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The role of chaotic resonance in cerebellar learning
Authors:Isao T Tokuda  Cheol E Han  Kazuyuki Aihara  Mitsuo Kawato  Nicolas Schweighofer
Institution:1. Department of Physics, Lanzhou University of Technology, Lanzhou 730050, China;2. School of Mathematics and Statistics, Shandong Normal University, Ji′nan, 250014, China;3. School of Science, Chongqing University of Posts and Telecommunications, Chongqing 430065, China;1. Yuri Gagarin State Technical University of Saratov, Politechnicheskaya, 77, Saratov 410054, Russia;2. Center for Biomedical Technology, Technical University of Madrid, Campus Montegancedo, Pozuelo de Alarcon, Madrid 28223, Spain;3. Saratov State University, Astrakhanskaya, 83, Saratov 410012, Russia;1. Departamento de Ciencias Exactas y Tecnología, Centro Universitario de los Lagos, Universidad de Guadalajara, Enrique Díaz de León 1144, Colonia Paseos de la Montaña, Lagos de Moreno, Jalisco, Mexico;2. Center for Biomedical Technology, Universidad Politécnica de Madrid, Campus Montegancedo, Pozuelo de Alarcón 28223, Madrid, Spain;3. Innopolis University, Universitetskaya Str. 1, Innopolis 420500, Republic of Tatarstan, Russia
Abstract:According to the cerebellar learning hypothesis, the inferior olive neurons, despite their low firing rates, are thought to transmit high-fidelity error signals to the cerebellar cortex. “Chaotic resonance”, via moderate electrical coupling between inferior olive neurons, has been proposed to realize efficient transmission of the error signal by desynchronizing spiking. Here, we first show that chaotic resonance is a robust phenomenon, as it does not depend upon the details of the inferior olive neuronal model. Second, we show that chaotic resonance enhances learning of a neural controller for fast arm movements. Furthermore, when both coupling and noise are considered simultaneously, we found that chaotic resonance widens the range of noise intensity within which efficient learning can be realized. We suggest that, from an energetic viewpoint, the spiking activity induced by chaos can be more economical than that induced by noise.
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