混沌神经网络与CPG的作用机制
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摘要
大脑皮层是一个具有混沌特性的非线性系统,中枢模式发生器可产生节律性运动.依据生物学经验,中枢模式发生器受大脑皮层控制,但两者作用机制的研究对于生物运动控制仍是一个开放性问题.文中建立了混沌神经网络与中枢模式发生器相互作用的模型和状态方程,通过分岔变化对模型的动态特性进行分析,说明混沌神经网络与中枢模式发生器间的相互工作机制,以及中枢模式发生器参数对模型的影响.同时,提出了大脑皮层有许多稳定点模式与步态模式相对应,大脑皮层模式的改变可控制步态模式的改变.研究结果表明,可通过调整大脑皮层自身外部输入和中枢模式发生器反馈回大脑皮层的值,来改变大脑皮层模式.
The cerebral cortex is a chaotic nonlinear system.The Central Pattern Generator(CPG)can generate a rhythmic movement.According to biological knowledge,the CPG is controlled by the central nervous.But the study of the mechanism for biological motion control is still an open question.In this paper,we establish the model for depicting the interaction between the chaotic neural network and CPG.Bifurcation analysis and phase are used to describe changes in system behavior and show the interaction mechanism.In addition,the influences of CPG parameters on the model are discussed.Many modes described at state equilibrium points in the cerebral cortex correspond to gait patterns,and the change of state equilibrium points in the cerebral cortex leads to the change of gait patterns.At the same time,the results show that the brain cortex patterns can be changed by adjusting the value of the brain cortex'external input and CPG's feedback to the cerebral cortex.
The cerebral cortex is a chaotic nonlinear system.The Central Pattern Generator(CPG)can generate a rhythmic movement.According to biological knowledge,the CPG is controlled by the central nervous.But the study of the mechanism for biological motion control is still an open question.In this paper,we establish the model for depicting the interaction between the chaotic neural network and CPG.Bifurcation analysis and phase are used to describe changes in system behavior and show the interaction mechanism.In addition,the influences of CPG parameters on the model are discussed.Many modes described at state equilibrium points in the cerebral cortex correspond to gait patterns,and the change of state equilibrium points in the cerebral cortex leads to the change of gait patterns.At the same time,the results show that the brain cortex patterns can be changed by adjusting the value of the brain cortex'external input and CPG's feedback to the cerebral cortex.
引文
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[2]MEES A,AIHARA K,ADACHI M,et al.Deterministic Prediction and Chaos in Squid Axon Response[J].Physics Letters A,1992,169(1):41-45.
[3]AIHARA K,TAKABE T,TOYODA M.Chaotic Neural Networks[J].Physics Letters A,1990,144(6):333-340.
[4]MATSUOKA K.Sustained Oscillations Generated by Mutually Inhibiting Neurons with Adaptation[J].Biological Cybernetics,1985,52(6):367-376.
[5]ZHANG J Q,GAO F,HAN X L,et al.Trot Gait Design and CPG Method for a Quadruped Robot[J].Journal of Bionic Engineering,2014,11(1):18-25.
[6]LU Q,TIAN J.Research on Walking Gait of Biped Robot Based on a Modified CPG Model[J].Mathematical Problems in Engineering,2015,2015:793208.
[7]ROSTRO-GONZALEZ H,CERNA-GARCIA P A,TREJO-CABALLERO G,et al.A CPG System Based on Spiking Neurons for Hexapod Robot Locomotion[J].Neurocomputing,2015,170:47-54.
[8]SFAKIOTAKIS M,FASOULAS J,KAVOUSSANOS M M,et al.Experimental Investigation and Propulsion Control for a Bio-inspired Robotic Undulatory Fin[J].Robotica,2015,33(5):1062-1084.
[9]WILLIAMS T L,MCMILLEN T.Strategies for Swimming:Explorations of the Behaviour of a Neuro-musculomechanical Model of the Lamprey[J].Biology Open,2015,4(3):253-258.
[10]MATSUO T,ISHII K.The Adjustment System of Phase Difference Using Neural Oscillator Network for a Snake-like Robot[C]//Proceedings of the SICE Annual Conference.Tokyo:SICE,2012:502-507.
[11]HASANZADEH S,AKBARZADEH A.Development of a New Spinning Gait for a Planar Snake Robot Using Central Pattern Generators[J].Intelligent Service Robotics,2013,6(2):109-120.
[12]BUSCHMANN T,EWALD A,TWICKEL A V,et al.Controlling Legs for Locomotion-insights from Robotics and Neurobiology[J].Bioinspiration&Biomimetics,2015,10:041001.
[13]TAGA G.A Model of the Neuro-musculo-skeletal System for Human Locomotion[J].Biological Cybernetics,1995,73(2):97-111.
[14]GISZTER S F.Motor Primitives—New Data and Future Questions[J].Current Opinion in Neurobiology,2015,33:156-165.
[15]TAGA G.A Model of the Neuro-musculo-skeletal System for Anticipatory Adjustment of Human Locomotion During Obstacle Avoidance[J].Biological Cybernetics,1998,78(1):9-17.
[16]KNIKOU M.Neural Control of Locomotion and Training-induced Plasticity After Spinal and Cerebral Lesions[J].Clinical Neurophysiology,2010,121(10):1655-1668.
[17]MATSUOKA K.Analysis of a Neural Oscillator[J].Biological Cybernetics,2011,104(4/5):297-304.