Self-Regulation and Neural Networks in Alcohol Use Disorders

酒精使用障碍中的自我调节和神经网络

• 批准号: 9145073
• 负责人: Donna Murray
• 金额: $ 6.07万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-03 至 2017-09-02
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9145073
• 关键词: Abstinence; Affect; Alcohol consumption; Alcohol dependence; Alcohol or Other Drugs use; Anterior; Basal Ganglia; Behavior; Biological Neural Networks; Brain; Brain region; Characteristics; Chronic; Clinical; Clinical Research; Cognition; Data; Data Analyses; Decision Making; Development; Frequencies; Functional Magnetic Resonance Imaging; Funding; Future; Glutamates; Impulsivity; Individual; Informal Social Control; Intervention; Link; Magnetic Resonance; Magnetic Resonance Imaging; Magnetic Resonance Spectroscopy; Maintenance; Measures; Mediation; Metabolic; Midbrain structure; Modeling; N-acetylaspartate; National Research Service Awards; Neurobiology; Neurocognitive; Neurons; Neurosciences; Opioid; Outcome Measure; Phenotype; Prefrontal Cortex; Prospective Studies; Protons; Radiology Specialty; Recovery; Relapse; Reporting; Research; Research Project Grants; Rest; Rewards; Risk-Taking; Severities; Smoking; Specificity; Substance Use Disorder; Substance abuse problem; Synaptic plasticity; Testing; Tobacco Use Disorder; Training; United States National Institutes of Health; Update; addiction; alcohol abstinence; alcohol abuse therapy; alcohol relapse; alcohol use disorder; base; behavior measurement; brain abnormalities; career; cigarette smoking; cingulate cortex; clinically relevant; cognitive control; drinking; experience; image processing; improved; neural circuit; neural correlate; neuroimaging; neuromechanism; non-alcoholic; non-smoking; novel; public health relevance; relapse risk; reward processing; substance abuse treatment; treatment strategy

 DESCRIPTION (provided by applicant): The neural mechanisms underlying self-regulation in alcohol use disorders (AUD) with and without comorbid cigarette smoking are clinically important yet unsolved issues of practical importance to substance abuse in general and to alcohol relapse and treatment in particular. This proposal aims to explore the relationships of self-regulation to resting brain neural circuitry (by functional connectivity) and neuronal viabiliy (by cortical metabolite concentrations) in large-scale neurocognitive networks and in the reward network of individuals with AUD compared with healthy controls. This study will use multi-modal data acquired as part of NIH-funded research projects and serve as a training vehicle for Dr. Murray to gain clinical research experience in multi- modal neuroimaging of individuals with AUD. We will relate various measures of self-regulation to within- network functional connectivity from resting state-functional MRI (rsfMRI) and to select metabolite concentrations (primarily N-acetylaspartate and glutamate) from localized proton magnetic resonance spectroscopy (1H MRS) in AUD individuals and healthy controls for comparison. We will determine the impact of a clinically relevant behavior (self-regulation) to both the strength of functional connectivity within brain networks (neurocognitive and reward networks) and the level of regional metabolite concentrations within major nodes of these networks in 4030 AUD individuals at one month of abstinence and in 2030 healthy controls. It is hypothesized that short-term abstinent AUD individuals will have altered functional connectivity within brain networks that is associated with poor self-regulation and low metabolite concentrations compared with healthy controls, and that these relationships are critically influenced by chronic cigarette smoking. In further exploratory analyses, the 15 smoking AUD individuals will be compared with a group of 15 smoking opioid dependent individuals precisely to test the specificity of the findings to AUD. The interrelationships between self-regulation, functional connectivity, and cortical metabolite concentrations are predicted to identify a set of measures that illuminate unique neural correlates of substance use behavior. Understanding the link between functional network connectivity and its associations to both self-regulation and metabolic activity within these networks promises to provide novel information regarding relapse risk proneness and improved treatment approaches in alcohol and tobacco use disorders.

 描述（由申请人提供）：伴有和不伴有共病吸烟的酒精使用障碍（AUD）中自我调节的神经机制是临床上重要但尚未解决的问题，对一般药物滥用和酒精复发和治疗具有实际重要性。该提案旨在探索与健康对照相比，在大规模神经认知网络和AUD个体的奖励网络中，自我调节与静息脑神经回路（通过功能连接）和神经元活力（通过皮质代谢物浓度）的关系。本研究将使用作为NIH资助的研究项目的一部分获得的多模态数据，并作为Murray博士的培训工具，以获得AUD患者多模态神经成像的临床研究经验。我们将在AUD个体和健康对照中将各种自我调节措施与静息状态功能性MRI（rsfMRI）的网络内功能连接联系起来，并从局部质子磁共振波谱（1H MRS）中选择代谢物浓度（主要是N-乙酰天冬氨酸和谷氨酸）进行比较。我们将确定临床相关行为（自我调节）对大脑网络（神经认知和奖励网络）内功能连接的强度以及这些网络主要节点内区域代谢物浓度水平的影响，其中4030名AUD个体在一个月的禁欲和2030名健康对照中。据推测，与健康对照组相比，短期戒烟的AUD个体将改变大脑网络内的功能连接，这与自我调节差和代谢物浓度低有关，并且这些关系受到慢性吸烟的严重影响。在进一步的探索性分析中，将15名吸烟的AUD个体与一组15名吸烟的阿片类药物依赖个体进行精确比较，以检测结果对AUD的特异性。自我调节，功能连接和皮质代谢物浓度之间的相互关系进行预测，以确定一组措施，照亮独特的神经相关的物质使用行为。了解功能网络连接之间的联系及其与这些网络中的自我调节和代谢活动之间的联系，有望提供有关复发风险倾向和改善酒精和烟草使用障碍治疗方法的新信息。