Comparison of brain connectomes using geodesic distance on manifold: A twins study

A. Yamin, M. Dayan, L. Squarcina, P. Brambilla, V. Murino, V. Diwadkar, D. Sona

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

fMRI is a unique non-invasive approach for understanding the functional organization of the human brain, and task-based fMRI promotes identification of functionally relevant brain regions associated with a given task. Here, we use fMRI (using the Poffenberger Paradigm) data collected in mono- and dizygotic twin pairs to propose a novel approach for assessing similarity in functional networks. In particular, we compared network similarity between pairs of twins in task-relevant and task-orthogonal networks. The proposed method measures the similarity between functional networks using a geodesic distance between graph Laplacians. With method we show that networks are more similar in monozygotic twins compared to dizygotic twins. Furthermore, the similarity in monozygotic twins is higher for task-relevant, than task-orthogonal networks.

Original languageEnglish
Title of host publicationISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging
PublisherIEEE Computer Society
Pages1797-1800
Number of pages4
ISBN (Electronic)9781538636411
DOIs
Publication statusPublished - Apr 1 2019
Event16th IEEE International Symposium on Biomedical Imaging, ISBI 2019 - Venice, Italy
Duration: Apr 8 2019Apr 11 2019

Publication series

NameProceedings - International Symposium on Biomedical Imaging
Volume2019-April
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Conference

Conference16th IEEE International Symposium on Biomedical Imaging, ISBI 2019
CountryItaly
CityVenice
Period4/8/194/11/19

Fingerprint

Connectome
Twin Studies
Monozygotic Twins
Dizygotic Twins
Brain
Magnetic Resonance Imaging

Keywords

  • Connectomes
  • Geodesic distance
  • Graph Laplacian
  • Task-based fMRI
  • Twins

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

Cite this

Yamin, A., Dayan, M., Squarcina, L., Brambilla, P., Murino, V., Diwadkar, V., & Sona, D. (2019). Comparison of brain connectomes using geodesic distance on manifold: A twins study. In ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging (pp. 1797-1800). [8759407] (Proceedings - International Symposium on Biomedical Imaging; Vol. 2019-April). IEEE Computer Society. https://doi.org/10.1109/ISBI.2019.8759407

Comparison of brain connectomes using geodesic distance on manifold : A twins study. / Yamin, A.; Dayan, M.; Squarcina, L.; Brambilla, P.; Murino, V.; Diwadkar, V.; Sona, D.

ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging. IEEE Computer Society, 2019. p. 1797-1800 8759407 (Proceedings - International Symposium on Biomedical Imaging; Vol. 2019-April).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Yamin, A, Dayan, M, Squarcina, L, Brambilla, P, Murino, V, Diwadkar, V & Sona, D 2019, Comparison of brain connectomes using geodesic distance on manifold: A twins study. in ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging., 8759407, Proceedings - International Symposium on Biomedical Imaging, vol. 2019-April, IEEE Computer Society, pp. 1797-1800, 16th IEEE International Symposium on Biomedical Imaging, ISBI 2019, Venice, Italy, 4/8/19. https://doi.org/10.1109/ISBI.2019.8759407
Yamin A, Dayan M, Squarcina L, Brambilla P, Murino V, Diwadkar V et al. Comparison of brain connectomes using geodesic distance on manifold: A twins study. In ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging. IEEE Computer Society. 2019. p. 1797-1800. 8759407. (Proceedings - International Symposium on Biomedical Imaging). https://doi.org/10.1109/ISBI.2019.8759407
Yamin, A. ; Dayan, M. ; Squarcina, L. ; Brambilla, P. ; Murino, V. ; Diwadkar, V. ; Sona, D. / Comparison of brain connectomes using geodesic distance on manifold : A twins study. ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging. IEEE Computer Society, 2019. pp. 1797-1800 (Proceedings - International Symposium on Biomedical Imaging).
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