Metalearning and neuromodulation
Metalearning and neuromodulation
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DOI：
10.1016/s0893-6080(02)00044-8
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发表时间：
2002-06-01
期刊：
影响因子：
7.8
通讯作者：
Doya, K
中科院分区：
文献类型：
--
作者：
Doya, K
本文从提升神经调节系统调节大脑分布式学习机制的全局信号的观点出发，提出了一种关于提升神经调节系统的计算理论。基于实验数据和理论模型，本文认为多巴胺对奖励预测的误差发出信号，血清素控制奖励预测的时间尺度，去甲肾上腺素控制动作选择的随机性，乙酰胆碱控制记忆更新的速度。在元学习计算理论的基础上，预测了这些神经调节剂与环境之间可能的相互作用。(C) 2002 Elsevier Science Ltd.版权所有。
This paper presents a computational theory on the roles of the ascending neuromodulatory systems from the viewpoint that they mediate the global signals that regulate the distributed learning mechanisms in the brain. Based on the review of experimental data and theoretical models, it is proposed that dopamine signals the error in reward prediction, serotonin controls the time scale of reward prediction, noradrenaline controls the randomness in action selection, and acetylcholine controls the speed of memory update. The possible interactions between those neuromodulators and the environment are predicted on the basis of computational theory of metalearning. (C) 2002 Elsevier Science Ltd. All rights reserved.