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

摘要 额叶的白色物质变性和突触丢失是最明显的神经变化 与年龄相关的认知能力下降 ，但这些变化影响解剖神经的程度 体内的电路和网络动力学在很大程度上是未知的。 在最近的人类研究中，相关的功能性MRI 在解剖学上相关的大脑区域发现的BOLD信号波动已被用于推断功能 “静息态”网络（RSN）连接，提供了一个有前途的非侵入性手段来研究的动态 活体脑网络 .解读在体全脑网络中年龄相关变化之间的关系 活动和细胞分子结构是理解认知衰老和神经退行性疾病的关键。 阿尔茨海默病和相关痴呆症（ADRD）是人类大脑中的一种疾病。的重点 该项目是关于与认知和衰老有关的功能不同的前额叶区域-- 外侧前额叶皮层 （LPFC）和内侧前额叶前扣带皮层（ACC）-参与不同的功能网络 在认知过程中扮演着不同的角色特别是ACC已经被牵连在控制功能 网络状态和RSN全脑动力学来调节灵活的行为，但确切的机制不是 完全理解不同前额叶区的兴奋性和抑制性微回路，以及它们的外在 通路可能在塑造功能连接的动态方面发挥重要作用。然而，在深度 解剖学和神经化学细胞和分子验证体内MRI测量的连通性， 还没有评估微结构的完整性以及这些性质如何随时间变化。这项建议旨在 揭示这些解剖回路的特性及其与RSN年龄相关变化的关系 动力学和认知能力的下降在我们完善的恒河猴模型的正常老化。根据振型分解 MRI和认知测试，结合单细胞转录组学，体外电生理学，神经束- 跟踪和高分辨率显微镜在年轻和老年成年恒河猴（猕猴），我们将 强调不同RSN年龄相关变化特征及其与白色物质完整性的关系， LPFC和ACC中的兴奋-抑制回路和外源性通路。我们将使用这种大规模的多模式 MRI和微观结构数据集，以建立一个可以定义生物标志物的计算机器学习框架 认知老化这一建议的总体假设是，功能和结构网络 LPFC和ACC区域的连通性和兴奋：抑制（E：I）平衡被不同地改变， 年龄，在模式下，与年龄相关的认知能力下降的特定方面。 建议的多式联运 研究将产生可用于推断人类大脑网络的神经基质并预测如何 他们会随着年龄而变化。这些数据将为开发新的神经功能成像生物标志物提供信息。 与衰老中的认知障碍相关的电路功能障碍，可以扩展到相关的 神经精神和神经变性疾病。

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.