Dynamic approaches to understanding social cognitive aging: A social network neuroscience approach

项目摘要 社会联系对于促进健康老龄化至关重要，包括延迟发病 老年痴呆症（AD）发展和维持社会关系依赖于 社会认知功能--人们理解、储存和应用的过程 关于其他人的信息。然而，健康的老龄化和AD与 社会认知功能确定这种下降背后的机制至关重要 最终改善AD的临床进程。神经科学是唯一适合 确定这些机制，因为社会行为背后的大脑区域 被很好地描述了。然而，在这一领域的有限工作， 阐明了大脑激活与老年人社会认知缺陷的关系。一 其原因可能是它依赖于相对狭窄的大脑激活措施， 贫乏的刺激，忽视了大脑功能和社会功能的动态本质， 交互.目前的建议通过应用尖端的 方法从网络神经科学领域到社会认知老化领域，研究如何 大脑网络中与年龄相关的变化-大脑区域的集合， 不成比例地影响社会认知功能。使用此 新的社交网络神经科学框架将最终改变我们对 健康老龄化和AD破坏社会认知功能的机制。在 目的1，我们比较了聚焦于特定大脑激活的传统方法 区域到大脑网络的方法，以确定哪些更好地涉及社会 认知缺陷（例如，心理理论;推断他人心理状态的能力）。目的2 探索老年人不太稳定的大脑网络是否能预测他们的心理理论 赤字该目的的探索性目标是确定动态（更多 自然主义）刺激提供了更大的洞察力与年龄相关的社会认知缺陷比 传统的静态刺激最后，目标3挑战了目前的假设，即老年人 社交认知缺陷仅限于他们的大脑在任务中的参与方式。具体地说， 我们研究了老年人的基线脑网络结构（在静息状态下） 预测他们随后的任务表现，并将此问题扩展到AD样本。 这项拟议中的研究将尖端的网络神经科学方法与社会学方法相结合， 认知老化，以促进我们对健康老龄化和AD的理解。最终这 该项目将有助于确定新的干预目标，以减缓AD的进展。

PROJECT SUMMARY Social connectedness is critical for promoting healthy aging, including delaying the onset of Alzheimer’s disease (AD). Developing and maintaining social relationships relies on social cognitive function – the process by which people understand, store, and apply information about others. However, healthy aging and AD are associated with declines in social cognitive function. Identifying the mechanisms underlying this decline is essential for ultimately improving the clinical course of AD. Neuroscience is uniquely suited to identify these mechanisms because the brain regions underlying social behavior have been well-characterized. However, the limited work in this domain has fallen short in elucidating how brain activation relates to older adults’ social cognitive deficits. One reason for this might be its reliance on relatively narrow measures of brain activation and impoverished stimuli, which neglect the dynamic nature of brain function and of social interactions. The current proposal addresses these gaps by applying cutting-edge methods from the field of network neuroscience to social cognitive aging to examine how age-related changes in brain networks – collections of brain regions that communicate disproportionately more with each other – affect social cognitive function. Using this novel social network neuroscience framework will ultimately transform our understanding of the mechanisms by which healthy aging and AD disrupt social cognitive function. In Aim 1, we compare traditional approaches of focusing on activation in specific brain regions to a brain networks approach in order to determine which better relates to social cognitive deficits (e.g., theory of mind; the ability to infer others’ mental states). Aim 2 explores whether older adults’ less stable brain networks predict their theory of mind deficits. An exploratory goal of this aim is to determine whether dynamic (more naturalistic) stimuli provide greater insight into age-related social cognitive deficits than traditional, static stimuli. Finally, Aim 3 challenges current assumptions that older adults’ social cognitive deficits are limited to how their brains engage during tasks. Specifically, we examine whether older adults’ baseline brain network structure (during resting state) predicts their subsequent task performance, and extend this question to an AD sample. The proposed study combines cutting-edge network neuroscience methods with social cognitive aging to advance our understanding of healthy aging and AD. Ultimately, this project will help identify novel targets for intervention to slow the progression of AD.