The present study used electroencephalography to examine mu rhythm suppression （a putative index of human mirror neuron system activation） at frontal sites （F3, Fz and F4）, central sites （C3, Cz and C4）, parieta...The present study used electroencephalography to examine mu rhythm suppression （a putative index of human mirror neuron system activation） at frontal sites （F3, Fz and F4）, central sites （C3, Cz and C4）, parietal sites （P3, Pz and P4） and occipital sites （O1 and O2）, while subjects observed real hand motion （real hand motion condition） and illustrative depictions of hand motion （drawn hand motion condition）. Experimental data revealed that mu rhythm suppression was exhibited in the mirror neuron system when subjects observed both real and drawn hand motion. Moreover, the mu rhythm recorded at the F3, Fz, F4, and Pz poles was significantly suppressed while observing both stimulus types, but no obvious mu suppression occurred at the O1, 02 and 03 poles. These results suggest that the observation of drawings of human hand actions can activate the human mirror neuron system. This evidence supports the hypothesis that the mirror neuron system may be involved in intransitively abstract action understanding.展开更多
Central pattern generators(CPGs)have been widely applied in robot motion control for the spontaneous output of coherent periodic rhythms.However,the underlying CPG network exhibits good convergence performance only wi...Central pattern generators(CPGs)have been widely applied in robot motion control for the spontaneous output of coherent periodic rhythms.However,the underlying CPG network exhibits good convergence performance only within a certain range of parameter spaces,and the coupling of oscillators affects the network output accuracy in complex topological relationships.Moreover,CPGs may diverge when parameters change drastically,and the divergence is irreversible,which is catastrophic for the control of robot motion.Therefore,normalized asymmetric CPGs(NA-CPGs)that normalize the amplitude parameters of Hopf-based CPGs and add a constraint function and a frequency regulation mechanism are proposed.NA-CPGs can realize parameter decoupling,precise amplitude output,and stable and rapid convergence,as well as asymmetric output waveforms.Thus,it can effectively cope with large parameter changes to avoid network oscillations and divergence.To optimize the parameters of the NA-CPG model,a reinforcement-learning-based online optimization method is further proposed.Meanwhile,a biomimetic robotic fish is illustrated to realize the whole optimization process.Simulations demonstrated that the designed NA-CPGs exhibit stable,secure,and accurate network outputs,and the proposed optimization method effectively improves the swimming speed and reduces the lateral swing of the multijoint robotic fish by 6.7%and 41.7%,respectively.The proposed approach provides a significant improvement in CPG research and can be widely employed in the field of robot motion control.展开更多
基金the Grants from the National Natural Science Foundation of China, No. 60775019, 60970062the Shanghai Pujiang Program, No. 09PJ1410200the Project-sponsored by SRF for ROCS, SEM
文摘The present study used electroencephalography to examine mu rhythm suppression （a putative index of human mirror neuron system activation） at frontal sites （F3, Fz and F4）, central sites （C3, Cz and C4）, parietal sites （P3, Pz and P4） and occipital sites （O1 and O2）, while subjects observed real hand motion （real hand motion condition） and illustrative depictions of hand motion （drawn hand motion condition）. Experimental data revealed that mu rhythm suppression was exhibited in the mirror neuron system when subjects observed both real and drawn hand motion. Moreover, the mu rhythm recorded at the F3, Fz, F4, and Pz poles was significantly suppressed while observing both stimulus types, but no obvious mu suppression occurred at the O1, 02 and 03 poles. These results suggest that the observation of drawings of human hand actions can activate the human mirror neuron system. This evidence supports the hypothesis that the mirror neuron system may be involved in intransitively abstract action understanding.
基金supported by the National Natural Science Foundation of China(61836015,U1909206,62022090,and 62033013).
文摘Central pattern generators(CPGs)have been widely applied in robot motion control for the spontaneous output of coherent periodic rhythms.However,the underlying CPG network exhibits good convergence performance only within a certain range of parameter spaces,and the coupling of oscillators affects the network output accuracy in complex topological relationships.Moreover,CPGs may diverge when parameters change drastically,and the divergence is irreversible,which is catastrophic for the control of robot motion.Therefore,normalized asymmetric CPGs(NA-CPGs)that normalize the amplitude parameters of Hopf-based CPGs and add a constraint function and a frequency regulation mechanism are proposed.NA-CPGs can realize parameter decoupling,precise amplitude output,and stable and rapid convergence,as well as asymmetric output waveforms.Thus,it can effectively cope with large parameter changes to avoid network oscillations and divergence.To optimize the parameters of the NA-CPG model,a reinforcement-learning-based online optimization method is further proposed.Meanwhile,a biomimetic robotic fish is illustrated to realize the whole optimization process.Simulations demonstrated that the designed NA-CPGs exhibit stable,secure,and accurate network outputs,and the proposed optimization method effectively improves the swimming speed and reduces the lateral swing of the multijoint robotic fish by 6.7%and 41.7%,respectively.The proposed approach provides a significant improvement in CPG research and can be widely employed in the field of robot motion control.
