How is Performance Evaluation Encoded in the Brain?

大脑中的绩效评估是如何编码的？

• 批准号: 9371400
• 负责人: Vikram Gadagkar
• 金额: $ 9.44万
• 依托单位: CORNELL UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-01 至 2019-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9371400
• 关键词: Animals; Auditory; Basal Ganglia; Behavior; Behavioral; Benchmarking; Birds; Brain; Calcium; Chronic; Communities; Complex; Computational Technique; Corpus striatum structure; Courtship; Cues; Custom; Data; Disease; Dopamine; Dystonia; Electrophysiology (science); Endoscopy; Evaluation; Exhibits; Feedback; Female; Fiber; Food; Goals; Huntington Disease; Image; Juice; Learning; Mammals; Mediating; Melissa; Memory; Mentors; Modeling; Monitor; Motor; Motor Skills; Motor output; Mus; Neurons; Neurosciences; Optical Methods; Optics; Outcome; Parkinson Disease; Pathway interactions; Performance; Phase; Photometry; Play; Process; Research; Resolution; Rewards; Role; Self-Examination; Signal Transduction; Social Environment; Social Interaction; Songbirds; Sports; Stereotyping; Symptoms; System; Techniques; Testing; Time; Update; Virus; auditory feedback; bird song; dopaminergic neuron; innovation; instrument; learned behavior; motor control; motor learning; multidisciplinary; nervous system disorder; neuromechanism; novel; optogenetics; outcome prediction; programs; sensory input; sequence learning; skills; social; tutoring; virtual

Dopamine (DA)-basal ganglia (BG) circuits are critical for motor control and learning. Our current understanding of these circuits comes largely from studies of animals learning for external rewards such as food or juice. Yet symptoms of diseases such as Parkinson’s, Huntington’s and dystonia include degradation of motor behaviors unrelated to reward seeking. In fact most of our behaviors, such as learning a sport or an instrument, are not simple actions in pursuit of rewards but are instead complex motor sequences learned by matching performance to internal goals. Mechanisms of this type of motor learning are poorly understood. The songbird model offers a unique opportunity to study how internally guided motor sequences are constructed. First, birdsong is learned by matching a complex vocal sequence to the memory of a tutor song, or ‘template’. Second, song learning requires a DA-BG circuit that is part of a tractable ‘song system.’ We will leverage these advantages to decipher how motor sequences are learned during ‘natural’ trial and error. To test if DA encodes error during internally-guided performance evaluation, I will record BG-projecting VTA neurons as I induce auditory error in specific song syllables using distorted auditory feedback (Aim 1, K99 phase). Preliminary results suggest DA encodes performance error, the difference between actual and predicted performance. DA activity was phasically suppressed after distorted syllables, consistent with a worse-than- predicted outcome, and was phasically activated at the precise moment of the song when a predicted distortion did not occur, consistent with a better-than-predicted outcome. Next I will resolve the paradox (Aim 2, K99 phase) of how DA activity both evaluates past behavior for learning and also modulates ongoing motor variability by recoding BG-projecting VTA neurons as birds transition from singing alone (variable ‘practice mode’) to singing to a female (stereotyped ‘performance mode’). Finally I will develop optical techniques (Aim 3.1) to chronically monitor VTA neurons over learning-relevant timescales to determine the origins and consequences of DA performance error (Aims 3.2 and 3.3, R00 phase). My mentor, Dr. Jesse Goldberg, co-mentor Dr. Joseph Fetcho, and collaborators Drs. Melissa Warden, Chris Schaffer, and Nozomi Nishimura all have extensive expertise in calcium imaging and optogenetics. Developing these techniques, along with frequent data presentations, attendance of seminars and professional courses, and close interactions with the strong collaborative Cornell neuroscience community, will equip me with the necessary skills for transitioning to independence. In the independent R00 phase, I will use these acquired skills and innovative behavioral, optical, and computational techniques to complete the proposed aims (Aims 3.2 and 3.3) and establish an independent research program focused on the neural mechanisms of natural motor sequence learning.

多巴胺（DA） - 基质神经节（BG）电路对于运动控制和学习至关重要。我们目前对这些电路的理解主要来自对动物学习外部奖励（例如食物或果汁）的研究。然而，帕金森氏症，亨廷顿和肌张力障碍等疾病的症状包括降解与寻求奖励无关的运动行为。实际上，我们的大多数行为，例如学习运动或乐器，不是追求奖励的简单动作，而是通过将性能与内部目标匹配来学到的复杂运动序列。这种运动学习的机制知之甚少。鸣禽模型提供了一个独特的机会，可以研究内部引导运动序列的构建方式。首先，通过将复杂的人声序列与导师歌曲的记忆或“模板”相匹配，从而学习了Birdsong。其次，歌曲学习需要一个DA-BG电路，该电路属于“歌曲系统”的一部分。我们将利用这些优势在“自然”试验和错误期间解释了如何学习运动序列。为了测试DA在内部引导性能评估期间是否编码错误，我将使用扭曲的听觉反馈（AIM 1，K99阶段）在特定的歌曲教学大纲中诱导特定歌曲课程中的听觉错误时记录BG项目的VTA神经元。初步结果表明DA编码性能错误，实际性能和预测性能之间的差异。 DA活性在扭曲的音节后被身体抑制，与预测的结果更糟糕，并且在没有发生预测失真的精确时刻在歌曲的精确时刻被物理激活，这与预测的结果更好。接下来，我将解决DA活动如何评估过去的学习行为的悖论（AIM 2，K99阶段），并通过重新编码BG-Projection VTA神经元作为鸟类从单独唱歌（可变的“实践模式”）转变为唱歌到女性（刻板的“表演模式”）来调节正在进行的运动变异性。最后，我将开发光学技术（AIM 3.1），以长期监测与学习相关的时间尺度的VTA神经元，以确定DA性能误差的起源和后果（AIMS 3.2和3.3，R00阶段）。我的导师杰西·戈德伯格（Jesse Goldberg）博士，约瑟夫·费彻（Joseph Fetcho）博士和合作者博士。 Melissa Warden，Chris Schaffer和Nozomi Nishimura在钙成像和光遗传学方面都有广泛的专业知识。开发这些技术，以及频繁的数据演示，进入半岛和专业课程的出席，以及与强大的协作康奈尔神经科学社区的紧密互动，将使我具备过渡到独立性的必要技能。在独立的R00阶段，我将使用这些获得的技能和创新的行为，光学和计算技术来完成所提出的目标（AIMS 3.2和3.3），并建立一个独立的研究计划，重点介绍了自然运动序列学习的神经机制。