Cortical spatiotemporal plasticity in humans

描述(由申请人提供)：了解 人类学习的复杂性和与之相关的大脑功能是最 基础科学的迷人旅程。除了是一个重要的 学术问题，大脑功能与学习相关的研究非常多 改进学习诊断和治疗的实际应用 残疾人士。学习障碍影响了10%-20%的美国人 对他们的生活质量和健康造成严重的社会经济后果。 这项建议侧重于理解正常的神经过程。 人类对听觉信息的学习，这种学习是短暂的，并以快速的方式发生 继承。这种处理的最直观的例子反映在我们的 学习和理解演讲的能力。学习这种形式的缺陷 信息与阅读障碍和语言学习障碍有关。 目前流行的几种工具用于研究 人类学习和相关的脑过程是正电子发射断层扫描 (PET)、功能磁共振成像(FMRI)、脑磁图 脑磁图(MEG)和脑电(EEG)。然而，在所有这些方法中，只有MEG 和EEG提供了足够的时间分辨率，这对拟议的研究至关重要 因为大脑对听觉刺激的反应通常发生在时间尺度上 以毫秒为单位。使用脑磁图和脑电获得的数据分析通常不需要 考虑大脑皮层活动的动力学，通常是简化的来源 和头部模型被假设，关于大脑可塑性的信息在 这种时尚很难理解和解释。最近几种新方法 已被开发用于处理脑磁图和脑电数据。然而，它的有用性 这些方法还没有在真实数据上得到充分的证明。 这项建议的第一个具体目标是研究和验证小说 分析将加强脑电和脑磁图数据解释的方法。我们 将使用逼真的头部建模来对分布式来源和帐户进行成像 来研究大脑活动的时空动态。我们将经验性地 验证这些方法的有用性，以了解 利用计算机模拟和实验研究脑功能可塑性。这个 该提案的第二个具体目标是确定 脑功能可塑性在时空反应中的动态变化 连续刺激和心理物理阈值的变化 是知觉学习的结果。我们将专注于在费率歧视中学习 在正常成人中的调幅音列作为迈向 理解发生在大脑中的简单时变听觉刺激学习 快速接班。我们将检查并关联学习诱导的行为 随着活动的空间和时间模式的变化而变化 在大脑皮层内和大脑皮层之间。 这种多学科的方法结合了科学的方法 使用脑磁图和脑电进行计算和脑功能成像应该会增强我们的 对人类感知的一般神经机制的理解 学习。这些在正常人身上的结果应该会提供至关重要的 用于开发、改进和评估诊断和 为有学习障碍的个人提供治疗。

DESCRIPTION (Provided by Applicant): Understanding the relationship between the complexity of human learning and associated brain function is one of the most fascinafing journeys of basic science. In addition to being an important academic question, studies of brain function assocIated with learning have very practical applications for improving diagnosis and therapy of learning disabilities. Learning disability affects between 10-20 percent of Americans with severe socioeconomic consequences on their quality of life and health. This proposal focuses on understanding the neural processes underlying normal human learning of auditory information that is transient and occurs in rapid succession. The most intuitive example of such processing is reflected in our ability to learn and understand speech. Deficits in learning such forms of information are associated with dyslexia and language-learning impairment. A few of the currently popular tools used to study the relationships between human learning and associated brain processes are Positron Emission Tomography (PET), Functional Magnetic Resonance Imaging (fMRI), Magnetoencephalography (MEG) and Electroencephalography (EEG). However, of all these methods only MEG and EEG offer adequate time resolution, essential for the proposed study because brain responses to auditory stimuli typically occur in the time-scale of milliseconds. Data obtained using MEG and EEG is often analyzed without consideration of the dynamics of cortical activity and often simplified source and head models are assumed, Information about brain plasticity obtained in this fashion is hard to understand and interpret. Recently several new methods have been developed to process MEG and EEG data. However, the usefulness of these methods has not been adequately demonstrated on real data. The first specific aim of this proposal is to research and to validate novel analyses methods that will enhance the interpretation of EEG and MEG data. We will use realistic head modeling for imaging distributed sources and account for the spatio-temporal dynamics of brain activity. We will empirically validate the usefulness of these methods to understand the dynamics of functional brain plasticity using computer simulations and experiments. The second specific aim of the proposal is to determine the relationship between the dynamics of functional brain plasticity in spatio-temporal responses to successive stimuli and changes in psychophysical thresholds that occur as a result of perceptual learning. We will focus on learning in rate discrimination of amplitude-modulated tone trains in normal adults as a first step towards understanding learning of simple time-varying auditory stimuli that occur in rapid succession. We will examine and correlate learning-induced behavioral changes with changes in the spatial and the temporal patterns of activity within and across cortical areas. Such a multidisciplinary approach which combines methods of scientific computing and functional brain imaging using MEG and EEG should enhance our understanding of general neural mechanisms underlying human perception learning. These results in normal individuals should provide crucial information for the development, refinement and evaluation of diagnosis and therapy for individuals with learning disability.