or registered attendee with access.
Full abstracts, figures, and presentations for Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition are available to registered attendees. This content becomes freely available to the public roughly two years after the meeting.
To request or purchase access, contact the ISMRM Central Office at info@ismrm.org.
1. Sanz Leon P, Knock SA, Woodman MM, et al. The virtual brain: A simulator of primate brain network dynamics. Front Neuroinform. 2013;7(MAY). doi:10.3389/fninf.2013.00010 [doi]
2. Schirner M, Domide L, Perdikis D, et al. Brain Modelling as a Service: The Virtual Brain on EBRAINS. ArXiv preprint. Published online 2021. https://doi.org/10.48550/arXiv.2102.05888. [doi]
3. D’Angelo E, Jirsa V. The quest for multiscale brain modeling. Trends Neurosci. 2022;45(10):777-790. doi:10.1016/j.tins.2022.06.007 [doi]
4. Jbabdi S, Johansen-Berg H. Tractography: Where Do We Go from Here? Brain Connect. 2011;1(3):169-183. doi:10.1089/brain.2011.0033 [doi]
5. Daducci A, Dal Palù A, Lemkaddem A, Thiran JP. COMMIT: Convex optimization modeling for microstructure informed tractography. IEEE Trans Med Imaging. 2015;34(1):246-257. doi:10.1109/TMI.2014.2352414 [doi]
6. Monteverdi A, Palesi F, Costa A, et al. Subject-specific features of excitation/inhibition profiles in neurodegenerative diseases. Front Aging Neurosci. 2022;14. doi:10.3389/fnagi.2022.868342 [doi]
7. Drakesmith M, Harms R, Rudrapatna SU, Parker GD, Evans CJ, Jones DK. Estimating axon conduction velocity in vivo from microstructural MRI. Neuroimage. 2019;203. doi:10.1016/j.neuroimage.2019.116186 [doi]
8. Mancini M, Tian Q, Fan Q, Cercignani M, Huang SY. Dissecting whole-brain conduction delays through MRI microstructural measures. Brain Struct Funct. 2021;226(8):2651-2663. doi:10.1007/s00429-021-02358-w [doi]
9. McNabb CB, Driver ID, Hyde V, et al. WAND: A multi-modal dataset integrating advanced MRI, MEG, and TMS for multi-scale brain analysis. Sci Data. 2025;12(1):220. doi:10.1038/s41597-024-04154-7 [doi]
10. Zhang H, Schneider T, Wheeler-Kingshott CAM, Alexander DC. NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain. Neuroimage. 2012;61(4):1000-1016. doi:10.1016/j.neuroimage.2012.03.072 [doi]
11. Buckner RL, Krienen FM, Castellanos A, Diaz JC, Yeo BTT. The organization of the human cerebellum estimated by intrinsic functional connectivity. J Neurophysiol. 2011;106(5):2322-2345. doi:10.1152/jn.00339.2011 [doi]
12. Thomas Yeo BT, Krienen FM, Sepulcre J, et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J Neurophysiol. 2011;106(3):1125-1165. doi:10.1152/jn.00338.2011 [doi]
13. Smith RE, Tournier JD, Calamante F, Connelly A. Anatomically-constrained tractography: Improved diffusion MRI streamlines tractography through effective use of anatomical information. Neuroimage. 2012;62(3):1924-1938. doi:10.1016/j.neuroimage.2012.06.005 [doi]
14. Tournier JD, Smith R, Raffelt D, et al. MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation. Neuroimage. 2019;202:116137. doi:https://doi.org/10.1016/j.neuroimage.2019.116137 [doi]
15. Gabusi I, Battocchio M, Bosticardo S, Schiavi S, Daducci A. Blurred streamlines: A novel representation to reduce redundancy in tractography. Med Image Anal. 2024;93:103101. doi:https://doi.org/10.1016/j.media.2024.103101 [doi]
16. Bosticardo S, Schiavi S, Schaedelin S, et al. Evaluation of tractography-based myelin-weighted connectivity across the lifespan. Front Neurosci. 2023;17. doi:10.3389/fnins.2023.1228952 [doi]
17. Schiavi S, Lu PJ, Weigel M, et al. Bundle myelin fraction (BMF) mapping of different white matter connections using microstructure informed tractography. Neuroimage. 2022;249. doi:10.1016/j.neuroimage.2022.118922 [doi]
18. Stikov N, Campbell JSW, Stroh T, et al. In vivo histology of the myelin g-ratio with magnetic resonance imaging. Neuroimage. 2015;118:397-405. doi:10.1016/j.neuroimage.2015.05.023 [doi]
19. Cercignani M, Giulietti G, Dowell NG, et al. Characterizing axonal myelination within the healthy population: a tract-by-tract mapping of effects of age and gender on the fiber g-ratio. Neurobiol Aging. 2017;49:109-118. doi:10.1016/j.neurobiolaging.2016.09.016 [doi]
20. Barakovic M, Girard G, Schiavi S, et al. Bundle-Specific Axon Diameter Index as a New Contrast to Differentiate White Matter Tracts. Front Neurosci. 2021;15. doi:10.3389/fnins.2021.646034 [doi]
21. Rushton WAH. A Theory of the Effects of Fibre Size in Medullated Nerve. Journal of Physiology. 1951;115:101-122. https://doi.org/10.1113/jphysiol.1951.sp004655. [doi]
22. Hansen ECA, Battaglia D, Spiegler A, Deco G, Jirsa VK. Functional connectivity dynamics: Modeling the switching behavior of the resting state. Neuroimage. 2015;105:525-535. doi:10.1016/j.neuroimage.2014.11.001 [doi]
23. Deco G, Ponce-Alvarez A, Hagmann P, Romani GL, Mantini D, Corbetta M. How local excitation-inhibition ratio impacts the whole brain dynamics. Journal of Neuroscience. 2014;34(23):7886-7898. doi:10.1523/JNEUROSCI.5068-13.2014 [doi]