Prefrontal and striatal activity related to values of objects and locations.

Prefrontal and striatal activity related to values of objects and locations.
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DOI:
10.3389/fnins.2012.00108
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发表时间:
2012
影响因子:
4.3
通讯作者:
Lee D
Lee D
中科院分区:
医学2区
文献类型:
--
作者:
Kim S;Cai X;Hwang J;Lee D

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通过特定行动获得的对象的价值通常决定了产生该行动的动机。以前的研究发现,神经信号与眼眶前额叶皮质中不同物体或物品的价值有关,而不同行动预期结果的价值广泛存在于与运动规划有关的多个大脑区域。然而,大脑如何将与各种物体相关的价值和关于它们位置的信息结合在一起尚不清楚。在这项研究中,我们测试了恒河猴背外侧前额叶皮质(DLPFC)和纹状体中的神经元是否可能参与多个参照系之间的值信号转换。猴子被训练进行跨时眼动选择,在这种选择中,眼跳目标的颜色和周围圆点的数量分别表示奖励的大小和延迟。在DLPFC和纹状体,与特定目标颜色和位置相关的时间折扣值(DV)由部分重叠的神经元群体编码。在DLPFC中,特定目标位置可获得的奖赏延迟和奖赏DVS的信息比目标颜色的相应信号出现得更早。一个简单的网络模型重现了类似的结果,该模型是为了计算不同地点的奖励DV而建立的。因此,DLPFC可能通过结合先前学习到的对象的值及其当前位置来在估计不同动作的值方面发挥重要作用。
The value of an object acquired by a particular action often determines the motivation to produce that action. Previous studies found neural signals related to the values of different objects or goods in the orbitofrontal cortex, while the values of outcomes expected from different actions are broadly represented in multiple brain areas implicated in movement planning. However, how the brain combines the values associated with various objects and the information about their locations is not known. In this study, we tested whether the neurons in the dorsolateral prefrontal cortex (DLPFC) and striatum in rhesus monkeys might contribute to translating the value signals between multiple frames of reference. Monkeys were trained to perform an oculomotor intertemporal choice in which the color of a saccade target and the number of its surrounding dots signaled the magnitude of reward and its delay, respectively. In both DLPFC and striatum, temporally discounted values (DVs) associated with specific target colors and locations were encoded by partially overlapping populations of neurons. In the DLPFC, the information about reward delays and DVs of rewards available from specific target locations emerged earlier than the corresponding signals for target colors. Similar results were reproduced by a simple network model built to compute DVs of rewards in different locations. Therefore, DLPFC might play an important role in estimating the values of different actions by combining the previously learned values of objects and their present locations.
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