Speech Motor Learning and Sensory Plasticity in Children and Adults

描述(由申请人提供)：建议的研究将集中在儿童言语运动发育的神经基础上。我们的计划是使用一种结合了先进的心理物理和神经成像技术的多模式方法。在我们与成年人的工作中，在人类手臂运动的背景下，我们开发了一种强大的新技术来识别大脑活动中与学习行为测量具体相关的变化。我们发现，与运动学习相关的大脑网络变化可以分为主要是运动本质上的变化，以及反映与运动学习相关的知觉变化的变化。在拟议的项目中，我们将研究5至12岁的健康儿童和健康的成年人。我们将使用功能连通性的功能磁共振测量来确定与与言语运动学习相关的运动和知觉变化相关的大脑网络。我们将测试这一假设，即与言语运动学习相关的大脑网络可以被划分为主要与运动功能变化相关的网络，以及涉及言语运动学习的知觉和感觉方面的网络。我们提出，在言语运动学习过程中活跃的感觉和运动网络可能在年幼的儿童中发挥更独立的作用，随着这些系统的成熟，它们变得更加紧密地耦合在一起。我们还将确定伴随言语运动学习的大脑活动如何与训练后在休息状态下观察到的大脑网络更持久的变化有关。假设是，言语运动学习过程中的大脑活动涉及处理感觉错误的网络，以及编码与适应和学习相关的预测性或前馈调整的网络。我们将测试这样一种想法，即在基于任务的学习过程中，与学习任务相关的大脑活动模式可以用来预测在完成学习任务后观察到的功能连接的持久变化。

DESCRIPTION (provided by applicant): The proposed studies will focus on the neural substrates of speech motor development in children. Our plan is to use a multi-modal approach that combines advanced psychophysical and neuroimaging techniques. In our work with adults, in the context of human arm movement, we have developed a powerful new technique to identify changes in brain activity that are specifically related to behavioral measures of learning We have found that changes in brain networks that occur in conjunction with motor learning can be partitioned into those that are primarily motor in nature and those that reflect the perceptual changes that occur in conjunction with motor learning. For the proposed project, we will study healthy children from ages 5 to 12 and healthy adults. We will use fMRI measures of functional connectivity to identify the brain networks that are associated with motor and perceptual changes that occur in association with speech motor learning. We will test the hypothesis that the brain networks associated with speech motor learning can be partitioned, as in limb movement, into those that are primarily associated with the changes in motor function and those involved in the perceptual and sensory aspects of speech motor learning. We propose that the sensory and motor networks active during speech motor learning may function more independently in younger children, becoming more tightly coupled as these systems mature. We will also determine how the brain activity that accompanies speech motor learning is related to the more durable changes in brain networks that are observed under-resting state conditions following training. The hypothesis is that brain activity during speech motor learning involves networks that process sensory errors and those that code predictive or feedforward adjustments associated with adaptation and learning. We will test the idea that patterns of brain activity during task based learning that are related to the these measures can be used to predict durable changes in functional connectivity that are observed after the completion of the learning task.