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Synchronization in Functional Networks of the Human Brain

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Abstract

Understanding the relationship between structural and functional organization represents one of the most important challenges in neuroscience. An increasing amount of studies show that this organization can be better understood by considering the brain as an interactive complex network. This approach has inspired a large number of computational models that combine experimental data with numerical simulations of brain interactions. In this paper, we present a summary of a data-driven computational model of synchronization between distant cortical areas that share a large number of overlapping neighboring (anatomical) connections. Such connections are derived from in vivo measures of brain connectivity using diffusion-weighted magnetic resonance imaging and are additionally informed by the presence of significant resting-state functionally correlated links between the areas involved. The dynamical processes of brain regions are simulated by a combination of coupled oscillator systems and a hemodynamic response model. The coupled oscillatory systems are represented by the Kuramoto phase oscillators, thus modeling phase synchrony between regional activities. The focus of this modeling approach is to characterize topological properties of functional brain correlation related to synchronization of the regional neural activity. The proposed model is able to reproduce remote synchronization between brain regions reaching reasonable agreement with the experimental functional connectivities. We show that the best agreement between model and experimental data is reached for dynamical states that exhibit a balance of synchrony and variations in synchrony providing the integration of activity between distant brain regions.

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Acknowledgements

AV and PH acknowledge support by Deutsche Forschungsgemeinschaft under Grant No. HO4695/3-1 and within the framework of Collaborative Research Center 910. We thank Yasser Iturria-Medina for sharing the DW-MRI data including fiber lengths used in the study. We also thank Jason Bassett for helpful discussions.

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  1. Philipp Hövel and Vesna Vuksanović have contributed equally to this work.

Authors and Affiliations

  1. School of Mathematical Sciences, University College Cork, Cork, T12 XF62, Ireland

    Philipp Hövel

  2. Institute of Theoretical Physics, Technische Universität Berlin, Hardenbergstraße 36, 10623, Berlin, Germany

    Philipp Hövel, Aline Viol, Philipp Loske & Leon Merfort

  3. Bernstein Center for Computational Neuroscience Berlin, Humboldt-Universität zu Berlin, Philippstraße 13, 10115, Berlin, Germany

    Philipp Hövel & Aline Viol

  4. Aberdeen Biomedical Imaging Centre, University of Aberdeen, Lilan Sutton Building, Foresterhill, Aberdeen, AB25 2ZD, UK

    Philipp Loske & Vesna Vuksanović

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  1. Philipp Hövel
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Correspondence to Philipp Hövel.

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Communicated by Paul Newton.

A List of Cortical and Subcortical Regions

A List of Cortical and Subcortical Regions

See Table 1.

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Hövel, P., Viol, A., Loske, P. et al. Synchronization in Functional Networks of the Human Brain. J Nonlinear Sci 30, 2259–2282 (2020). https://doi.org/10.1007/s00332-018-9505-7

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