Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
566-04-006 ISMRM Abstract

Alterations of network volume, topology and dynamics distinguish congenital from slowly progressive cerebellar ataxias

Accepted
Marta Gaviraghi 1, Anita Monteverdi2, Sara Bulgheroni3, Marta Mercati3, Anna Nigri4, Marina Grisoli4, Stefano D’Arrigo3, Claudia A Gandini Wheeler-Kingshott, Claudia Casellato1, Fulvia Palesi1, Egidio D’Angelo1,2
1Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
2Digital Neuroscience Centre, IRCCS Mondino Foundation, Pavia, Italy
3Department of Pediatric Neuroscience, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy
4Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy
Presenting Author: Marta Gaviraghi

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.

Log in

References

1. Bailey J, Oliveri A, Levin E. Childhood Cerebellar Ataxia. J Child Neurol. 2012;27(9):1138-1145. doi:10.1177/0883073812448231 [doi]
2. Krygier M, Mazurkiewicz-Bełdzińska M. Milestones in genetics of cerebellar ataxias. Neurogenetics. 2021;22(4):225-234. doi:10.1007/s10048-021-00656-3 [doi]
3. Schaefer A, Kong R, Gordon EM, et al. Local-Global Parcellation of the Human Cerebral Cortex from Intrinsic Functional Connectivity MRI. Cereb Cortex. 2018;28(9):3095-3114. doi:10.1093/cercor/bhx179 [doi]
4. Patenaude B, Smith SM, Kennedy DN, Jenkinson M. A Bayesian model of shape and appearance for subcortical brain segmentation. Neuroimage. 2011;56(3):907-922. doi:10.1016/j.neuroimage.2011.02.046 [doi]
5. Faber J, Kügler D, Bahrami E, et al. CerebNet: A fast and reliable deep-learning pipeline for detailed cerebellum sub-segmentation. Neuroimage. 2022;264(September):119703. doi:10.1016/j.neuroimage.2022.119703 [doi]
6. Diedrichsen J, Maderwald S, Küper M, et al. Imaging the deep cerebellar nuclei: A probabilistic atlas and normalization procedure. Neuroimage. 2011;54(3):1786-1794. doi:10.1016/j.neuroimage.2010.10.035 [doi]
7. 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]
8. 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]
9. Tournier JD, , F. Calamante and a. C. Improved probabilistic streamlines tractography by 2 nd order integration over fibre orientation distributions. Ismrm. 2010;88(2003):2010.
10. Battaglia D, Boudou T, Hansen ECA, et al. Dynamic Functional Connectivity between order and randomness and its evolution across the human adult lifespan. Neuroimage. 2020;222(February):117156. doi:10.1016/j.neuroimage.2020.117156 [doi]
11. Borgatti SP, Everett MG. Model of core / periphery structures. Soc Networks. 1999;21:375-395.
12. Rubinov M, Sporns O. Complex network measures of brain connectivity: Uses and interpretations. Neuroimage. 2010;52(3):1059-1069. doi:10.1016/j.neuroimage.2009.10.003 [doi]
13. Onnela JP, Saramäki J, Kertész J, Kaski K. Intensity and coherence of motifs in weighted complex networks. Phys Rev E. 2005;71(6):65103. doi:10.1103/PhysRevE.71.065103 [doi]
14. Sanzleon 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]
15. Deco G, Ponce-Alvarez A, Hagmann P, Romani GL, Mantini D, Corbetta M. How local excitation-inhibition ratio impacts the whole brain dynamics. J Neurosci. 2014;34(23):7886-7898. doi:10.1523/JNEUROSCI.5068-13.2014 [doi]
16. Monteverdi A, Palesi F, Schirner M, et al. Virtual brain simulations reveal network-specific parameters in neurodegenerative dementias. Front Aging Neurosci. 2023;15(July):1-15. doi:10.3389/fnagi.2023.1204134 [doi]
17. Kong X, Kong R, Orban C, et al. Sensory-motor cortices shape functional connectivity dynamics in the human brain. Nat Commun. 2021;12(1). doi:10.1038/s41467-021-26704-y [doi]
18. Jollife IT, Cadima J. Principal component analysis: A review and recent developments. Philos Trans R Soc A Math Phys Eng Sci. 2016;374(2065). doi:10.1098/rsta.2015.0202 [doi]
19. Arthur D, Vassilvitskii S. k-means++: The Advantages of Careful Seeding. Published online 2007:1027-1035. doi:10.1145/1283383.1283494 [doi]
20. Tibshirani R, Walther G, Hastie T. Estimating the number of clusters in a data set via the gap statistic. J R Stat Soc Ser B Stat Methodol. 2001;63(2):411-423. doi:10.1111/1467-9868.00293 [doi]

Cite this abstract