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Graph Ricci Curvatures Reveal Atypical Functional Connectivity in Autism Spectrum Disorder

Pavithra Elumalai, Yasharth Yadav, Nitin Williams, Emil Saucan, Jürgen Jost, View ORCID ProfileAreejit Samal
doi: https://doi.org/10.1101/2021.11.28.470231
Pavithra Elumalai
1The Institute of Mathematical Sciences (IMSc), Chennai, India
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Yasharth Yadav
1The Institute of Mathematical Sciences (IMSc), Chennai, India
2Indian Institute of Science Education and Research (IISER), Pune, India
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Nitin Williams
3Helsinki Institute of Information Technology, Department of Computer Science, Aalto University, Finland
4Department of Neuroscience & Biomedical Engineering, Aalto University, Finland
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  • For correspondence: nitin.williams@aalto.fi asamal@imsc.res.in
Emil Saucan
5Department of Applied Mathematics, ORT Braude College, Karmiel, Israel
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Jürgen Jost
6Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany
7The Santa Fe Institute, Santa Fe, NM, USA
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Areejit Samal
1The Institute of Mathematical Sciences (IMSc), Chennai, India
8Homi Bhabha National Institute (HBNI), Mumbai, India
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  • ORCID record for Areejit Samal
  • For correspondence: nitin.williams@aalto.fi asamal@imsc.res.in
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SUMMARY

While standard graph-theoretic measures have been widely used to characterize atypical resting-state functional connectivity in autism spectrum disorder (ASD), geometry-inspired network measures have not been applied. In this study, we apply Forman-Ricci and Ollivier-Ricci curvatures to compare networks of ASD and typically developing individuals (N = 1112) from the Autism Brain Imaging Data Exchange I (ABIDE-I) dataset. We find brain-wide and region-specific ASD-related differences for both Forman-Ricci and Ollivier-Ricci curvatures, with region-specific differences concentrated in Default Mode, Somatomotor and Ventral Attention networks for Forman-Ricci curvature. We use meta-analysis decoding to demonstrate that brain regions with curvature differences are associated to those cognitive domains known to be impaired in ASD. Further, we show that brain regions with curvature differences overlap with those brain regions whose non-invasive stimulation improves ASD-related symptoms. These results suggest the utility of graph Ricci curvatures in characterizing atypical connectivity of clinically relevant regions in ASD and other neurodevelopmental disorders.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • ↵$ Lead contact

  • We have revised the title and main text to improve the presentation of results reported in the manuscript.

  • https://github.com/asamallab/Curvature-FCN-ASD

  • https://youtu.be/ch7-dOA-Vlo

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted December 21, 2021.
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Graph Ricci Curvatures Reveal Atypical Functional Connectivity in Autism Spectrum Disorder
Pavithra Elumalai, Yasharth Yadav, Nitin Williams, Emil Saucan, Jürgen Jost, Areejit Samal
bioRxiv 2021.11.28.470231; doi: https://doi.org/10.1101/2021.11.28.470231
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Graph Ricci Curvatures Reveal Atypical Functional Connectivity in Autism Spectrum Disorder
Pavithra Elumalai, Yasharth Yadav, Nitin Williams, Emil Saucan, Jürgen Jost, Areejit Samal
bioRxiv 2021.11.28.470231; doi: https://doi.org/10.1101/2021.11.28.470231

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