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pro vyhledávání: '"Dante, R"'
We present a mean field solution of the dynamics of a Greenberg-Hastings neural network with both excitatory and inhibitory units. We analyse the dynamical phase transitions that appear in the stationary state as the model parameters are varied. Anal
Externí odkaz:
http://arxiv.org/abs/2312.17645
Autor:
Pawłowska, Agnieszka I., Dąbczyński, Paweł, Lalik, Sebastian, Carbajal, Juan Pablo, Chialvo, Dante R., Rysz, Jakub
The memristive device is one of the basic elements of novel, brain-inspired, fast, and energy-efficient information processing systems in which there is no separation between memorization and information analysis functions. Since the first demonstrat
Externí odkaz:
http://arxiv.org/abs/2305.13466
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-8 (2024)
Abstract It has been repeatedly reported that the collective dynamics of social insects exhibit universal emergent properties similar to other complex systems. In this note, we study a previously published data set in which the positions of thousands
Externí odkaz:
https://doaj.org/article/3a944f7cd80541e784699974a03f37b9
Publikováno v:
Physical Review E 106, 054140 (2022)
While the support for the relevance of critical dynamics to brain function is increasing, there is much less agreement on the exact nature of the advocated critical point. Thus, a considerable number of theoretical efforts are currently concentrated
Externí odkaz:
http://arxiv.org/abs/2207.02320
Microorganisms self-organize in very large communities exhibiting complex fluctuations. Despite recent advances, still the mechanism by which these systems are able to exhibit large variability at the one hand and dynamical robustness on the other, i
Externí odkaz:
http://arxiv.org/abs/2206.12384
Autor:
Moraes, Juliane T., Trejo, Eyisto J. Aguilar, Camargo, Sabrina, Ferreira, Silvio C., Chialvo, Dante R.
Previous work showed that the collective activity of large neuronal networks can be tamed to remain near its critical point by a feedback control that maximizes the temporal correlations of the mean-field fluctuations. Since such correlations behave
Externí odkaz:
http://arxiv.org/abs/2206.10000
Autor:
Camargo, Sabrina, Martin, Daniel A., Trejo, Eyisto J. Aguilar, de Florian, Aylen, Nowak, Maciej A., Cannas, Sergio A., Grigera, Tomas S., Chialvo, Dante R.
Publikováno v:
Phys. Rev. E 108, 034302 (2023)
The advent of novel opto-genetics technology allows the recording of brain activity with a resolution never seen before. The characterisation of these very large data sets offers new challenges as well as unique theory-testing opportunities. Here we
Externí odkaz:
http://arxiv.org/abs/2206.07797
Autor:
Trejo, Eyisto J. Aguilar, Martin, Daniel A., De Zoysa, Dulara, Bowen, Zac, Grigera, Tomas S., Cannas, Sergio A., Losert, Wolfgang, Chialvo, Dante R.
Publikováno v:
Phys. Rev. E 106, 054313. Published 29 November 2022
In this article, a correlation metric $\kappa_C$ is proposed for the inference of the dynamical state of neuronal networks. $\kappa_C$ is computed from the scaling of the correlation length with the size of the observation region, which shows qualita
Externí odkaz:
http://arxiv.org/abs/2205.11341
Autor:
Tiago L. Ribeiro, Peter Jendrichovsky, Shan Yu, Daniel A. Martin, Patrick O. Kanold, Dante R. Chialvo, Dietmar Plenz
Publikováno v:
Cell Reports, Vol 43, Iss 2, Pp 113762- (2024)
Summary: In the mammalian cortex, even simple sensory inputs or movements activate many neurons, with each neuron responding variably to repeated stimuli—a phenomenon known as trial-by-trial variability. Understanding the spatial patterns and dynam
Externí odkaz:
https://doaj.org/article/e074c0ff48d94f838be17916e9d4f481
Already two decades passed since the first applications of graph theory to brain neuroimaging. Since that early description, the characterization of the brain as a very large interacting complex network has evolved in several directions. In this brie
Externí odkaz:
http://arxiv.org/abs/2112.09806