Integration of Gravitational Torques in Cerebellar Pathways Allows for the Dynamic Inverse Computation of Vertical Pointing Movements of a Robot Arm

被引:16
作者
Gentili, Rodolphe J.
Papaxanthis, Charalambos
Ebadzadeh, Mehdi
Eskiizmirliler, Selim
Ouanezar, Sofiane
Darlot, Christian
机构
[1] CNRS UMR 7060, Université Paris Descartes, Paris-5, Paris
[2] Université Paris Diderot, Paris-7, Paris
[3] INSERM U887, Motricité-Plasticité, Université de Bourgogne, Dijon
[4] Ecole supérieure des Télécommunications, Paris
[5] Amirkabir University of Technology, Computer Engineering and Information Technology Department, Tehran
[6] Cognitive Motor Neuroscience laboratory, Department of Kinesiology, University of Maryland, School of Public Health, College Park, MD
来源
PLOS ONE | 2009年 / 4卷 / 04期
关键词
BASAL GANGLIA; MOTOR CONTROL; REACHING MOVEMENTS; NEURONAL-ACTIVITY; INTERNAL-MODELS; SENSORIMOTOR; CORTEX; PREDICTION; DIRECTION; MUSCLES;
D O I
10.1371/journal.pone.0005176
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background: Several authors suggested that gravitational forces are centrally represented in the brain for planning, control and sensorimotor predictions of movements. Furthermore, some studies proposed that the cerebellum computes the inverse dynamics (internal inverse model) whereas others suggested that it computes sensorimotor predictions (internal forward model). Methodology/Principal Findings: This study proposes a model of cerebellar pathways deduced from both biological and physical constraints. The model learns the dynamic inverse computation of the effect of gravitational torques from its sensorimotor predictions without calculating an explicit inverse computation. By using supervised learning, this model learns to control an anthropomorphic robot arm actuated by two antagonists McKibben artificial muscles. This was achieved by using internal parallel feedback loops containing neural networks which anticipate the sensorimotor consequences of the neural commands. The artificial neural networks architecture was similar to the large-scale connectivity of the cerebellar cortex. Movements in the sagittal plane were performed during three sessions combining different initial positions, amplitudes and directions of movements to vary the effects of the gravitational torques applied to the robotic arm. The results show that this model acquired an internal representation of the gravitational effects during vertical arm pointing movements. Conclusions/Significance: This is consistent with the proposal that the cerebellar cortex contains an internal representation of gravitational torques which is encoded through a learning process. Furthermore, this model suggests that the cerebellum performs the inverse dynamics computation based on sensorimotor predictions. This highlights the importance of sensorimotor predictions of gravitational torques acting on upper limb movements performed in the gravitational field.
引用
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页数:16
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