Skip to main content

Joint Representation of Functional and Structural Profiles for Identifying Common and Consistent 3-Hinge Gyral Folding Landmark

  • Conference paper
  • First Online:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 (MICCAI 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14227))

  • 2452 Accesses

Abstract

The 3-hinge is a form of cortical fold, which is the intersection of the three gyri. And it has been proved to be unique anatomically, structurally, and functionally connective patterns. Compared with the normal gyri, the 3-hinge gyri have stronger structural connectivity and participate in more functional networks. Therefore, it is of great significance to further explore the 3-hinge regions, which could give more new insights on the study of mechanism of cortical folding patterns. However, for the large differences in brain across subjects, it is difficult to identify consistent 3-hinge regions across subjects and most previous studies on 3-hinges consistency merely focused on a single mode. In order to study the multi-modal consistency of 3-hinge regions, this paper proposes a joint representation of functional and structural profiles for identifying common and consistent 3-hinges. We use the representation of 3-hinge patterns in the functional network to obtain the functional consistency of 3-hinges cross subjects, then the distance between 3-hinge regions and Dense Individualized and Common Connectivity-Based Cortical Landmarks (DICCCOL) system to obtain the structural consistency. Combining these two sets of stability, 38 functionally and structurally consistent 3-hinge regions were successfully identified cross subjects. These consistent 3-hinge regions based on multi-modal data are more consistent than that merely based on structural data and experimental results elucidate those consistent 3-hinge regions are more correlated with visual function. This work deepens the understanding of the stability of 3-hinge regions and provides a basis for further inter-group analysis of 3-hinge gyral folding.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Deng, F., et al.: A functional model of cortical gyri and sulci. Brain Struct. Funct. 219, 1473–1491 (2014)

    Google Scholar 

  2. Li, K., et al.: Gyral folding pattern analysis via surface profiling. Neuroimage 52, 1202–1214 (2010)

    Article  Google Scholar 

  3. Ge, F., et al.: Denser growing fiber connections induce 3-hinge gyral folding. Cereb. Cortex N. Y. N 1991(28), 1064–1075 (2018)

    Article  Google Scholar 

  4. Li, X., et al.: Commonly preserved and species-specific gyral folding patterns across primate brains. Brain Struct. Funct. 222, 2127–2141 (2017)

    Article  Google Scholar 

  5. Zhang, T., et al.: Cortical 3-hinges could serve as hubs in cortico-cortical connective network. Brain Imaging Behav. 14, 2512–2529 (2020)

    Article  Google Scholar 

  6. Zhang, T., et al.: Identifying Cross-individual Correspondences of 3-hinge Gyri. Med. Image Anal. 63, 101700 (2020)

    Article  Google Scholar 

  7. Zhang, S., et al.: A DICCCOL-based K-nearest landmark detection method for identifying common and consistent 3-hinge gyral folding landmarks. Chaos Solitons Fractals. 158, 112018 (2022)

    Article  Google Scholar 

  8. Van Essen, D.C., Smith, S.M., Barch, D.M., Behrens, T.E.J., Yacoub, E., Ugurbil, K.: WU-Minn HCP Consortium: the WU-Minn human connectome project: an overview. Neuroimage 80, 62–79 (2013)

    Article  Google Scholar 

  9. Woolrich, M.W., et al.: Bayesian analysis of neuroimaging data in FSL. Neuroimage 45, S173-186 (2009)

    Article  Google Scholar 

  10. Jiang, X., et al.: Modeling functional dynamics of cortical gyri and sulci. In: Ourselin, S., Joskowicz, L., Sabuncu, M.R., Unal, G., Wells, W. (eds.) MICCAI 2016. LNCS, vol. 9900, pp. 19–27. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46720-7_3

    Chapter  Google Scholar 

  11. Liu, H., et al.: Elucidating functional differences between cortical gyri and sulci via sparse representation HCP grayordinate fMRI data. Brain Res. 1672, 81–90 (2017)

    Article  Google Scholar 

  12. Lv, J., et al.: Holistic atlases of functional networks and interactions reveal reciprocal organizational architecture of cortical function. IEEE Trans. Biomed. Eng. 62, 1120–1131 (2015)

    Article  Google Scholar 

  13. Zhu, D., et al.: DICCCOL: dense individualized and common connectivity-based cortical landmarks. Cereb. Cortex 23, 786–800 (2013)

    Article  Google Scholar 

  14. Rolls, E.T., Huang, C.-C., Lin, C.-P., Feng, J., Joliot, M.: Automated anatomical labelling atlas 3. Neuroimage 206, 116189 (2020)

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (62006194); High-level researcher start-up projects (06100-23SH0201228); Basic Research Projects of Characteristic Disciplines (G2023WD0146).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Shu Zhang .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Zhang, S., Wang, R., Kang, Y., Yu, S., Hu, H., Zhang, H. (2023). Joint Representation of Functional and Structural Profiles for Identifying Common and Consistent 3-Hinge Gyral Folding Landmark. In: Greenspan, H., et al. Medical Image Computing and Computer Assisted Intervention – MICCAI 2023. MICCAI 2023. Lecture Notes in Computer Science, vol 14227. Springer, Cham. https://doi.org/10.1007/978-3-031-43993-3_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-43993-3_16

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-43992-6

  • Online ISBN: 978-3-031-43993-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics