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*Neuroscience and Biological Information Processing [#md796902] We have theoretically studied neural network models [1-3] and developed new methods to analyze real data of neuronal spikes [4-6] for understanding information processing and various behaviors in living systems. We are also collaborating with other laboratories performing experiments on nervous activities [7]. Moreover, we are constructing a basic methodology for realizing a novel computation device by using information processing schemes of living systems [8]. + Y. Kakimoto and K. Aihara, New Math. and Natural Comput., Vol.5, No. 1, pp.123-134 (2009). + T. Kanamaru and K. Aihara, Neural Comput., Vol.22, No.5, pp.1383-1398 (2009). + S. Kubota, K. Hamaguchi, and K. Aihara, Neural Computing and Applications, Vol.18, No.6, pp.591-602 (2009). + K. Fujiwara and K. Aihara, J. Artificial Life and Robotics, Vol.13, No.2, pp.470-473 (2009). + K. Fujiwara and K. Aihara, European Phys. J. B, Vol.68, No.2, pp.283-289 (2009). + Y. Hirata and K. Aihara, J. Neurosci. Methods, Vol.183, No.2, pp.277-286 (2009). + H. Mushiake, K. Sakamoto, N. Saito, T. Inui, and K. Aihara, Int. Review of Neurobiology, Vol.85, pp.1-11 (2009). + H. Tanaka, T. Morie, and K. Aihara, IEICE Trans. Fund. Electron. Comm. Comput. Sci., Vol.E92-A, No.7, pp.1096-1098 (2009). *Complex Systems Mathematical Modeling [#o5308a2b] *Nonlinear Dynamical Systems and its Applications [#c84d3134] The aim of our research on nonlinear science is to understand the essence of complex behaviors through mathematical modelling and analyses of nonlinear systems. The topics of our research include coupled oscillators [1,2], game theory [3,4], complex networks [5], recurrence plots [6], and hybrid dynamical systems [7]. We are also trying to develop a new method to address determinism and nonlinearity of real systems and applying them to data analysis of wind profile [8], gray-scale image restoration [9], pattern analysis of partial discharges, and economic data analysis. + I. Nishikawa, N. Tsukamoto, and K. Aihara, Physica D, Vol.238, pp.1197-1202 (2009). + Y. Hirata, M. Aono, and K. Aihara, Chaos, Vol.20, 013117 (2010). + B. Wang, Y. Han, L. Chen, and K. Aihara, Phys. Lett. A, Vol.373, pp.1519-1523 (2009). + K. Hashimoto and K. Aihara, J. Theor. Biol., Vol.258, pp.637-645 (2009). + H. Fan, Z. Wang, L. Chen, and K. Aihara, Phys. Rev. E, Vol.79, 026107 (2009). + Y. Hirata and K. Aihara, Phys. Rev. E, Vol.81, 016203 (2009). + G. Tanaka, S. Tsuji, and K. Aihara, Phys. Lett. A, Vol.373, pp.3134-3139 (2009). + D. Mandic, S. Javidi, A. Kuh, and K. Aihara, Renewable Energy, Vol.34, No.1, pp.196-201 (2009). + G. Tanaka and K. Aihara, IEEE Trans, Neural Networks, Vol.20, No.9, pp.1463-1473 (2009). We study a variety of complex systems and problems―biological systems, social systems, economic systems, diseases, energy problems, natural disasters, and so on―through mathematical modeling and data analyses. We also try to establish fundamental theories and methods for analyzing those specific systems. We aim at further development of researches based on the joint works with the Collaborative Research Center for Innovative Mathematical Modelling. *Mathematical Modeling of Biochemical Systems [#t4a56ead] We have constructed mathematical models and developed methods for analyzing experimental images and data to understand quantitative features of cell development and differentiation. We have clarified mechanisms and roles of stochastic fluctuations in cell systems [1,2] and elucidated the mechanism of circadian rhythms related to jet lag syncrome [3]. Moreover, we perform theoretical studies on oscillations signal transductions in biomolecular networks [4-7]. + H. Tozaki, T. J. Kobayashi, et al., FEBS Letter, Vol.582, No.7, pp.1067-1072 (2008). + H. Okano, T. J Kobayashi, et al., Biophys. J., Vol.95, pp.1063-1074 (2008). + H. Ukai, T. J. Kobayashi, et al., Nature Cell Biology, Vol.9, No.11, pp.1327—1334 (2007). + R. Wang, C. Li, L. Chen, and K. Aihara, Proc. IEEE, Vol.96, No.8, pp.1361-1385 (2008). + X.-M. Zhao, R.-S. Wang, L. Chen, and K. Aihara, Nucleic Acids Res., Vol.36, No.9, e48 (2008). + X.-M. Zhao, R.-S. Wang, L. Chen, and K. Aihara, Journal of Bioinformatics and Computational Biology, Vol.7, No.2, pp.309-322 (2009). +L. Chen, R. Wang, C. Li, and K. Aihara, [[Modeling Biomolecular Networks in Cells: Structures and Dynamics>../../発表文献/書籍リスト/Modeling Biomolecular Networks in Cells]], Springer (2010). *Mathematical Modeling of Diseases [#kb74e6ec] We have been studied mathematical modeling of diseases that should be addressed emergently. Especially, we aim at understanding the essential mechanism and the origin of a disease and proposing a possible effective approach to avoid or treat the disease. We have constructed mathematical models of prostate cancer and discussed the efficacy of intermittent hormone therapy compared with conventional continuous one [1-6]. We have also developed mathematical methods to predict clinical time series data of the biomarker [7] and optimize the schedule of treatments [8] towards practical applications. Infectious diseases like pandemic flu are the other major topic of our research, for which we have approached with mathematical model analyses [9] and large-scale simulations based on individual-based-models by using person trip data. + A. Ideta, G. Tanaka, T. Takeuchi, and K. Aihara, J. Nonlinear Sci. Vol.18, No.6, 593-614 (2008). + G. Tanaka, K. Tsumoto, S. Tsuji, and K. Aihara, Physica D , Vol.237, No.20, 2616-2627 (2008). + N. Shimada and K. Aihara, Math. Biosci. Vol.214, No.1/2, 134-139 (2008). + Q. Guo, Y. Tao, and K. Aihara, Int. J. Bifur. Chaos, Vol.18, No.12, 3789-3797 (2008). + Y. Tao, Q. Guo, and K. Aihara, J. Nonl. Sci., Vol.20, No.2, pp.219-240 (2010). + G. Tanaka, Y. Hirata, N. Bruchovsky, S. Goldenberg, and K. Aihara, Phil. Trans. R. Soc. A, Vol.368, pp.5029-5044 (2010). + Y. Hirata, N. Bruchovsky, and K. Aihara, J. Theor. Biol., Vol.264, No.2, pp.517-527 (2010). + T. Suzuki, N. Bruchovsky, and K. Aihara, Phil. Trans. R. Soc. A, Vol.368, pp.5045-5059 (2010). + B. Wang, K. Aihara, and B. J. Kim, Phys. Lett. A, Vol.373, pp.3877-3882 (2009). *Dynamics of Neural Networks and Its Applications [#ya44fbb1] We are trying to clarify the mechanism of real neural networks and to reveal the high-order functions of the brain through developing mathematical models of neurons/neural networks and identifying underlying non-trivial mathematical structure. As an application, we are also developing analog silicon neural networks and AI. #ref(数理生命情報学研究室/ 研究紹介/chaos_neurocomputer.jpg,,50%); -Recent publications --T. Sase, Y. Katori, M. Komuro, and K. Aihara: Front. Comp. Neurosci., Vol. 11, Article 18 (2017). --Y. Li, M. Oku, G. He, and K. Aihara: Neural Netw., Vol. 88, pp. 9-21 (2017). --T. Nanami and T. Kohno: Front. Neurosci., Vol. 10, Article No. 181 (2016). --C. I. Tajima, S. Tajima, K. Koida, H. Komatsu, K. Aihara, and H. Suzuki: Sci. Rep., Vol. 6, Article No. 22536 (2016). --T. Kiwaki and K. Aihara: Artif. Intell. Res., Vol. 4, No. 1, 53 (2015). --T. Leleu, K. Aihara: Phys. Rev. E, Vol. 91, 022804 (2015). *Nonlinear Systems Analysis and Its Applications to the Real World Systems [#i4e9d478] We are studying chaos and many other complex phenomena in the world that have some regularity behind the complexity, by using nonlinear dynamical systems theory. We focus on the "nonlinearity" of the target systems, develop mathematical models that can reproduce the complex phenomena, and analyze the models to reveal the essential factors. Topics include: synchronization of coupled oscillators, forecast of renewable energy generation, analysis of economic and seismic data, etc. #ref(数理生命情報学研究室/ 研究紹介/chaosNN_simulation.jpg,,100%) -Recent publications --T. Omi, Y. Hirata, and K. Aihara: Phys. Rev. E, Vol. 96, 012303 (2017). --K. Kamiyama, M. Komuro, and K. Aihara: IJBC, Vol. 27, No. 3, 1730012 (2017). --T. Yuan, K. Aihara, and G. Tanaka: Phys. Rev. E, Vol. 95, No. 1, 012315 (2017). --M. Chayama, and Y. Hirata: Phys. Lett. A, Vol. 380, pp. 2359-2365 (2016). --M. Fukino, Y. Hirata, and K. Aihara: Chaos, Vol. 26, No. 2, 023116 (2016). --T. Sase, J. Peña Ramírez, K. Kitajo, K. Aihara, and Y. Hirata: Phys. Lett. A, Vol. 380, pp. 1151-1163 (2016). --L. Speidel, R. Lambiotte, K. Aihara, N. Masuda: Phys. Rev. E, Vol. 91, 012806 (2015). *Quantum Artificial Brain and Combinatorial Optimization [#xc3f1488] We are mathematically studying a new paradigm of computation—quantum artificial brain—based on neural information processing and optical quantum computing. It aims for solving problems that are difficult for conventional computers such as combinatorial optimization problems in a rapid and accurate manner, which may contribute to resolve many social issues. -Recent publications --T. Inagaki, Y. Haribara, K. Igarashi, T. Sonobe, S. Tamate, T. Honjo, A. Marandi, P.L. McMahon, T. Umeki, K. Enbutsu, O. Tadanaga, H. Takenouchi, K. Aihara, K. Kawarabayashi, K. Inoue, S. Utsunomiya, and H. Takesue, Science, Vol. 354, No. 6312, pp. 603-606 (2016). --P.L. McMahon, A. Marandi, Y. Haribara, R. Hamerly, C. Langrock, S. Tamate, T. Inagaki, H. Takesue, S. Utsunomiya, K. Aihara, R.L. Byer, M.M. Fejer, H. Mabuchi, and Y. Yamamoto, Science, Vol. 354, No.6312, pp.614-617 (2016). --H. Sakaguchi, K. Ogata, T. Isomura, S. Utsunomiya, Y. Yamamoto, and K. Aihara, Entropy, Vol. 18, No. 10, 365 (2016). --Y. Haribara, S. Utsunomiya, and Y. Yamamoto: Entropy, Vol. 18, No. 4, 151 (2016).