Aging and the Cognitive and Neural Bases of Implicit Associative Learning

描述（由申请人提供）：总体目标是了解内隐概率联想学习的认知和神经基础，以及这些基础如何随成人年龄而变化。学习被认为是内隐的，当人们在没有打算学习或意识到他们所学到的东西的情况下获得有关结构规律的信息。对于适应世界而言，内隐学习可能比外显/陈述式学习更重要，尤其是在成年后期，因为很少有时间花在正规学校教育上，这是一个强调外显学习的环境。尽管如此，内隐学习的衰老研究却少得多，也许是因为与年龄相关的缺陷有时很小或根本不存在。这种明显的节约产生了一个悖论：联想内隐学习所需要的神经系统在健康的衰老过程中显示出结构和功能的衰退，那么老年人如何才能相对擅长它呢？这是通过采用两个研究领域的主题来解决的：认知神经科学提供了两种互动学习系统的证据——一种基于内侧颞叶（MTL），另一种基于纹状体——可以促进这种学习。衰老的认知神经科学提供的证据表明，这些神经系统中的一个对衰老比另一个更敏感，而且老年人的大脑在完成同样的任务时往往与年轻人的大脑不同。这些主题引出了两个假设。首先，内隐概率联想学习并不是在健康的老龄化中得以保留，而是以持续的年龄相关的学习缺陷为特征，这种缺陷早在中年就可以被发现。这些缺陷随着实践的进展而更加明显，不能仅仅归因于与年龄相关的一般处理资源的缺陷。相反，它们反映了纹状体学习系统功能的根本缺陷。其次，这些系统的相对平衡随着年龄的增长而变化；在训练早期，年轻人和老年人的颞叶颞叶系统都占主导地位，但随着训练的进行，年轻人开始依赖纹状体系统，而老年人继续依赖相对完整的颞叶颞叶系统。这使得老年人在训练的早期就能保持接近年轻人的水平，而不是更晚。这些假设将通过行为和神经成像研究进行测试，使用最近开发的三胞胎学习任务（TLT）。目的1是表征内隐概率联想学习的年龄差异。目的2是测试交互系统假说对衰老的行为影响，目的3是表征年轻人和老年人内隐概率联想学习的神经基础，并将其与行为联系起来。这些目标对于培养成功的老龄化和独立生活非常重要，因为内隐联想学习是适应新人群、环境和技术以及受伤后重新学习技能所必需的。

DESCRIPTION (provided by applicant): The overall aim is to understand the cognitive and neural bases of implicit probabilistic associative learning and how these vary with adult age. Learning is said to be implicit when people acquire information about structural regularities without intending to learn or becoming aware of what they have learned. Implicit learning is likely more important for adapting to the world than its explicit/declarative counterparts, particularly in later adulthood when little time is spent in formal schooling, a setting which emphasizes explicit learning. Nonetheless, the aging of implicit learning has been studied much less, perhaps because age-related deficits have sometimes been small or non-existent. This apparent sparing creates a paradox: Associative implicit learning calls on neural systems that show structural and functional declines in healthy aging, and so how would older people be relatively good at it? This is addressed by adopting themes from two research areas: Cognitive neuroscience provides evidence that two interactive learning systems--one based on the Medial Temporal Lobe (MTL) and the other based on the striatum--can contribute to such learning. The cognitive neuroscience of aging provides evidence that one of these neural systems is more sensitive to aging than the other, and that older brains often do the same task differently from younger brains. These themes lead to two hypotheses. First, that implicit probabilistic associative learning is not spared in healthy aging, but rather is characterized by persistent age-related learning deficits that can be detected as early as middle-age. These deficits are more pronounced as practice progresses, and cannot be attributed solely to age-related deficits in general processing resources. Rather, they reflect a fundamental deficit in the function of the striatal learning system. Second, the relative balance of these systems changes with age; early in training the MTL system dominates in both young and old adults, but as training proceeds the young adults come to rely on the striatal system, whereas the old continue to rely on their relatively intact MTL system. This enables old adults to maintain near- young levels of performance very early in training, but not later. These hypotheses will be tested by conducting behavioral and neuroimaging studies, using a recently developed triplets-learning-task (TLT). Aim 1 is to characterize age differences in implicit probabilistic associative learning. Aim 2 is to test behavioral implications for aging of the interactive systems hypothesis, and Aim 3 is to characterize the neural bases of implicit probabilistic associative learning in young and old adults, and relate them to behavior. These aims are important for fostering successful aging and independent living, because implicit associative learning is needed for adapting to new people, environments, and technologies, as well as for relearning skills after injury. PUBLIC HEALTH RELEVANCE: Understanding the cognitive and neural bases of implicit forms of learning, and how to maximize such learning at all ages, is key to fostering successful aging, because implicit learning is essential for adapting to new environments and people, and for recovering function after injury and stroke. Further, identifying how implicit learning is affected by healthy aging will ultimately help to distinguish healthy from pathological aging (e.g., Alzheimer's disease). To the extent that implicit learning is spared in pathological aging, it can be the basis for remediation, thereby extending independent living, and improving the quality of life of patients and caregivers.