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Brain’s Dynamic Functional Organization with Simultaneous EEG-fMRI Networks

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Complex Networks XIV (CompleNet 2023)

Part of the book series: Springer Proceedings in Complexity ((SPCOM))

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Abstract

The brain’s functional networks can be assessed using imaging techniques like functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). Recent studies have suggested a link between the dynamic functional connectivity (dFC) captured by these two modalities, but the exact relationship between their spatiotemporal organization is still unclear. Since these networks are spatially embedded, a question arises whether the topological features captured can be explained exclusively by the spatial constraints. We investigated the global structure of resting-state EEG and fMRI data, including a spatially informed null model and found that fMRI networks are more modular over time, in comparison to EEG, which captured a less clustered topology. This resulted in overall low similarity values. However, when investigating the community structure beyond spatial constraints, this similarity decreased. We show that even though EEG and fMRI functional connectomes are slightly linked, the two modalities essentially capture different information over time, with most but not all topology being explained by the underlying spatial embedding.

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Notes

  1. 1.

    https://github.com/juanitacabral/LEiDA.

  2. 2.

    http://neuroimage.usc.edu/brainstorm.

  3. 3.

    https://github.com/compneuro-da/rsHRF.

  4. 4.

    https://github.com/Yquetzal/spaceCorrectedLouvainDC.

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Acknowledgments

This work was supported by national funds through FCT – Fundação para a Ciência e Tecnologia, under grant UIDB/50021/2020 and UIDP/50009/2020. AST acknowledges support by the FCT through the LASIGE Research Unit, ref. UIDB/00408/2020 and ref. UIDP/ 00408/2020. APF acknowledges support by FCT through ref. UIDB/50021/2020. PF acknowledges support by FCT through LARSyS, ref. UDIP/50009/2020.

Author information

Authors and Affiliations

  1. ISR-Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal

    Francisca Ayres-Ribeiro & Patrícia Figueiredo

  2. INESC-ID and Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal

    Francisca Ayres-Ribeiro & Alexandre P. Francisco

  3. LASIGE, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal

    Francisca Ayres-Ribeiro & Andreia Sofia Teixeira

  4. EEG and Epilepsy Unit, Department of Clinical Neurosciences, University of Geneva, Geneva, Switzerland

    Jonathan Wirsich

  5. Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Universidade de Coimbra, Coimbra, Portugal

    Rodolfo Abreu

  6. Institute for Nuclear Sciences Applied to Health (ICNAS), Universidade de Coimbra, Coimbra, Portugal

    Rodolfo Abreu

  7. Laboratory for Functional and Metabolic Imaging, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

    João Jorge

  8. Swiss Center for Electronics and Microtechnology (CSEM), Systems Division, Neuchâtel, Switzerland

    João Jorge

Authors
  1. Francisca Ayres-Ribeiro
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  2. Jonathan Wirsich
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  3. Rodolfo Abreu
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  4. João Jorge
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  5. Andreia Sofia Teixeira
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  6. Alexandre P. Francisco
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  7. Patrícia Figueiredo
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Corresponding author

Correspondence to Francisca Ayres-Ribeiro .

Editor information

Editors and Affiliations

  1. Faculty of Sciences, University of Lisbon, Lisbon, Portugal

    Andreia Sofia Teixeira

  2. Department of Computer Science, University of Exeter, Exeter, UK

    Federico Botta

  3. Department of Physics, University of Aveiro, Aveiro, Portugal

    José Fernando Mendes

  4. Department of Computer Science, University of Exeter, Exeter, UK

    Ronaldo Menezes

  5. Department of Electrical, Electronic and Computer Engineering, University of Catania, Catania, Italy

    Giuseppe Mangioni

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Ayres-Ribeiro, F. et al. (2023). Brain’s Dynamic Functional Organization with Simultaneous EEG-fMRI Networks. In: Teixeira, A.S., Botta, F., Mendes, J.F., Menezes, R., Mangioni, G. (eds) Complex Networks XIV. CompleNet 2023. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-031-28276-8_1

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