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Mechanisms of Parkinsonian Impulsivity in Human Subthalamic Nucleus

Mechanisms of Parkinsonian Impulsivity in Human Subthalamic Nucleus
人丘脑底核帕金森病冲动的机制
批准号:
8702698
负责人:
John Pearson
金额:
$23.55万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-04-15 至 2016-03-31

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中文摘要
翻译
描述(由申请人提供):虽然治疗帕金森氏病(PD)的典型治疗方法--多巴胺能药物和脑深部刺激(DBS)--被证明能有效缓解与疾病相关的运动障碍,但这些方法也会导致行为副作用,包括强迫性赌博、性欲亢奋和复杂的、无目的的刻板印象行为(“平底船”)。虽然许多工作已经研究了导致D的震颤、僵硬和其他运动效应的神经活动的潜在模式,但对人类冲动副作用的神经起源知之甚少。我们建议在接受DBS电极植入手术的实际PD患者群体中,描述导致这些冲动控制失败的神经活动模式。这种程序提供了在人类单个神经元水平收集数据的独特机会,因为外科医生依靠术中电生理学来确定丘脑底核(STN)的解剖边界,底核是DBS治疗帕金森病的典型靶点。使用多通道Ad-Tech微线阵列,我们将同时记录STN和附近结构中单个单位活动的多个通道(包括尖峰和场势),同时受试者执行认知任务,证实与人类群体中的冲动有关。在气球模拟风险任务(BART)中,参与者在决定何时停止给电脑控制的气球充气时,必须平衡风险和回报,气球的点数和爆裂风险都随着体积的增大而增加。在停止信号反应任务(SSRT)中,参与者必须在出现“开始”提示时尽可能快地做出反应,但在播放“停止”音调时应尽快做出反应。在神经层面,BART让我们能够阐明风险、结果(包括回报和厌恶)和预期之间的关联,而SSRT,一个在动物模型和人类中都得到了很好研究的冲动模型,与计算模型有很强的联系,将使我们不仅能够确定冲动控制失败背后的单个单位,而且还将确定网络层面的活动模式。通过这些实验和计算模型,我们将表征PD患者冲动的神经相关性,这将允许设计减轻冲动副作用的DBS方案。R21机制将被用来进一步发展和简化术中环境中的多通道记录和认知测试的过程,并验证单个神经元活动和停止信号任务中的行为模型之间的假设联系。
英文摘要
DESCRIPTION (provided by applicant): While the typical treatments for Parkinson's disease (PD), dopaminergic drugs and deep brain stimulation (DBS), are proven to be effective in mitigating the motor deficits associated with the disease, these same methods also give rise to behavioral side effects including compulsive gambling, hypersexuality, and complex, purposeless stereotyped behavior ("punding"). And while much work has investigated the underlying patterns of neural activity giving rise to tremor, rigidity, and other motor effects of D, little is known about the neural genesis of impulsive side effects in humans. We propose to characterize the patterns of neural activity underlying these failures of impulse control in an actual PD patient population undergoing surgery for the implantation of DBS electrodes. Such procedures offer a unique opportunity to collect data at the single neuron level in humans, since surgeons rely on intraoperative electrophysiology to identify the anatomical boundaries of the subthalamic nucleus (STN), the typical target of DBS in PD. Using multi-channel Ad-Tech microwire arrays, we will simultaneously record multiple channels of single unit activity (both spikes and field potentials ) in STN and nearby structures while subjects perform cognitive tasks with validated links to impulsivity in human populations. In the balloon analogue risk task (BART) participants must balance risk and reward as they decide when to stop inflating a computerized balloon whose point value and risk of popping both grow with size. In the stop signal reaction task (SSRT), participants must respond as quickly as possible when a "go" cue appears, but countermand this response when a "stop" tone is played. At the neural level, the BART allows us to elucidate correlates of risk, outcome (both rewarding and aversive), and anticipation, while the SSRT, a well-studied model of impulsivity in both animal models and humans with strong links to computational models, will allow us to determine not only single unit but network-level patterns of activity underlying failures in impulse control. Through these experiments, as well as computational modeling, we will characterize neural correlates of impulsivity in PD patients that will allow for the design of DBS protocols that mitigate impulsive side effects. The R21 mechanism will be used to further develop and streamline the process of multichannel recording and cognitive testing in the intraoperative setting and validate the hypothesized link between single neuron activity and models of behavior in the stop signal task.
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Real-time mapping and adaptive testing for neural population hypotheses
  • 批准号:
    10838393
  • 项目类别:
  • 资助金额:
    $18.82万
  • 财政年份:
    2022
  • 负责人:
    John Pearson
  • 依托单位:
Real-time mapping and adaptive testing for neural population hypotheses
  • 批准号:
    10838394
  • 项目类别:
  • 资助金额:
    $20.11万
  • 财政年份:
    2022
  • 负责人:
    John Pearson
  • 依托单位:
Nonparametric Bayes Methods for Big Data in Neuroscience
  • 批准号:
    9099840
  • 项目类别:
  • 资助金额:
    $14.43万
  • 财政年份:
    2014
  • 负责人:
    John Pearson
  • 依托单位:
Nonparametric Bayes Methods for Big Data in Neuroscience
  • 批准号:
    9310000
  • 项目类别:
  • 资助金额:
    $14.43万
  • 财政年份:
    2014
  • 负责人:
    John Pearson
  • 依托单位:
海外基金