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[EN] Brain dynamics, neuron activity, information transfer in brains, etc., are a vast field where a large number of questions remain unsolved. Nowadays, computer simulation is playing a key role in the study of such an immense variety of problems. In this work, we explored the possibility of studying brain dynamics using cellular automata, more precisely the famous Game of Life (GoL). The model has some important features (i.e., pseudo-criticality, 1/f noise, universal computing), which represent good reasons for its use in brain dynamics modelling. We have also considered that the model maintains sufficient flexibility. For instance, the timestep is arbitrary, as are the spatial dimensions. As first steps in our study, we used the GoL to simulate the evolution of several neurons (i.e., a statistically significant set, typically a million neurons) and their interactions with the surrounding ones, as well as signal transfer in some simple scenarios. The way that signals (or life) propagate across the grid was described, along with a discussion on how this model could be compared with brain dynamics. Further work and variations of the model were also examined. ; This work was partially supported by the European Union's Seventh Framework Programme (FP7-REGPOT-2012-2013-1) under grant agreement no 316165. This work was done with the support of the Czech Science Foundation, project 17-17921S. ; Fraile, A.; Panagiotakis, E.; Christakis, N.; Acedo Rodríguez, L. (2018). Cellular automata and artificial brain dynamics. Mathematical and Computational Applications (Online). 23(4):1-23. https://doi.org/10.3390/mca23040075 ; S ; 1 ; 23 ; 23 ; 4 ; TURING, A. M. (1950). I.—COMPUTING MACHINERY AND INTELLIGENCE. Mind, LIX(236), 433-460. doi:10.1093/mind/lix.236.433 ; Sarkar, P. (2000). A brief history of cellular automata. ACM Computing Surveys, 32(1), 80-107. doi:10.1145/349194.349202 ; Ermentrout, G. B., & Edelstein-Keshet, L. (1993). Cellular Automata Approaches to Biological Modeling. Journal of Theoretical Biology, ...

1 23 4 ; S ; [EN] Brain dynamics, neuron activity, information transfer in brains, etc., are a vast field where a large number of questions remain unsolved. Nowadays, computer simulation is playing a key role in the study of such an immense variety of problems. In this work, we explored the possibility of studying brain dynamics using cellular automata, more precisely the famous Game of Life (GoL). The model has some important features (i.e., pseudo-criticality, 1/f noise, universal computing), which represent good reasons for its use in brain dynamics modelling. We have also considered that the model maintains sufficient flexibility. For instance, the timestep is arbitrary, as are the spatial dimensions. As first steps in our study, we used the GoL to simulate the evolution of several neurons (i.e., a statistically significant set, typically a million neurons) and their interactions with the surrounding ones, as well as signal transfer in some simple scenarios. The way that signals (or life) propagate across the grid was described, along with a discussion on how this model could be compared with brain dynamics. Further work and variations of the model were also examined. This work was partially supported by the European Union's Seventh Framework Programme (FP7-REGPOT-2012-2013-1) under grant agreement no 316165. This work was done with the support of the Czech Science Foundation, project 17-17921S. Fraile, A.; Panagiotakis, E.; Christakis, N.; Acedo Rodríguez, L. (2018). Cellular automata and artificial brain dynamics. Mathematical and Computational Applications (Online). 23(4):1-23. https://doi.org/10.3390/mca23040075 TURING, A. M. (1950). I.—COMPUTING MACHINERY AND INTELLIGENCE. Mind, LIX(236), 433-460. doi:10.1093/mind/lix.236.433 Sarkar, P. (2000). A brief history of cellular automata. ACM Computing Surveys, 32(1), 80-107. doi:10.1145/349194.349202 Ermentrout, G. B., & Edelstein-Keshet, L. (1993). Cellular Automata Approaches to Biological Modeling. Journal of Theoretical Biology, 160(1), 97-133. ...