Aging, implicit learning, and white matter integrity

描述（由申请人提供）：拟议研究的主要目标是了解年轻人和老年人内隐学习和白色物质微观结构之间的关系。研究白色物质完整性在内隐学习老化过程中的作用，将扩展关于寿命认知神经科学的新兴文献。内隐学习是在没有意图或意识的情况下发生的，直到最近，它的研究还不如外显学习。这是不幸的，因为对环境中有害物质的敏感性在整个生命中是必不可少的。近年来认知和神经科学对内隐学习的研究表明，内隐学习有多种形式，涉及不同的神经基质，但衰老研究通常把内隐学习视为单一的学习。在这里，我们将专注于两种类型的内隐学习，序列学习和空间背景学习之间的分离，这对于研究大脑行为关系的年龄变化特别重要，因为它们调用不同的大脑系统，这些系统受到健康老龄化的不同影响。影像学和患者研究表明，内隐序列学习依赖于额叶-纹状体-小脑网络，内隐空间背景学习是由内侧颞叶介导的。拟议的实验将是第一个使用扩散张量成像（DTI）来测量连接神经网络的白色物质的完整性（具体目标2）在同一组参与者中检查这种分离的实验。DTI研究表明，白色物质的完整性随着年龄的增长而下降，特别是在前脑区域，这可能会影响健康老年人的认知表现。在这项研究中，老年人预计会受到损害的内隐序列学习，但不内隐空间背景学习（具体目标1），这一发现与健康老龄化影响额纹状体系统比内侧颞叶的观点一致。多元回归分析还将检查与年龄相关的大脑变化是否影响这两个内隐学习任务与来自其相应神经网络的白色物质完整性之间的关系，这是第一个使用内隐学习任务评估大脑-行为关系中的年龄差异的方法，其中行为表现随着年龄的增长而受损和保留（具体目标3）。本研究的结果与成功老化相关。内隐学习通过使人们能够适应变化（即新的环境，人和技术）来促进独立生活，并可以促进事故或中风后脑损伤的恢复。因此，识别内隐学习形式与其潜在的白色物质连接之间的年龄相关稳定性对于旨在最大化成功老化和脑损伤后恢复的训练计划非常重要。

DESCRIPTION (provided by applicant): The primary goal of the proposed research is to understand the relationship between implicit learning and white matter microstructure in younger and older adults. Examining the role of white matter integrity in the aging of implicit learning will extend the emerging literature on lifespan cognitive neuroscience. Implicit learning occurs without intent or awareness of what has been learned, and until recently it has been studied less that its explicit counterpart. This is unfortunate because sensitivity to regularities in the environment is essential throughout life. Recent cognitive and neuroscience research on implicit learning indicates that there are multiple forms of implicit learning that call on different neural substrates, but aging research usually treats implicit learning as though it is unitary. Here, we will focus on a dissociation between two types of implicit learning, sequence learning and spatial context learning, that are especially important for studying age changes in brain-behavior relationships because they call on different brain systems that are differentially affected by healthy aging. Imaging and patient studies suggest that implicit sequence learning relies on a frontal-striatal-cerebellar network, and implicit spatial context learning is mediated by the medial temporal lobes. The proposed experiment will be the first to examine this dissociation in the same group of participants using diffusion tensor imaging (DTI) to measure the integrity of white matter that connects neural networks (Specific Aim 2). DTI research has shown that white matter integrity declines with aging, especially in anterior brain regions, which may affect cognitive performance in healthy older adults. In this study, older adults are expected to be impaired at implicit sequence learning, but not implicit spatial context learning (Specific Aim 1), a finding consistent with the view that healthy aging affects the frontal-striatal system more than the medial temporal lobes. Multiple regression analyses will also examine if age-related brain changes affect the relationships between these two implicit learning tasks and white matter integrity from their corresponding neural networks, being the first to-assess age differences in brain-behavior relationships using implicit learning tasks in which behavioral performance is both impaired and spared with aging (Specific Aim 3). Results from this study are relevant to successful aging. Implicit learning promotes independent living by enabling people to adapt to change (i.e. new settings, people, and technologies), and can facilitate recovery from brain damage following accidents or strokes. Thus, identifying age-related stability between forms of implicit learning and their underlying white matter connectivity is important for training programs aimed at maximizing successful aging and recovery after brain damage.