...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>The European Journal of Neuroscience >From prediction error to incentive salience: Mesolimbic computation of reward motivation
【24h】

From prediction error to incentive salience: Mesolimbic computation of reward motivation

机译：从预测误差到激励显着：奖励激励的中边缘计算

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Reward contains separable psychological components of learning, incentive motivation and pleasure. Most computational models have focused only on the learning component of reward, but the motivational component is equally important in reward circuitry, and even more directly controls behavior. Modeling the motivational component requires recognition of additional control factors besides learning. Here I discuss how mesocorticolimbic mechanisms generate the motivation component of incentive salience. Incentive salience takes Pavlovian learning and memory as one input and as an equally important input takes neurobiological state factors (e.g. drug states, appetite states, satiety states) that can vary independently of learning. Neurobiological state changes can produce unlearned fluctuations or even reversals in the ability of a previously learned reward cue to trigger motivation. Such fluctuations in cue-triggered motivation can dramatically depart from all previously learned values about the associated reward outcome. Thus, one consequence of the difference between incentive salience and learning can be to decouple cue-triggered motivation of the moment from previously learned values of how good the associated reward has been in the past. Another consequence can be to produce irrationally strong motivation urges that are not justified by any memories of previous reward values (and without distorting associative predictions of future reward value). Such irrationally strong motivation may be especially problematic in addiction. To understand these phenomena, future models of mesocorticolimbic reward function should address the neurobiological state factors that participate to control generation of incentive salience.
机译：奖励包含学习，激励动机和愉悦感的可分离心理成分。大多数计算模型只关注奖励的学习部分，但动机部分在奖励电路中同样重要，甚至更直接地控制行为。对动机成分进行建模除了学习外还需要识别其他控制因素。在这里，我讨论了中皮层皮质机制如何产生激励显着性的激励成分。激励显着性将巴甫洛夫式的学习和记忆作为一种输入，而同等重要的输入则采用可以独立于学习而变化的神经生物学状态因素（例如药物状态，食欲状态，饱腹状态）。神经生物学状态的变化会导致先前学习的奖励线索触发动机的能力产生无法学习的波动甚至逆转。提示触发的动机的这种波动可能会大大偏离有关奖励结果的所有先前学习的值。因此，激励显着性与学习之间的差异的一个结果可能是，将时刻的提示触发的动机与相关的奖励过去的良好程度的先前学习的值脱钩。另一个结果可能是产生非理性的强烈动机冲动，而这些冲动并没有被先前奖励值的任何记忆所证明（并且不会扭曲对未来奖励值的联想预测）。这种非理性的强烈动机在成瘾中尤其成问题。为了理解这些现象，未来的中皮层皮质奖励功能模型应解决参与控制激励显着性产生的神经生物学状态因素。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号