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Cellular automata and artificial brain dynamics

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Cellular automata and artificial brain dynamics

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dc.contributor.author Fraile, Alberto es_ES
dc.contributor.author Panagiotakis, E. es_ES
dc.contributor.author Christakis, N. es_ES
dc.contributor.author Acedo Rodríguez, Luis es_ES
dc.date.accessioned 2020-04-24T07:14:31Z
dc.date.available 2020-04-24T07:14:31Z
dc.date.issued 2018 es_ES
dc.identifier.uri http://hdl.handle.net/10251/141463
dc.description.abstract [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. es_ES
dc.description.sponsorship 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. es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Mathematical and Computational Applications (Online) es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Cellular automata es_ES
dc.subject Game of life es_ES
dc.subject Brain dynamics es_ES
dc.title Cellular automata and artificial brain dynamics es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/mca23040075 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/316165/EU/Crete Center for Quantum Complexity and Nanotechnology/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GACR//17-17921S/ es_ES
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation 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 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/mca23040075 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 23 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 23 es_ES
dc.description.issue 4 es_ES
dc.identifier.eissn 2297-8747 es_ES
dc.relation.pasarela S\383881 es_ES
dc.contributor.funder Czech Science Foundation es_ES
dc.description.references TURING, A. M. (1950). I.—COMPUTING MACHINERY AND INTELLIGENCE. Mind, LIX(236), 433-460. doi:10.1093/mind/lix.236.433 es_ES
dc.description.references Sarkar, P. (2000). A brief history of cellular automata. ACM Computing Surveys, 32(1), 80-107. doi:10.1145/349194.349202 es_ES
dc.description.references Ermentrout, G. B., & Edelstein-Keshet, L. (1993). Cellular Automata Approaches to Biological Modeling. Journal of Theoretical Biology, 160(1), 97-133. doi:10.1006/jtbi.1993.1007 es_ES
dc.description.references Boccara, N., Roblin, O., & Roger, M. (1994). Automata network predator-prey model with pursuit and evasion. Physical Review E, 50(6), 4531-4541. doi:10.1103/physreve.50.4531 es_ES
dc.description.references Gerhardt, M., & Schuster, H. (1989). A cellular automaton describing the formation of spatially ordered structures in chemical systems. Physica D: Nonlinear Phenomena, 36(3), 209-221. doi:10.1016/0167-2789(89)90081-x es_ES
dc.description.references Zhu, M. F., Lee, S. Y., & Hong, C. P. (2004). Modified cellular automaton model for the prediction of dendritic growth with melt convection. Physical Review E, 69(6). doi:10.1103/physreve.69.061610 es_ES
dc.description.references KANSAL, A. R., TORQUATO, S., HARSH, G. R., CHIOCCA, E. A., & DEISBOECK, T. S. (2000). Simulated Brain Tumor Growth Dynamics Using a Three-Dimensional Cellular Automaton. Journal of Theoretical Biology, 203(4), 367-382. doi:10.1006/jtbi.2000.2000 es_ES
dc.description.references Hopfield, J. J. (1982). Neural networks and physical systems with emergent collective computational abilities. Proceedings of the National Academy of Sciences, 79(8), 2554-2558. doi:10.1073/pnas.79.8.2554 es_ES
dc.description.references TSOUTSOURAS, V., SIRAKOULIS, G. C., PAVLOS, G. P., & ILIOPOULOS, A. C. (2012). SIMULATION OF HEALTHY AND EPILEPTIFORM BRAIN ACTIVITY USING CELLULAR AUTOMATA. International Journal of Bifurcation and Chaos, 22(09), 1250229. doi:10.1142/s021812741250229x es_ES
dc.description.references Acedo, L., Lamprianidou, E., Moraño, J.-A., Villanueva-Oller, J., & Villanueva, R.-J. (2015). Firing patterns in a random network cellular automata model of the brain. Physica A: Statistical Mechanics and its Applications, 435, 111-119. doi:10.1016/j.physa.2015.05.017 es_ES
dc.description.references Chialvo, D. R. (2010). Emergent complex neural dynamics. Nature Physics, 6(10), 744-750. doi:10.1038/nphys1803 es_ES
dc.description.references Priesemann, V. (2014). Spike avalanches in vivo suggest a driven, slightly subcritical brain state. Frontiers in Systems Neuroscience, 8. doi:10.3389/fnsys.2014.00108 es_ES
dc.description.references Langton, C. G. (1990). Computation at the edge of chaos: Phase transitions and emergent computation. Physica D: Nonlinear Phenomena, 42(1-3), 12-37. doi:10.1016/0167-2789(90)90064-v es_ES
dc.description.references Friedman, N., Ito, S., Brinkman, B. A. W., Shimono, M., DeVille, R. E. L., Dahmen, K. A., … Butler, T. C. (2012). Universal Critical Dynamics in High Resolution Neuronal Avalanche Data. Physical Review Letters, 108(20). doi:10.1103/physrevlett.108.208102 es_ES
dc.description.references Kello, C. T. (2013). Critical branching neural networks. Psychological Review, 120(1), 230-254. doi:10.1037/a0030970 es_ES
dc.description.references Werner, G. (2007). Metastability, criticality and phase transitions in brain and its models. Biosystems, 90(2), 496-508. doi:10.1016/j.biosystems.2006.12.001 es_ES
dc.description.references Bak, P., Chen, K., & Creutz, M. (1989). Self-organized criticality in the ’Game of Life". Nature, 342(6251), 780-782. doi:10.1038/342780a0 es_ES
dc.description.references Hemmingsson, J. (1995). Consistent results on ‘Life’. Physica D: Nonlinear Phenomena, 80(1-2), 151-153. doi:10.1016/0167-2789(95)90071-3 es_ES
dc.description.references Nordfalk, J., & Alstrøm, P. (1996). Phase transitions near the «game of Life». Physical Review E, 54(2), R1025-R1028. doi:10.1103/physreve.54.r1025 es_ES
dc.description.references Ninagawa, S., Yoneda, M., & Hirose, S. (1998). 1ƒ fluctuation in the «Game of Life». Physica D: Nonlinear Phenomena, 118(1-2), 49-52. doi:10.1016/s0167-2789(98)00025-6 es_ES
dc.description.references Allegrini, P., Menicucci, D., Bedini, R., Fronzoni, L., Gemignani, A., Grigolini, P., … Paradisi, P. (2009). Spontaneous brain activity as a source of ideal1/fnoise. Physical Review E, 80(6). doi:10.1103/physreve.80.061914 es_ES
dc.description.references Fox, M. D., & Raichle, M. E. (2007). Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nature Reviews Neuroscience, 8(9), 700-711. doi:10.1038/nrn2201 es_ES
dc.description.references Linkenkaer-Hansen, K., Nikouline, V. V., Palva, J. M., & Ilmoniemi, R. J. (2001). Long-Range Temporal Correlations and Scaling Behavior in Human Brain Oscillations. The Journal of Neuroscience, 21(4), 1370-1377. doi:10.1523/jneurosci.21-04-01370.2001 es_ES
dc.description.references Gilden, D., Thornton, T., & Mallon, M. (1995). 1/f noise in human cognition. Science, 267(5205), 1837-1839. doi:10.1126/science.7892611 es_ES
dc.description.references Bédard, C., Kröger, H., & Destexhe, A. (2006). Does the1/fFrequency Scaling of Brain Signals Reflect Self-Organized Critical States? Physical Review Letters, 97(11). doi:10.1103/physrevlett.97.118102 es_ES
dc.description.references Wolfram, S. (1983). Statistical mechanics of cellular automata. Reviews of Modern Physics, 55(3), 601-644. doi:10.1103/revmodphys.55.601 es_ES
dc.description.references “Life Universal Computer”http://www.igblan.free-online.co.uk/igblan/ca/ es_ES
dc.description.references Bagnoli, F., Rechtman, R., & Ruffo, S. (1991). Some facts of life. Physica A: Statistical Mechanics and its Applications, 171(2), 249-264. doi:10.1016/0378-4371(91)90277-j es_ES
dc.description.references Garcia, J. B. C., Gomes, M. A. F., Jyh, T. I., Ren, T. I., & Sales, T. R. M. (1993). Nonlinear dynamics of the cellular-automaton ‘‘game of Life’’. Physical Review E, 48(5), 3345-3351. doi:10.1103/physreve.48.3345 es_ES
dc.description.references Huang, S.-Y., Zou, X.-W., Tan, Z.-J., & Jin, Z.-Z. (2003). Network-induced nonequilibrium phase transition in the «game of Life». Physical Review E, 67(2). doi:10.1103/physreve.67.026107 es_ES
dc.description.references Blok, H. J., & Bergersen, B. (1999). Synchronous versus asynchronous updating in the «game of Life». Physical Review E, 59(4), 3876-3879. doi:10.1103/physreve.59.3876 es_ES
dc.description.references Schönfisch, B., & de Roos, A. (1999). Synchronous and asynchronous updating in cellular automata. Biosystems, 51(3), 123-143. doi:10.1016/s0303-2647(99)00025-8 es_ES
dc.description.references Reia, S. M., & Kinouchi, O. (2014). Conway’s game of life is a near-critical metastable state in the multiverse of cellular automata. Physical Review E, 89(5). doi:10.1103/physreve.89.052123 es_ES
dc.description.references De la Torre, A. C., & Mártin, H. O. (1997). A survey of cellular automata like the «game of life». Physica A: Statistical Mechanics and its Applications, 240(3-4), 560-570. doi:10.1016/s0378-4371(97)00046-0 es_ES
dc.description.references Beer, R. D. (2004). Autopoiesis and Cognition in the Game of Life. Artificial Life, 10(3), 309-326. doi:10.1162/1064546041255539 es_ES
dc.description.references Beer, R. D. (2014). The Cognitive Domain of a Glider in the Game of Life. Artificial Life, 20(2), 183-206. doi:10.1162/artl_a_00125 es_ES
dc.description.references Yuste, S. B., & Acedo, L. (2000). Number of distinct sites visited byNrandom walkers on a Euclidean lattice. Physical Review E, 61(3), 2340-2347. doi:10.1103/physreve.61.2340 es_ES
dc.description.references Lachaux, J.-P., Pezard, L., Garnero, L., Pelte, C., Renault, B., Varela, F. J., & Martinerie, J. (1997). Spatial extension of brain activity fools the single-channel reconstruction of EEG dynamics. Human Brain Mapping, 5(1), 26-47. doi:10.1002/(sici)1097-0193(1997)5:1<26::aid-hbm4>3.0.co;2-p es_ES
dc.description.references McDowell, J. E., Kissler, J. M., Berg, P., Dyckman, K. A., Gao, Y., Rockstroh, B., & Clementz, B. A. (2005). Electroencephalography/magnetoencephalography study of cortical activities preceding prosaccades and antisaccades. NeuroReport, 16(7), 663-668. doi:10.1097/00001756-200505120-00002 es_ES
dc.description.references Holsheimer, J., & Feenstra, B. W. . (1977). Volume conduction and EEG measurements within the brain: A quantitative approach to the influence of electrical spread on the linear relationship of activity measured at different locations. Electroencephalography and Clinical Neurophysiology, 43(1), 52-58. doi:10.1016/0013-4694(77)90194-8 es_ES
dc.description.references Hodgkin, A. L., & Huxley, A. F. (1952). A quantitative description of membrane current and its application to conduction and excitation in nerve. The Journal of Physiology, 117(4), 500-544. doi:10.1113/jphysiol.1952.sp004764 es_ES
dc.description.references Porooshani, H., Porooshani, A. H., Gannon, L., & Kyle, G. M. (2004). Speed of progression of migrainous visual aura measured by sequential field assessment. Neuro-Ophthalmology, 28(2), 101-105. doi:10.1076/noph.28.2.101.23739 es_ES
dc.description.references Hutsler, J. J. (2003). The specialized structure of human language cortex: Pyramidal cell size asymmetries within auditory and language-associated regions of the temporal lobes. Brain and Language, 86(2), 226-242. doi:10.1016/s0093-934x(02)00531-x es_ES
dc.description.references Wilson, H. R., & Cowan, J. D. (1972). Excitatory and Inhibitory Interactions in Localized Populations of Model Neurons. Biophysical Journal, 12(1), 1-24. doi:10.1016/s0006-3495(72)86068-5 es_ES
dc.description.references Conway’s Game of Life. Examples of patternshttps://en.wikipedia.org/wiki/Conway%27s_Game_of_Life#Examples_of_patterns es_ES
dc.description.references Gardner, M. (1970). Mathematical Games. Scientific American, 223(4), 120-123. doi:10.1038/scientificamerican1070-120 es_ES
dc.description.references Packard, N. H., & Wolfram, S. (1985). Two-dimensional cellular automata. Journal of Statistical Physics, 38(5-6), 901-946. doi:10.1007/bf01010423 es_ES
dc.description.references Nunomura, A., Perry, G., Aliev, G., Hirai, K., Takeda, A., Balraj, E. K., … Smith, M. A. (2001). Oxidative Damage Is the Earliest Event in Alzheimer Disease. Journal of Neuropathology & Experimental Neurology, 60(8), 759-767. doi:10.1093/jnen/60.8.759 es_ES
dc.description.references Kitamura, T., Ogawa, S. K., Roy, D. S., Okuyama, T., Morrissey, M. D., Smith, L. M., … Tonegawa, S. (2017). Engrams and circuits crucial for systems consolidation of a memory. Science, 356(6333), 73-78. doi:10.1126/science.aam6808 es_ES
dc.description.references Anderson, P. W. (1972). More Is Different. Science, 177(4047), 393-396. doi:10.1126/science.177.4047.393 es_ES


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