Neural Economics and Biological Substrates of Valuation

描述(由申请人提供)：持续的经济评估是任何必须以有限的资源运行的系统的核心功能，也就是说，所有可移动的生物。对神经评估机制的需求源于移动生物神经系统可获得的信息的绝对广度和多样性，以及必须优先考虑感觉刺激和可能的行为输出的事实。这就提出了一个基本的信息处理问题：必须将截然不同的刺激和行为输出置于某种共同的估值范围内。没有神经系统的内部估值系统，生物将无法评估本质上不同的事件的相对价值，比如喝水、闻食物、扫描捕食者、安静地坐在太阳下等等。为了决定一种适当的行为，神经系统必须估计每一种潜在行为或刺激的价值，将其转换为共同的标尺(货币)，并使用该标尺来确定行动路线。这一问题长期以来一直受到行为心理学家和经济学家的重视；然而，直到最近，人类才通过实验研究了潜在的神经基础。中脑多巴胺系统及其投射到的目标神经结构现在已被确定为参与未来奖励事件的估值。特别是，计算工作表明，这些多巴胺神经元的一个子集编码并分发一个预测误差信号，代表实际奖励和预测奖励之间的持续差异。多巴胺能功能的这种预测误差模型现在已经导致了预测人类在顺序决策任务中的行为的行为模型。这些任务提出的问题是：“人类如何重视奖赏刺激的持续变化？”这是一个对药物滥用具有重要影响的问题。然而，目前还没有生物学方法来与这些基于模型的行为预测相关联。这项提议的长期目标是在连续决策任务的执行过程中使用功能磁共振成像(FMRI)来探测与人类表现相关的大脑反应。这项工作将提供对人类大脑中存在的估值机制的基本见解。

DESCRIPTION (provided by applicant): Ongoing economic evaluation is a central function for any system that must operate with limited, finite resources, that is, all mobile creatures. The need for neural valuation mechanisms arises from the sheer breadth and variety of information available to a mobile creature's nervous system, and the fact that sensory stimuli and possible behavioral output must be prioritized. This presents a fundamental information-processing problem: vastly different stimuli and behavioral output must be placed on some common valuation scale. Without internal valuation systems in the nervous system, a creature would be unable to assess the relative value of intrinsically different events like drinking water, smelling food, scanning for predators, sitting quietly in the sun, and so forth. To decide on an appropriate behavior, the nervous system must estimate the value of each of these potential actions or stimuli, convert it to a common scale (currency), and use this scale to determine a course of action. This issue has long been appreciated by behavioral psychologists and economists; however, only recently have the underlying neural substrates been addressed experimentally in humans. Midbrain dopamine systems and the target neural structures to which they project have now been identified as participating in the valuation of future rewarding events. In particular, computational work has shown that a subset of these dopamine neurons encode and distribute a prediction error signal representing the ongoing difference between actual reward and predicted reward. This prediction error model of dopaminergic function has now led to behavioral models that predict human behavior on sequential decision-making tasks. These tasks ask the question: "How do humans value ongoing changes in rewarding stimuli?", a question with important implications for drug abuse. However, there has been no biological measure to correlate with these model-based behavioral predictions. The long-term goal of this proposal is to use functional magnetic resonance imaging (fMRI) during the execution of sequential decision tasks to probe the brain responses that correlate with human performance. This work will provide fundamental insights into valuations mechanisms present in human brains.