Neurobiological bases of drug abuse: Novel techniques

药物滥用的神经生物学基础：新技术

• 批准号: 6788298
• 负责人: STEVEN BRADLEY LOWEN
• 金额: $ 16.05万
• 依托单位: MCLEAN HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-08-10 至 2008-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6788298
• 关键词: bioengineering /biomedical engineering; bioimaging /biomedical imaging; biomaterial evaluation; biomedical equipment; biomedical equipment development; body movement; brain electrical activity; computer program /software; craving; cues; drug abuse; functional magnetic resonance imaging; human subject; image processing; model design /development; neurobiology; odors; olfactory stimulus; patient oriented research; phantom model; postdoctoral investigator; reinforcer; technology /technique development; training

DESCRIPTION (provided by applicant): This is a request for 5 years of funding through the "Mentored Quantitative Research Career Award" (K25) mechanism. The applicant, a biomedical/electrical engineer, proposes a comprehensive training/research program in drug abuse and brain imaging. The long term goal of the applicant is to become an independent and interdisciplinary investigator, skilled in the application of functional magnetic resonance imaging (fMRI) methods for the study of substance abuse research. The research component of the award will develop and improve fMRI techniques for the study of substance abuse and addiction in human subjects. Current fMRI technology suffers from three shortcomings which limit its usefulness in a drug-abuse context. First, stimuli for craving studies are limited to auditory and visual modalities, while odors are known to cause powerful emotional effects. Second, motion artifacts remain a serious problem in fMRI studies, especially for drug-dependent populations. No independent verification of motion currently exists, and motion compensation software is not reliable. Third, slowly varying physiological "noise" comprises the major signal component of fMRI data sets, often swamping the effect being measured. Current data analysis methods attempt to exclude this noise from analysis, but the noise remains a critical limitation of all current fMRI data analysis paradigms. Three separate technical development efforts are proposed. First, an odor delivery system, compatible with the high magnetic fields in the fMRI scanner, will be developed and reduced to practice. This system will enable fMRI studies of craving induced by odor, known to be a potent modality. Second, a motion analysis system will be used to obtain accurate measurements of subject motion during scans. After validation, software phantoms will be developed, and together with the motion analysis system will evaluate available motion analysis packages. Finally, motion data will be incorporated into scanner function, so that resulting fMRI data will be almost free of motion artifacts. Third, a wavelet-based fractal analysis of fMRI data will be developed. This method focuses on the slowly varying physiological "noise" which plagues other analysis techniques, turning a liability into an asset and our work shows that it readily highlights drug effects. The training plan will include coursework in neuroscience, pharmacology, and drug abuse; seminars in responsible conduct of research; laboratory rotations; grant writing experience; and regular meetings with the mentors. The timeline of the training will be matched to coincide with the progress of the research projects.

描述(由申请人提供)： 这是通过“导师量化研究事业奖”(K25)机制申请5年的资助。申请者是一名生物医学/电气工程师，他提出了一项关于药物滥用和脑成像的综合培训/研究计划。申请者的长期目标是成为一名独立和跨学科的调查员，熟练应用功能磁共振成像(FMRI)方法研究药物滥用。该奖项的研究部分将开发和改进fMRI技术，用于研究人类受试者的药物滥用和成瘾。目前的功能磁共振成像技术存在三个缺陷，限制了其在药物滥用背景下的有效性。首先，渴望研究的刺激物仅限于听觉和视觉形式，而气味已知会产生强烈的情感效果。其次，运动伪影仍然是fMRI研究中的一个严重问题，特别是对于药物依赖人群。目前还不存在对运动的独立验证，运动补偿软件也不可靠。第三，缓慢变化的生理“噪声”构成了fMRI数据集的主要信号成分，通常会淹没正在测量的效果。目前的数据分析方法试图从分析中排除这种噪声，但噪声仍然是当前所有fMRI数据分析范例的关键限制。提出了三种不同的技术开发努力。首先，将开发一种与功能磁共振扫描仪中的高磁场兼容的气味输送系统，并将其付诸实践。该系统将能够对气味引起的渴望进行功能磁共振研究，众所周知，这是一种有效的方式。其次，将使用运动分析系统来获得扫描过程中对象运动的准确测量。验证后，将开发软件体模，并与运动分析系统一起评估现有的运动分析包。最后，运动数据将被合并到扫描仪功能中，从而得到的fMRI数据将几乎没有运动伪影。第三，将开展基于小波的fMRI数据的分形分析。这种方法专注于缓慢变化的生理“噪音”，这种噪音困扰着其他分析技术，将负债转化为资产，我们的工作表明，它很容易突出药物的影响。培训计划将包括神经科学、药理学和药物滥用方面的课程；负责任地进行研究的研讨会；实验室轮换；赠款撰写经验；以及与导师的定期会议。培训的时间表将与研究项目的进展相匹配。