It appears you don't have support to open PDFs in this web browser. To view this file, Open with your PDF reader
Abstract
The scaling of correlations as a function of size provides important hints to understand critical phenomena on a variety of systems. Its study in biological structures offers two challenges: usually they are not of infinite size, and, in the majority of cases, dimensions can not be varied at will. Here we discuss how finite-size scaling can be approximated in an experimental system of fixed and relatively small extent, by computing correlations inside of a reduced field of view of various widths (we will refer to this procedure as “box-scaling”). A relation among the size of the field of view, and measured correlation length, is derived at, and away from, the critical regime. Numerical simulations of a neuronal network, as well as the ferromagnetic 2D Ising model, are used to verify such approximations. Numerical results support the validity of the heuristic approach, which should be useful to characterize relevant aspects of critical phenomena in biological systems.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
Details
1 Universidad Nacional de Gral. San Martín, Instituto de Ciencias Físicas (ICIFI-CONICET), Center for Complex Systems and Brain Sciences (CEMSC3), Escuela de Ciencia y Tecnología, San Martín, Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina (GRID:grid.423606.5) (ISNI:0000 0001 1945 2152)
2 Section on Critical Brain Dynamics, National Institute of Mental Health, National Institutes of Health, Bethesda, USA (GRID:grid.416868.5) (ISNI:0000 0004 0464 0574)
3 Universidad Nacional de Córdoba, Instituto de Física Enrique Gaviola (IFEG-CONICET), Facultad de Matemática Astronomía Física y Computación, Córdoba, Argentina (GRID:grid.10692.3c) (ISNI:0000 0001 0115 2557); Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina (GRID:grid.423606.5) (ISNI:0000 0001 1945 2152)
4 Universidad Nacional de La Plata, Instituto de Física de Líquidos y Sistemas Biológicos (IFLySiB-CONICET), La Plata, Argentina (GRID:grid.9499.d) (ISNI:0000 0001 2097 3940); Universidad Nacional de La Plata, Departamento de Física, Facultad de Ciencias Exactas, La Plata, Argentina (GRID:grid.9499.d) (ISNI:0000 0001 2097 3940); Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina (GRID:grid.423606.5) (ISNI:0000 0001 1945 2152)
5 Universidad Nacional de Gral. San Martín, Instituto de Ciencias Físicas (ICIFI-CONICET), Center for Complex Systems and Brain Sciences (CEMSC3), Escuela de Ciencia y Tecnología, San Martín, Argentina (GRID:grid.416868.5); Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina (GRID:grid.423606.5) (ISNI:0000 0001 1945 2152)