Prefrontal-cingulate functional networks in aging monkeys: neural circuit substrates of cognitive aging

摘要 额叶白质变性和突触丢失是最明显的神经变化 与年龄相关的认知功能下降有关 ，但这些变化对解剖神经的影响程度 活体内的电路和网络动力学在很大程度上是未知的。 在最近的人体研究中，相关的功能磁共振 在与解剖学相关的大脑区域发现的大胆信号波动已被用来推断功能 “休眠状态”网络(RSN)连接，提供了一种很有前途的非侵入性手段来研究 活体中的脑网络 。破译体内全脑网络中与年龄相关的变化之间的关系 活动和细胞-分子结构是理解认知老化和神经退行性变的关键 人类大脑中的阿尔茨海默病和相关痴呆症(ADRD)。这件事的重点是 该项目是关于与认知和衰老有关的不同功能的前额叶区域-- 外侧前额叶皮质 (LPFC)和内侧前额叶前扣带回皮质(ACC)--参与不同的功能网络 并在认知过程中扮演不同的角色。特别是ACC被牵连到控制功能 网络状态和RSN全脑动力学调节灵活的行为，但确切的机制还不是 完全理解。不同前额叶区域内的兴奋性和抑制性微回路及其外源性 通路可能在塑造功能连接的动态过程中发挥重要作用。然而，深入地讲， 活体MRI连通性测量的解剖学和神经化学细胞和分子验证 微观结构的完整性以及这些特性如何随着年龄的变化还没有得到评估。这项提议旨在 揭示这些解剖环路的特性及其与RSN年龄相关变化的关系 我们建立的恒河猴正常衰老模型中的动力学和认知衰退。使用多模式 核磁共振和认知测试，结合单细胞转录，体外电生理学，神经束- 在幼年和老年成年恒河猴(Macaca Mulatta)的示踪和高分辨率显微镜下，我们将 突出不同RSN中年龄相关变化的特征及其与白质完整性的关系， LPFC和ACC中的兴奋-抑制回路和外在通路。我们将使用这种大规模的多式联运 MRI和显微结构数据集，以构建可以定义生物标记物的计算机器学习框架 认知老化的影响。这一提议的总体假设是功能和结构网络 连接性和兴奋性：LPFC和ACC区域的抑制性(E：I)平衡随 年龄，在与年龄相关的认知衰退的特定方面的基础上。 建议的多式联运 研究将产生可用于推断人脑网络的神经底物并预测如何 它们会随着年龄的增长而变化。这些数据将为神经功能成像生物标志物的开发提供信息 与衰老中的认知障碍相关的电路功能障碍，可以延伸到相关的 神经精神和神经退行性疾病。

Abstract White matter degeneration and synapse loss in the frontal lobe are the most pronounced neural changes associated with age-related cognitive decline , but the extent to which these changes affect anatomical neural circuits and network dynamics in vivo are largely unknown. In recent human studies, correlated functional MRI BOLD signal fluctuations found across anatomically related brain areas have been used to infer functional “resting-state” network (RSN) connectivity, providing a promising non-invasive means to study the dynamics of brain networks in vivo . Deciphering the relationships between age-related changes in in vivo whole-brain network activity and the cellular-molecular architecture is key to understanding cognitive aging and neurodegenerative disease, such as Alzheimer’s Disease and Related Dementias (ADRD), in the human brain. The focus of this project is on functionally-distinct prefrontal areas implicated in cognition and aging-- the lateral prefrontal cortex (LPFC),) and medial prefrontal anterior cingulate cortex (ACC)—which participate in distinct functional networks and have diverse roles in cognitive processing. The ACC in particular has been implicated in controlling functional network states and RSN whole brain dynamics to mediate flexible behavior, but the exact mechanisms are not fully understood. The excitatory and inhibitory microcircuits within distinct prefrontal areas, and their extrinsic pathways likely play an important role in shaping the dynamics of functional connectivity. However, in depth anatomical and neurochemical cellular and molecular validation of in vivo MRI measures of connectivity and microstructural integrity and how these properties change with age have not been assessed. This proposal aims to unravel the properties of these anatomical circuits and their relationships with age-related changes in RSN dynamics and cognitive decline in our well-established rhesus monkey model of normal aging. Using multimodal MRI and cognitive testing, combined with single-cell transcriptomics, in vitro electrophysiology, neural tract- tracing and high-resolution microscopy in young and aged adult rhesus monkeys (Macaca mulatta), we will highlight features of age-related changes in distinct RSNs and their relationship to white matter integrity, excitatory-inhibitory circuitry and extrinsic pathways in LPFC and ACC. We will use this large-scale multi-modal MRI and microstructural dataset to build a computational machine learning framework that can define biomarkers of cognitive aging. The overall hypothesis of this proposal is that functional and structural network connectivity and excitatory:inhibitory (E:I) balance of LPFC and ACC areas are differentially altered with age, in patterns that underlie specific aspects of age-related cognitive decline. The proposed multimodal studies will yield data that can be used to infer the neural substrates of human brain networks and predict how they change across age. These data will inform development of novel functional imaging biomarkers for neural circuit dysfunctions associated with cognitive impairments in aging, which can be extended to related neuropsychiatric and neurodegenerative diseases.