Brain network mechanisms of aging-related cognitive decline

衰老相关认知能力下降的脑网络机制

• 批准号: 10543603
• 负责人: Michael William Cole
• 金额: $ 39.17万
• 依托单位: RUTGERS THE STATE UNIV OF NJ NEWARK
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-03-01 至 2023-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10543603
• 关键词: Administrative Supplement; Affect; Age; Aging; Alzheimer' s Disease; Amyloid beta-Protein; Award; Behavior; Brain; Brain region; COVID-19 pandemic; Cognition; Cognitive deficits; Data; Data Analyses; Data Collection; Elderly; Functional Magnetic Resonance Imaging; Funding; Goals; Grain; Grant; Impaired cognition; Individual Differences; Interruption; Knowledge; Learning; Life; Link; Liquid substance; Literature; Measures; Mediating; Memory impairment; Meta-Analysis; Methods; Movement; Network-based; Neurodegenerative Disorders; Participant; Pathway interactions; Patient Recruitments; Play; Process; Property; Public Health; Rest; Role; Route; Series; Task Performances; Testing; Time; Training; base; cognitive ability; cognitive control; cognitive process; cognitive reserve; cognitive task; cognitive training; experience; healthy aging; improved; improved outcome; innovation; long term memory; recruit; relating to nervous system; tool; young adult

PROJECT SUMMARY/ABSTRACT Aging-related cognitive decline has been independently linked to alterations in resting-state functional connectivity (RSFC) and cognitive task activations using functional MRI (fMRI), yet it is now well established that there is a strong statistical relationship between RSFC and task activations. This is despite these being quite distinct measures: RSFC is calculated as correlations among distributed brain activity time series during rest, while task activations are localized brain activity amplitude changes during active task performance. The network mechanisms underlying the RSFC-activation relationship are unknown, yet understanding this relationship would clarify how aging alters both RSFC and cognitive task activations. For RSFC, linking to cognitive task activations may help explain why RSFC is associated with cognitive processes despite being measured independently of tasks testing those processes. For cognitive task activations, linking to RSFC may bring a unified network-based understanding to the varied aging-related activation changes identified across many brain regions and tasks. Thus, there is a critical need to determine the network mechanisms underlying the relationship between RSFC and cognitive task activations. Without such knowledge, obtaining a unified understanding of the neural basis of aging-related cognitive decline is unlikely. The overall objective of this proposal is to identify network mechanisms that can account for the alterations in both RSFC and cognitive task activations that occur with aging-related decline (from ages 18-28 to 65-75) of cognitive control abilities among healthy older adults. This focus on cognitive control reflects its importance to adaptive, goal-directed behavior in daily life. Further, cognitive control network (CCN) regions have RSFC network “hub” properties well suited to regulate general cognitive ability. Of particular relevance to aging, cognitive control is one of the abilities most affected by both healthy aging and Alzheimer’s disease, and it plays a role in long-term memory deficits (a key feature of Alzheimer’s disease). This proposal’s central hypothesis is that aging-related alterations in RSFC reflect changes in intrinsic network pathways that influence brain activations during task performance, and hence mediate disruption of cognitive control abilities. Three approaches will be utilized across three aims to test our central hypothesis. Briefly, the first will utilize an innovative approach to predict activation abnormalities based on RSFC abnormalities in healthy older adults. The second will utilize individual differences to determine the contribution of CCN hub disruption to aging-related cognitive decline. The third will utilize the established influence of cognitive training on RSFC to investigate the role of functional network plasticity in aging-related cognitive decline. This project is expected to markedly improve understanding of the brain network basis of cognitive decline from healthy aging, in addition to improving general understanding of the large-scale network mechanisms underlying cognition.

项目摘要/摘要 与衰老相关的认知下降已与静息状态功能的改变独立联系 使用功能MRI（fMRI）的连接性（RSFC）和认知任务激活，但现在已经建立了 RSFC和任务激活之间存在牢固的统计关系。这是dospite 非常不同的措施：RSFC计算为分布式大脑活动时间序列之间的相关性 休息，而任务激活是在主动任务执行过程中局部大脑活动放大器。 RSFC激活关系基础的网络机制尚不清楚，但要理解这一点 关系将阐明衰老如何改变RSFC和认知任务激活。对于RSFC，链接到 认知任务激活可能有助于解释为什么RSFC与认知过程有关 独立于测试这些过程的任务进行衡量。对于认知任务激活，链接到RSFC可能 将基于网络的统一理解带入各种与衰老相关的激活变化 许多大脑区域和任务。这是确定网络机制的迫切需要 RSFC和认知任务激活之间的关系。没有这样的知识，获得统一 了解与衰老相关的认知下降的神经基础的理解是不可能的。总体目标 建议是确定可以说明RSFC和认知改变的网络机制 随着衰老相关的下降（从18-28岁到65-75岁）的任务激活的认知控制能力 在健康的老年人中。对认知控制的重点反映了其对适应性，目标定向的重要性 日常生活中的行为。此外，认知控制网络（CCN）区域具有RSFC网络“集线器”属性 非常适合调节一般认知能力。与衰老特别相关，认知控制是 受健康衰老和阿尔茨海默氏病影响最大的能力，它在长期记忆中起作用 缺陷（阿尔茨海默氏病的关键特征）。该提议的中心假设是与衰老有关 RSFC的变化反映了在任务过程中影响大脑激活的内在网络途径的变化 性能，从而介导认知控制能力的破坏。将使用三种方法 在三个目标中，旨在检验我们的中心假设。简而言之，第一个将利用一种创新的方法来预测 基于健康老年人的RSFC异常的激活异常。第二个将利用个人 确定CCN中心破坏对与衰老相关的认知能力下降的贡献的差异。第三名 利用认知培训对RSFC的既定影响来研究功能网络的作用 与衰老相关的认知下降中的可塑性。预计该项目将显着提高对 除了提高对健康衰老的认知能力下降的基础外，还提高了对 认知基础的大规模网络机制。

项目成果

Combining Multiple Functional Connectivity Methods to Improve Causal Inferences.

• DOI: 10.1162/jocn_a_01580
• 发表时间: 2021-03
• 期刊: Journal of cognitive neuroscience
• 影响因子: 3.2
• 作者: Sanchez-Romero R;Cole MW
• 通讯作者: Cole MW

Latent functional connectivity underlying multiple brain states.

• DOI: 10.1162/netn_a_00234
• 发表时间: 2022-06
• 期刊: NETWORK NEUROSCIENCE
• 影响因子: 4.7
• 作者: McCormick, Ethan M;Arnemann, Katelyn L;Ito, Takuya;Hanson, Stephen Jose;Cole, Michael W
• 通讯作者: Cole, Michael W

Constructing neural network models from brain data reveals representational transformations linked to adaptive behavior.

• DOI: 10.1038/s41467-022-28323-7
• 发表时间: 2022-02-03
• 期刊: Nature communications
• 影响因子: 16.6
• 作者: Ito T;Yang GR;Laurent P;Schultz DH;Cole MW
• 通讯作者: Cole MW

Activity flow underlying abnormalities in brain activations and cognition in schizophrenia.

• DOI: 10.1126/sciadv.abf2513
• 发表时间: 2021-07
• 期刊: Science advances
• 影响因子: 13.6
• 作者: Hearne LJ;Mill RD;Keane BP;Repovš G;Anticevic A;Cole MW
• 通讯作者: Cole MW

Structural MRI and functional connectivity features predict current clinical status and persistence behavior in prescription opioid users.

结构 MRI 和功能连接特征可预测处方阿片类药物使用者当前的临床状态和持续行为。

• DOI: 10.1016/j.nicl.2021.102663
• 发表时间: 2021
• 期刊: NeuroImage. Clinical
• 作者: Mill RD;Winfield EC;Cole MW;Ray S
• 通讯作者: Ray S