Defining the Neuromuscular Mechanisms of Vocal Error Correction

定义声音纠错的神经肌肉机制

• 批准号: 8717041
• 负责人: Kyle Harish Srivastava
• 金额: $ 4.27万
• 依托单位: GEORGIA INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-01-15 至 2017-01-14
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8717041
• 关键词: Accounting; Acoustics; Adolescent; Adult; Affect; American; Anatomy; Animal Model; Animals; Behavior; Behavioral; Behavioral Paradigm; Biological Models; Brain; Cell Nucleus; Development; Disease; Electric Stimulation; Electrodes; Electromyography; Electrophysiology (science); Foundations; Future; Generations; Goals; Human; Implanted Electrodes; Individual; Intramuscular; Learning; Maps; Mechanics; Modeling; Modification; Motor; Motor Neurons; Muscle; Neurons; Organ; Output; Pattern; Performance; Physiological; Production; Rehabilitation therapy; Research; Research Proposals; Signal Transduction; Songbirds; Speech; Speech Disorders; Synapses; System; Techniques; Testing; Tracer; Weight; Work; auditory feedback; base; bird song; design; effective therapy; human subject; improved; innovation; insight; member; mind control; motor control; neuromuscular; neurophysiology; public health relevance; relating to nervous system; research study; sensory feedback; vocal control; vocal learning

DESCRIPTION (provided by applicant): The transformation of neural signals to muscle activity to behavioral output defines how the brain controls behavior, and a full account of brain function demands that we understand this transformation. Vocal motor control is critical to our ability to communicate, and yet we still do not understand how the brain controls vocal muscle activity and acoustic output. This gap in understanding hinders our ability to understand the general principles of vocal behavior and develop effective treatments for the various speech disorders affecting millions of Americans. The well-characterized and relatively simple organization of the songbird brain makes it an ideal model system for understanding normal and disordered vocal control. Furthermore, our lab has developed innovative behavioral paradigms that use auditory feedback manipulations to induce vocal error correction in adult songbirds, providing a model for the auditory feedback manipulations used to treat vocal disorders in humans. The research described in my proposal will include experimental approaches not possible in human subjects to learn how altered sensory feedback can modify patterns of vocal muscle activation during vocal error correction and reveal how such adaptive modifications are implemented by the brain. The proposed research will therefore significantly advance the songbird as an animal model for investigating the mechanisms and optimizing the design of behavioral paradigms for vocal rehabilitation. The objective of this proposal is to quantify how patterns of vocal muscle activity are transformed into acoustic output, reshaped during vocal error correction, and controlled by individual premotor neurons (i.e. those that directly activate motor neurons, which in turn activate the vocal muscles). This work will utilize electrophysiology to record premotor neurons and electromyography (EMG) to record vocal muscles. It is hypothesized that each premotor neuron controls multiple muscles, each of which, in turn, controls multiple acoustic parameters and, thus, subsets of vocal muscles must change their activity in concert to shift individual acoustic parameters of song during vocal learning. Aim 1 wil reveal the mechanics of the transformation from vocal muscle activity to acoustic parameters. Acoustic features of song will be correlated with EMG activity recorded using intramuscular electrodes, and targeted electrical stimulation of single vocal muscles will be used to drive changes in those acoustic features. Aim 2 will quantify changes in vocal muscle activity during vocal learning to demonstrate how the songbird system implements learning using the available mechanics of the vocal organ. Aim 3 will characterize the functional projections from single premotor neurons to the vocal muscles using simultaneous neural and muscular recording. Quantitative analysis (spike-triggered EMG) will then be used to determine whether individual premotor neurons control single or multiple muscles to drive song. This work will provide insight into the neuromuscular mechanisms underlying vocal learning and motor control while laying a foundation for future studies in speech control and sensorimotor learning.

描述（由申请人提供）：神经信号对肌肉活动的转化定义了大脑如何控制行为，并且对大脑功能的完整说明我们需要我们理解这种转变。声带控制对我们的交流能力至关重要，但是我们仍然不了解大脑如何控制声带活动和声音输出。理解的这一差距阻碍了我们理解声音行为的一般原则并为影响数百万美国人的各种语音疾病开发有效治疗的能力。鸣禽大脑的特征良好且相对简单的组织使其成为理解正常和无序的人声控制的理想模型系统。此外，我们的实验室开发了创新的行为范式，这些范式使用听觉反馈操纵来诱导成人鸣禽的声音误差校正，为用于治疗人类声音障碍的听觉反馈操纵提供了模型。我的提案中描述的研究将包括人类受试者不可能的实验方法，以了解改变的感觉反馈如何在声带纠正过程中修改声音肌肉激活的模式，并揭示大脑如何实现这种适应性修饰。因此，拟议的研究将大大推动鸣禽作为一种动物模型，以研究机制并优化行为范式的人声康复。 该提案的目的是量化声音肌肉活动的模式如何转化为声学输出，在声音误差校正期间重塑，并由单个前前神经元控制（即那些直接激活运动神经元的神经元，从而激活声音肌肉）。这项工作将利用电生理学记录前神经元和肌电图（EMG）来记录声带肌肉。假设每个前运动神经元控制多个肌肉，每种肌肉反过来又控制了多个声学参数，因此，声带肌肉的子集必须在声音学习过程中将其活动转变为演奏以改变歌曲的单个声学参数。 AIM 1 WIL揭示了从声音肌肉活动到声学参数的转化机制。歌曲的声学特征将与使用肌内电极记录的EMG活性相关，并且单声肌肉的靶向电刺激将用于驱动这些声学特征的变化。 AIM 2将量化声乐学习过程中声乐肌肉活动的变化，以证明鸣禽系统如何使用声音器官的可用机制来实现学习。 AIM 3将使用同时的神经和肌肉记录来表征从单个前神经元到声带的功能投影。然后将使用定量分析（SPIKE触发的EMG）来确定单个前神经元是否控制单个或多个肌肉来驱动歌曲。这项工作将提供有关声音学习和运动控制基础的神经肌肉机制的洞察力，同时为语音控制和感觉运动学习的未来研究奠定了基础。