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Please use this identifier to cite or link to this item: http://hdl.handle.net/10481/32991

Title: Frustrated hierarchical synchronization and emergent complexity in the human connectome network
Authors: Villegas, Pablo
Moretti, Paolo
Muñoz Martínez, Miguel Ángel
Issue Date: 2014
Abstract: The spontaneous emergence of coherent behavior through synchronization plays a key role in neural function, and its anomalies often lie at the basis of pathologies. Here we employ a parsimonious (mesoscopic) approach to study analytically and computationally the synchronization (Kuramoto) dynamics on the actual human-brain connectome network. We elucidate the existence of a so-far-uncovered intermediate phase, placed between the standard synchronous and asynchronous phases, i.e. between order and disorder. This novel phase stems from the hierarchical modular organization of the connectome. Where one would expect a hierarchical synchronization process, we show that the interplay between structural bottlenecks and quenched intrinsic frequency heterogeneities at many different scales, gives rise to frustrated synchronization, metastability, and chimera-like states, resulting in a very rich and complex phenomenology. We uncover the origin of the dynamic freezing behind these features by using spectral graph theory and discuss how the emerging complex synchronization patterns relate to the need for the brain to access –in a robust though flexible way– a large variety of functional attractors and dynamical repertoires without ad hoc fine-tuning to a critical point
Sponsorship: We acknowledge financial support from J. de Andalucía, grant P09-FQM-4682 and we thank O. Sporns for providing us access to the human connectome data.
Publisher: Nature Publishing Group
Keywords: Computational science
Complex networks
URI: http://hdl.handle.net/10481/32991
ISSN: 2045-2322
Rights : Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License
Citation: Villegas, P.; Moretti, P.; Muñoz, M.A. Frustrated hierarchical synchronization and emergent complexity in the human connectome network. Scientific Reports, 4: 5990 (2014). [http://hdl.handle.net/10481/32991]
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