Vocal motor control and sensorimotor learning - behavior, muscles, and neurons

描述（由申请人提供）：神经科学的一个中心目标是了解学习算法是如何通过神经元和肌肉实现的。然而，尽管对人类进行了数十年的心理物理学研究，我们对运动学习是如何在生理上实现的理解还是初级的。因此，在学习的心理物理模型和重塑行为的运动程序的生理变化之间存在着一个关键的差距。鸣禽为研究行为可塑性提供了一个生理上可接近的模型系统。然而，先前对歌曲学习的研究时间尺度太长，不允许单个神经元记录，因此不可能确定学习背后神经活动的变化。此外，人们对歌唱肌肉本身的功能知之甚少，这限制了我们对发声肌肉和激活它们的神经元如何控制重要的行为声学参数的理解。提出的实验通过将人类运动心理物理学的行为和计算方法与鸣禽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，克服了这些障碍。我们的长期目标是了解当动物在其一生中获得发声行为并保持发声表现时，大脑是如何控制和修改发声输出的。提出的实验的目的是揭示一个单一的声学参数-基本频率（音高）-是如何在短期声乐纠错过程中被修改的。我们的中心假设是，音高学习在很大程度上依赖于先前感觉运动经验的统计数据，发声肌肉在不同的发声手势（“歌曲音节”）中对音高施加双向影响，并且音调学习是通过改变声音结构来实现的

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.