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

声音运动控制和感觉运动学习 - 行为、肌肉和神经元

• 批准号: 8628886
• 负责人: Samuel Sober
• 金额: $ 32.14万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-03-01 至 2018-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8628886
• 关键词: Acoustics; Algorithms; Animals; Area; Auditory pitch; Automobile Driving; Behavior; Behavior Control; Behavioral; Biological Models; Biomechanics; Birds; Brain; Cell Nucleus; Clinical; Complex; Data; Disease; E-learning; Frequencies; Gestures; Goals; Human; Individual; Investigation; Learning; Link; Modeling; Motor; Motor Activity; Muscle; Nervous System Trauma; Neurodegenerative Disorders; Neurons; Neurosciences; Outcome Study; Output; Patients; Performance; Physiological; Plastics; Probability; Problem Solving; Process; Production; Prosencephalon; Psychological reinforcement; Psychophysics; Rehabilitation therapy; Research; Schedule; Sensory; Signal Transduction; Site; Songbirds; Speech Disorders; Stroke; Structure; System; Testing; Time; Work; auditory feedback; base; design; experience; improved; innovation; insight; learned behavior; mathematical model; mind control; motor control; motor learning; nervous system disorder; neural circuit; neurophysiology; programs; public health relevance; relating to nervous system; research study; statistics; theories; vocal control; vocal learning

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.

描述（由申请人提供）：神经科学的核心目标是了解如何由神经元和肌肉实施学习算法。然而，尽管在人类中进行了数十年的心理物理研究，但我们对生理学习方式实施的理解是基本的。因此，学习的心理物理模型与重塑行为的运动计划的生理变化之间存在一个关键的差距。鸣禽提供了一个可访问生理可访问的模型系统，以研究行为可塑性。但是，以前在时间尺度上研究了歌曲学习太长，无法允许单神经元录音，因此无法确定学习构成的神经活动的变化。此外，歌曲肌肉本身的功能知之甚少，从而限制了我们对激活它们的声带和神经元如何控制行为重要的声学参数的理解。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可及性相结合，将学习算法与神经元和肌肉联系起来，从而克服了这些障碍。我们的长期目标是了解大脑如何控制和修饰声音输出，因为动物会获得声音行为并在其一生中保持声音表现。提出的实验的目的是揭示在短期声音误差校正期间修改单个声学参数（基本频率（音调））的方式。我们的核心假设是，音调学习在很大程度上取决于先前的感觉运动体验的统计数据，声音肌肉在跨不同的人声手势（“ Song Syllables”）上对音调产生双向影响，并且通过更改来实现音高学习 神经元在前脑前核中发射的爆发的尖峰含量。利用大量的初步数据，三个具体目标将检验这一假设。第一个目的将通过使用听觉反馈来推动唱歌鸟的自适应音高的变化来挑战当前声乐学习的理论。第二个特定目的将量化单个声音肌肉的功能，并通过结合精确的肌肉刺激，行为操纵和EMG记录来揭示学习过程中肌肉活动的变化。第三个目标（首次）将定义神经活动的变化，这些变化是通过在快速的人声学习范式中从单个神经元录制的声音学习的基础的变化，确定了声带可塑性的源头，并确定鸣人是在线学习过程中研究神经活动变化的唯一可用系统之一。这种方法具有创新性，因为它使我们能够在学习过程中检测到在线运动命令信号的变化，从而在行为和生理方法之间提供了至关重要的联系。这些研究很重要，因为对感觉运动学习机制的更好理解可以帮助设计康复策略，从而利用复杂行为的可塑性。