The human nervous system is equipped with a forward kinematics model, which calculates the hand positions using proprioceptive information. Since signi2cant evidence suggests that the forward dynamics model is used for general motion control, the forward kinematics model also seems to be used for the control of visually guided reaching. However, we believe that the forward kinematics model plays no role, or only a supplemental role, in the 2nal stages of visually guided hand position control. Instead, we propose that this is mainly handled by the inverse kinematics model. To explain the relatively large errors ofthe internal models in the human nervous system, Maeda et al. (Proceedings ofthe 1993 International Joint Conf erence on Neural Networks (IJCNN’93 Nagoya), 1993, pp. 1317–1320) proposed a neural network architecture called independent scalar learning elements summations (ISLES) model. We will provide evidence based on experimental results and a mathematical analysis using the ISLES model to support our hypothesis. c � 2002 Published by Elsevier Science B.V.
['Eimei Oyama', 'Taro Maeda', 'Susumu Tachi', 'Karl F. MacDorman', 'Arvin Agah']
On the use of forward kinematic models in visually guided hand position control—analysis based on ISLES model