Computational roles of inhibition in human action control

摘要 皮质-基底节回路的经典神经认知模型暗示兴奋性信号驱动和抑制 信号抑制，行为输出。然而，抑制可以支持其他计算。关于动物的研究 运动系统和人类感觉系统已经显示出抑制形成神经的增益和调谐特性 人口。本申请的总体目标是建立用于增益调制和调谐的角色 动作准备期间的人体运动系统，并评估这些计算在多大程度上与 抑制的神经化学能力。因此，拟议的实验将检验中心假设 人皮质脊髓通路内的增益和调谐在准备过程中动态变化 并与运动皮质中抑制性神经递质的可用性有关。这样做的第一个具体目标是 其应用是测试人体运动系统内的假设增益在动作准备期间增加 促进选定操作的执行。第二个具体目标是检验空间调谐的假设 在动作准备过程中，运动表示法会变得尖锐。而目标1检查的是一个计算性的 用于促进所选动作的执行的机制，目标2研究了用于 从相邻和重叠表示的池中选择动作。我们将使用非侵入性大脑 刺激：检查给定肌肉内(目标1)和一组肌肉之间的兴奋性模式 (目标2)检测行为任务执行过程中增益和调谐的变化。第三个具体问题 此应用程序的目的是探索增益、调谐和抑制药的局部可用性之间的关系 皮质中的神经递质γ-氨基丁酸(GABA)。将检查个体差异以进行测试 局部GABA的可用性是否与增益和调谐变化的大小相关。我们假设 运动皮质中GABA含量较高的个体将在动作中表现出更大的增益增加和更敏锐的调谐 准备工作。这项拟议的工作具有创新性，因为增益和调谐在人类运动中的作用 系统的研究严重不足，它们与神经化学内容的联系也完全没有被探索过。这 这项研究意义重大，因为研究结果可能会改变我们对抑制在行为中的作用的理解 控制力。抑制机制的异常与帕金森氏症、中风、 和肌张力障碍，从拟议的实验中获得的知识可以帮助确定治疗的新靶点 干预措施。 在这份多元化增刊中，我们请求为行动控制的研究生Hayami Nishio女士提供资金 实验室(PI温室)，模拟非侵入性脑刺激产生的电场 目标2中提出的技术。这一新的添加将把解剖学特性与神经化学特性分开 可影响电机系统调谐测量的属性。Nishio女士将接受汽车培训 生理学、导航脑刺激、计算方法和职业发展。

Abstract Classic neurocognitive models of cortico-basal ganglia circuits imply excitatory signals drive, and inhibitory signals suppress, behavioral output. However, inhibition can support other computations. Research on animal motor systems and human sensory systems has shown inhibition shapes the gain and tuning properties of neural populations. The overall objectives of this application are to establish roles for gain modulation and tuning within the human motor system during action preparation and to evaluate to what extent these computations relate to the neurochemical capacity for inhibition. Accordingly, the proposed experiments will test the central hypothesis that gain and tuning within the human corticospinal pathway change dynamically during the preparation of actions and relate to inhibitory neurotransmitter availability in motor cortex. The first specific aim of this application is to test the hypothesis gain within the human motor system increases during action preparation to facilitate the execution of a selected action. The second specific aim is to test the hypothesis spatial tuning of motor representations sharpens during action preparation. Whereas Aim 1 examines a computational mechanism for facilitating the execution of a selected action, Aim 2 examines a computational mechanism for selecting actions from a pool of neighboring and overlapping representations. We will use non-invasive brain stimulation to examine the patterns of excitability within a given muscle (Aim 1) and across a group of muscles (Aim 2) to detect changes in gain and tuning, respectively, during behavioral task performance. The third specific aim of this application is to explore relationships between gain, tuning, and local availability of the inhibitory neurotransmitter gamma-amino butyric acid (GABA) in the cortex. Individual differences will be examined to test whether the availability of local GABA correlates with the magnitude of gain and tuning changes. We hypothesize individuals with more GABA in motor cortex will exhibit greater increases in gain and sharper tuning during action preparation. The proposed work is innovative because the roles of gain and tuning within the human motor system are crucially understudied and their links to neurochemical content are completely unexplored. This research is significant because the results could change our interpretation of the roles of inhibition in behavioral control. Abnormalities in inhibitory mechanisms are associated with symptoms of Parkinson’s disease, stroke, and dystonia, and knowledge gained from the proposed experiments can help identify new targets for therapeutic interventions. In this diversity supplement, we request funding for Ms. Hayami Nishio, a graduate student in the Action Control Laboratory (PI Greenhouse), to model the electric fields produced by the non-invasive brain stimulation technique proposed in Aim 2. This novel addition will separate anatomical properties from neurochemical properties that can influence motor system tuning measurements. Ms. Nishio will receive training in motor physiology, navigated brain stimulation, computational methods, and career development.