Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/122334
Title: Dominance of metric correlations in two-dimensional neuronal cultures described through a Random Field Ising Model
Author: Hernández Navarro, Lluís
Orlandi, Javier G.
Cerruti, Benedetta
Vives i Santa-Eulàlia, Eduard
Soriano i Fradera, Jordi
Keywords: Model d'Ising
Transformacions de fase (Física estadística)
Ising model
Phase transformations (Statistical physics)
Issue Date: 18-May-2017
Publisher: American Physical Society
Abstract: We introduce a novel random field Ising model, grounded on experimental observations, to assess the importance of metric correlations in cortical circuits in vitro. Metric correlations arise from both the finite axonal length and the heterogeneity in the spatial arrangement of neurons. The experiments consider the response of neuronal cultures to an external electric stimulation for a gradually weaker connectivity strength between neurons, and in cultures with different spatial configurations. The model can be analytically solved in the metric-free, mean-field scenario. The presence of metric correlations precipitates a strong deviation from the mean field. Null models of the same networks that preserve the distribution of connections recover the mean field. Our results show that metric-inherited correlations in spatial networks dominate the connectivity blueprint, mask the actual distribution of connections, and may emerge as the asset that shapes network dynamics.
Note: Reproducció del document publicat a: https://doi.org/10.1103/PhysRevLett.118.208101
It is part of: Physical Review Letters, 2017, vol. 118, num. 20, p. 208101-1-208101-5
URI: http://hdl.handle.net/2445/122334
Related resource: https://doi.org/10.1103/PhysRevLett.118.208101
ISSN: 0031-9007
Appears in Collections:Articles publicats en revistes (Física de la Matèria Condensada)
Articles publicats en revistes (Institut de Recerca en Sistemes Complexos (UBICS))

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