CRCNS: Functional Brain Networks with Tensioned Stability for Optimal Processing
CRCNS: Functional Brain Networks with Tensioned Stability for Optimal Processing
批准号:
10488285
负责人:
Erik Bollt
金额:
$33.38万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-09-15 至 2025-08-31
关键词:
AdolescenceAlcohol consumptionAlcoholsAreaBiologicalBrainBrain DiseasesBrain imagingBrain regionClinical ResearchCognitiveCoinDataData SetDevelopmentDiagnosisEtiologyFormulationFunctional ImagingFutureHumanKnowledgeLeadMapsMathematical Model SimulationMathematicsMethodologyMethodsNeurosciencesParticipantPatient CarePlayPrincipal InvestigatorProcessRestRoleScienceSeriesSystemTimeWorkalcohol misusealcohol use disorderbasebrain dysfunctioncooperative studydesigndrinking behavioreffective therapyflexibilityneurodevelopmentneuroimagingnovel diagnosticsnovel therapeutic interventionpotential biomarkerrelating to nervous systemsuccesstargeted therapy trialsunderage drinking
中文摘要
了解酒精使用和滥用背后的大脑过程对于发展
有效治疗酒精使用障碍或AUD。人脑成像在很大程度上造就了我们目前的
对澳元的了解,但还有更多的事情需要了解。最近,人类神经科学一直在
由网络科学和神经成像(现在被称为网络神经科学)的整合而转变。
脑功能成像被用来产生网络来检查相互关联的同步组
大脑区域。这个项目的主要假设是大脑同步只有大脑
大脑网络故事。这项研究断言,起作用的大脑网络实际上有两个关键的子层。
第一层是使用相关方法识别的良好建立的同步网络,
称为协作功能网络(CFN)。第二层是一个建议的网络,它可以抵抗
同步,被称为不渗透功能网络(干扰素)。干扰素对于转移来说是必不可少的
子网络内部和子网络之间的同步,以支持认知需求的变化。这两个层面
在紧张中共存,每个人都扮演着各自的角色,以支持稳定而灵活的大脑功能。这个项目
数学建模与仿真相结合的方法在饮酒预测中的应用
国家酒精与青春期神经发育联盟(NCANDA)数据集中的行为。
该项目的成功将证明,CFN和干扰素都是更完整的
了解正常和异常的大脑功能。我们迫切需要更深入的了解
关于酒精使用/滥用以及更好地诊断和治疗AUD的建议。不幸的是,潜在的生物标志物
针对这些疾病的治疗试验不断失败。这个项目可能会有变革性的
潜力,因为它带来了一种以前未被发现的大脑组织原理,并可能导致新的
基于对CFN和干扰素的综合认识的诊断和治疗策略设计。在……里面
除了改变我们对AUD的理解,这项工作还有可能给临床带来革命性的变化
研究和护理一系列脑部疾病的患者。
英文摘要
Understanding the brain processes underlying alcohol use and misuse are essential for the development of
effective treatments for alcohol use disorder or AUD. Human brain imaging has greatly contributed to our current
understanding of AUD, but much more remains to be understood. Most recently, human neuroscience has been
transformed by the integration of network science and neuroimaging (now coined network neuroscience).
Functional brain imaging is used to generate networks to examine interconnected groups of synchronized
brain regions. The overarching hypothesis of this project is that brain synchronization is only half of the
brain network story. This work asserts that functional brain networks actually have two critical sublayers.
The first layer is the well-established network of synchronization that is identified using correlation methods,
called the cooperative functional network (cFN). The second layer is a proposed network that resists
synchronization and is called the impervious functional network (iFN). The iFN is essential for shifting
synchronization within and between subnetworks to support shifts in cognitive demands. The two layers
coexist in tension, each playing their own role to support stable, yet flexible, brain function. This project
combines mathematical modeling and simulation with application of the methods to predict alcohol drinking
behavior in National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) data set.
Success of this project will demonstrate that both cFN and iFN are essential components of a more complete
understanding of normal and abnormal brain function. There is a desperate need for a deeper understanding
of alcohol use/misuse and for better diagnosis and treatment of AUD. Unfortunately, potential biomarkers
and treatment trials targeting these conditions have continually failed. This project could have transformative
potential as it brings forth a previously undiscovered organizational principle of the brain, and could lead to new
diagnostic and therapeutic strategies designs based on the combined knowledge of the cFN and iFN. In
addition to transforming our understanding of AUD, this work has the potential to revolutionize clinical
studies and the care of patients with a range of brain disorders.
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CRCNS: Functional Brain Networks with Tensioned Stability for Optimal Processing
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批准号:10395742
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项目类别:
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资助金额:$34.75万
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财政年份:2021
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负责人:Erik Bollt
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依托单位:
CRCNS: Functional Brain Networks with Tensioned Stability for Optimal Processing
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批准号:10683341
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项目类别:
-
资助金额:$33.38万
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财政年份:2021
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负责人:Erik Bollt
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依托单位:
海外基金