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，以做出更有效的决定，经常调整我们的预期，以适应我们过去经历的结果。在一个动态的世界中，这一调整过程本身必须是适应性的，因为有时会发生变化，使过去的结果与未来的预期无关。例如，采集者必须认识到，一棵垂死的树将不再像它健康的时候那样结出那么多的果实。这项拟议研究的目的是检验这一新的假设，即某些个体在决策过程中的差异，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利用过去的经验为未来的决策提供信息的差异造成的。我们认为，每个人在认识和应对两种不同形式的不确定性方面有很大的不同。一种形式的不确定性称为噪声，它代表了一个原本稳定的过程中的随机波动。另一种形式的不确定性称为波动性，它代表了这一过程本身的根本性变化。个人自适应决策的范围从面对嘈杂或波动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。我们已经确定了管理这种自适应信念更新的计算原则，其中包括对当前环境中不稳定变化的发生速度的先前预期的重要性。我们还提出，重要的潜在计算是由前扣带皮质(ACC)神经元的活动编码的。为了验证这些假设，我们使用两个互补的目标，在不同年龄的个体受试者中提供多个ACC活动的测量，这些个体执行的任务旨在直接测量 每条新信息对关于动态环境的现有信念的影响程度。第一个目标是使用年轻和年长猴子的行为和神经生理记录相结合的记录，以高空间和时间分辨率提供相关神经计算的测量结果。第二个目的是结合行为以及基于fMRI和EEG的人类受试者大脑活动的测量，这些测量可以直接与更高分辨率的猴子数据进行比较。人类研究还包括这项任务的几个版本，其中一个版本旨在直接操纵和衡量对环境变化速度的先前预期，从而提供了关于这些决定所产生的个体和与年龄相关的差异的更广泛的视角。这项拟议的研究代表了一个新的研究领域，可能会为人们在一个动态的世界中如何做出有效的决定提供深远的见解。

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.