Administrative Supplement: Vocal motor control and sensorimotor learning - behavior, muscles, and neurons

描述(申请人提供)：神经科学的一个中心目标是了解学习算法是如何由神经元和肌肉实现的。然而，尽管人类进行了数十年的心理物理学研究，但我们对运动学习是如何在生理上实现的了解还很初级。因此，在学习的心理物理模型和重塑行为的运动程序中的生理变化之间存在着关键的差距。鸣禽提供了一个生理上可用来研究行为可塑性的模型系统。然而，之前对歌曲学习的研究时间太长，不能进行单神经元记录，因此无法识别构成学习基础的神经活动的变化。此外，歌声肌肉本身的功能知之甚少，限制了我们对声带肌肉和激活它们的神经元如何控制行为上重要的声学参数的理解。拟议的实验克服了这些障碍，将来自人类运动心理物理学的行为和计算方法与鸣鸟系统的神经生理学可及性相结合，将学习算法与神经元和肌肉联系起来。我们的长期目标是了解随着动物获得发声行为并在其一生中保持发声表现，大脑是如何控制和改变发声输出的。拟议的实验的目的是揭示单个声学参数--基频(基音)--在短期发声纠错过程中是如何被修改的。我们的中心假设是，音调学习强烈依赖于先前感觉运动经验的统计，发声肌肉通过不同的发声手势对音调施加双向影响(“歌曲音节”)，音调学习是通过改变 由前脑前运动核神经元发出的脉冲的尖峰含量。根据大量的初步数据，三个具体目标将检验这一假设。第一个目标将挑战当前的发声学习理论，使用听觉反馈的操纵来驱动鸣禽的适应性音调变化。第二个具体目标将量化个别发声肌肉的功能，并通过结合精确定时的肌肉刺激、行为操作和肌电记录来揭示肌肉活动在学习过程中的变化。第三个目标将(首次)通过记录快速发声学习范例中的单个神经元，确定发声运动可塑性的位置，并将鸣禽建立为研究在线学习期间神经活动变化的仅有的可用系统之一，来定义支撑发声学习的神经活动的变化。这种方法是创新的，因为它允许我们在学习过程中在线检测运动命令信号的变化，为运动学习的行为方法和生理方法之间提供了关键的联系。这些研究意义重大，因为更好地理解感觉运动学习的机制可以帮助设计利用复杂行为的可塑性的康复策略。

DESCRIPTION (provided by applicant): A central goal of neuroscience is to understand how learning algorithms are implemented by neurons and muscles. However, despite decades of psychophysical studies in humans, our understanding of how motor learning is implemented physiologically is rudimentary. A critical gap therefore exists between psychophysical models of learning and the physiological changes in the motor program that reshape behavior. Songbirds provide a physiologically accessible model system in which to investigate behavioral plasticity. However, song learning has previously been studied on timescales too long to allow single-neuron recordings, making it impossible to identify the changes in neural activity that underlie learning. Furthermore, the functions of the song muscles themselves are poorly understood, limiting our understanding of how vocal muscles and the neurons that activate them control behaviorally important acoustic parameters. The proposed experiments overcome these obstacles by combining behavioral and computational approaches drawn from human motor psychophysics with the neurophysiological accessibility of the songbird system, linking learning algorithms to neurons and muscles. Our long-term goal is to understand how the brain controls and modifies vocal output as an animal acquires vocal behaviors and maintains vocal performance throughout its lifetime. The objective of the proposed experiments is to reveal how a single acoustic parameter - fundamental frequency (pitch) - is modified during short-term vocal error correction. Our central hypothesis is that pitch learning depends strongly on the statistics of prior sensorimotor experience, that vocal muscles exert bidirectional influence on pitch across different vocal gestures ("song syllables"), and that pitch learning is implemented by altering the spike content of bursts fired by neurons in a forebrain premotor nucleus. Drawing on significant quantities of preliminary data, three specific aims will test this hypothesis. The first aim will challenge current theories of vocal learning by using manipulations of auditory feedback to drive adaptive pitch changes in singing birds. The second specific aim will quantify the functions of individual vocal muscles and reveal how muscle activity changes during learning by combining precisely-timed muscle stimulation, behavioral manipulations, and EMG recordings. The third aim will (for the first time) define the changes neural activity that underlie vocal learning by recording from single neurons during a rapid vocal learning paradigm, identifying a locus of vocal motor plasticity and establishing the songbird as one of the only available systems for studying changes in neural activity during online learning. This approach is innovative because it allows us to detect changes in motor command signals online during learning, providing a critical link between behavioral and physiological approaches to motor learning. These studies are significant because a better understanding of the mechanisms of sensorimotor learning could aid in the design of rehabilitative strategies that exploit the plasticity of complex behavio.