Learning optimal adaptation strategies in unpredictable motor tasks.
Learning optimal adaptation strategies in unpredictable motor tasks.
复制标题
DOI：
10.1523/jneurosci.3075-08.2009
复制
发表时间：
2009-05-20
期刊：
影响因子：
--
通讯作者：
Mehring C
中科院分区：
文献类型：
--
作者：
Braun DA;Aertsen A;Wolpert DM;Mehring C
拿起一个我们认为是满的空牛奶纸盒是一个熟悉的自适应控制的例子，因为估计纸盒重量的自适应过程必须与将纸盒移动到期望位置的控制过程同时进行。在这里，我们表明运动系统最初在这些不可预测的任务中产生高度可变的行为，但最终收敛到由简单的最优性原则预测的适应性反应的定型模式。这些结果表明，适应可以被特别调整，以最佳方式识别特定任务的参数。
Picking up an empty milk carton that we believe to be full is a familiar example of adaptive control, because the adaptation process of estimating the carton's weight must proceed simultaneously to the control process of moving the carton to a desired location. Here we show that the motor system initially generates highly variable behavior in such unpredictable tasks but eventually converges to stereotyped patterns of adaptive responses predicted by a simple optimality principle. These results suggest that adaptation can become specifically tuned to identify task-specific parameters in an optimal manner.