Griffiths phases and the stretching of criticality in brain networks

By Paolo Moretti, Miguel Angel Muñoz. Nature Communications, 2013

356 citations recorded by the source corpus.

Hallmarks of criticality, such as power-laws and scale invariance, have been empirically found in cortical-network dynamics and it has been conjectured that operating at criticality entails functional advantages, such as optimal computational capabilities, memory and large dynamical ranges. As critical behaviour requires a high degree of fine tuning to emerge, some type of self-tuning mechanism needs to be invoked. Here we show that, taking into account the complex hierarchical-modular architecture of cortical networks, the singular critical point is replaced by an extended critical-like region that corresponds—in the jargon of statistical mechanics—to a Griffiths phase. Using computational and analytical approaches, we find Griffiths phases in synthetic hierarchical networks and also in empirical brain networks such as the human connectome and that of Caenorhabditis elegans. Stretched critical regions, stemming from structural disorder, yield enhanced functionality in a generic way, facilitating the task of self-organizing, adaptive and evolutionary mechanisms selecting for criticality. Neural interactions taking place in the brain seemingly occur at criticality, but little is known about how this state is achieved. Moretti and Muñoz identify the signatures of so-called Griffiths phases stemming from the hierarchical topology of brain networks, which could point to an explanation.

Subfields: Cognitive Neuroscience, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/ff1feb2dff0b14d0c95a2a81cea4cc9cfa76d1e0

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Citations in the corpus

Colloquium: Criticality and dynamical scaling in living systems (2017, background): “9 Moretti and Muñoz (2013) and Muñoz et al. (2010), Appendix A and in what follows).”
Functional connectivity dynamics: Modeling the switching behavior of the resting state (2015, methodology): “Still, inviting comparison with a Griffiths phase (Moretti and Muñoz, 2013), we can speak of a relatively narrow “critical range” of parameters, in which many bifurcations in cascade lead to the birth and death of a multitude of attractor branches, and result in themost entropic dynamical repertoire”
Criticality in the brain: A synthesis of neurobiology, models and cognition. (2017, background): “However, complex networks may allow critical-like behaviour to occur in a region of parameter space instead of a single point (Moretti and Muñoz, 2013).”
Self-organized criticality as a fundamental property of neural systems (2014, background): “For the brain with its highly hierarchical and modular structure, it is likely that critical points generalize to critical regions (Grifﬁths phases) (Moretti and Muñoz, 2013).”