Reward Inference by Primate Prefrontal and Striatal Neurons
Reward Inference by Primate Prefrontal and Striatal Neurons
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灵长类动物前额叶和纹状体神经元的奖励推理
DOI：
10.1523/jneurosci.2263-13.2014
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发表时间：
2014-01
期刊：
影响因子：
--
通讯作者：
Masamichi Sakagami
中科院分区：
文献类型：
--
作者：
Xiaochuan Pan Hongwei Fan Kosuke Sawa Ichiro;Masamichi Sakagami
大脑包含多个不同的系统，涉及奖励预测。为了了解这些过程的性质，我们记录了单单位活动的外侧前额叶皮层（LPFC）和纹状体的猴子执行奖励推理任务，使用不对称的奖励时间表。我们发现，在LPFC和纹状体的神经元预测奖励值的刺激，以前已经很好地经历了设置奖励数量的不对称奖励任务。重要的是，这些LPFC神经元可以使用传递性推理预测刺激的奖励值，即使猴子还没有直接学习刺激-奖励关联;而这些纹状体神经元没有表现出这种能力。然而，由于存在两个设定的奖励量（大和小），所选择的纹状体神经元能够排他性地推断奖励值（例如，大）在直接体验具有另一奖励值的替代刺激之后的来自一对的一个新刺激（例如，小）。我们的研究结果表明，虽然神经元预测奖励价值的旧刺激在LPFC也可以这样做，通过传递性推理的新刺激，那些在纹状体只能预测奖励通过排他性推理的新刺激。此外，纹状体显示出比以前推测的无模型学习更复杂的功能。
The brain contains multiple yet distinct systems involved in reward prediction. To understand the nature of these processes, we recorded single-unit activity from the lateral prefrontal cortex (LPFC) and the striatum in monkeys performing a reward inference task using an asymmetric reward schedule. We found that neurons both in the LPFC and in the striatum predicted reward values for stimuli that had been previously well experienced with set reward quantities in the asymmetric reward task. Importantly, these LPFC neurons could predict the reward value of a stimulus using transitive inference even when the monkeys had not yet learned the stimulus–reward association directly; whereas these striatal neurons did not show such an ability. Nevertheless, because there were two set amounts of reward (large and small), the selected striatal neurons were able to exclusively infer the reward value (e.g., large) of one novel stimulus from a pair after directly experiencing the alternative stimulus with the other reward value (e.g., small). Our results suggest that although neurons that predict reward value for old stimuli in the LPFC could also do so for new stimuli via transitive inference, those in the striatum could only predict reward for new stimuli via exclusive inference. Moreover, the striatum showed more complex functions than was surmised previously for model-free learning.
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DOI：
10.1073/pnas.1221681110
发表时间：
2013-02
期刊：
Proceedings of the National Academy of Sciences
影响因子：
--
作者：
M. Yamada;L. Uddin;Hidehiko Takahashi;Yasuyuki Kimura;K. Takahata;Ririko Kousa;Y. Ikoma;Yoko Eguchi;H. Takano;Hiroshi Ito;M. Higuchi;T. Suhara
通讯作者：
M. Yamada;L. Uddin;Hidehiko Takahashi;Yasuyuki Kimura;K. Takahata;Ririko Kousa;Y. Ikoma;Yoko Eguchi;H. Takano;Hiroshi Ito;M. Higuchi;T. Suhara
DOI：
10.1073/pnas.0601247103
发表时间：
2006-05-02
影响因子：
11.1
作者：
Hauser, M;Spaulding, B
通讯作者：
Spaulding, B
影响因子：
56.9
作者：
Blaisdell, AP;Sawa, K;Waldmann, MR
通讯作者：
Waldmann, MR
影响因子：
64.8
作者：
MCGONIGLE, BO;CHALMERS, M
通讯作者：
CHALMERS, M
影响因子：
2
作者：
White, IM;Wise, SP
通讯作者：
Wise, SP