SYSTEMS CONNECTIVITY + BRAIN ACTIVATION:IMAGING STUDIES OF LANGUAGE + PERCEPTION

系统连接大脑激活：语言感知的成像研究

• 批准号: 7292509
• 负责人: MARCEL Adam JUST
• 金额: $ 35.09万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-06 至 2012-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7292509
• 关键词: Address; Affect; Area; Autistic Disorder; Behavioral; Brain; Characteristics; Complex; Comprehension; Computer Simulation; Computer information processing; Data; Deception; Development; Disease; Functional Magnetic Resonance Imaging; Goals; Image; Impairment; Individual; Intervention; Language; Learning; Machine Learning; Magnetic Resonance Imaging; Metaphor; Methodology; Methods; Modality; Modeling; Participant; Process; Range; Research; Semantics; Specificity; Structure; Symptoms; System; Techniques; Testing; Thinking; base; brain tissue; innovation; language perception; psychologic; relating to nervous system; size; social; social cognition; theories; tool; visual cognition

The overriding aim of this project is to relate the major symptoms of autism to abnormalities in their neural substrates, providing a neural systems-level analysis of autism, and focusing on neural systems connectivity. The primary method will be to perform fMRI studies of several different types of thinking to obtain information about underlying brain function, and to simultaneously acquire information about the size and integrity of brain tissues. The fMRI studies will provide information about cortical activation, but also about functional connectivity or the synchronization of the activation between areas. The project has developed the beginnings of a theory proposing that autism is marked by disordered connectivity among regions, particularly affecting the connectivity between frontal areas and more posterior areas. The connectivity framework is being used to formulate and test hypotheses and then integrate the new findings into a coherent theory. The new studies will deepen and broaden the understanding of the underlying neural disorder. The deepening will include the integration of several imaging modalities, so that the connectivity can be understood at more levels and in more detail. The broadening will consist of examining a wider range of tasks, to include conceptual comprehension, high-level perceptual tasks, and social tasks. This broadening is essential for determining the generality or specificity of the brain function characteristics of autism. The specifics aims are 1: To characterize brain function in the processing of higher conceptual levels of language comprehension, visual cognition, and dynamic social cognition; 2: To characterize the semantic representation of single words in individual participants with autism applying innovative machine learning techniques to fMRI data; 3: To relate functional characteristics of the brain to anatomical characteristics at the individual participant level; 4: To further develop the theory of disordered connectivity in autism, integrating functional (fMRI) and anatomical (MRI and DTI)characteristics of autism and using computational modeling as a theory-building tool. This research will continue to build an understanding of the relationship between the behavioral impairments that characterize autism and their neural basis. The connectivity model for autism advanced on the basis of this research has significantly influenced the field and validates the complex information processing development by Minshew, Goldstein and Williams. The combined model is proving to be promising in altering conceptualizations of autism and opening the way for new intervention methods(see deception learning for example). This research addresses Autism Research Matrix Goals # 2,6,22,23,26,34.

这个项目的首要目标是将自闭症的主要症状与他们的神经系统异常联系起来。 基板，提供自闭症的神经系统水平的分析，并专注于神经系统的连接。 主要的方法将是对几种不同类型的思维进行功能磁共振成像研究，以获得信息 关于潜在的大脑功能，并同时获得有关的大小和完整性的信息， 脑组织功能磁共振成像研究将提供有关皮层激活的信息， 连接性或区域之间激活的同步。该项目开发了 一个理论的开端，提出自闭症的特点是区域之间的无序连接， 特别是影响前部区域和更后部区域之间的连通性。连接性 框架被用来制定和测试假设，然后将新的发现整合到一个 连贯理论新的研究将加深和拓宽对潜在的神经系统的理解。 disorder.深化将包括几种成像模式的整合， 可以在更多层面、更详细地理解。扩大范围将包括审查更广泛的 任务，包括概念理解，高级知觉任务和社会任务。这 加宽对于确定脑功能特征的一般性或特异性是必不可少的， 自闭症具体目标是：1.表征大脑在高级概念加工中的功能 语言理解、视觉认知和动态社会认知的关系; 2：表征语义 应用创新机器学习的自闭症个体参与者的单个单词表示 技术的功能磁共振成像数据; 3：将大脑的功能特征与解剖特征， 个体参与者水平; 4：为了进一步发展自闭症中的无序连接理论， 整合自闭症的功能（fMRI）和解剖（MRI和DTI）特征，并使用计算 建模作为理论构建工具。 这项研究将继续建立一个理解之间的关系，行为 自闭症的特征和他们的神经基础。自闭症的连通性模型 这项研究的基础对该领域产生了重大影响，并验证了复杂信息 由Minshew，Goldstein和威廉姆斯加工开发。事实证明， 有望改变自闭症的概念化，并为新的干预方法开辟道路（见 例如欺骗学习）。这项研究涉及自闭症研究矩阵目标#2，6，22，23，26，34。