Homological Landscape of Human Brain Functional Sub-Circuits

Author:

Duong-Tran Duy12,Kaufmann Ralph3ORCID,Chen Jiong14ORCID,Wang Xuan5,Garai Sumita1,Xu Frederick H.1,Bao Jingxuan1,Amico Enrico67,Kaplan Alan D.8ORCID,Petri Giovanni91011,Goni Joaquin121314,Zhao Yize15,Shen Li1ORCID

Affiliation:

1. Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA

2. Department of Mathematics, United States Naval Academy, Annapolis, MD 21402, USA

3. Department of Mathematics, Purdue University, West Lafayette, IN 47907, USA

4. Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Pennsylvania, PA 19104, USA

5. Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA 22030, USA

6. Neuro-X Institute, Swiss Federal Institute of Technology Lausanne, 1015 Geneva, Switzerland

7. Department of Radiology and Medical Informatics, University of Geneva, 1211 Geneva, Switzerland

8. Computational Engineering Division, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA

9. CENTAI Institute, 10138 Torino, Italy

10. NPLab, Network Science Institute, Northeastern University London, London E1W 1LP, UK

11. Networks Unit, IMT Lucca Institute, 55100 Lucca, Italy

12. Purdue Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN 47907, USA

13. School of Industrial Engineering, Purdue University, West Lafayette, IN 47907, USA

14. Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 47907, USA

15. School of Public Health, Yale University, New Heaven, CT 06520, USA

Abstract

Human whole-brain functional connectivity networks have been shown to exhibit both local/quasilocal (e.g., a set of functional sub-circuits induced by node or edge attributes) and non-local (e.g., higher-order functional coordination patterns) properties. Nonetheless, the non-local properties of topological strata induced by local/quasilocal functional sub-circuits have yet to be addressed. To that end, we proposed a homological formalism that enables the quantification of higher-order characteristics of human brain functional sub-circuits. Our results indicate that each homological order uniquely unravels diverse, complementary properties of human brain functional sub-circuits. Noticeably, the H1 homological distance between rest and motor task was observed at both the whole-brain and sub-circuit consolidated levels, which suggested the self-similarity property of human brain functional connectivity unraveled by a homological kernel. Furthermore, at the whole-brain level, the rest–task differentiation was found to be most prominent between rest and different tasks at different homological orders: (i) Emotion task (H0), (ii) Motor task (H1), and (iii) Working memory task (H2). At the functional sub-circuit level, the rest–task functional dichotomy of the default mode network is found to be mostly prominent at the first and second homological scaffolds. Also at such scale, we found that the limbic network plays a significant role in homological reconfiguration across both the task and subject domains, which paves the way for subsequent investigations on the complex neuro-physiological role of such network. From a wider perspective, our formalism can be applied, beyond brain connectomics, to study the non-localized coordination patterns of localized structures stretching across complex network fibers.

Funder

National Institutes of Health

National Science Foundation

Office of Naval Research

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

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