Comparing Apples and Oranges: Using Reward-Specific and Reward-General Subjective Value Representation in the Brain
Comparing Apples and Oranges: Using Reward-Specific and Reward-General Subjective Value Representation in the Brain
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DOI：
10.1523/jneurosci.2218-11.2011
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发表时间：
2011-10-12
影响因子：
5.3
通讯作者：
Glimcher, Paul W.
中科院分区：
文献类型：
--
作者：
Levy, Dino J.;Glimcher, Paul W.
人类受试者能够在不同类型的奖励中做出选择，这表明，评估不同奖励类型的神经回路必须收敛。经济学理论认为，这些收敛点代表了不同奖励类型在一个共同尺度上的主观价值（SV）。为了检验这些假设，并绘制出奖励评估的神经回路，我们让被试在大脑扫描仪中对金钱、食物和水做出了有风险的选择。我们发现，不同奖励类型的风险偏好高度相关;一个人在选择货币彩票时表现出的风险厌恶程度预测了他们对食物和水的风险厌恶程度。我们还发现，部分不同的神经网络代表了货币和食物奖励的SV，并且这些不同的网络显示出特定的收敛点。下丘脑主要代表食物SV，后扣带回主要代表金钱SV。在腹内侧前额叶皮层（vmPFC）和纹状体中，有一个共同的区域代表两种奖励类型的SV，但在我们的数据集中，只有vmPFC在一个适合选择的共同尺度上显著代表金钱和食物的SV。相关性分析表明，货币和食物的估值领域和共同领域的VMPFC和纹状体的相互作用。这可能表明，不同奖励类型的部分不同的估值网络收敛于统一的估值网络，这使得不同奖励类型之间的直接比较成为可能，从而指导估值和选择。
The ability of human subjects to choose between disparate kinds of rewards suggests that the neural circuits for valuing different reward types must converge. Economic theory suggests that these convergence points represent the subjective values (SVs) of different reward types on a common scale for comparison. To examine these hypotheses and to map the neural circuits for reward valuation we had food and water-deprived subjects make risky choices for money, food, and water both in and out of a brain scanner. We found that risk preferences across reward types were highly correlated; the level of risk aversion an individual showed when choosing among monetary lotteries predicted their risk aversion toward food and water. We also found that partially distinct neural networks represent the SVs of monetary and food rewards and that these distinct networks showed specific convergence points. The hypothalamic region mainly represented the SV for food, and the posterior cingulate cortex mainly represented the SV for money. In both the ventromedial prefrontal cortex (vmPFC) and striatum there was a common area representing the SV of both reward types, but only the vmPFC significantly represented the SVs of money and food on a common scale appropriate for choice in our data set. A correlation analysis demonstrated interactions across money and food valuation areas and the common areas in the vmPFC and striatum. This may suggest that partially distinct valuation networks for different reward types converge on a unified valuation network, which enables a direct comparison between different reward types and hence guides valuation and choice.