Network Analysis and Computational Modeling Core

网络分析和计算建模核心

• 批准号: 10526832
• 负责人: CHRISTOPHER COURT LAPISH
• 金额: $ 15.88万
• 依托单位: INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS
• 依托单位国家: 美国
• 财政年份: 1989
• 资助国家: 美国
• 起止时间: 1989-12-01 至 2027-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10526832
• 关键词: ARHGEF5 gene; Alcohol consumption; Alcohols; Area; Articulation; Artificial Intelligence; Behavioral; Biophysics; Brain; Complement; Computer Models; Data; Data Analyses; Data Set; Electrophysiology (science); Functional Magnetic Resonance Imaging; Genetic Determinism; Goals; Heritability; Human; Impairment; Indiana; Lead; Link; Measures; Modeling; NCAM1 gene; Network-based; Neurobiology; Neurophysiology - biologic function; Pathology; Pathway Analysis; Population; Population Analysis; Predisposition; Prosencephalon; Research; Risk; Rodent; Services; Signal Transduction; Source; Statistical Data Interpretation; System; Techniques; Testing; Translations; Work; addiction; alcohol research; alcohol response; alcohol use disorder; dynamic system; experience; high intensity drinking; insight; multidimensional data; neural; neural circuit; novel; novel strategies; synergism; translational potential; virtual

Project Summary This renewal of the P60 Indiana Alcohol Research Center (IARC) will identify the changes in brain activity that predispose one to Binge and High Intensity Drinking (BHID). Towards this goal, the IARC will be collecting large, dense data sets from humans and rodents with a range of techniques that acquire multiple, simultaneous measures of neural function. This creates a critical need for an IARC service core that provide expertise in network analysis and computational modeling to the center’s research components. The goal of the NACM is to interrogate the brain networks and neural circuits that underlie BHID in a translational manner. The objective of the NCAM is to therefore increase synergy and translation across species and components, and to integrate the center’s data into computational models capable of articulating the pathology in neural circuits that underlie BHID. The NACM will work closely with the research components to implement and develop analyses and computational modeling techniques that capture network and systems-level interactions. Accomplishing this will provide added rigor and more integrated, synergistic conclusions generated by IARC components. Thus, the NCAM will provide advanced, targeted analyses and computational models that increase synergy among the components. This will disseminate current IARC expertise in statistical analyses and computational modeling to the center more broadly. As a core, the NACM does not set out to test specific hypotheses, but rather, to work closely with the research components to add rigor and synergy. This allows each component to assess their hypotheses more effectively, with the long-term goal of providing more integrated model of the mechanisms of BHID. This will be accomplished in three Specific Aims: Specific Aim 1: Identify altered, potentially translational, network functions in BHID in humans and rodents. Specific Aim 2: Apply population analysis and artificial intelligence-based approaches to identify altered computations in BHID to human and rodent data. Specific Aim 3: Build computational models of corticolimbic systems altered in BHID. The positive impact of the NACM will be to provide insight into how computations performed by brain networks are altered in those at risk for BHID and AUD. Understanding this will inspire novel approaches to treatment that more tightly link heritable changes in neural circuit function to BHID.

项目摘要 P60印第安纳州酒精研究中心(IARC)的这次更新将确定大脑活动的变化 使人容易酗酒和高强度饮酒(BHID)。为了实现这一目标，IARC将收集 来自人类和啮齿动物的大量、密集的数据集，使用一系列技术获取多个、 同时测量神经功能。这就产生了对IARC服务核心的迫切需求，该服务核心提供 在网络分析和计算建模方面的专业知识，为中心的研究组件。的目标是 NACM将以翻译的方式询问BHID背后的大脑网络和神经电路。 因此，NCAM的目标是增加跨物种和组件的协同作用和翻译， 并将该中心的数据整合到能够阐明神经病理的计算模型中 BHID背后的电路。NACM将与研究部门密切合作，实施和 开发捕获网络和系统级交互的分析和计算建模技术。 实现这一点将增加IARC产生的更严格和更综合的、协同的结论 组件。因此，NCAM将提供先进的、有针对性的分析和计算模型 提高各组成部分之间的协同效应。这将传播目前IARC在统计分析方面的专业知识 以及更广泛的计算建模到中心。作为一个核心，NACM并不打算测试特定的 更确切地说，是与研究组成部分密切合作，以增加严密性和协同性。这使得 每个组成部分更有效地评估他们的假设，长期目标是提供更多 BHID作用机理的综合模型。这将通过三个具体目标来实现： 具体目标1：确定BHID在人类和啮齿动物中的改变，潜在的翻译，网络功能。 具体目标2：应用人口分析和基于人工智能的方法来识别变化 BHID中对人类和啮齿动物数据的计算。 具体目标3：建立BHID改变的皮质边缘系统的计算模型。 NACM的积极影响将是提供对大脑网络如何执行计算的洞察 在BHID和AUD的风险人群中发生改变。了解这一点将启发治疗的新方法 这更紧密地将神经回路功能的可遗传变化与BHID联系在一起。