VISUALIZATION OF FUNCTIONAL CONNECTIVITY IN BRAIN

这是一个合作研究项目的一部分， 物理学家、数学家、工程师、计算机 科学家、健康信息学专家和神经科学家， 导致设计和实施“新技术 神经科学问题的答案。 在他们最普遍的 形式，神经科学问题的核心，这项拨款可能是 我们如何识别、提取、量化 对来自表面EEG的生物学显著模式进行分类和索引 记录或SPECT，PET和功能性MRI（fMRI）数据集？ 做 这些模式使我们深入了解了 大脑，或提供认知或疾病的定量描述 国家？ 我们的基本假设是， 从SPECT、PET、EEG导出的空间和时间协方差模式 和功能磁共振成像数据提供了生物学相关的功能测量， 大脑中的连通性。 在过去的一年里，我们收集了 并分析了使用4特斯拉的常见手指运动范例的数据， fMRI和PET。

This is part of a collaborative research program that fosters interactions between physicists, mathematicians, engineers, computer scientists, health informatics specialists and neuroscientists and lead to the design and implementation of "novel technological solutions to particular neuroscience questions. In their most general form, the neuroscience questions central to this grant may be formulated as follows: How can we identify, extract, quantify, classify and index biologically significant patterns from surface EEG recordings or from SPECT, PET and functional MRI (fMRI) data sets? Do these patterns yield insights into the functional organization of the brain, or provide quantitative descriptors of cognitive or disease states? Our basic hypothesis is that quantitative descriptions of spatial and temporal covariance patterns derived from SPECT, PET, EEG and fMRI data provide biologically relevant measures of functional connectivity in the brain. During the last year, we have collected and analyzed data on a common finger movement paradigm using 4 Tesla fMRI and PET.