首页> 美国卫生研究院文献>eLife >Dopamine neurons learn relative chosen value from probabilistic rewards
【2h】

Dopamine neurons learn relative chosen value from probabilistic rewards

机译:多巴胺神经元从概率奖励中学习相对选择的价值

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Economic theories posit reward probability as one of the factors defining reward value. Individuals learn the value of cues that predict probabilistic rewards from experienced reward frequencies. Building on the notion that responses of dopamine neurons increase with reward probability and expected value, we asked how dopamine neurons in monkeys acquire this value signal that may represent an economic decision variable. We found in a Pavlovian learning task that reward probability-dependent value signals arose from experienced reward frequencies. We then assessed neuronal response acquisition during choices among probabilistic rewards. Here, dopamine responses became sensitive to the value of both chosen and unchosen options. Both experiments showed also the novelty responses of dopamine neurones that decreased as learning advanced. These results show that dopamine neurons acquire predictive value signals from the frequency of experienced rewards. This flexible and fast signal reflects a specific decision variable and could update neuronal decision mechanisms.>DOI:
机译:经济学理论将奖励概率作为定义奖励价值的因素之一。个人从经验丰富的奖励频率中学习预测概率性奖励的线索的价值。基于多巴胺神经元的响应随奖励概率和期望值增加而增加的概念,我们询问猴子中的多巴胺神经元如何获取此值信号,该信号可能代表经济决策变量。我们在巴甫洛夫式的学习任务中发现,奖励的概率依赖性值信号是由经验丰富的奖励频率产生的。然后,我们在选择概率性奖励时评估了神经元反应的获得。在这里,多巴胺反应变得对选择的和未选择的选择的价值敏感。两项实验均显示,多巴胺神经元的新奇反应随着学习的进展而降低。这些结果表明,多巴胺神经元从经验奖励的频率中获取预测价值信号。这种灵活而快速的信号反映了特定的决策变量,并可以更新神经元决策机制。> DOI:

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

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