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A Circuit Approach to Mechanisms and Predictors of Topiramate Response

A Circuit Approach to Mechanisms and Predictors of Topiramate Response
托吡酯反应机制和预测因子的电路方法
批准号:
10473684
负责人:
Amit Etkin
金额:
$44.11万
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-09-20 至 2024-08-31

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中文摘要
翻译
摘要 创伤后应激障碍(PTSD)是一种慢性致残障碍,目前疗效有限 治疗。其严重程度和功能损害与频繁的酒精使用障碍并存。 (AUD),单独或与创伤后应激障碍联合治疗的有效治疗也有限。饮酒可以 在创伤后应激障碍的情绪失调的更广泛的框架内被考虑,因为它通常最初被视为 一种(通常是不适应的)应对痛苦情绪的方式。当饮酒时间过长且过度时, 酒精依赖会随之而来,表现为明显更严重的功能障碍和精神障碍 前额叶功能与情绪调节。总而言之,这些证据表明:a)降低了 调节过度的负面情绪是PTSD+AUD患者饮酒的主要脆弱因素;以及b) 前额叶-杏仁核神经回路相互作用的个体差异可能是重要的预测因子和/或 创伤后应激障碍+AUD治疗结果的机械决定因素。因此,临床上有迫切的需求。 推进PTSD+AUD的治疗,这是通过了解谁是最有效的 对给定的治疗效果最好,该治疗的有效机制是什么?在这里我们 建议使用复杂的协调/调解框架和多模式来回答这些问题 比较治疗的随机临床试验背景下的人脑回路功能评估 PTSD+AUD+托吡酯与安慰剂的比较。托吡酯的效用是有证据的,它有助于 抑制γ-氨基丁酸信号和拮抗兴奋性谷氨酸信号 治疗AUD,初步证据表明PTSD+AUD有效,使其成为有希望的靶点 神经机械学研究。因此,我们方法的核心是一门彻底的认知神经科学 情绪反应性及其对一般负性刺激的调节和对酒精线索的反应 更具体地说(使用功能磁共振成像(FMRI))。除此之外,还有一次切割- 同时经颅磁图在神经生理学水平上对相同脑回路的边缘映射 刺激和脑电(TMS/EEG)。鉴于托吡酯的药理作用,并发的TMS/EEG是一种 是直接询问其神经生理行为的理想工具。这是因为TMS/EEG指数不同 与兴奋和抑制相关的神经生理反应对脑环路靶向的影响 神经刺激,脑电反应定位于特定皮质结构,由 FMRI任务,并在神经元的时间尺度上进行研究。
英文摘要
SUMMARY Post-traumatic stress disorder (PTSD) is a chronic and disabling disorder with currently limited effective treatments. Its severity and functional impairment is compounded by frequently comorbid alcohol use disorder (AUD), which also has limited effective treatments in isolation or in combination with PTSD. Alcohol use can be considered within the broader framework of emotion dysregulation in PTSD, as it is often pursued initially as an (often maladaptive) way to cope with distressing emotions. When alcohol use is prolonged and excessive, alcohol dependence can ensue, manifesting in substantially greater functional impairment and deficiency of prefrontal function and emotion regulation. Together, these lines of evidence suggest that: a) reduced ability to regulate excessive negative affect presents a primary vulnerability factor for alcohol use in PTSD+AUD; and b) individual differences in prefrontal-amygdala neural circuit interactions may be important predictors and/or mechanistic determinants of outcomes for PTSD + AUD treatments. As such, there is a pressing clinical need to advance the treatment of PTSD+AUD, which is most efficiently accomplished by understanding who responds best to a given treatment and what are the mechanisms by which that treatment works. Here we propose to answer these questions using a sophisticated moderation/mediation framework and multi-modal human brain circuit functional assessments in the context of a randomized clinical trial comparing the treatment of PTSD+AUD with topiramate versus placebo. Evidence exists for the utility of topiramate, which facilitates inhibitory γ-amino-butyric acid (GABA) signaling and antagonizes excitatory glutamatergric signaling, in the treatment of AUD, with initial evidence of utility for PTSD+AUD, making it a promising target for neuromechanistic study. Therefore, at the heart of our approach is a thorough cognitive neuroscience assessment of emotional reactivity and regulation to general negative stimuli and reactivity to alcohol cues more specifically (using functional magnetic resonance imaging (fMRI)). This is complemented by a cutting- edge mapping of the same brain circuits at the neurophysiological level using concurrent transcranial magnetic stimulation and EEG (TMS/EEG). Given the pharmacological action of topiramate, concurrent TMS/EEG is an ideal tool for direct interrogation of its neurophysiological actions. This is because TMS/EEG indexes distinct excitation-related and inhibition-related neurophysiological responses to brain circuit-targeted targeted neurostimulation, with EEG responses source-localized to the specific cortical structures investigated by the fMRI tasks above and investigated at a neuronal temporal scale.
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Validating of Machine Learning-Based EEG Treatment Biomarkers in Depression
  • 批准号:
    10009501
  • 项目类别:
  • 资助金额:
    $98.81万
  • 财政年份:
    2020
  • 负责人:
    Amit Etkin
  • 依托单位:
Validating of Machine Learning-Based EEG Treatment Biomarkers in Depression
  • 批准号:
    10116492
  • 项目类别:
  • 资助金额:
    $118.41万
  • 财政年份:
    2020
  • 负责人:
    Amit Etkin
  • 依托单位:
Validating of Machine Learning-Based EEG Treatment Biomarkers in Depression
  • 批准号:
    10366060
  • 项目类别:
  • 资助金额:
    $101.65万
  • 财政年份:
    2020
  • 负责人:
    Amit Etkin
  • 依托单位:
Assessing an electroencephalography (EEG) biomarker of response to transcranial magnetic stimulation for major depression
海外基金