Characterizing Genetic, Neurotransmitter receptors and Macroscopic Brain Interactions via Multi-scale Analytical Modeling

通过多尺度分析模型表征遗传、神经递质受体和宏观大脑相互作用

• 批准号: RGPIN-2021-02670
• 负责人: IturriaMedina, Yasser
• 金额: $ 2.7万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=761344
• 关键词: Characterizing; Genetic; Neurotransmitter; receptors; Macroscopic

Amongst the multiple challenges that we are faced when trying to understand the brain, our current inability at integrating multiscale data (molecular, neuroimaging, cognitive, behavioral) into a unified generative model stands out. To solve this problem requires the development of novel mathematical, neuroscience and computational techniques, which form the basis of this proposal. From the molecular (e.g. genes, neurotransmitter receptors) to the macroscopic (e.g. neuroimaging) scales, the brain constitutes a complex dynamic system. It is known that each cognitive/behavioral state is the result of concurrent causal interactions between the multiple biological scales. However, most generative models of brain dynamics only focus on macroscopic functional brain signals, not characterizing the molecular basis underlying brain multifactorial dynamics and, importantly, failing to consider other crucial biological factors (e.g. cerebrovascular flow, metabolism, neuronal tissue density). This research aims to: i)Construct an integrative mathematical model to consider the spatiotemporal multiscale and multifactorial interactions between genes, neurotransmitter receptors, multifactorial macroscopic brain factors (neuronal activity integrity, glucose metabolism, vascular flow, gray matter density) and individual cognitive/behavioral properties. We will use dynamic system equations to define a unifying formulation capturing the direct interactions among across-scales biological factors and cognitive/behavioral states. Data from large-scale databases (e.g. Allen Brain Atlas, receptors atlases from Research Center Julich, Gene Expression Omnibus) will be used for developing the model and validating its applicability. We hypothesize that the post-hoc analysis of personalized transcriptomic-receptor-imaging model parameters will reveal essential biological mechanisms. ii)Use the defined molecular-neuroimaging-cognitive brain framework to characterize the molecular and macroscopic impact of different demographic (sex, gender, educational level), life style (diet, physical exercise, sleep habits) and environmental conditions (geographic location, social and community context) on each individual's brain and cognition/behavior. We hypothesize that post-hoc analysis of model parameters will clarify the biological impact of different demographic, lifestyle and environmental conditions. iii)Share all resulting analytic tools with the research community via an already developed open-access user-friendly software. Sharing the integrated molecular-neuroimaging-cognitive brain framework will accelerate its validation and international use. This program will train 4 HQPs (2 MAs and 2 PhDs) and enhance our understanding of the spatiotemporal multiscale brain interactions underlying human cognition and behavior; thus, establishing the critical foundation for understanding and modulating multifactorial brain states from a mechanistic perspective.

在我们试图理解大脑时所面临的诸多挑战中，我们目前无法将多尺度数据（分子、神经成像、认知、行为）整合到一个统一的生成模型中。为了解决这个问题，需要发展新的数学、神经科学和计算技术，这些技术构成了本提案的基础。从分子层面（如基因、神经递质受体）到宏观层面（如神经成像），大脑构成了一个复杂的动态系统。我们知道，每一种认知/行为状态都是多个生物尺度之间同时发生的因果相互作用的结果。然而，大多数脑动力学的生成模型只关注宏观的脑功能信号，而没有表征脑多因子动力学的分子基础，更重要的是，没有考虑其他关键的生物学因素（如脑血管流量、代谢、神经元组织密度）。本研究旨在：1)构建一个综合的数学模型，以考虑基因、神经递质受体、多因素宏观脑因素（神经元活动完整性、葡萄糖代谢、血管流动、灰质密度）和个体认知/行为特性之间的时空多尺度多因子相互作用。我们将使用动态系统方程来定义一个统一的公式，以捕获跨尺度生物因素和认知/行为状态之间的直接相互作用。来自大型数据库的数据（例如Allen Brain Atlas，来自Julich研究中心的受体地图集，Gene Expression Omnibus）将用于开发模型并验证其适用性。我们假设个性化转录组-受体-成像模型参数的事后分析将揭示基本的生物学机制。ii)使用已定义的分子-神经成像-认知脑框架来表征不同人口统计学（性别、性别、教育水平）、生活方式（饮食、体育锻炼、睡眠习惯）和环境条件（地理位置、社会和社区背景）对每个人的大脑和认知/行为的分子和宏观影响。我们假设，模型参数的事后分析将澄清不同的人口统计，生活方式和环境条件的生物影响。iii)通过已开发的开放获取的用户友好软件与研究社区共享所有结果分析工具。共享集成的分子-神经成像-认知脑框架将加速其验证和国际应用。该计划将培养4名HQPs（2名硕士和2名博士），并加强我们对人类认知和行为背后的时空多尺度大脑相互作用的理解；因此，建立了从机制角度理解和调节多因素大脑状态的关键基础。