Functional networks underlying cognitive decline in aging and Alzheimer's disease

衰老和阿尔茨海默病认知能力下降的功能网络

• 批准号: 10758193
• 负责人: Jacob Ziontz
• 金额: $ 4.45万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10758193
• 关键词: Affect; Age; Age-associated memory impairment; Aging; Alzheimer' s Disease; Alzheimer' s disease pathology; Amyloid; Amyloid beta-Protein; Area; Behavior; Behavioral; Biological Markers; Biometry; Brain; Brain region; Characteristics; Cognition; Cognitive; Cognitive aging; Communication; Data; Data Analyses; Disease; Educational process of instructing; Elderly; Ensure; Environment; Episodic memory; Fellowship; Functional Imaging; Functional Magnetic Resonance Imaging; Future; Hippocampus; Imaging Techniques; Impaired cognition; Individual; Lead; Measures; Mediating; Memory; Mentorship; Neocortex; Nerve Degeneration; Network-based; Neuropsychology; Neurosciences; Pathologic; Pathology; Performance; Positron-Emission Tomography; Postdoctoral Fellow; Research; Research Personnel; Resolution; Rest; Role; Synapses; Task Performances; Techniques; Testing; Tracer; Training; Work; age effect; age related; amyloid pathology; behavioral outcome; career; cognitive ability; cognitive change; cognitive function; cognitive neuroscience; cognitive performance; executive function; experimental study; memory encoding; multimodal neuroimaging; neocortical; network dysfunction; neural; neuroimaging; neuromechanism; normal aging; novel; prospective; protein aggregation; tau Proteins; tau aggregation; tool

Project Summary Aging and Alzheimer’s disease (AD) are characterized by progressive cognitive decline, ranging from mild to severe deficits in episodic memory and executive function. In addition, recent work has begun to identify networks of functional connections across the brain whose activity subserve specific cognitive functions. Network dysfunction is a feature of AD, but alterations in cognition-related networks may also be detectable in normal aging. Positron emission tomography (PET) imaging of pathological amyloid-β (Aβ) and tau proteins has revealed that their accumulation is related to cognitive decline in older adults. The mechanisms by which these protein aggregates lead to impaired cognitive function are still not well understood, but recent work suggests that Aβ and tau accumulation may alter the integrity of functional brain networks. This project will investigate the impact of AD pathology on these networks and their role in age-related cognitive decline. Using a novel network definition approach, behaviorally-specific functional networks will be defined in older adults using both resting state and task fMRI data. Neuropsychological episodic memory and executive function measures as well as memory performance in an fMRI task will be used as behavioral outcomes to define these networks. In addition, AD pathology will be measured using the 11C-PiB (Aβ) and 18F-Flortaucipir (tau) PET tracers. In Aim 1, whole-brain resting state functional connectivity will be used to define networks based on episodic memory and executive function performance, and the overall strength of these networks will be related to pathology and cognitive performance. In Aim 2, functional connectivity and behavioral data from a memory encoding fMRI experiment will be used to define a task-based network, which will again be related to pathology and cognition. Finally, in Aim 3, we will compare these networks in terms of their topography, relationship with AD pathology, and ability to predict longitudinal cognitive decline. Overall, this study will investigate changes in functional brain networks as a mechanism by which cognition declines, offering a compelling new tool for researchers to predict cognitive change in aging and disease. Completion of this project will provide training in (1) multimodal neuroimaging and processing, (2) novel biostatistical techniques for neuroimaging data analysis, (3) the cognitive neuroscience of aging and AD, (4) scientific communication, and (5) teaching and mentorship. The Helen Wills Neuroscience Institute at UC Berkeley provides an ideal environment for this research, bringing together world-class experts in neuroimaging, biostatistics, and cognitive neuroscience who will aid in the completion of this project. The sponsor Dr. William Jagust is uniquely suited for overseeing this work, having built a career on applying multimodal neuroimaging techniques to better understand the underlying mechanisms of aging and AD. The proposed research and training plans will ensure the applicant successfully completes the project and is prepared for a competitive post-doctoral fellowship and research career understanding the neural mechanisms of age- and disease-related cognitive decline.

Project Summary Aging and Alzheimer’s disease (AD) are characterized by progressive cognitive decline, ranging from mild to severe deficits in episodic memory and executive function. In addition, recent work has begun to identify networks of functional connections across the brain whose activity subserve specific cognitive functions. Network dysfunction is a feature of AD, but alterations in cognition-related networks may also be detectable in normal aging. Positron emission tomography (PET) imaging of pathological amyloid-β (Aβ) and tau proteins has revealed that their accumulation is related to cognitive decline in older adults. The mechanisms by which these protein aggregates lead to impaired cognitive function are still not well understood, but recent work suggests that Aβ and tau accumulation may alter the integrity of functional brain networks. This project will investigate the impact of AD pathology on these networks and their role in age-related cognitive decline. Using a novel network definition approach, behaviorally-specific functional networks will be defined in older adults using both resting state and task fMRI data. Neuropsychological episodic memory and executive function measures as well as memory performance in an fMRI task will be used as behavioral outcomes to define these networks. In addition, AD pathology will be measured using the 11C-PiB (Aβ) and 18F-Flortaucipir (tau) PET tracers. In Aim 1, whole-brain resting state functional connectivity will be used to define networks based on episodic memory and executive function performance, and the overall strength of these networks will be related to pathology and cognitive performance. In Aim 2, functional connectivity and behavioral data from a memory encoding fMRI experiment will be used to define a task-based network, which will again be related to pathology and cognition. Finally, in Aim 3, we will compare these networks in terms of their topography, relationship with AD pathology, and ability to predict longitudinal cognitive decline. Overall, this study will investigate changes in functional brain networks as a mechanism by which cognition declines, offering a compelling new tool for researchers to predict cognitive change in aging and disease. Completion of this project will provide training in (1) multimodal neuroimaging and processing, (2) novel biostatistical techniques for neuroimaging data analysis, (3) the cognitive neuroscience of aging and AD, (4) scientific communication, and (5) teaching and mentorship. The Helen Wills Neuroscience Institute at UC Berkeley provides an ideal environment for this research, bringing together world-class experts in neuroimaging, biostatistics, and cognitive neuroscience who will aid in the completion of this project. The sponsor Dr. William Jagust is uniquely suited for overseeing this work, having built a career on applying multimodal neuroimaging techniques to better understand the underlying mechanisms of aging and AD. The proposed research and training plans will ensure the applicant successfully completes the project and is prepared for a competitive post-doctoral fellowship and research career understanding the neural mechanisms of age- and disease-related cognitive decline.