Using Neuroimaging Markers to Understand Risk Factors and Consequences of Cannabis on Brain Structure and Function
使用神经影像标记物了解大麻对大脑结构和功能的危险因素和后果
基本信息
- 批准号:10681316
- 负责人:
- 金额:$ 12.83万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-09-01 至 2026-08-31
- 项目状态:未结题
- 来源:
- 关键词:AddressAdolescenceAdolescentAgeAnxietyAreaAwardBehavior assessmentBehavioralBehavioral ResearchBig DataBrainCannabisChildChildhoodChronicClinical TrialsCognitionCollaborationsDataData SetData Storage and RetrievalDevelopmentDrug usageEducational process of instructingFactor AnalysisFoundationsFundingFutureGoalsGrowthImageImpulsivityIndependent Scientist AwardKnowledgeLaboratoriesLassoLearningLightLongevityMeasuresMedical MarijuanaMental DepressionMentorsMethodsModelingNeurosciencesPainParentsParticipantPatient Self-ReportPatientsPhasePopulationReportingReproducibilityResearchResearch Project GrantsRiskRisk FactorsRunningSamplingScanningScientistSolidStatistical Data InterpretationStructureSubstance Use DisorderTechniquesTestingThinnessTimeTrainingValidationVisitWagesWorkaddictionbehavioral outcomebrain basedcareercareer developmentcognitive developmentdetection methoddisorder riskexperimental studyimprovedindexinglarge datasetslongitudinal datasetmachine learning predictionmarijuana use disorderneuralneural correlateneuroimagingneuroimaging markerparallel computerpredictive modelingprogramsskillssubstance usetheoriestoolvector
项目摘要
Project Summary
This application for an Independent Scientist Award (K02) requests support to develop a program of
brain-based and behavioral research on substance use disorders (SUD), especially cannabis use disorder
(CUD). My laboratory is supported in part by a funded R01 (DA039135) that seeks to understand the effects of
medical marijuana on the brain, cognition, and escalation to CUD. In the next phase of my career, I propose to
learn enhanced analytical techniques (e.g. machine learning and predictive modeling) that can capitalize on
newly-available, large, longitudinal datasets that can answer fundamental questions about the development of
SUD that cannot be answered in small populations. In addition, I propose a secondary training goal of gaining
expertise in developmental neuroscience, to broaden the populations I can study to include children and
adolescents at-risk for SUD. Together, these skillsets will allow me to greatly expand the types of questions I
can ask, by allowing me to answer questions about SUD using both large observational data-sets, and also
targeted experimental manipulations (such as my R01). My goal at the end of this K02 to have the tools to not
only use big data to better understand risk factors and consequences of addiction in large samples, but also to
use this knowledge to inform future experimental studies and clinical trials that I can conduct in my lab.
The scientific focus of this application is a research project, using the publicly-available Adolescent
Brain and Cognitive Development (ABCD) dataset of 11,877 children scanned longitudinally, to understand
how trajectories of change in impulsivity associate with brain-based abnormalities and SUD risk. The aims for
the ABCD analysis project are to (1) define the factorial structure of impulsivity in the ABCD dataset as it may
portend SUD risk (using a confirmatory factor model which will be applied to the array of behavioral tasks, self-
report measures, and parent reports), (2) determine structural and functional brain measures that correlate with
impulsivity, and (3) examine how longitudinal changes in brain signatures of impulsivity are associated with risk
for SUD. To accomplish these aims, I will participate in courses and train with collaborators with expertise in
developmental neuroscience and in statistical analyses of big data. The skills I learn in the K02 period will be
used not only to query the ABCD dataset, but also to enhance the sophistication of neuroimaging analyses of
my R01 data and any future data collected in my laboratory. This training will enhance my laboratory by
significantly expanding the questions I can address, improving my analytic skills, furthering my ability to
collaborate, and providing a foundation for mentoring junior scientists. In the absence of K02 support, I will
need to cover my salary through teaching and administrative work, which would detract from my research,
training, and mentoring activities. This K02 award will provide protected time to develop my research program
and receive this training that will be critical for my career development as an addiction neuroscientist.
项目摘要
独立科学家奖(K 02)的申请要求支持开发一个项目,
对物质使用障碍(SUD),特别是大麻使用障碍的大脑和行为研究
(CUD)。我的实验室部分得到了R 01(DA 039135)的资助,该项目旨在了解
医用大麻对大脑、认知的影响,并升级为CUD。在我职业生涯的下一个阶段,我提议
学习增强的分析技术(例如机器学习和预测建模),
新提供的大型纵向数据集,可以回答有关发展的基本问题,
SUD在小群体中无法回答。此外,我提出了一个次要的培训目标,
发展神经科学方面的专业知识,以扩大我可以研究的人群,包括儿童和
有SUD风险的青少年。总之,这些技能组合将使我能够大大扩展我的问题类型。
我可以问,通过允许我使用大型观测数据集回答有关SUD的问题,
有针对性的实验操作(如我的R 01)。我的目标是在这个K 02结束时有工具,
我们不仅要利用大数据更好地了解大样本中成瘾的风险因素和后果,
利用这些知识为我在实验室进行的未来实验研究和临床试验提供信息。
本申请的科学重点是一个研究项目,使用公开的青少年
大脑和认知发展(ABCD)数据集,11,877名儿童纵向扫描,以了解
冲动性的变化轨迹如何与大脑异常和SUD风险相关。目标是
ABCD分析项目是(1)定义ABCD数据集中冲动的因子结构,因为它可能
预示SUD风险(使用验证性因素模型,该模型将应用于一系列行为任务,自我,
报告措施,和家长报告),(2)确定结构和功能的大脑措施,
冲动性,(3)研究冲动性大脑特征的纵向变化如何与风险相关
对于SUD。为了实现这些目标,我将参加课程,并与具有以下专业知识的合作者一起培训:
发展神经科学和大数据的统计分析。我在K 02期间学习的技能将是
不仅用于查询ABCD数据集,而且还用于增强神经成像分析的复杂性。
我的R 01数据和我实验室将来收集的任何数据。这次培训将提高我的实验室,
大大扩展了我可以解决的问题,提高了我的分析能力,提高了我的能力,
合作,并为指导初级科学家提供基础。在没有K 02支持的情况下,我将
我需要通过教学和行政工作来支付我的薪水,这会分散我的研究,
培训和指导活动。这个K 02奖将提供受保护的时间来发展我的研究计划
接受这个培训,这对我作为一名成瘾神经科学家的职业发展至关重要。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
State-Level Recreational Cannabis Legalization Is Not Differentially Associated with Cannabis Risk Perception Among Children: A Multilevel Regression Analysis.
州级休闲大麻合法化与儿童大麻风险感知没有差异相关:多级回归分析。
- DOI:10.1089/can.2022.0162
- 发表时间:2024
- 期刊:
- 影响因子:3.8
- 作者:Gilman,JodiM;Iyer,MallikaT;Pottinger,EmmaG;Klugman,EmmaM;Hughes,Dylan;Potter,Kevin;Tervo-Clemmens,Brenden;Roffman,JoshuaL;Evins,AEden
- 通讯作者:Evins,AEden
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Jodi Gilman其他文献
Jodi Gilman的其他文献
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{{ truncateString('Jodi Gilman', 18)}}的其他基金
Evaluation of Cannabidiol for Reduction of Brain Neuroinflammation
大麻二酚减少脑神经炎症的评价
- 批准号:
10185880 - 财政年份:2021
- 资助金额:
$ 12.83万 - 项目类别:
Evaluation of Cannabidiol for Reduction of Brain Neuroinflammation
大麻二酚减少脑神经炎症的评价
- 批准号:
10413981 - 财政年份:2021
- 资助金额:
$ 12.83万 - 项目类别:
Using Neuroimaging Markers to Understand Risk Factors and Consequences of Cannabis on Brain Structure and Function
使用神经影像标记物了解大麻对大脑结构和功能的危险因素和后果
- 批准号:
10468167 - 财政年份:2021
- 资助金额:
$ 12.83万 - 项目类别:
Evaluation of Cannabidiol for Reduction of Brain Neuroinflammation
大麻二酚减少脑神经炎症的评价
- 批准号:
10605299 - 财政年份:2021
- 资助金额:
$ 12.83万 - 项目类别:
Using Neuroimaging Markers to Understand Risk Factors and Consequences of Cannabis on Brain Structure and Function
使用神经影像标记物了解大麻对大脑结构和功能的危险因素和后果
- 批准号:
10301282 - 财政年份:2021
- 资助金额:
$ 12.83万 - 项目类别:
Medical Marijuana, Neurocognition, and Subsequent Substance Use
医用大麻、神经认知和后续药物使用
- 批准号:
9309847 - 财政年份:2017
- 资助金额:
$ 12.83万 - 项目类别:
Neurobehavioral Characterization of Social Influence in Drug Addiction
吸毒成瘾的社会影响的神经行为特征
- 批准号:
8650806 - 财政年份:2013
- 资助金额:
$ 12.83万 - 项目类别:
Neurobehavioral Characterization of Social Influence in Drug Addiction
吸毒成瘾的社会影响的神经行为特征
- 批准号:
9039573 - 财政年份:2013
- 资助金额:
$ 12.83万 - 项目类别:
Neurobehavioral Characterization of Social Influence in Drug Addiction
吸毒成瘾的社会影响的神经行为特征
- 批准号:
8827747 - 财政年份:2013
- 资助金额:
$ 12.83万 - 项目类别:
Neurobehavioral Characterization of Social Influence in Drug Addiction
吸毒成瘾的社会影响的神经行为特征
- 批准号:
9258413 - 财政年份:2013
- 资助金额:
$ 12.83万 - 项目类别:
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