Individual, age-dependent differences in ACC-mediated adaptive decision making

描述（由申请人提供）：我们从经验中学习，以做出更有效的决策，经常调整我们的期望，以匹配我们过去经历过的结果。在一个动态的世界中，这种调整过程本身必须是适应性的，因为有时发生的变化使过去的结果与未来的期望无关。例如，觅食者必须认识到，一棵垂死的树将不再像健康时那样结出那么多的果实。拟议研究的目标是测试一个新的假设，即决策中的某些个体差异，包括一些系统地依赖于年龄的差异，是由于观察到的世界变化如何影响使用过去的经验来为未来的决策提供信息的差异。我们认为，个人在如何识别和应对两种不同形式的不确定性方面存在很大差异。不确定性的一种形式，称为噪声，代表了稳定过程中的随机波动。另一种形式的不确定性，称为波动性，代表了过程本身的根本变化。个体适应性决策的范围从面对嘈杂或不稳定的新数据时总是调整预期的倾向，到形成相对不受新数据影响的稳定预期的倾向。我们已经确定了控制这种自适应信念更新的计算原理，其中包括对当前环境中波动变化发生率的先验预期的重要性。我们还提出，重要的基础计算编码的前扣带皮层（ACC）的神经元的活动。为了验证这些假设，我们使用了两个互补的目标，它们提供了不同年龄的个体受试者执行任务时ACC活动的多种测量，这些任务旨在直接测量 每一条新信息对动态环境的现有信念的影响量。第一个Aim使用年轻和年长猴子的行为和神经生理学记录，提供具有高空间和时间分辨率的相关神经计算的测量。第二个目标使用了结合行为和基于功能磁共振成像和脑电图的人类受试者大脑活动测量，可以直接与更高分辨率的猴子数据进行比较。人类研究还包括该任务的几个版本，其中一个旨在直接操纵和测量对环境变化率的先前预期，这为这些决策中出现的个体和年龄相关差异提供了更广泛的视角。这项拟议中的研究代表了一个新的研究领域，可能会为个人如何在动态世界中做出有效决策提供深远的见解。

DESCRIPTION (provided by applicant): We learn from experience to make more effective decisions, often adjusting our expectations to match outcomes that we have experienced in the past. In a dynamic world, this adjustment process must itself be adaptive, because sometimes changes occur that render past outcomes irrelevant to future expectations. For example, a forager must recognize that a dying tree will no longer yield as much fruit as when it was healthy. The goal of the proposed research is to test the novel hypothesis that certain individual differences in decision- making, including some that depend systematically on age, result from differences in how observed changes in the world affect the use of past experiences to inform future decisions. We propose that individuals differ substantially in how they recognize and respond to two different forms of uncertainty. One form of uncertainty, called noise, represents random fluctuations in an otherwise stable process. The other form of uncertainty, called volatility, represents fundamental changes in the process itself. Individual, adaptive decision-making ranges from a tendency to always adjust expectations in the face of either noisy or volatile new data, to a tendency to form stable expectations that are relatively unaffected by new data. We have identified computational principles that govern this kind of adaptive belief updating, which include the importance of prior expectations about the rate of occurrence of volatile changes in the current environment. We also propose that the important underlying computations are encoded by the activity of neurons in the anterior cingulate cortex (ACC). To test these hypotheses, we use two complementary Aims that provide multiple measures of ACC activity in individual subjects of different ages performing tasks designed to measure directly the amount of influence each new piece of information has on existing beliefs about a dynamic environment. The first Aim uses combined behavior and neurophysiological recordings in younger and older monkeys, providing measurements of the relevant neural computations with high spatial and temporal resolution. The second Aim uses combined behavior and fMRI- and EEG-based measurements of brain activity in human subjects, which can be compared directly to the higher-resolution monkey data. The human studies also include several versions of the task, including one designed to manipulate and measure prior expectations about the rate of environmental changes directly, that provide a broader view of the individual and age-related differences that occur with these kinds of decisions. The proposed research represents a novel field of study that is likely to provide far-reaching insights into how individuals make effective decisions in a dynamic world.