Prescription opiate, drug cue processing network, and neural connectivity

处方鸦片、药物线索处理网络和神经连接

• 批准号: 9372837
• 负责人: Suchismita Ray
• 金额: $ 13.19万
• 依托单位: RUTGERS, THE STATE UNIV OF N.J.
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2018-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9372837
• 关键词: Abstinence; Age; Alcohol or Other Drugs use; Algorithms; Americas; Amygdaloid structure; Analysis of Covariance; Area; Attention; Automobile Driving; Base of the Brain; Behavior Therapy; Brain; Brain region; Centers for Disease Control and Prevention (U.S.); Cessation of life; Chronic; Cocaine; Collection; Control Groups; Cues; Data; Decision Making; Dependency; Development; Diffusion Magnetic Resonance Imaging; Disease; Drug Metabolic Detoxication; Drug Modelings; Drug Prescriptions; Drug usage; Drug user; Elements; Epidemic; Female; Foundations; Functional Magnetic Resonance Imaging; Funding; Future; Gender; Goals; Grant; Heroin; Image; Imaging Device; Imaging Techniques; Impairment; Individual; Intervention; Knowledge; Literature; Long-Term Effects; Measures; Memory; Methods; Opiate Addiction; Opiates; Overdose; Participant; Persons; Pharmaceutical Preparations; Pharmacology; Planning Techniques; Prevention; Questionnaires; Recruitment Activity; Reporting; Research; Rest; Sampling; Scanning; Severities; Sex Characteristics; Signal Transduction; Structure; Structure-Activity Relationship; Techniques; Testing; Theoretical model; Woman; Work; alcohol and other drug; attentional bias; base; craving; cue reactivity; density; disorder later incidence prevention; drug seeking behavior; executive function; gray matter; imaging study; long term memory; male; men; misuse of prescription only drugs; morphometry; motivated behavior; network models; neuroimaging; nigrostriatal system; overdose death; prescription drug abuse; prescription opiate; prescription opioid; prescription pain reliever; relating to nervous system; response; sample fixation; visual stimulus; white matter

Abstract This application is in response to PAR-15-326 to facilitate the PI's entry using neuroimaging in opiate addiction, thereby expanding her prior research expertise into the field of opiate research. The PI will work with her collaborators to develop expertise in diffusion tensor imaging (DTI) technique to conduct a multi-method assessment to better understand brain structure-function relationship in prescription opiate users. Opiate overdose, specifically the prescription opiate overdose has taken the form of epidemic in the U.S. The goal of this proposal is to provide a multimethod assessment of structural and functional brain changes within prescription opiate users' drug cue processing network (DCPN; implicated in drug seeking behavior) using functional magnetic resonance imaging (fMRI) and the tools of structural, functional and effective connectivity analysis. This is a proposal to collect the first structural, functional and effective connectivity data between the regions within the DCPN in prescription opiate dependents (PODs) and matched controls. If funded, this I/START grant will allow the PI to transition to the opiate addiction field. She will combine her existing neuroimaging knowledge with new knowledge on DTI technique that she plans to gather during this grant period, and finally would like to apply her expertise into the new field of prescription opiate. By using the voxel based morphometry (VBM) and DTI techniques, the PI and her collaborators will explore group differences in structural gray matter volume and density (VBM) and white matter connectivity (DTI) in regions within the DCPN. The functional connectivity (using a resting state task) between the regions within the DCPN and the effective connectivity (using a prescription opiate cue exposure task) between the regions within the DCPN will be compared between the POD and control groups (Aim 1). Sex differences in brain structure and function within the DCPN between the POD and control groups using VBM, DTI, a resting state task and a prescription opiate cue exposure task will be explored (Aim 2). Thirty PODs and 30 age and gender matched controls will be recruited. Each participant will take part in one imaging session and will complete alcohol and other drug use questionnaires. During the resting state scan, participants will fixate on a cross. During the prescription opiate cue exposure task, participants will view prescription opiate related and neutral visual stimuli and will provide craving ratings. During DTI Imaging, participants will view a fixation cross. For the VBM analysis, a MANCOVA will be performed between the groups with gray matter volume (or gray matter density) as a repeated factor. For each analysis, factor scores will be derived. Independent sample t-tests will then be conducted between the PODs and controls on factor scores (DTI, functional, effective connectivity). Correlations between craving ratings and each factor score in PODs will be calculated. A separate 2 (sex) x 2 (group) ANCOVA will be conducted for each factor score probing for sex by group interactions. This project may help for future development of brain-based algorithms to optimize treatment of individual PODs.

抽象的 该应用程序是对PAR-15-326的响应 从而将她先前的研究专业知识扩展到鸦片研究领域。 PI将与她合作 合作者开发扩散张量成像（DTI）技术的专业知识以进行多方法 评估以更好地了解处方鸦片使用者中的大脑结构功能关系。鸦片 过量服用，特别是处方药过量服用过量已经采取了美国的流行形式 该建议是为结构和功能性大脑变化的多方法评估 处方鸦片用户的药物提示加工网络（DCPN；与毒品寻求行为有关） 功能磁共振成像（fMRI）和结构，功能和有效连通性的工具 分析。这是收集第一个结构，功能和有效的连通性数据的建议 DCPN中的区域处方药依赖者（POD）和匹配的控件中的区域。如果资助，这是 I/Start Grant将允许PI过渡到鸦片成瘾字段。她将结合她现有的 她计划在这笔赠款期间收集的有关DTI技术的新知识的神经影像学知识 时期，最终希望将她的专业知识应用于处方鸦片的新领域。通过使用体素 基于形态计量学（VBM）和DTI技术，PI和她的合作者将探索群体差异 结构灰质体积和密度（VBM）和白质连接性（DTI） DCPN。 DCPN和DCPN区域之间的功能连接性（使用静止状态任务） DCPN区域之间的有效连通性（使用处方鸦片提示暴露任务）将 在POD和对照组之间进行比较（AI​​M 1）。大脑结构和功能上的性别差异 在POD和对照组之间使用VBM，DTI，静止状态任务和处方 鸦片提示曝光任务将探索（AIM 2）。 30个豆荚和30岁和性别匹配的控制将 被招募。每个参与者将参加一次成像会议，并将完成酒精和其他药物 使用问卷。在休息状态扫描期间，参与者将固定在十字架上。在处方期间 鸦片提示暴露任务，参与者将查看处方鸦片相关和中性视觉刺激，并将 提供渴望评分。在DTI成像期间，参与者将查看固定十字架。对于VBM分析， Mancova将在具有灰质体积（或灰质密度）的组之间进行 重复因素。对于每个分析，将得出因子得分。那么独立的样本t检验将是 在豆荚和控制因子得分（DTI，功能，有效连通性）之间进行。 将计算渴望等级与豆荚中每个因子得分之间的相关性。单独的2（性）x 2 （组）将对通过小组相互作用为性别探测的每个因子分数进行ANCOVA。这个项目 可能有助于未来开发基于大脑的算法以优化单个豆荚的处理。