How is Performance Evaluation Encoded in the Brain?

多巴胺(DA)-基底神经节（BG）回路对运动控制和学习至关重要。我们目前对这些回路的理解主要来自对动物学习外部奖励（如食物或果汁）的研究。然而，帕金森氏症、亨廷顿氏症和肌张力障碍等疾病的症状包括与寻求奖励无关的运动行为的退化。事实上，我们的大多数行为，如学习一项运动或一种乐器，并不是追求奖励的简单行为，而是通过将表现与内部目标相匹配而习得的复杂动作序列。这种类型的运动学习机制尚不清楚。鸣禽模型提供了一个独特的机会来研究内部引导的运动序列是如何构建的。首先，鸟鸣是通过将复杂的声音序列与导师的歌曲或“模板”的记忆相匹配来学习的。其次，歌曲学习需要一个DA-BG电路，这是一个可处理的“歌曲系统”的一部分。“我们将利用这些优势来破译运动序列是如何在‘自然’试验和错误中学习的。”为了测试DA是否在内部引导的表现评估中编码错误，我将在使用扭曲的听觉反馈诱导特定歌曲音节的听觉错误时记录bg投射的VTA神经元（Aim 1， K99阶段）。初步结果表明，DA编码存在性能误差，实际性能与预测性能存在差异。在出现扭曲的音节后，DA活动被阶段性地抑制，这与预期的结果相一致；而在歌曲播放的准确时刻，当预期的扭曲没有发生时，DA活动被阶段性地激活，这与预期的结果相一致。接下来，我将解决悖论（目标2，K99阶段），即DA活动如何评估过去的学习行为，并通过重新编码bg投射的VTA神经元来调节正在进行的运动变异性，因为鸟类从单独唱歌（可变的“练习模式”）转变为向雌性唱歌（定型的“表演模式”）。最后，我将开发光学技术（目标3.1），在学习相关的时间尺度上长期监测VTA神经元，以确定数据处理性能误差的起源和后果（目标3.2和3.3，R00阶段）。我的导师杰西·戈德堡博士，共同导师约瑟夫·费乔博士，以及我的合作者。Melissa Warden， Chris Schaffer和Nozomi Nishimura都在钙成像和光遗传学方面拥有丰富的专业知识。发展这些技术，加上频繁的数据展示，参加研讨会和专业课程，以及与康奈尔大学神经科学社区的密切合作，将使我具备向独立过渡所必需的技能。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提出的目标（目标3.2和3.3），并建立一个独立的研究计划，专注于自然运动序列学习的神经机制。

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.