Neural Mechanisms Underlying Nicotine and Alcohol Combinations: Quantitative fMRI

尼古丁和酒精组合背后的神经机制:定量功能磁共振成像

基本信息

  • 批准号:
    8323023
  • 负责人:
  • 金额:
    $ 19.11万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2012
  • 资助国家:
    美国
  • 起止时间:
    2012-02-15 至 2014-01-31
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): Our long-term objective is to bring together non-invasive quantitative functional magnetic resonance imaging (q-fMRI) with a newly developed cutting-edge analysis method to study changes in neuronal metabolism and cerebrovascular function that occurs during psychoactive drug use. Specific Aims: Our first specific aim is to validate the components of the q-fMRI acquisition, which requires several different kinds of fMRI scans (or multimodal measurements). The second aim then applies the q-MRI method to study the functional brain networks that define brain activity when a person is simply resting and not engaged in any activity. These networks each consist of a unique set of regions that spontaneously fluctuate together in order to be "tuned" for future task performance. The effects of nicotine and alcohol and their interaction on these resting state networks are the focus of the application of our new q-fMRI strategy. q-fMRI measurements require several different scans, including making measurements of perfusion and oxygen metabolism, and an integrated analysis of all of these different results will be much more informative than separate analyses of each measurement. However, the analysis method, the linked independent component analysis (linked ICA) approach is very new and has never been applied to q-fMRI measurements or any other measurements of psychoactive drug effects. Thus, the third aim is to apply this novel analysis method to data acquired under different drug conditions to identify patterns of related activity in our multimodal fMRI data. Research Design and Methods: A randomized within-subject study of 23 healthy subjects will be done as follows: fMRI scanning will begin four hours after pre-treatment with either nicotine or placebo patch (randomized). Alcohol will then be consumed by subjects while in the scanner and a second scanning session will be done of the combination of nicotine (placebo) + alcohol to assess changes in resting state functional connectivity due to alcohol and nicotine and their interactions. Significance: Linked ICA with q-fMRI measurements is an innovative strategy for studying brain function that could have a significant impact in the ability of fMRI to give an integrated picture of the spectrum of effects that drugs of abuse may have on brain function, and is thus ideally suited to the goals of the CEBRA mechanism. By applying this technique to study alcohol and nicotine co-use, we also will contribute greatly to the understanding of this significant health problem. PUBLIC HEALTH RELEVANCE: Our long-term goal is to develop innovative brain imaging techniques to study the changes in brain activity that occur during psychoactive drug use. Nicotine and alcohol are frequently used together and their combined use contributes to more than half a million deaths each year, with more alcoholics dying from smoking-related diseases than from alcohol-related diseases. The first application of the new methods we are proposing will be to study the effects on brain function of nicotine and alcohol together to shed light on th complex interactions between these two drugs that drives their combined use.
描述(由申请人提供):我们的长期目标是将非侵入性定量功能磁共振成像(q-fMRI)与新开发的尖端分析方法结合在一起,以研究精神活性药物使用期间发生的神经元代谢和脑血管功能的变化。具体目标:我们的第一个具体目标是验证q-fMRI采集的组成部分,这需要几种不同类型的fMRI扫描(或多模态测量)。第二个目标是应用q-MRI方法来研究功能性大脑网络,当一个人只是休息而不从事任何活动时,这些网络定义了大脑活动。这些网络都由一组独特的区域组成,这些区域自发地一起波动,以便为未来的任务表现进行“调整”。尼古丁和酒精对这些静息态网络的影响及其相互作用是我们新的q-fMRI策略应用的重点。q-fMRI测量需要几种不同的扫描,包括灌注和氧代谢的测量,对所有这些不同结果的综合分析将比对每个测量结果的单独分析提供更多的信息。然而,分析方法,链接独立成分分析(链接伊卡)的方法是非常新的,从来没有被应用到q-fMRI测量或任何其他精神活性药物的影响的测量。因此,第三个目标是将这种新的分析方法应用于在不同药物条件下获得的数据,以识别我们的多模态fMRI数据中的相关活动模式。研究设计和方法:将对23例健康受试者进行随机化受试者内研究,如下所示:fMRI扫描将在尼古丁或安慰剂贴剂(随机化)预处理后开始4小时开始。然后,受试者在扫描仪中饮酒,并对尼古丁(安慰剂)+酒精的组合进行第二次扫描,以评估酒精和尼古丁及其相互作用引起的静息状态功能连接的变化。重要性:将伊卡与q-fMRI测量相关联是研究脑功能的一种创新策略,它可能对fMRI的能力产生重大影响,从而提供滥用药物可能对脑功能产生的影响的综合图像,因此非常适合CEBRA机制的目标。通过应用这项技术来研究酒精和尼古丁的共同使用,我们也将大大有助于了解这一重大的健康问题。 公共卫生关系:我们的长期目标是开发创新的大脑成像技术,以研究精神活性药物使用期间大脑活动的变化。尼古丁和酒精经常一起使用,两者的结合使用每年导致50多万人死亡,死于吸烟相关疾病的酗酒者多于死于酒精相关疾病的酗酒者。我们提出的新方法的第一个应用将是研究尼古丁和酒精对大脑功能的影响,以揭示这两种药物之间复杂的相互作用,从而推动它们的联合使用。

项目成果

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LISA D NICKERSON其他文献

LISA D NICKERSON的其他文献

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{{ truncateString('LISA D NICKERSON', 18)}}的其他基金

Sex Differences in the Effects of Alcohol Use Disorder on Brain Circuitry using Existing Data
使用现有数据研究酒精使用障碍对大脑回路影响的性别差异
  • 批准号:
    9321385
  • 财政年份:
    2016
  • 资助金额:
    $ 19.11万
  • 项目类别:
Precision Functional Neuroimaging Core
精密功能神经影像核心
  • 批准号:
    10594027
  • 财政年份:
    2015
  • 资助金额:
    $ 19.11万
  • 项目类别:
Multi-modal MRI data fusion to assess neurobiological effects of marijuana use
多模态 MRI 数据融合评估大麻使用的神经生物学影响
  • 批准号:
    9095283
  • 财政年份:
    2014
  • 资助金额:
    $ 19.11万
  • 项目类别:
Multi-modal MRI data fusion to assess neurobiological effects of marijuana use
多模态 MRI 数据融合评估大麻使用的神经生物学影响
  • 批准号:
    8671685
  • 财政年份:
    2014
  • 资助金额:
    $ 19.11万
  • 项目类别:
Multi-modal MRI data fusion to assess neurobiological effects of marijuana use
多模态 MRI 数据融合评估大麻使用的神经生物学影响
  • 批准号:
    8889245
  • 财政年份:
    2014
  • 资助金额:
    $ 19.11万
  • 项目类别:
Neural Mechanisms Underlying Nicotine and Alcohol Combinations: Quantitative fMRI
尼古丁和酒精组合背后的神经机制:定量功能磁共振成像
  • 批准号:
    8423709
  • 财政年份:
    2012
  • 资助金额:
    $ 19.11万
  • 项目类别:
Novel Use of fMRI to Study Substance Abuse Problems
功能磁共振成像研究药物滥用问题的新用途
  • 批准号:
    7033000
  • 财政年份:
    2005
  • 资助金额:
    $ 19.11万
  • 项目类别:
Novel Use of fMRI to Study Substance Abuse Problems
功能磁共振成像研究药物滥用问题的新用途
  • 批准号:
    7600619
  • 财政年份:
    2005
  • 资助金额:
    $ 19.11万
  • 项目类别:
Novel Use of fMRI to Study Substance Abuse Problems
功能磁共振成像研究药物滥用问题的新用途
  • 批准号:
    7218747
  • 财政年份:
    2005
  • 资助金额:
    $ 19.11万
  • 项目类别:
Novel Use of fMRI to Study Substance Abuse Problems
功能磁共振成像研究药物滥用问题的新用途
  • 批准号:
    7388298
  • 财政年份:
    2005
  • 资助金额:
    $ 19.11万
  • 项目类别:

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