Cortical spatiotemporal plasticity in humans

人类皮质时空可塑性

• 批准号: 6781360
• 负责人: SRIKANTAN S. NAGARAJAN
• 金额: $ 5万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-02-01 至 2005-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6781360
• 关键词: auditory stimulus; behavioral /social science research tag; bioimaging /biomedical imaging; clinical research; computer simulation; discrimination learning; electroencephalography; human subject; magnetoencephalography; neural plasticity; psychoacoustics; sequential perception; sound perception

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.

描述（申请人提供）：了解 人类学习和相关的大脑功能的复杂性是最重要的 基础科学之旅。除了很重要 学术问题，与学习相关的大脑功能的研究非常 改善学习诊断和治疗的实际应用 残疾。学习障碍影响10-20％的美国人 对他们的生活质量和健康造成了严重的社会经济后果。 该提案的重点是理解正常的神经过程 人类对瞬态的听觉信息的学习，并迅速发生 演替。这种处理的最直观的例子反映在我们的 学习和理解语音的能力。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。 一些目前流行的工具用于研究 人类学习和相关的大脑过程是正电子发射断层扫描 （PET），功能性磁共振成像（fMRI），磁性摄影 （MEG）和脑电图（EEG）。但是，在所有这些方法中，只有梅格 脑电图提供足够的时间分辨率，对于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 毫秒。通常不得分析使用MEG和EEG获得的数据 考虑皮层活动的动力学以及通常简化的来源 假设头部模型，有关大脑可塑性的信息 这种方式很难理解和解释。最近几种新方法 已开发用于处理MEG和EEG数据。但是，有用的 这些方法尚未在实际数据上充分证明。 该提案的第一个具体目的是研究和验证新颖 分析方法将增强脑电图和MEG数据的解释。我们 将使用现实的头建模来成像分布式来源和帐户 用于大脑活动的时空动力学。我们会经验 验证这些方法的实用性以了解 使用计算机模拟和实验的功能性大脑可塑性。这 该提案的第二个具体目的是确定 在时空反应中功能性脑可塑性的动力学 连续的刺激和心理物理阈值的变化作为一个 感知学习的结果。我们将专注于学习率歧视 正常成年人的振幅调制音调火车是迈向的第一步 了解发生在中的简单时变听觉刺激 快速继承。我们将检查并关联学习引起的行为 随着空间和活动时间模式的变化的变化 内部和跨皮质区域。 这种多学科方法结合了科学方法 使用MEG和EEG计算和功能性大脑成像应增强我们的 了解人类感知的一般神经机制 学习。这些结果在正常人中应提供至关重要的 有关诊断和评估的开发，完善和评估的信息 为学习障碍的人提供治疗。