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2. Emergence of chaotic resonance controlled by extremely weak feedback signals in neural systems.

Author

Tran, Anh Tu, Nobukawa, Sou, Wagatsuma, Nobuhiko, Inagaki, Keiichiro, Doho, Hirotaka, Yamanishi, Teruya, Nishimura, Haruhiko, Velasco, Saul Diaz Infante, Yilmaz, Ergin, Yao, Yuangen, and Yuan, Guoyong

Subjects
FEEDBACK control systems, STOCHASTIC resonance, FRONTAL lobe, ORBITS (Astronomy), BIOLOGICAL systems
Abstract

Introduction: Chaotic resonance is similar to stochastic resonance, which emerges from chaos as an internal dynamical fluctuation. In chaotic resonance, chaos-chaos intermittency (CCI), in which the chaotic orbits shift between the separated attractor regions, synchronizes with a weak input signal. Chaotic resonance exhibits higher sensitivity than stochastic resonance. However, engineering applications are difficult because adjusting the internal system parameters, especially of biological systems, to induce chaotic resonance from the outside environment is challenging. Moreover, several studies reported abnormal neural activity caused by CCI. Recently, our study proposed that the double-Gaussian-filtered reduced region of orbit (RRO) method (abbreviated as DG-RRO), using external feedback signals to generate chaotic resonance, could control CCI with a lower perturbation strength than the conventional RRO method. Method: This study applied the DG-RRO method to a model which includes excitatory and inhibitory neuron populations in the frontal cortex as typical neural systems with CCI behavior. Results and discussion: Our results reveal that DG-RRO can be applied to neural systems with extremely low perturbation but still maintain robust effectiveness compared to conventional RRO, even in noisy environments. [ABSTRACT FROM AUTHOR]

Published
2024
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7. Bihemispheric Cerebellar Spiking Network Model to Simulate Acute VOR Motor Learning

Author

Inagaki, Keiichiro, Hirata, Yutaka, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Hirose, Akira, editor, Ozawa, Seiichi, editor, Doya, Kenji, editor, Ikeda, Kazushi, editor, Lee, Minho, editor, and Liu, Derong, editor

Published
2016
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12. A Next Generation Modeling Environment PLATO: Platform for Collaborative Brain System Modeling

Author

Usui, Shiro, Inagaki, Keiichiro, Kannon, Takayuki, Kamiyama, Yoshimi, Satoh, Shunji, Kamiji, Nilton L., Hirata, Yutaka, Ishihara, Akito, Shouno, Hayaru, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Leung, Chi Sing, editor, Lee, Minho, editor, and Chan, Jonathan H., editor

Published
2009
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42. Improvement of Simulation Platform for providing reliable and easy use model simulation environment

Author

Hirata Yutaka, Kannon Takayuki, Yamazaki Tadashi, Ikeno Hidetoshi, Usui Shiro, Satoh Shunji, Okumura Yoshihiro, Wagatsuma Hiroaki, Inagaki Keiichiro, Ishihara Akito, and Kamiyama Yoshimi

Subjects
Computer science, business.industry, Embedded system, Biomedical Engineering, Neuroscience (miscellaneous), Model simulation, business, Simulation, Computer Science Applications
Published
2014
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