The Neural Basis of Risky Decision Making

这项赠款由2004财政年度人类和社会动力学（HSD）竞赛资助，为一系列使用功能性磁共振成像（fMRI）检查参与决策的大脑系统的研究提供资金。许多决定必须在事先不知道其后果的情况下做出，并承担一定程度的身体或财务风险。尽管人们对风险决策所涉及的认知过程已经有了很好的了解，但这些过程背后的大脑系统才刚刚开始被探索。该项目将研究大脑处理奖励和惩罚的途径是如何参与决策的，通过成像大脑活动，而个人做出关于风险赌博的决定（例如，在确定收到20美元或50/50的机会之间选择50美元或0美元）。要检查的因素包括风险和无风险决策的关系，极端概率对风险决策的影响，以及在不断变化的风险背景下决策的动态。将在成像期间获得皮肤电导的测量，以便可以量化生理唤醒并将其与行为和大脑活动相关联。分析将集中在与奖励或惩罚经验相关的特定大脑区域的活动是否能预测个人的决定。每个受试者的行为也将使用正式的决策理论模型进行表征，描述这种行为的参数将与大脑活动有关。如果成功，这项研究将为大脑如何做出决策提供新的见解。特别是，这些结果将有助于将行为决策的定量模型与其神经生物学基础联系起来。关于决策的神经基础的知识将鼓励在神经和认知水平上的模型趋同，并将为神经科学家提供新的方法来描述大脑活动和行为之间的关系。

This grant, funded under the Human and Social Dynamics (HSD) Competition for FY 2004, provides funding for a set of studies that use functional magnetic resonance imaging (fMRI) to examine the brain systems involved in decision making. Many decisions must be made without advance knowledge of their consequences and under some degree of physical or financial risk. Whereas the cognitive processes involved in decision making under risk are well understood, the brain systems that underlie these processes have only begun to be explored. This project will examine how brain pathways for the processing of reward and punishment are involved in decision making, by imaging brain activity while individuals make decisions regarding risky gambles (for example, the choice between a sure receipt $20 or a 50/50 chance of either $50 or $0). Factors to be examined include the relation of risky and riskless decisions, the effects of extreme probabilities on risky decision making, and the dynamics of decision making in a context of changing risk. Measures of skin conductance will be obtained during imaging, so that physiological arousal can be quantified and related to behavior and brain activity. Analyses will focus on whether activity in particular brain regions related to the experience of reward or punishment will be predictive of the individual's decisions. Each subject's behavior will also be characterized using formal decision theory models, and the parameters describing this behavior will be related to brain activity. If successful, this research will provide novel insights into how the brain makes decisions. In particular, the results will help to relate quantitative models of behavioral decision making with their neurobiological underpinnings. Knowledge about the neural basis of decision making will encourage convergence across models at the neural and cognitive levels, and will provide neuroscientists with new ways to characterize the relation between brain activity and behavior.