Competition between learned reward and error outcome predictions in anterior cingulate cortex.

Competition between learned reward and error outcome predictions in anterior cingulate cortex.
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DOI:
10.1016/j.neuroimage.2009.11.065
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发表时间:
2010-02-15
期刊:
影响因子:
5.7
通讯作者:
Brown, Joshua W.
Brown, Joshua W.
中科院分区:
医学1区
文献类型:
--
作者:
Alexander, William H.;Brown, Joshua W.

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前扣带皮层(ACC)与行为监测和认知控制有关。非人类灵长类动物对ACC的研究显示出突出的奖励信号,但这些在人类研究中是难以捉摸的,而主要表现为冲突和错误效应。在这里,我们展示了人类ACC中不同的食欲和厌恶活动。错误似然假设表明,ACC活动的增加与错误的可能性成正比,并且ACC对预测错误的后果大小也很敏感。先前的研究进一步表明,当错误的潜在后果增加时,错误可能性效应会达到上限,这可能是由于平均奖励的减少。我们通过独立操纵任务反应的奖励大小和错误可能性来探索这个问题,同时控制激励变化信号任务中潜在的错误后果。fMRI结果排除了预期奖励对错误可能性效应的调节作用,支持预期奖励和错误可能性之间的竞争效应。动态因果模型表明,错误可能性和预期奖励信号是前扣带皮层固有的,而不是从其他地方接收到的。这些发现与前扣带皮层活动作为风险感知和预测回报信号的解释一致。
The anterior cingulate cortex (ACC) is implicated in performance monitoring and cognitive control. Non-human primate studies of ACC show prominent reward signals, but these are elusive in human studies, which instead show mainly conflict and error effects. Here we demonstrate distinct appetitive and aversive activity in human ACC. The error likelihood hypothesis suggests that ACC activity increases in proportion to the likelihood of an error, and ACC is also sensitive to the consequence magnitude of the predicted error. Previous work further showed that error likelihood effects reach a ceiling as the potential consequences of an error increase, possibly due to reductions in the average reward. We explored this issue by independently manipulating reward magnitude of task responses and error likelihood while controlling for potential error consequences in an incentive change signal task. The fMRI results ruled out a modulatory effect of expected reward on error likelihood effects in favor of a competition effect between expected reward and error likelihood. Dynamic causal modeling showed that error likelihood and expected reward signals are intrinsic to the ACC rather than received from elsewhere. These findings agree with interpretations of ACC activity as signaling both perceptions of risk and predicted reward.
额叶中的神经元编码多个决策变量的值。
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