Neural Mechanisms of Cost and Benefit Integration During Decision-Making

描述（由申请人提供）：有效决策是权衡成本和收益的过程。虽然在过去的二十年里，人类和猴子衡量利益的神经机制已经取得了巨大的进展，但人们对这些物种的大脑如何衡量成本知之甚少。然而，越来越多来自人类和猴子的证据表明，成本和收益可能是由不同的神经系统编码的，并在决策级联的相当晚的时候整合在一起。在这里，我们提出了一套简单的实验，旨在将人类和猴子在决策过程中的成本和收益正交化，同时我们测量和操纵一系列决策相关区域的神经活动。我们的目标是验证这样一个假设，即独立的前部区域（主要在额叶皮层）维持着成本和收益的独立表征，这些表征随后被整合到通常被称为额顶叶选择回路的选择中（在动眼肌任务中）。为了验证这一假设，我们提出了一套互补的人类功能磁共振成像（fMRI）实验和猴子单单元记录和muscimol失活实验。功能磁共振实验允许对我们的假设进行大规模的全脑测试。单个单位研究允许对每个领域的成本和效益代表程度进行严格的定量测量，并有能力在成本效益整合中为某些或所有这些领域建立因果关系。

DESCRIPTION (provided by applicant): Making decisions efficiently is the process of weighing costs and benefits. And while enormous progress has been made in the last two decades towards understanding the neural mechanisms by which humans and monkeys weigh benefits, much less is known about how the brains of these species weigh costs. There is, however, growing evidence from both humans and monkeys indicating that costs and benefits may be encoded by distinct neural systems and integrated quite late in the decision cascade. Here we propose a set of simple experiments designed to orthogonalize costs and benefits during human and monkey decision-making while we measure - and manipulate - neural activity in a suite of decision-related areas. Our goal is to test the hypothesis that separate anterior areas (mostly in the frontal cortex) maintain separate representations of costs and benefits, representations that are subsequently integrated for choice (in oculomotor tasks) in what are often called the fronto-parietal choice circuits. To test this hypothesis we propose a complementary set of functional Magnetic Resonance Imaging (fMRI) experiments in humans and single unit recording and muscimol inactivation experiments in monkeys. The fMRI experiments allow for a large-scale whole-brain test of our hypothesis. The single unit studies allow a rigorous quantitative measurement of the degree of cost and benefit representation in each area and the ability to establish a causal for some or all of these areas in cost benefit integration.