Defining the neural ensembles of cocaine addiction

定义可卡因成瘾的神经系统

基本信息

  • 批准号:
    10405465
  • 负责人:
  • 金额:
    $ 3.15万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2020
  • 资助国家:
    美国
  • 起止时间:
    2020-06-01 至 2023-05-31
  • 项目状态:
    已结题

项目摘要

Project summary Substance use disorder is a public health concern with no effective, long-lasting pharmacotherapies. A large amount of effort has been put into defining the neural basis of addictive behaviors as well as the factors that lead to the development of drug addiction. Past research has focused on the role of entire brain regions in mediating addiction and recently, with advances in genetic approaches, genetically defined cellular populations. However, recent work has shown that even within these defined populations, only a small percentage of cells are activated to a given stimulus. Thus, moving forward, it will be important to identify the role of functionally defined neural populations – termed ensembles – in addictive behaviors. Here, we aim to understand how ensembles in the nucleus accumbens (NAc) that are activated by cocaine encode information and drive volitional cocaine consumption. In this proposal, we will combine translational addiction models (mouse self-administration) with optical tools for recording (fiber photometry) and manipulating (optogenetics) functionally defined ensembles to elucidate what information is encoded within them and how they control complex behaviors. Together, this proposal will give me the technical and theoretical training to answer complex questions about the neural control of behavior and its dysregulation in substance use disorder. In Aim 1, I will define what aspects of cocaine- associated behaviors these cells encode by using fiber photometry to record from cocaine-activated ensembles in vivo while animals self-administer cocaine. In Aim 2, I will determine if these ensembles are sufficient to drive self-administration by allowing mice to perform optical self-stimulation tasks in ChR2-tagged cocaine-activated ensembles. Finally, in Aim 3, we will define how temporally specific activation or inhibition of these cells during specific stimuli alters self-administration. By photo-stimulating or -inhibiting these cocaine ensembles during self- administration, we can define the sufficiency and necessity of these neural populations in various aspects of drug-taking (acquisition, consumption, and drug seeking/relapse). These experiments will provide new information about the cell-specific populations that drive both initial drug taking as well as the behaviors that define substance use disorder. By focusing on functionally defined neuronal populations, we will discover subpopulations that would be unobservable when applying a priori broad genetic markers. Through these novel findings, we will learn more about the mechanisms that mediate progression to drug addiction in specific subpopulations so that we will be able, in the future, to decrease cocaine-taking behavior without producing addictive or aversive effects.
项目摘要 药物使用障碍是公共卫生的问题,没有有效的,持久的药物治疗 Puento的努力数量是为了捍卫成瘾者的神经基础以及thactor thactor的领导 吸毒成瘾的发展。 除了遗传方法的进步,遗传学定义的细胞群体以及最近的进步。 最近的工作表明,即使在定义的普通范围内,也只有一小部分单元被激活 对于给定的刺激。 种群 - 称为合奏 - 在这里,我们的目标是如何了解您的合奏 可卡因编码信息并驱动可卡因激活的核成分(NAC)(NAC) 消费。 用于记录的光学工具(光纤光度法)和操纵(光遗传学)功能定义的合奏 阐明它们在其中编码哪些信息。 建议将为我提供技术和技术培训,以回答复杂的报价。 在AIM 1中,行为ATS失调。 相关行为这些细胞通过使用光纤光度法编码从可卡因活化的合奏中记录 当动物自我管理可卡因时,我将确定这些集合是否足以驱动 通过允许小鼠在CHR2标记的可卡因激活中执行光学自我刺激任务来进行自我管理 合奏。最后,在AIM 3中,我们将定义在暂时的激活或抑制。 特定的刺激通过照片刺激或抑制这些可卡因在自我的过程中改变自我管理 行政管理,我们可以在这些神经种群的各个方面定义这些神经种群的附加性和必要性 吸毒(获取,消费和寻求/复发)将提供新的经验。 有关药物服用的细胞特异性流行信息以及行为的信息 通过专注于功能定义的神经元种群来定义使用障碍 在应用先验广泛的遗传标记时,将无法观察到的亚群体。 调查结果,我们将进一步了解有关在特定中介导吸毒进展的机制 亚孔管量,因此将来能够降低可卡因的行为而无需产生 上瘾或厌恶效果。

项目成果

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Kimberly C Thibeault其他文献

Kimberly C Thibeault的其他文献

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{{ truncateString('Kimberly C Thibeault', 18)}}的其他基金

Defining the neural ensembles of cocaine addiction
定义可卡因成瘾的神经系统
  • 批准号:
    9907353
  • 财政年份:
    2020
  • 资助金额:
    $ 3.15万
  • 项目类别:

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Defining the neural ensembles of cocaine addiction
定义可卡因成瘾的神经系统
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  • 财政年份:
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  • 资助金额:
    $ 3.15万
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  • 财政年份:
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