Körding Konrad P, Wolpert Daniel M
Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139, USA.
Trends Cogn Sci. 2006 Jul;10(7):319-26. doi: 10.1016/j.tics.2006.05.003. Epub 2006 Jun 27.
Action selection is a fundamental decision process for us, and depends on the state of both our body and the environment. Because signals in our sensory and motor systems are corrupted by variability or noise, the nervous system needs to estimate these states. To select an optimal action these state estimates need to be combined with knowledge of the potential costs or rewards of different action outcomes. We review recent studies that have investigated the mechanisms used by the nervous system to solve such estimation and decision problems, which show that human behaviour is close to that predicted by Bayesian Decision Theory. This theory defines optimal behaviour in a world characterized by uncertainty, and provides a coherent way of describing sensorimotor processes.
动作选择是我们的一个基本决策过程，它取决于我们身体和环境的状态。由于我们感觉和运动系统中的信号会受到变异性或噪声的干扰，神经系统需要对这些状态进行估计。为了选择最优动作，这些状态估计需要与不同动作结果的潜在成本或奖励的知识相结合。我们回顾了最近的一些研究，这些研究调查了神经系统用于解决此类估计和决策问题的机制，结果表明人类行为接近贝叶斯决策理论所预测的行为。该理论定义了在一个充满不确定性的世界中的最优行为，并提供了一种连贯的方式来描述感觉运动过程。
