M
Mauricio Girardi-Schappo
Researcher at University of São Paulo
Publications - 31
Citations - 314
Mauricio Girardi-Schappo is an academic researcher from University of São Paulo. The author has contributed to research in topics: Phase transition & Directed percolation. The author has an hindex of 9, co-authored 29 publications receiving 199 citations. Previous affiliations of Mauricio Girardi-Schappo include Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto & Montreal Neurological Institute and Hospital.
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Journal ArticleDOI
A brief history of excitable map-based neurons and neural networks
TL;DR: This review gives a short historical account of the excitable maps approach for modeling neurons and neuronal networks and suggests for further work like more efficient maps, compartmental modeling and close dynamical comparison with conductance-based models.
Journal ArticleDOI
Subsampled Directed-Percolation Models Explain Scaling Relations Experimentally Observed in the Brain.
Tawan T. A. Carvalho,Antonio J. Fontenele,Mauricio Girardi-Schappo,Mauricio Girardi-Schappo,Thaís Feliciano,Leandro A. A. Aguiar,Thais P. L. Silva,Nivaldo A. P. de Vasconcelos,Pedro V. Carelli,Mauro Copelli +9 more
TL;DR: In this article, the authors show that subsampling the model and adjusting the time bin used to define avalanches are sufficient ingredients to change the apparent exponents of the critical point.
Journal ArticleDOI
Griffiths phase and long-range correlations in a biologically motivated visual cortex model.
Mauricio Girardi-Schappo,Germano S. Bortolotto,Jheniffer J. Gonsalves,Leonel Teixeira Pinto,M. H. R. Tragtenberg +4 more
TL;DR: An avalanching biologically motivated model of mammals visual cortex is studied and an extended critical-like region – a Griffiths phase – is found characterized by divergent susceptibility and zero order parameter suggesting that critical be-havior may be found in the visual system.
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Critical avalanches and subsampling in map-based neural networks coupled with noisy synapses.
TL;DR: A model of noisy chemical synapse is studied and critical avalanches for the spatiotemporal activity of the neural network are obtained, verifying that networks of functionally excitable neurons with fast synapses present power-law avalanches, due to rebound spiking dynamics.
Journal ArticleDOI
Synaptic balance due to homeostatically self-organized quasicritical dynamics
Mauricio Girardi-Schappo,Ludmila Brochini,Ariadne de Andrade Costa,Tawan T. A. Carvalho,Osame Kinouchi +4 more
TL;DR: This model unifies two different perspectives on cortical spontaneous activity: both critical avalanches and fluctuation-driven AI firing arise from SOqC homeostatic adaptation, and are indeed two sides of the same coin.