Universal and non-universal neural dynamics on small world connectomes: a finite size scaling analysis
| Autor: | Dante R. Chialvo, Juan Ignacio Perotti, Sergio A. Cannas, Mahdi Zarepour, Orlando V. Billoni |
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| Rok vydání: | 2019 |
| Předmět: |
Physics - Physics and Society
Phase transition FOS: Physical sciences Physics and Society (physics.soc-ph) NEURAL NETWORKS FINITE SIZE SCALING Parameter space 01 natural sciences 010305 fluids & plasmas purl.org/becyt/ford/1 [https] CRITICALITY 0103 physical sciences Statistical physics 010306 general physics Scaling Physics Human Connectome purl.org/becyt/ford/1.3 [https] Disordered Systems and Neural Networks (cond-mat.dis-nn) Condensed Matter - Disordered Systems and Neural Networks Renormalization group Nonlinear Sciences - Adaptation and Self-Organizing Systems SMALL WORLD NETWORKS Percolation Connectome Critical exponent Adaptation and Self-Organizing Systems (nlin.AO) |
| Zdroj: | CONICET Digital (CONICET) Consejo Nacional de Investigaciones Científicas y Técnicas instacron:CONICET |
| DOI: | 10.48550/arxiv.1905.05280 |
| Popis: | Evidence of critical dynamics has been recently found in both experiments and models of large scale brain dynamics. The understanding of the nature and features of such critical regime is hampered by the relatively small size of the available connectome, which prevent among other things to determine its associated universality class. To circumvent that, here we study a neural model defined on a class of small-world network that share some topological features with the human connectome. We found that varying the topological parameters can give rise to a scale-invariant behavior belonging either to mean field percolation universality class or having non universal critical exponents. In addition, we found certain regions of the topological parameters space where the system presents a discontinuous (i.e., non critical) dynamical phase transition into a percolated state. Overall these results shed light on the interplay of dynamical and topological roots of the complex brain dynamics. Comment: 6 pages, 6 figures |
| Databáze: | OpenAIRE |
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