Network Analysis and Computational Modeling Core

项目摘要 P60印第安纳州酒精研究中心（IARC）的更新将确定大脑活动的变化， 易使人暴饮暴食和高强度饮酒（BHID）。为了实现这一目标，IARC将收集 大型，密集的数据集，从人类和啮齿动物与一系列的技术，获得多个， 同时测量神经功能。这就迫切需要一个IARC服务核心， 网络分析和计算建模方面的专业知识，以中心的研究组成部分。的目标 NACM是以翻译的方式询问BHID的大脑网络和神经回路。 因此，NCAM的目标是增加物种和组分之间的协同作用和翻译， 并将该中心的数据整合到能够阐明神经系统病理学的计算模型中， BHID的基础电路。NACM将与研究部门密切合作， 开发分析和计算建模技术，以捕获网络和系统级交互。 做到这一点将使国际癌症研究机构得出更加严谨和更加综合的协同结论 件.因此，NCAM将提供先进的、有针对性的分析和计算模型， 加强各组成部分之间的协同作用。这将传播国际癌症研究机构目前在统计分析方面的专门知识 和计算建模的中心。作为一个核心，NACM并不打算测试特定的 假设，而是与研究组成部分密切合作，以增加严谨性和协同作用。这允许 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的 BHID机制的综合模型。这将通过三个具体目标来实现： 具体目标1：确定人类和啮齿动物中BHID的改变的、潜在的翻译网络功能。 具体目标2：应用群体分析和基于人工智能的方法来识别改变的 BHID中的计算与人类和啮齿动物的数据进行比较。 具体目标3：建立BHID中改变的皮质边缘系统的计算模型。 NACM的积极影响将是深入了解大脑网络如何执行计算 在BHID和AUD风险人群中发生改变。理解这一点将激发新的治疗方法 将神经回路功能的遗传变化与BHID更紧密地联系起来。

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.