Resting brain networks and implicit learning in healthy aging

健康老龄化过程中的休息大脑网络和内隐学习

• 批准号: 8649660
• 负责人: Chelsea Marie Stillman
• 金额: $ 3万
• 依托单位: GEORGETOWN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8649660
• 关键词: Accounting; Adult; Age; Aptitude; Awareness; Behavioral; Brain; Brain region; Budgets; Cognitive; Communication; Complex; Conscious; Elderly; Environment; Event; Fostering; Functional Magnetic Resonance Imaging; Future; Goals; Habits; Image; Independent Living; Individual; Individual Differences; Laboratory Study; Language Development; Learning; Life; Measures; Medial; Mediating; Pattern; Performance; Predictive Value; Process; Psyche structure; Quality of life; Readiness; Reporting; Research; Rest; Scanning; Stroke; System; Technology; Temporal Lobe; Testing; Time; Triplet Multiple Birth; Uncertainty; age difference; age group; age related; base; cognitive function; healthy aging; improved; insight; interest; nerve injury; neuromechanism; public health relevance; relating to nervous system; sequence learning; skills; young adult

DESCRIPTION (provided by applicant): The overall aim of this project is to test our hypothesis that the intrinsic communication of neural systems in the absence of any external goals or task demands (i.e., in a resting state), predicts individual and age differences in implict probabilistic sequence learning (IL). IL is a type of learning that occurs without conscious awareness or intent and is central to many fundamental life skills, such as adapting to ever-changing technologies and environments. It is important to examine the neural mechanisms underlying the age-related deficits in IL that are typically observed when older adults are compared to younger ones because being able to learn in this way can have implications for maintaining independence and quality of life. How brain regions communicate with each other in a resting state--when mental activity is unconstrained--has recently emerged as an important neural mechanism underlying individual and age differences in cognitive functioning. A measure of resting state communication, called resting state functional connectivity (rsFC) has even been found to predict future individual differences in cognitive performance, suggesting that rsFC may be promoting a neural system's "readiness" to perform cognitive tasks. So far, however, research on the predictive value of rsFC for performance on specific cognitive processes, such as learning, is limited. The proposed study will be the first to examine whether rsFC can predict individual and adult age differences in a type of implicit learning in which people must become sensitive to subtle probabilistic patterns. Aim 1 will measure rsFC before healthy young and older adults complete a measure of IL, the Triplets Learning Task (TLT), and will assess whether individual differences in rsFC between task-relevant regions predict IL in the TLT. It is hypothesized that more positive rsFC between the caudate and MTL, two brain regions known to be coactivated during IL, will predict better IL in both young and older adults and also mediate age differences in IL. These hypotheses are based on the preliminary study for this proposal, which found the predicted relationship between caudate-MTL connectivity and IL in younger adults, and on previous fMRI studies showing that age differences in IL are related to the task-evoked activity of these regions. Aim 2 will assess how rsFC, measured prior to the TLT, relates to patterns of connectivity during the TLT, and how changes in connectivity between the rest and task states relate to IL. We hypothesize that (1) young adults will show greater changes in connectivity from rest to task than older adults and (2) Greater changes in connectivity between the caudate and MTL from rest to task will be related to better IL for both age groups. These hypotheses are based on studies showing that functional connections between brain regions change based on cognitive state, and on studies showing declines in the state-related adaptability of functional connections with age. Characterizing the neural systems underlying IL will foster a better understanding of the changes in essential behavioral functions that occur in healthy aging.

描述（由申请人提供）：该项目的总体目标是测试我们的假设，即在没有任何外部目标或任务要求的情况下，神经系统的内在通信（即，在休息状态下），预测个体和年龄的差异，隐含的概率序列学习（IL）。IL是一种在没有意识或意图的情况下发生的学习，是许多基本生活技能的核心，例如适应不断变化的技术和环境。重要的是要检查与年龄相关的IL缺陷的神经机制，这些缺陷通常在老年人与年轻人相比时观察到，因为能够以这种方式学习可能对保持独立性和生活质量有影响。大脑区域如何在休息状态下相互交流-当心理活动不受约束时-最近已经成为认知功能中个体和年龄差异的重要神经机制。一种被称为静息状态功能连接（resting state functional connectivity，rsFC）的静息状态通信测量方法甚至被发现可以预测未来认知表现的个体差异，这表明rsFC可能正在促进神经系统执行认知任务的“准备”。然而，到目前为止，关于rsFC对特定认知过程（如学习）的预测价值的研究有限。这项研究将是第一个研究rsFC是否可以预测一种内隐学习中的个体和成人年龄差异的研究，在这种内隐学习中，人们必须对微妙的概率模式变得敏感。目标1将在健康的年轻人和老年人完成IL测量（三胞胎学习任务（TLT））之前测量rsFC，并将评估任务相关区域之间rsFC的个体差异是否可预测TLT中的IL。据推测，尾状核和MTL（已知在IL期间共激活的两个大脑区域）之间的rsFC阳性率较高，将预示年轻人和老年人的IL水平更高，并且还介导 年龄差异大。这些假设是基于对这一提议的初步研究，该研究发现在年轻人中尾状核-MTL连接和IL之间的预测关系，以及先前的fMRI研究表明IL的年龄差异与这些区域的任务诱发活动有关。目标2将评估在TLT之前测量的rsFC如何与TLT期间的连接模式相关，以及休息和任务状态之间的连接变化如何与IL相关。我们假设：（1）年轻人从休息到任务的连接变化比老年人更大;（2）从休息到任务的尾状核和MTL之间的连接变化更大，这与两个年龄组的IL更好有关。这些假设是基于研究表明，大脑区域之间的功能连接根据认知状态而变化，以及研究表明功能连接的状态相关适应性随着年龄的增长而下降。表征IL背后的神经系统将促进对健康老龄化中发生的基本行为功能变化的更好理解。