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Homological Landscape of Human Brain Functional Sub-Circuits

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  • Duy Duong-Tran

    (Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
    Department of Mathematics, United States Naval Academy, Annapolis, MD 21402, USA
    These authors contributed equally to this work.)

  • Ralph Kaufmann

    (Department of Mathematics, Purdue University, West Lafayette, IN 47907, USA
    These authors contributed equally to this work.)

  • Jiong Chen

    (Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
    Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Pennsylvania, PA 19104, USA
    These authors contributed equally to this work.)

  • Xuan Wang

    (Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA 22030, USA)

  • Sumita Garai

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

  • Frederick H. Xu

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

  • Jingxuan Bao

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

  • Enrico Amico

    (Neuro-X Institute, Swiss Federal Institute of Technology Lausanne, 1015 Geneva, Switzerland
    Department of Radiology and Medical Informatics, University of Geneva, 1211 Geneva, Switzerland)

  • Alan D. Kaplan

    (Computational Engineering Division, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA)

  • Giovanni Petri

    (CENTAI Institute, 10138 Torino, Italy
    NPLab, Network Science Institute, Northeastern University London, London E1W 1LP, UK
    Networks Unit, IMT Lucca Institute, 55100 Lucca, Italy)

  • Joaquin Goni

    (Purdue Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN 47907, USA
    School of Industrial Engineering, Purdue University, West Lafayette, IN 47907, USA
    Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 47907, USA)

  • Yize Zhao

    (School of Public Health, Yale University, New Heaven, CT 06520, USA)

  • Li Shen

    (Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, 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 H 1 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 ( H 0 ), (ii) Motor task ( H 1 ), and (iii) Working memory task ( H 2 ). 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.

Suggested Citation

  • Duy Duong-Tran & Ralph Kaufmann & Jiong Chen & Xuan Wang & Sumita Garai & Frederick H. Xu & Jingxuan Bao & Enrico Amico & Alan D. Kaplan & Giovanni Petri & Joaquin Goni & Yize Zhao & Li Shen, 2024. "Homological Landscape of Human Brain Functional Sub-Circuits," Mathematics, MDPI, vol. 12(3), pages 1-25, January.
  • Handle: RePEc:gam:jmathe:v:12:y:2024:i:3:p:455-:d:1330345
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    References listed on IDEAS

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    3. Richard J. Gardner & Erik Hermansen & Marius Pachitariu & Yoram Burak & Nils A. Baas & Benjamin A. Dunn & May-Britt Moser & Edvard I. Moser, 2022. "Toroidal topology of population activity in grid cells," Nature, Nature, vol. 602(7895), pages 123-128, February.
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