Internal models underlying grasp can be additively combined
Internal models underlying grasp can be additively combined
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DOI：
10.1007/s00221-003-1730-z
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发表时间：
2004-04-01
影响因子：
2
通讯作者：
Wolpert, DM
中科院分区：
文献类型：
--
作者：
Davidson, PR;Wolpert, DM
我们通过研究人们在精确抓握物体时产生的力来研究我们将两个学习到的内部模型相加联合收割机的能力。受试者被要求交替举起两个物理外观相同但重量不同的物体。使用提离前的夹持力缩放来估计与每个物体相关的内部模型的输出。当交替举起两个不同重量的物体时，形成适当的内部模型。然后，通过将它们一个堆叠在另一个上来组合物体，并且将组合的物体举起。结果表明，受试者可以添加联合收割机内部模型的对象动态，但总和是有偏见的默认估计对象的重量。
Our ability to additively combine two learned internal models was investigated by studying the forces people generate when lifting objects with a precision grip. Subjects were required to alternately lift two objects of identical physical appearance but differing weight. Grip force scaling prior to lift-off was used to estimate the output of the internal model associated with each object. Appropriate internal models were formed when alternately lifting two objects of different weight. The objects were then combined by stacking them one upon the other, and the combined object was lifted. Results show that subjects can additively combine internal models of object dynamics but the sum is biased by a default estimate of the object's weight.